Consideration of Optimal Input on Semi-Active Shock Control System
Kawashima, Takeshi
In press working, unidirectional transmission of mechanical energy is expected in order to maximize the life of the dies. To realize this transmission, the author has developed a shock control system based on the sliding mode control technique. The controller makes a collision-receiving object effectively deform plastically by adjusting the force of the actuator inserted between the colliding objects, while the deformation of the colliding object is held at the necessity minimum. However, the actuator has to generate a large force corresponding to the impulsive force. Therefore, development of such an actuator is a formidable challenge. The author has proposed a semi-active shock control system in which the impulsive force is adjusted by a brake mechanism, although the system exhibits inferior performance. Thus, the author has also designed an actuator using a friction device for semi-active shock control, and proposed an active seatbelt system as an application. The effectiveness has been confirmed by a numerical simulation and model experiment. In this study, the optimal deformation change of the colliding object is theoretically examined in the case that the collision-receiving object has perfect plasticity and the colliding object has perfect elasticity. As a result, the optimal input condition is obtained so that the ratio of the maximum deformation of the collision-receiving object to the maximum deformation of the colliding object becomes the maximum. Additionally, the energy balance is examined.
Ekkachai, Kittipong; Nilkhamhang, Itthisek
2016-11-01
In recent years, intelligent prosthetic knees have been developed that enable amputees to walk as normally as possible when compared to healthy subjects. Although semi-active prosthetic knees utilizing magnetorheological (MR) dampers offer several advantages, they lack the ability to generate active force that is required during some states of a normal gait cycle. This prevents semi-active knees from achieving the same level of performance as active devices. In this work, a new control algorithm for a semi-active prosthetic knee during the swing phase is proposed to reduce this gap. The controller uses neural network predictive control and particle swarm optimization to calculate suitable command signals. Simulation results using a double pendulum model show that the generated knee trajectory of the proposed controller is more similar to the normal gait than previous open-loop controllers at various ambulation speeds. Moreover, the investigation shows that the algorithm can be calculated in real time by an embedded system, allowing for easy implementation on real prosthetic knees.
Semi-active control of helicopter vibration using controllable stiffness and damping devices
Anusonti-Inthra, Phuriwat
Semi-active concepts for helicopter vibration reduction are developed and evaluated in this dissertation. Semi-active devices, controllable stiffness devices or controllable orifice dampers, are introduced; (i) in the blade root region (rotor-based concept) and (ii) between the rotor and the fuselage as semi-active isolators (in the non-rotating frame). Corresponding semi-active controllers for helicopter vibration reduction are also developed. The effectiveness of the rotor-based semi-active vibration reduction concept (using stiffness and damping variation) is demonstrated for a 4-bladed hingeless rotor helicopter in moderate- to high-speed forward flight. A sensitivity study shows that the stiffness variation of root element can reduce hub vibrations when proper amplitude and phase are used. Furthermore, the optimal semi-active control scheme can determine the combination of stiffness variations that produce significant vibration reduction in all components of vibratory hub loads simultaneously. It is demonstrated that desired cyclic variations in properties of the blade root region can be practically achieved using discrete controllable stiffness devices and controllable dampers, especially in the flap and lag directions. These discrete controllable devices can produce 35--50% reduction in a composite vibration index representing all components of vibratory hub loads. No detrimental increases are observed in the lower harmonics of blade loads and blade response (which contribute to the dynamic stresses) and controllable device internal loads, when the optimal stiffness and damping variations are introduced. The effectiveness of optimal stiffness and damping variations in reducing hub vibration is retained over a range of cruise speeds and for variations in fundamental rotor properties. The effectiveness of the semi-active isolator is demonstrated for a simplified single degree of freedom system representing the semi-active isolation system. The rotor
DEFF Research Database (Denmark)
Feng, Ju; Ying, Zu-Guang; Zhu, Wei-Qiu
2012-01-01
A minimax stochastic optimal semi-active control strategy for stochastically excited quasi-integrable Hamiltonian systems with parametric uncertainty by using magneto-rheological (MR) dampers is proposed. Firstly, the control problem is formulated as an n-degree-of-freedom (DOF) controlled, uncer...
Semi Active Control of Civil Structures, Analytical and Numerical Studies
Kerboua, M.; Benguediab, M.; Megnounif, A.; Benrahou, K. H.; Kaoulala, F.
Structural control for civil structures was born out of a need to provide safer and more efficient designs with the reality of limited resources. The purpose of structural control is to absorb and to reflect the energy introduced by dynamic loads such as winds, waves, earthquakes, and traffic. Today, the protection of civil structures from severe dynamic loading is typically achieved by allowing the structures to be damaged. Semi-active control devices, also called "smart" control devices, assume the positive aspects of both the passive and active control devices. A semi-active control strategy is similar to the active control strategy. Only here, the control actuator does not directly apply force to the structure, but instead it is used to control the properties of a passive energy device, a controllable passive damper. Semi-active control strategies can be used in many of the same civil applications as passive and active control. One method of operating smart cable dampers is in a purely passive capacity, supplying the dampers with constant optimal voltage. The advantages to this strategy are the relative simplicity of implementing the control strategy as compared to a smart or active control strategy and that the dampers are more easily optimally tuned in- place, eliminating the need to have passive dampers with unique optimal damping coefficients. This research investigated semi-active control of civil structures for natural hazard mitigation. The research has two components, the seismic protection of buildings and the mitigation of wind-induced vibration in structures. An ideal semi-active motion equation of a composite beam that consists of a cantilever beam bonded with a PZT patch using Hamilton's principle and Galerkin's method was treated. A series R-L and a parallel R-L shunt circuits are coupled into the motion equation respectively by means of the constitutive relation of piezoelectric material and Kirchhoff's law to control the beam vibration. A
Time delay effects on large-scale MR damper based semi-active control strategies
International Nuclear Information System (INIS)
Cha, Y-J; Agrawal, A K; Dyke, S J
2013-01-01
This paper presents a detailed investigation on the robustness of large-scale 200 kN MR damper based semi-active control strategies in the presence of time delays in the control system. Although the effects of time delay on stability and performance degradation of an actively controlled system have been investigated extensively by many researchers, degradation in the performance of semi-active systems due to time delay has yet to be investigated. Since semi-active systems are inherently stable, instability problems due to time delay are unlikely to arise. This paper investigates the effects of time delay on the performance of a building with a large-scale MR damper, using numerical simulations of near- and far-field earthquakes. The MR damper is considered to be controlled by four different semi-active control algorithms, namely (i) clipped-optimal control (COC), (ii) decentralized output feedback polynomial control (DOFPC), (iii) Lyapunov control, and (iv) simple-passive control (SPC). It is observed that all controllers except for the COC are significantly robust with respect to time delay. On the other hand, the clipped-optimal controller should be integrated with a compensator to improve the performance in the presence of time delay. (paper)
A comparison of optimal semi-active suspension systems regarding vehicle ride comfort
Koulocheris, Dimitrios; Papaioannou, Georgios; Chrysos, Emmanouil
2017-10-01
The aim of this work is to present a comparison of the main semi active suspension systems used in a passenger car, after having optimized the suspension systems of the vehicle model in respect with ride comfort and road holding. Thus, a half car model, equipped with controllable dampers, along with a seat and a driver was implemented. Semi-active suspensions have received a lot of attention since they seem to provide the best compromise between cost (energy consumption, actuators/sensors hardware) and performance in comparison with active and passive suspensions. In this work, the semi active suspension systems studied are comfort oriented and consist of (a) the two version of Skyhook control (two states skyhook and skyhook linear approximation damper), (b) the acceleration driven damper (ADD), (c) the power driven damper (PDD), (d) the combination of Skyhook and ADD (Mixed Skyhook-ADD) and (e) the combination of the two with the use of a sensor. The half car model equipped with the above suspension systems was excited by a road bump, and was optimized using genetic algorithms (GA) in respect with ride comfort and road holding. This study aims to highlight how the optimization of the vehicle model could lead to the best compromise between ride comfort and road holding, overcoming their well-known trade-off. The optimum results were compared with important performance metrics regarding the vehicle’s dynamic behaviour in general.
A model for signal processing and predictive control of semi-active ...
Indian Academy of Sciences (India)
Abstract. The theory for structural control has been well developed and applied to perform excellent energy dissipation using dampers. Both active and semi-active control systems may be used to decide on the optimal switch point of the damper based on the current and past structural responses to the excitation of external.
Semi-active control of a cable-stayed bridge under multiple-support excitations.
Dai, Ze-Bing; Huang, Jin-Zhi; Wang, Hong-Xia
2004-03-01
This paper presents a semi-active strategy for seismic protection of a benchmark cable-stayed bridge with consideration of multiple-support excitations. In this control strategy, Magnetorheological (MR) dampers are proposed as control devices, a LQG-clipped-optimal control algorithm is employed. An active control strategy, shown in previous researches to perform well at controlling the benchmark bridge when uniform earthquake motion was assumed, is also used in this study to control this benchmark bridge with consideration of multiple-support excitations. The performance of active control system is compared to that of the presented semi-active control strategy. Because the MR fluid damper is a controllable energy- dissipation device that cannot add mechanical energy to the structural system, the proposed control strategy is fail-safe in that bounded-input, bounded-output stability of the controlled structure is guaranteed. The numerical results demonstrated that the performance of the presented control design is nearly the same as that of the active control system; and that the MR dampers can effectively be used to control seismically excited cable-stayed bridges with multiple-support excitations.
Semi-active vibration control in cable-stayed bridges under the condition of random wind load
International Nuclear Information System (INIS)
Heo, G; Joonryong, Jeon
2014-01-01
This paper aims at an experimental study on the real-time vibration control of bridge structures using a semi-active vibration control method that has been in the spotlight recently. As structures are becoming larger and larger, structural harmful vibration caused by unspecified external forces such as earthquakes, gusts of wind, and collisions has been brought to attention as an important issue. These harmful vibrations can cause not only user anxiety but also severe structural damage or even complete failure of structures. Therefore, in view of structural safety and economical long-term maintenance, real-time control technology of the harmful structural vibration is urgently required. In this paper, a laboratory-scale model of a cable-stayed bridge was built, and a shear-type MR damper and a semi-active vibration control algorithm (Lyapunov and clipped optimal) were applied for the control of harmful vibration of the model bridge, in real time. On the basis of the test results, each semi-active control algorithm was verified quantitatively. (papers)
DEFF Research Database (Denmark)
Bhowmik, Subrata
2011-01-01
This paper presents a neural network based semi-active control method for a rotary type magnetorheological (MR) damper. The characteristics of the MR damper are described by the classic Bouc-Wen model, and the performance of the proposed control method is evaluated in terms of a base exited shear...... to determine the damper current based on the derived optimal damper force. For that reason an inverse MR damper model is also designed based on the neural network identification of the particular rotary MR damper. The performance of the proposed controller is compared to that of an optimal pure viscous damper...
Parameterized data-driven fuzzy model based optimal control of a semi-batch reactor.
Kamesh, Reddi; Rani, K Yamuna
2016-09-01
A parameterized data-driven fuzzy (PDDF) model structure is proposed for semi-batch processes, and its application for optimal control is illustrated. The orthonormally parameterized input trajectories, initial states and process parameters are the inputs to the model, which predicts the output trajectories in terms of Fourier coefficients. Fuzzy rules are formulated based on the signs of a linear data-driven model, while the defuzzification step incorporates a linear regression model to shift the domain from input to output domain. The fuzzy model is employed to formulate an optimal control problem for single rate as well as multi-rate systems. Simulation study on a multivariable semi-batch reactor system reveals that the proposed PDDF modeling approach is capable of capturing the nonlinear and time-varying behavior inherent in the semi-batch system fairly accurately, and the results of operating trajectory optimization using the proposed model are found to be comparable to the results obtained using the exact first principles model, and are also found to be comparable to or better than parameterized data-driven artificial neural network model based optimization results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Numerical research of the optimal control problem in the semi-Markov inventory model
International Nuclear Information System (INIS)
Gorshenin, Andrey K.; Belousov, Vasily V.; Shnourkoff, Peter V.; Ivanov, Alexey V.
2015-01-01
This paper is devoted to the numerical simulation of stochastic system for inventory management products using controlled semi-Markov process. The results of a special software for the system’s research and finding the optimal control are presented
Numerical research of the optimal control problem in the semi-Markov inventory model
Energy Technology Data Exchange (ETDEWEB)
Gorshenin, Andrey K. [Institute of Informatics Problems, Russian Academy of Sciences, Vavilova str., 44/2, Moscow, Russia MIREA, Faculty of Information Technology (Russian Federation); Belousov, Vasily V. [Institute of Informatics Problems, Russian Academy of Sciences, Vavilova str., 44/2, Moscow (Russian Federation); Shnourkoff, Peter V.; Ivanov, Alexey V. [National research university Higher school of economics, Moscow (Russian Federation)
2015-03-10
This paper is devoted to the numerical simulation of stochastic system for inventory management products using controlled semi-Markov process. The results of a special software for the system’s research and finding the optimal control are presented.
Using block pulse functions for seismic vibration semi-active control of structures with MR dampers
Rahimi Gendeshmin, Saeed; Davarnia, Daniel
2018-03-01
This article applied the idea of block pulse functions in the semi-active control of structures. The BP functions give effective tools to approximate complex problems. The applied control algorithm has a major effect on the performance of the controlled system and the requirements of the control devices. In control problems, it is important to devise an accurate analytical technique with less computational cost. It is proved that the BP functions are fundamental tools in approximation problems which have been applied in disparate areas in last decades. This study focuses on the employment of BP functions in control algorithm concerning reduction the computational cost. Magneto-rheological (MR) dampers are one of the well-known semi-active tools that can be used to control the response of civil Structures during earthquake. For validation purposes, numerical simulations of a 5-story shear building frame with MR dampers are presented. The results of suggested method were compared with results obtained by controlling the frame by the optimal control method based on linear quadratic regulator theory. It can be seen from simulation results that the suggested method can be helpful in reducing seismic structural responses. Besides, this method has acceptable accuracy and is in agreement with optimal control method with less computational costs.
Directory of Open Access Journals (Sweden)
Farong Kou
2018-01-01
Full Text Available In order to coordinate the damping performance and energy regenerative performance of energy regenerative suspension, this paper proposes a structure of a vehicle semi-active energy regenerative suspension with an electro-hydraulic actuator (EHA. In light of the proposed concept, a specific energy regenerative scheme is designed and a mechanical properties test is carried out. Based on the test results, the parameter identification for the system model is conducted using a recursive least squares algorithm. On the basis of the system principle, the nonlinear model of the semi-active energy regenerative suspension with an EHA is built. Meanwhile, linear-quadratic-Gaussian control strategy of the system is designed. Then, the influence of the main parameters of the EHA on the damping performance and energy regenerative performance of the suspension is analyzed. Finally, the main parameters of the EHA are optimized via the genetic algorithm. The test results show that when a sinusoidal is input at the frequency of 2 Hz and the amplitude of 30 mm, the spring mass acceleration root meam square value of the optimized EHA semi-active energy regenerative suspension is reduced by 22.23% and the energy regenerative power RMS value is increased by 40.51%, which means that while meeting the requirements of vehicle ride comfort and driving safety, the energy regenerative performance is improved significantly.
Semi-active Control of Magneto-Rheological Dampers with Negative Stiffness
DEFF Research Database (Denmark)
Bhowmik, Subrata
2009-01-01
performance by introduction of apparent negative damper stiffness. The design of the control strategy aims at maximizing the damping ratio of the critical mode of the structure. Explicit solutions for the complex valued natural frequency of the damped structure and the associated damping ratio are obtained...... sufficiently accurate. This is done by letting the desired force be the input to an inverse Bingham model, which provides the corresponding desired voltage level of the MR damper. Numerical simulations are conducted to demonstrate the performance of the proposed semi-active control strategy with apparent......Effective damping of large and flexible structures by semi-active dampers relies greatly on the control strategy applied, which should combine the robustness of passive devices and the increased damping performance often available from active control. For structural control the Magneto...
Semi-active H∞ control of high-speed railway vehicle suspension with magnetorheological dampers
Zong, Lu-Hang; Gong, Xing-Long; Xuan, Shou-Hu; Guo, Chao-Yang
2013-05-01
In this paper, semi-active H∞ control with magnetorheological (MR) dampers for railway vehicle suspension systems to improve the lateral ride quality is investigated. The proposed semi-active controller is composed of a H∞ controller as the system controller and an adaptive neuro-fuzzy inference system (ANFIS) inverse MR damper model as the damper controller. First, a 17-degree-of-freedom model for a full-scale railway vehicle is developed and the random track irregularities are modelled. Then a modified Bouc-Wen model is built to characterise the forward dynamic characteristics of the MR damper and an inverse MR damper model is built with the ANFIS technique. Furthermore, a H∞ controller composed of a yaw motion controller and a rolling pendulum motion (lateral motion+roll motion) controller is established. By integrating the H∞ controller with the ANFIS inverse model, a semi-active H∞ controller for the railway vehicle is finally proposed. Simulation results indicate that the proposed semi-active suspension system possesses better attenuation ability for the vibrations of the car body than the passive suspension system.
Nie, Shida; Zhuang, Ye; Wang, Yong; Guo, Konghui
2018-01-01
The performance of velocity & displacement-dependent damper (VDD), inspired by the semi-active control, is analyzed. The main differences among passive, displacement-dependent and semi-active dampers are compared on their damping properties. Valve assemblies of VDD are modelled to get an insight into its working principle. The mechanical structure composed by four valve assemblies helps to enable VDD to approach the performance by those semi-active control dampers. The valve structure parameters are determined by the suggested two-step process. Hydraulic model of the damper is built with AMEsim. Simulation result of F-V curves, which is similar to those of semi-active control damper, demonstrates that VDD could achieve the similar performance of semi-active control damper. The performance of a quarter vehicle model employing VDD is analyzed and compared with semi-active suspension. Simulation results show that VDD could perform as good as a semi-active control damper. In addition, no add-on hardware or energy consumption is needed for VDD to achieve the remarkable performance.
Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng
2017-10-01
Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.
Design and Test of Semi-Active Vibration-Reducing System for Lathe
Directory of Open Access Journals (Sweden)
Hongsheng Hu
2014-09-01
Full Text Available In this paper, its theory design, analysis and test system of semi-active vibration controlling system used for precision machine have been done. Firstly, lathe bed and spindle entity were modeled by using UG software; Then modes of the machine bed and the key components of spindle were obtained by using ANSYS software; Finally, harmonic response analysis of lathe spindle under complex load was acquired, which provided a basis of MR damper’s structure optimization design for a certain type of precision machine. In order to prove its effectives, a prototype semi-active vibration controlling lathe with MR damper was developed. Tests have been done, and comparison results between passive vibration isolation equipment and semi-active vibration controlling equipment proved its good performances of MR damper.
A Semi-active Control System for Wind Turbines
DEFF Research Database (Denmark)
Caterino, N.; Georgakis, Christos T.; Trinchillo, F.
2014-01-01
A semi-active (SA) control system based on the use of smart magnetorheological (MR) dampers to control the structural response of a wind turbine is proposed herein. The innovative approach is based on the implementation and use of a variable-properties base restraint. This is able to modify in real......, and a control algorithm that instantaneously commands the latter during the motion, making them to modulate the reactive force as needed to achieve the performance goals. The design and operation of such a system are shown with reference to a case study consisting of an almost 100 m tall wind turbine, realized...
Adaptive semi-active control of buildings under seismic solicitations
International Nuclear Information System (INIS)
Roberti, V.; Jezequel, L.
1993-01-01
This paper describes an adaptive semi-active control method whereby nonlinear distributed systems are identified by their dynamical response. Approximate procedures are proposed which take into account the nonlinear behavior of the dynamic system considered. It is shown that only slight knowledge of nonlinearities is needed to apply feedback and feedforward control laws. The method is implemented to a simple example of a building with three degrees of freedom and the numerical results are analyzed
Ragab, Kh. A.; Bouaicha, A.; Bouazara, M.
2017-09-01
The semi-solid casting process has the advantage of providing reliable mechanical aluminum parts that work continuously in dynamic as control arm of the suspension system in automotive vehicles. The quality performance of dynamic control arm is related to casting mold and gating system designs that affect the fluidity of semi-solid metal during filling the mold. Therefore, this study focuses on improvement in mechanical performance, depending on material characterization, and casting design optimization, of suspension control arms made of A357 aluminum semi-solid alloys. Mechanical and design analyses, applied on the suspension arm, showed the occurrence of mechanical failures at unexpected weak points. Metallurgical analysis showed that the main reason lies in the difficult flow of semi-solid paste through the thin thicknesses of a complex geometry. A design modification procedure is applied to the geometry of the suspension arm to avoid this problem and to improve its quality performance. The design modification of parts was carried out by using SolidWorks design software, evaluation of constraints with ABAQUS, and simulation of flow with ProCast software. The proposed designs showed that the modified suspension arm, without ribs and with a central canvas designed as Z, is considered as a perfect casting design showing an increase in the structural strength of the component. In this case, maximum von Mises stress is 199 MPa that is below the yield strength of the material. The modified casting mold design shows a high uniformity and minim turbulence of molten metal flow during semi-solid casting process.
Semi-active control for vibration mitigation of structural systems incorporating uncertainties
International Nuclear Information System (INIS)
Miah, Mohammad S; Chatzi, Eleni N; Weber, Felix
2015-01-01
This study introduces a novel semi-active control scheme, where the linear-quadratic regulator (LQR) is combined with an unscented Kalman filter (UKF) observer, for the real-time mitigation of structural vibration. Due to a number of factors, such as environmental effects and ageing processes, the controlled system may be characterized by uncertainties. The UKF, which comprises a nonlinear observer, is employed herein for devising an adaptive semi-active control scheme capable of tackling such a challenge. This is achieved through the real-time realization of joint state and parameter estimation during the structural control process via the proposed LQR-UKF approach. The behavior of the introduced scheme is exemplified through two numerical applications. The efficacy of the devised methodology is firstly compared against the standard LQR-KF approach in a linear benchmark application where the system model is assumed known a priori, and secondly, the method is validated on a joint state and parameter estimation problem where the system model is assumed uncertain, formulated as nonlinear, and updated in real-time. (paper)
Reducing braking distance by control of semi-active suspension
Energy Technology Data Exchange (ETDEWEB)
Niemz, T.
2007-07-01
This thesis presents a control algorithm for semi-active suspensions to reduce the braking distance of passenger cars. Active shock absorbers are controlled and used to influence the vertical dynamics during ABS-controlled full braking. The core of the approach presented in this paper is based on a switching control logic. The control algorithm is implemented in a compact class passenger car. Test drives on a real road, using a braking machine for reproducibility reasons, have been executed. It could be shown that it is possible to reduce the braking distance by affecting on the vertical dynamics of a passenger car in general. This is the first experimental result of this kind published ever. The amount of reduction depends on the height profile of the testing track chosen and on the initial velocity. On a road with an unevenness comparable to the one on a typical German Autobahn an average reduction of 1-2%, compared to the best passive damping, was achieved. (orig.)
Decentralized stabilization of semi-active vibrating structures
Pisarski, Dominik
2018-02-01
A novel method of decentralized structural vibration control is presented. The control is assumed to be realized by a semi-active device. The objective is to stabilize a vibrating system with the optimal rates of decrease of the energy. The controller relies on an easily implemented decentralized switched state-feedback control law. It uses a set of communication channels to exchange the state information between the neighboring subcontrollers. The performance of the designed method is validated by means of numerical experiments performed for a double cantilever system equipped with a set of elastomers with controlled viscoelastic properties. In terms of the assumed objectives, the proposed control strategy significantly outperforms the passive damping cases and is competitive with a standard centralized control. The presented methodology can be applied to a class of bilinear control systems concerned with smart structural elements.
Directory of Open Access Journals (Sweden)
Rildova
2005-01-01
Full Text Available Based on the observations in the past earthquake events, the traction elevators in buildings are known to be vulnerable to earthquake induced ground motions. Among several components of an elevator, the counterweight being heaviest is also known to be more susceptible than others. The inertial effects of the counterweight can overstress the guide rails on which it moves. Here we investigate to use the well-known acceleration feedback-based active and semi-active control methods to reduce stresses in the rails. The only way a control action can be applied to a moving counterweight-rail system is through a mass damper placed in the plane of the counterweight. For this, a part of the counterweight mass can be configured as a mass damper attached to a small actuator for an active scheme or to a magneto-rheological damper for a semi-active scheme. A comprehensive numerical study is conducted to evaluate the effectiveness of the proposed configuration of control system. It is observed that the two control schemes are effective in reducing the stress response by about 20 to 25% and improve the system fragility over a good range of seismic intensities.
Semi-active control of a sandwich beam partially filled with magnetorheological elastomer
Dyniewicz, Bartłomiej; Bajkowski, Jacek M.; Bajer, Czesław I.
2015-08-01
The paper deals with the semi-active control of vibrations of structural elements. Elastomer composites with ferromagnetic particles that act as magnetorheological fluids are used. The damping coefficient and the shear modulus of the elastomer increases when it is exposed to an electro-magnetic field. The control of this process in time allows us to reduce vibrations more effectively than if the elastomer is permanently exposed to a magnetic field. First the analytical solution for the vibrations of a sandwich beam filled with an elastomer is given. Then the control problem is defined and applied to the analytical formula. The numerical solution of the minimization problem results in a periodic, perfectly rectangular control function if free vibrations are considered. Such a temporarily acting magnetic field is more efficient than a constantly acting one. The surplus reaches 20-50% or more, depending on the filling ratio of the elastomer. The resulting control was verified experimentally in the vibrations of a cantilever sandwich beam. The proposed semi-active control can be directly applied to engineering vibrating structural elements, for example helicopter rotors, aircraft wings, pads under machines, and vehicles.
Development of semi-active hydraulic damper as active interaction ...
Indian Academy of Sciences (India)
Semi-auto controller; displacement semi-active hydraulic damper; ... 2000), and Magnetorheological Damper (Dyke et al 1998) were widely discussed or used. ... driving force provided by electrical motor causes the subordinate structure to ...
Optimal control of motorsport differentials
Tremlett, A. J.; Massaro, M.; Purdy, D. J.; Velenis, E.; Assadian, F.; Moore, A. P.; Halley, M.
2015-12-01
Modern motorsport limited slip differentials (LSD) have evolved to become highly adjustable, allowing the torque bias that they generate to be tuned in the corner entry, apex and corner exit phases of typical on-track manoeuvres. The task of finding the optimal torque bias profile under such varied vehicle conditions is complex. This paper presents a nonlinear optimal control method which is used to find the minimum time optimal torque bias profile through a lane change manoeuvre. The results are compared to traditional open and fully locked differential strategies, in addition to considering related vehicle stability and agility metrics. An investigation into how the optimal torque bias profile changes with reduced track-tyre friction is also included in the analysis. The optimal LSD profile was shown to give a performance gain over its locked differential counterpart in key areas of the manoeuvre where a quick direction change is required. The methodology proposed can be used to find both optimal passive LSD characteristics and as the basis of a semi-active LSD control algorithm.
El-Khoury, O.; Kim, C.; Shafieezadeh, A.; Hur, J. E.; Heo, G. H.
2015-06-01
This study performs a series of numerical simulations and shake-table experiments to design and assess the performance of a nonlinear clipped feedback control algorithm based on optimal polynomial control (OPC) to mitigate the response of a two-span bridge equipped with a magnetorheological (MR) damper. As an extended conventional linear quadratic regulator, OPC provides more flexibility in the control design and further enhances system performance. The challenges encountered in this case are (1) the linearization of the nonlinear behavior of various components and (2) the selection of the weighting matrices in the objective function of OPC. The first challenge is addressed by using stochastic linearization which replaces the nonlinear portion of the system behavior with an equivalent linear time-invariant model considering the stochasticity in the excitation. Furthermore, a genetic algorithm is employed to find optimal weighting matrices for the control design. The input current to the MR damper installed between adjacent spans is determined using a clipped stochastic optimal polynomial control algorithm. The performance of the controlled system is assessed through a set of shake-table experiments for far-field and near-field ground motions. The proposed method showed considerable improvements over passive cases especially for the far-field ground motion.
International Nuclear Information System (INIS)
El-Khoury, O; Shafieezadeh, A; Hur, J E; Kim, C; Heo, G H
2015-01-01
This study performs a series of numerical simulations and shake-table experiments to design and assess the performance of a nonlinear clipped feedback control algorithm based on optimal polynomial control (OPC) to mitigate the response of a two-span bridge equipped with a magnetorheological (MR) damper. As an extended conventional linear quadratic regulator, OPC provides more flexibility in the control design and further enhances system performance. The challenges encountered in this case are (1) the linearization of the nonlinear behavior of various components and (2) the selection of the weighting matrices in the objective function of OPC. The first challenge is addressed by using stochastic linearization which replaces the nonlinear portion of the system behavior with an equivalent linear time-invariant model considering the stochasticity in the excitation. Furthermore, a genetic algorithm is employed to find optimal weighting matrices for the control design. The input current to the MR damper installed between adjacent spans is determined using a clipped stochastic optimal polynomial control algorithm. The performance of the controlled system is assessed through a set of shake-table experiments for far-field and near-field ground motions. The proposed method showed considerable improvements over passive cases especially for the far-field ground motion. (paper)
On generalized semi-infinite optimization and bilevel optimization
Stein, O.; Still, Georg J.
2000-01-01
The paper studies the connections and differences between bilevel problems (BL) and generalized semi-infinite problems (GSIP). Under natural assumptions (GSIP) can be seen as a special case of a (BL). We consider the so-called reduction approach for (BL) and (GSIP) leading to optimality conditions
Availability Control for Means of Transport in Decisive Semi-Markov Models of Exploitation Process
Migawa, Klaudiusz
2012-12-01
The issues presented in this research paper refer to problems connected with the control process for exploitation implemented in the complex systems of exploitation for technical objects. The article presents the description of the method concerning the control availability for technical objects (means of transport) on the basis of the mathematical model of the exploitation process with the implementation of the decisive processes by semi-Markov. The presented method means focused on the preparing the decisive for the exploitation process for technical objects (semi-Markov model) and after that specifying the best control strategy (optimal strategy) from among possible decisive variants in accordance with the approved criterion (criteria) of the activity evaluation of the system of exploitation for technical objects. In the presented method specifying the optimal strategy for control availability in the technical objects means a choice of a sequence of control decisions made in individual states of modelled exploitation process for which the function being a criterion of evaluation reaches the extreme value. In order to choose the optimal control strategy the implementation of the genetic algorithm was chosen. The opinions were presented on the example of the exploitation process of the means of transport implemented in the real system of the bus municipal transport. The model of the exploitation process for the means of transports was prepared on the basis of the results implemented in the real transport system. The mathematical model of the exploitation process was built taking into consideration the fact that the model of the process constitutes the homogenous semi-Markov process.
Directory of Open Access Journals (Sweden)
Zhengchao Xie
2013-01-01
Full Text Available Semi-active air suspension is increasingly used on heavy-duty vehicles due to its capabilities of consuming less power and low cost and providing better ride quality. In this study, a new low cost but effective approach, fuzzy-wheelbase preview controller with wavelet denoising filter (FPW, is developed for semi-active air suspension system. A semi-active suspension system with a rolling lobe air spring is firstly modeled and a novel front axle vertical acceleration-based road prediction model is constructed. By adopting a sensor on the front axle, the road prediction model can predict more reliable road information for the rear wheel. After filtering useless signal noise, the proposed FPW can generate a noise-insensitive control damping force. Simulation results show that the ride quality, the road holding, the handling capability, the road friendliness, and the comprehensive performance of the semi-active air suspension with FPW outperform those with the traditional active suspension with PID-wheelbase preview controller (APP. It can also be seen that, with the addition of the wavelet filter, the impact of sensor noise on the suspension performance can be minimized.
Zamani, Abbas-Ali; Tavakoli, Saeed; Etedali, Sadegh
2017-03-01
Fractional order PID (FOPID) controllers are introduced as a general form of classical PID controllers using fractional calculus. As this controller provides good disturbance rejection and is robust against plant uncertainties it is appropriate for the vibration mitigation in structures. In this paper, an FOPID controller is designed to adjust the contact force of piezoelectric friction dampers for semi-active control of base-isolated structures during far-field and near-field earthquake excitations. A multi-objective cuckoo search algorithm is employed to tune the controller parameters. Considering the resulting Pareto optimal front, the best input for the FOPID controller is selected. For seven pairs of earthquakes and nine performance indices, the performance of the proposed controller is compared with those provided by several well-known control techniques. According to the simulation results, the proposed controller performs better than other controllers in terms of simultaneous reduction of the maximum base displacement and story acceleration for various types of earthquakes. Also, it provides acceptable responses in terms of inter-story drifts, root mean square of base displacements and floor acceleration. In addition, the evaluation of robustness for a stiffness uncertainty of ±10% indicates that the proposed controller gives a robust performance against such modeling errors. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Portfolio Optimization in a Semi-Markov Modulated Market
International Nuclear Information System (INIS)
Ghosh, Mrinal K.; Goswami, Anindya; Kumar, Suresh K.
2009-01-01
We address a portfolio optimization problem in a semi-Markov modulated market. We study both the terminal expected utility optimization on finite time horizon and the risk-sensitive portfolio optimization on finite and infinite time horizon. We obtain optimal portfolios in relevant cases. A numerical procedure is also developed to compute the optimal expected terminal utility for finite horizon problem
Minimum energy control and optimal-satisfactory control of Boolean control network
International Nuclear Information System (INIS)
Li, Fangfei; Lu, Xiwen
2013-01-01
In the literatures, to transfer the Boolean control network from the initial state to the desired state, the expenditure of energy has been rarely considered. Motivated by this, this Letter investigates the minimum energy control and optimal-satisfactory control of Boolean control network. Based on the semi-tensor product of matrices and Floyd's algorithm, minimum energy, constrained minimum energy and optimal-satisfactory control design for Boolean control network are given respectively. A numerical example is presented to illustrate the efficiency of the obtained results.
Semi-active control of tracked vehicle suspension incorporating magnetorheological dampers
Ata, W. G.; Salem, A. M.
2017-05-01
In past years, the application of magnetorheological (MR) and electrorheological dampers in vehicle suspension has been widely studied, mainly for the purpose of vibration control. This paper presents theoretical study to identify an appropriate semi-active control method for MR-tracked vehicle suspension. Three representative control algorithms are simulated including the skyhook, hybrid and fuzzy-hybrid controllers. A seven degrees-of-freedom tracked vehicle suspension model incorporating MR dampers has been adopted for comparison between the performance of the three controllers. The model differential equations are derived based on Newton's second law of motion and the proposed control methods are developed. The performance of each control method under bump and sinusoidal road profiles for different vehicle speeds is simulated and compared with the performance of the conventional suspension system in time and frequency domains. The results show that the performance of tracked vehicle suspension with MR dampers is substantially improved. Moreover, the fuzzy-hybrid controller offers an excellent integrated performance in reducing the body accelerations as well as wheel bounce responses compared with the classical skyhook and hybrid controllers.
Optimal Control via Integrating the Dynamics of Magnetorheological Dampers and Structures
Directory of Open Access Journals (Sweden)
Amir Fayezioghani
2015-03-01
Full Text Available Magnetorheological (MR dampers have the advantage of being tuned by low voltages. This has attracted many researchers to develop semi-active control of structures in theory and practice. Most of the control strategies first obtain the desired forces of dampers without taking their dynamics into consideration and then determine the input voltages according to those forces. As a result, these strategies may face situations where the desired forces cannot be produced by the dampers. In this article, by integrating the equations of the dynamics of MR dampers and the structural motion, and solving them in one set, a more concise semi-active optimal control strategy is presented, so as to bypass the aforementioned drawback. Next, a strong database that can be utilized to form a controller for more realistic implementations is produced. As an illustrative example, the optimal voltages of the dampers of a six-storey shear building are obtained under the scaled El-Centro earthquake and used to train a set of integrated analysis-adaptive neuro-fuzzy inference systems (ANFISs as a controller. Results show that the overall performance of the proposed strategy is higher than most of the other conventional methods.
Energy Technology Data Exchange (ETDEWEB)
Addona, Davide, E-mail: d.addona@campus.unimib.it [Università degli Studi di Milano Bicocca, (MILANO BICOCCA) Dipartimento di Matematica (Italy)
2015-08-15
We obtain weighted uniform estimates for the gradient of the solutions to a class of linear parabolic Cauchy problems with unbounded coefficients. Such estimates are then used to prove existence and uniqueness of the mild solution to a semi-linear backward parabolic Cauchy problem, where the differential equation is the Hamilton–Jacobi–Bellman equation of a suitable optimal control problem. Via backward stochastic differential equations, we show that the mild solution is indeed the value function of the controlled equation and that the feedback law is verified.
International Nuclear Information System (INIS)
Moutinho, Carlos
2015-01-01
This paper is focused on the control problems related to semi-active tuned mass dampers (TMDs) used to reduce harmonic vibrations, specially involving civil structures. A simplified version of the phase control law is derived and its effectiveness is investigated and evaluated. The objective is to improve the functioning of control systems of this type by simplifying the measurement process and reducing the number of variables involved, making the control system more feasible and reliable. Because the control law is of ON/OFF type, combined with appropriate trigger conditions, the activity of the actuation system may be significantly reduced, which may be of few seconds a day in many practical cases, increasing the durability of the device and reducing its maintenance. Moreover, due to the ability of the control system to command the motion of the inertial mass, the semi-active TMD is relatively insensitive to its initial tuning, resulting in the capability of self-tuning and in the possibility of controlling several vibration modes of a structure over a significant broadband frequency. (paper)
DEFF Research Database (Denmark)
Zhou, Q.; Nielsen, Søren R.K.; Qu, W. L.
2006-01-01
Three-dimensional semi-active vibration control of an inclined sag cable with discrete magnetorheological (MR) dampers is investigated in this paper using the finite difference method (FDM). A modified Dahl model is used to describe the dynamic property of MR damper. The nonlinear equations...
State observer-based sliding mode control for semi-active hydro-pneumatic suspension
Ren, Hongbin; Chen, Sizhong; Zhao, Yuzhuang; Liu, Gang; Yang, Lin
2016-02-01
This paper proposes an improved virtual reference model for semi-active suspension to coordinate the vehicle ride comfort and handling stability. The reference model combines the virtues of sky-hook with ground-hook control logic, and the hybrid coefficient is tuned according to the longitudinal and lateral acceleration so as to improve the vehicle stability especially in high-speed condition. Suspension state observer based on unscented Kalman filter is designed. A sliding mode controller (SMC) is developed to track the states of the reference model. The stability of the SMC strategy is proven by means of Lyapunov function taking into account the nonlinear damper characteristics and sprung mass variation of the vehicle. Finally, the performance of the controller is demonstrated under three typical working conditions: the random road excitation, speed bump road and sharp acceleration and braking. The simulation results indicated that, compared with the traditional passive suspension, the proposed control algorithm can offer a better coordination between vehicle ride comfort and handling stability. This approach provides a viable alternative to costlier active suspension control systems for commercial vehicles.
Modelling and optimization of semi-solid processing of 7075 Al alloy
Binesh, B.; Aghaie-Khafri, M.
2017-09-01
The new modified strain-induced melt activation (SIMA) process presented by Binesh and Aghaie-Khafri was optimized using a response surface methodology to improve the thixotropic characteristics of semi-solid 7075 alloy. The responses, namely the average grain size and the shape factor, were considered as functions of three independent input variables: effective strain, isothermal holding temperature and time. Mathematical models for the responses were developed using the regression analysis technique, and the adequacy of the models was validated by the analysis of variance method. The calculated results correlated fairly well with the experiments. It was found that all the first- and second-order terms of the independent parameters and the interactive terms of the effective strain and holding time were statistically significant for the responses. In order to simultaneously optimize the responses, the desirable values for the effective strain, holding temperature and time were predicted to be 5.1, 609 °C and 14 min, respectively, when employing the desirability function approach. Based on the optimization results, a significant improvement in the average grain size and shape factor of the semi-solid slurry prepared by the new modified SIMA process was observed.
A reduced energy supply strategy in active vibration control
Ichchou, M. N.; Loukil, T.; Bareille, O.; Chamberland, G.; Qiu, J.
2011-12-01
In this paper, a control strategy is presented and numerically tested. This strategy aims to achieve the potential performance of fully active systems with a reduced energy supply. These energy needs are expected to be comparable to the power demands of semi-active systems, while system performance is intended to be comparable to that of a fully active configuration. The underlying strategy is called 'global semi-active control'. This control approach results from an energy investigation based on management of the optimal control process. Energy management encompasses storage and convenient restitution. The proposed strategy monitors a given active law without any external energy supply by considering purely dissipative and energy-demanding phases. Such a control law is offered here along with an analysis of its properties. A suboptimal form, well adapted for practical implementation steps, is also given. Moreover, a number of numerical experiments are proposed in order to validate test findings.
A reduced energy supply strategy in active vibration control
International Nuclear Information System (INIS)
Ichchou, M N; Loukil, T; Bareille, O; Chamberland, G; Qiu, J
2011-01-01
In this paper, a control strategy is presented and numerically tested. This strategy aims to achieve the potential performance of fully active systems with a reduced energy supply. These energy needs are expected to be comparable to the power demands of semi-active systems, while system performance is intended to be comparable to that of a fully active configuration. The underlying strategy is called 'global semi-active control'. This control approach results from an energy investigation based on management of the optimal control process. Energy management encompasses storage and convenient restitution. The proposed strategy monitors a given active law without any external energy supply by considering purely dissipative and energy-demanding phases. Such a control law is offered here along with an analysis of its properties. A suboptimal form, well adapted for practical implementation steps, is also given. Moreover, a number of numerical experiments are proposed in order to validate test findings
Optimizing area under the ROC curve using semi-supervised learning.
Wang, Shijun; Li, Diana; Petrick, Nicholas; Sahiner, Berkman; Linguraru, Marius George; Summers, Ronald M
2015-01-01
Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two classes. Traditional AUC optimization techniques are supervised learning methods that utilize only labeled data (i.e., the true class is known for all data) to train the classifiers. In this work, inspired by semi-supervised and transductive learning, we propose two new AUC optimization algorithms hereby referred to as semi-supervised learning receiver operating characteristic (SSLROC) algorithms, which utilize unlabeled test samples in classifier training to maximize AUC. Unlabeled samples are incorporated into the AUC optimization process, and their ranking relationships to labeled positive and negative training samples are considered as optimization constraints. The introduced test samples will cause the learned decision boundary in a multidimensional feature space to adapt not only to the distribution of labeled training data, but also to the distribution of unlabeled test data. We formulate the semi-supervised AUC optimization problem as a semi-definite programming problem based on the margin maximization theory. The proposed methods SSLROC1 (1-norm) and SSLROC2 (2-norm) were evaluated using 34 (determined by power analysis) randomly selected datasets from the University of California, Irvine machine learning repository. Wilcoxon signed rank tests showed that the proposed methods achieved significant improvement compared with state-of-the-art methods. The proposed methods were also applied to a CT colonography dataset for colonic polyp classification and showed promising results.
Semi-Active Control of Precast RC Columns under Seismic Action
Caterino, Nicola; Spizzuoco, Mariacristina
2017-10-01
This work is inspired by the idea of dissipating seismic energy at the base of prefabricated RC columns via semi-active (SA) variable dampers exploiting the base rocking. It was performed a wide numerical campaign to investigate the seismic behaviour of a pre-cast RC column with a variable base restraint. The latter is based on the combined use of a hinge, elastic springs, and magnetorheological (MR) dampers remotely controlled according to the instantaneous response of the structural component. The MR devices are driven by a SA control algorithm purposely written to modulate the dissipative capability so as to reduce base bending moment without causing excessive displacement at the top. The proposed strategy results to be really promising, since the base restraint relaxation, that favours the base moment demand reduction, is accompanied by a high enhancement of the dissipated energy due to rocking that can be even able to reduce top displacement in respect to the “fixed base rotation” conditions.
On the Benefits of Semi-Active Suspensions with Inerters
Directory of Open Access Journals (Sweden)
Xin-Jie Zhang
2012-01-01
Full Text Available Inerters have become a hot topic in recent years especially in vehicle, train, building suspension systems, etc. Eight different layouts of suspensions were analyzed with a quarter-car model in this paper. Dimensionless root mean square (RMS responses of the sprung mass vertical acceleration, the suspension travel, and the tire deflection are derived which were used to evaluate the performance of the quarter-car model. The behaviour of semi-active suspensions with inerters using Groundhook, Skyhook, and Hybrid control has been evaluated and compared to the performance of passive suspensions with inerters. Sensitivity analysis was applied to the development of a high performance semi-active suspension with an inerter. Numerical simulations indicate that a semi-active suspension with an inerter has much better performance than the passive suspension with an inerter, especially with the Hybrid control method, which has the best compromise between comfort and road holding quality.
Optimal Wentzell Boundary Control of Parabolic Equations
International Nuclear Information System (INIS)
Luo, Yousong
2017-01-01
This paper deals with a class of optimal control problems governed by an initial-boundary value problem of a parabolic equation. The case of semi-linear boundary control is studied where the control is applied to the system via the Wentzell boundary condition. The differentiability of the state variable with respect to the control is established and hence a necessary condition is derived for the optimal solution in the case of both unconstrained and constrained problems. The condition is also sufficient for the unconstrained convex problems. A second order condition is also derived.
Optimal Wentzell Boundary Control of Parabolic Equations
Energy Technology Data Exchange (ETDEWEB)
Luo, Yousong, E-mail: yousong.luo@rmit.edu.au [RMIT University, School of Mathematical and Geospatial Sciences (Australia)
2017-04-15
This paper deals with a class of optimal control problems governed by an initial-boundary value problem of a parabolic equation. The case of semi-linear boundary control is studied where the control is applied to the system via the Wentzell boundary condition. The differentiability of the state variable with respect to the control is established and hence a necessary condition is derived for the optimal solution in the case of both unconstrained and constrained problems. The condition is also sufficient for the unconstrained convex problems. A second order condition is also derived.
Directory of Open Access Journals (Sweden)
Sang-Hoon Yeo
2016-12-01
Full Text Available Movement planning is thought to be primarily determined by motor costs such as inaccuracy and effort. Solving for the optimal plan that minimizes these costs typically leads to specifying a time-varying feedback controller which both generates the movement and can optimally correct for errors that arise within a movement. However, the quality of the sensory feedback during a movement can depend substantially on the generated movement. We show that by incorporating such state-dependent sensory feedback, the optimal solution incorporates active sensing and is no longer a pure feedback process but includes a significant feedforward component. To examine whether people take into account such state-dependency in sensory feedback we asked people to make movements in which we controlled the reliability of sensory feedback. We made the visibility of the hand state-dependent, such that the visibility was proportional to the component of hand velocity in a particular direction. Subjects gradually adapted to such a sensory perturbation by making curved hand movements. In particular, they appeared to control the late visibility of the movement matching predictions of the optimal controller with state-dependent sensory noise. Our results show that trajectory planning is not only sensitive to motor costs but takes sensory costs into account and argues for optimal control of movement in which feedforward commands can play a significant role.
Yeo, Sang-Hoon; Franklin, David W; Wolpert, Daniel M
2016-12-01
Movement planning is thought to be primarily determined by motor costs such as inaccuracy and effort. Solving for the optimal plan that minimizes these costs typically leads to specifying a time-varying feedback controller which both generates the movement and can optimally correct for errors that arise within a movement. However, the quality of the sensory feedback during a movement can depend substantially on the generated movement. We show that by incorporating such state-dependent sensory feedback, the optimal solution incorporates active sensing and is no longer a pure feedback process but includes a significant feedforward component. To examine whether people take into account such state-dependency in sensory feedback we asked people to make movements in which we controlled the reliability of sensory feedback. We made the visibility of the hand state-dependent, such that the visibility was proportional to the component of hand velocity in a particular direction. Subjects gradually adapted to such a sensory perturbation by making curved hand movements. In particular, they appeared to control the late visibility of the movement matching predictions of the optimal controller with state-dependent sensory noise. Our results show that trajectory planning is not only sensitive to motor costs but takes sensory costs into account and argues for optimal control of movement in which feedforward commands can play a significant role.
Averaging and Linear Programming in Some Singularly Perturbed Problems of Optimal Control
Energy Technology Data Exchange (ETDEWEB)
Gaitsgory, Vladimir, E-mail: vladimir.gaitsgory@mq.edu.au [Macquarie University, Department of Mathematics (Australia); Rossomakhine, Sergey, E-mail: serguei.rossomakhine@flinders.edu.au [Flinders University, Flinders Mathematical Sciences Laboratory, School of Computer Science, Engineering and Mathematics (Australia)
2015-04-15
The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite time horizon. We mostly focus on problems with time discounting criteria but a possibility of the extension of results to periodic optimization problems is discussed as well. Our consideration is based on earlier results on averaging of SP control systems and on linear programming formulations of optimal control problems. The idea that we exploit is to first asymptotically approximate a given problem of optimal control of the SP system by a certain averaged optimal control problem, then reformulate this averaged problem as an infinite-dimensional linear programming (LP) problem, and then approximate the latter by semi-infinite LP problems. We show that the optimal solution of these semi-infinite LP problems and their duals (that can be found with the help of a modification of an available LP software) allow one to construct near optimal controls of the SP system. We demonstrate the construction with two numerical examples.
Ride performance of a high speed rail vehicle using controlled semi active suspension system
Sharma, Sunil Kumar; Kumar, Anil
2017-05-01
The rail-wheel interaction in a rail vehicle running at high speed results in large amplitude vibration of carbody that deteriorates the ride comfort of travellers. The role of suspension system is crucial to provide an acceptable level of ride performance. In this context, an existing rail vehicle is modelled in vertical, pitch and roll motions of carbody and bogies. Additionally, nonlinear stiffness and damping parameters of passive suspension system are defined based on experimental data. In the secondary vertical suspension system, a magneto-rheological (MR) damper is included to improve the ride quality and comfort. The parameters of MR damper depend on the current, amplitude and frequency of excitations. At different running speeds, three semi-active suspension strategies with MR damper are analysed for periodic track irregularity and the resulting performance indices are juxtaposed with the nonlinear passive suspension system. The disturbance rejection and force tracking damper controller algorithms are applied to control the desired force of MR damper. This study reveals that the vertical vibrations of a vehicle can be reduced significantly by using the proposed semi-active suspension strategies. Moreover, it naturally results in improved ride quality and passenger’s comfort in comparison to the existing passive system.
Decreasing the damage in smart structures using integrated online DDA/ISMP and semi-active control
International Nuclear Information System (INIS)
Karami, K; Amini, F
2012-01-01
Integrated structural health monitoring (SHM) and vibration control has been considered recently by researchers. Up to now, all of the research in the field of integrated SHM and vibration control has been conducted using control devices and control algorithms to enhance system identification and damage detection. In this study, online SHM is used to improve the performance of structural vibration control, unlike previous research. Also, a proposed algorithm including integrated online SHM and a semi-active control strategy is used to reduce both damage and seismic response of the main structure due to strong seismic disturbance. In the proposed algorithm the nonlinear behavior of the building structure is simulated during the excitation. Then, using the measured data and the damage detection algorithm based on identified system Markov parameters (DDA/ISMP), a method proposed by the authors, damage corresponding to axial and bending stiffness of all structural elements is identified. In this study, a 20 t MR damper is employed as a control device to mitigate both damage and dynamic response of the building structure. Also, the interaction between SHM and a semi-active control strategy is assessed. To illustrate the efficiency of the proposed algorithm, a two bay two story steel braced frame structure is used. By defining the damage index and damage rate index, the input current of the MR damper is generated using a fuzzy logic controller. The obtained results show that the possibility of smart building creation is provided using the proposed algorithm. In comparison to the widely used strategy of only vibration control, it is shown that the proposed algorithm is more effective. Furthermore, in the proposed algorithm, the total consumed current intensity and generated control forces are considerably less than for the strategy of only vibration control. (paper)
Decreasing the damage in smart structures using integrated online DDA/ISMP and semi-active control
Karami, K.; Amini, F.
2012-10-01
Integrated structural health monitoring (SHM) and vibration control has been considered recently by researchers. Up to now, all of the research in the field of integrated SHM and vibration control has been conducted using control devices and control algorithms to enhance system identification and damage detection. In this study, online SHM is used to improve the performance of structural vibration control, unlike previous research. Also, a proposed algorithm including integrated online SHM and a semi-active control strategy is used to reduce both damage and seismic response of the main structure due to strong seismic disturbance. In the proposed algorithm the nonlinear behavior of the building structure is simulated during the excitation. Then, using the measured data and the damage detection algorithm based on identified system Markov parameters (DDA/ISMP), a method proposed by the authors, damage corresponding to axial and bending stiffness of all structural elements is identified. In this study, a 20 t MR damper is employed as a control device to mitigate both damage and dynamic response of the building structure. Also, the interaction between SHM and a semi-active control strategy is assessed. To illustrate the efficiency of the proposed algorithm, a two bay two story steel braced frame structure is used. By defining the damage index and damage rate index, the input current of the MR damper is generated using a fuzzy logic controller. The obtained results show that the possibility of smart building creation is provided using the proposed algorithm. In comparison to the widely used strategy of only vibration control, it is shown that the proposed algorithm is more effective. Furthermore, in the proposed algorithm, the total consumed current intensity and generated control forces are considerably less than for the strategy of only vibration control.
Bilateral human-robot control for semi-autonomous UAV navigation
Wopereis, Han Willem; Fumagalli, Matteo; Stramigioli, Stefano; Carloni, Raffaella
2015-01-01
This paper proposes a semi-autonomous bilateral control architecture for unmanned aerial vehicles. During autonomous navigation, a human operator is allowed to assist the autonomous controller of the vehicle by actively changing its navigation parameters to assist it in critical situations, such as
Semi-active friction damper for buildings subject to seismic excitation
Mantilla, Juan S.; Solarte, Alexander; Gomez, Daniel; Marulanda, Johannio; Thomson, Peter
2016-04-01
Structural control systems are considered an effective alternative for reducing vibrations in civil structures and are classified according to their energy supply requirement: passive, semi-active, active and hybrid. Commonly used structural control systems in buildings are passive friction dampers, which add energy dissipation through damping mechanisms induced by sliding friction between their surfaces. Semi-Active Variable Friction Dampers (SAVFD) allow the optimum efficiency range of friction dampers to be enhanced by controlling the clamping force in real time. This paper describes the development and performance evaluation of a low-cost SAVFD for the reduction of vibrations of structures subject to earthquakes. The SAVFD and a benchmark structural control test structure were experimentally characterized and analytical models were developed and updated based on the dynamic characterization. Decentralized control algorithms were implemented and tested on a shaking table. Relative displacements and accelerations of the structure controlled with the SAVFD were 80% less than those of the uncontrolled structure
A novel technique for active vibration control, based on optimal
Indian Academy of Sciences (India)
In the last few decades, researchers have proposed many control techniques to suppress unwanted vibrations in a structure. In this work, a novel and simple technique is proposed for the active vibration control. In this technique, an optimal tracking control is employed to suppress vibrations in a structure by simultaneously ...
The Method of Optimization of Hydropower Plant Performance for Use in Group Active Power Controller
Directory of Open Access Journals (Sweden)
Glazyrin G.V.
2017-04-01
Full Text Available The problem of optimization of hydropower plant performance is considered in this paper. A new method of calculation of optimal load-sharing is proposed. The method is based on application of incremental water flow curves representing relationship between the per unit increase of water flow and active power. The optimal load-sharing is obtained by solving the nonlinear equation governing the balance of total active power and the station power set point with the same specific increase of water flow for all turbines. Unlike traditional optimization techniques, the solution of the equation is obtained without taking into account unit safe operating zones. Instead, if calculated active power of a unit violates the permissible power range, load-sharing is recalculated for the remaining generating units. Thus, optimal load-sharing algorithm suitable for digital control systems is developed. The proposed algorithm is implemented in group active power controller in Novosibirsk hydropower plant. An analysis of operation of group active power controller proves that the application of the proposed method allows obtaining optimal load-sharing at each control step with sufficient precision.
Directory of Open Access Journals (Sweden)
Tian Jiande
2015-01-01
Full Text Available A kind of semi-active hydraulic engine mount is studied in this paper. After careful analysis of its structure and working principle, the FEA simulation of it was divided into two cases. One is the solenoid valve is open, so the air chamber connects to the atmosphere, and Fluid-Structure Interaction was used. Another is the solenoid valve is closed, and the air chamber has pressure, so Fluid-Structure-Gas Interaction was used. The test of this semi-active hydraulic engine mount was carried out to compare with the simulation results, and verify the accuracy of the model. Then the dynamic characteristics-dynamic stiffness and damping angle were analysed by simulation and test. This paper provides theoretical support for the development and optimization of the semi-active hydraulic engine mount.
A semi-active control suspension system for railway vehicles with magnetorheological fluid dampers
Wei, Xiukun; Zhu, Ming; Jia, Limin
2016-07-01
The high-speed train has achieved great progress in the last decades. It is one of the most important modes of transportation between cities. With the rapid development of the high-speed train, its safety issue is paid much more attention than ever before. To improve the stability of the vehicle with high speed, extra dampers (i.e. anti-hunting damper) are used in the traditional bogies with passive suspension system. However, the curving performance of the vehicle is undermined due to the extra lateral force generated by the dampers. The active suspension systems proposed in the last decades attempt to solve the vehicle steering issue. However, the active suspension systems need extra actuators driven by electrical power or hydraulic power. There are some implementation and even safety issues which are not easy to be overcome. In this paper, an innovative semi-active controlled lateral suspension system for railway vehicles is proposed. Four magnetorheological fluid dampers are fixed to the primary suspension system of each bogie. They are controlled by online controllers for enhancing the running stability on the straight track line on the one hand and further improving the curving performance by controlling the damper force on the other hand. Two control strategies are proposed in the light of the pure rolling concept. The effectiveness of the proposed strategies is demonstrated by SIMPACK and Matlab co-simulation for a full railway vehicle with two conventional bogies.
Real-time Collision Avoidance and Path Optimizer for Semi-autonomous UAVs.
Hawary, A. F.; Razak, N. A.
2018-05-01
Whilst UAV offers a potentially cheaper and more localized observation platform than current satellite or land-based approaches, it requires an advance path planner to reveal its true potential, particularly in real-time missions. Manual control by human will have limited line-of-sights and prone to errors due to careless and fatigue. A good alternative solution is to equip the UAV with semi-autonomous capabilities that able to navigate via a pre-planned route in real-time fashion. In this paper, we propose an easy-and-practical path optimizer based on the classical Travelling Salesman Problem and adopts a brute force search method to re-optimize the route in the event of collisions using range finder sensor. The former utilizes a Simple Genetic Algorithm and the latter uses Nearest Neighbour algorithm. Both algorithms are combined to optimize the route and avoid collision at once. Although many researchers proposed various path planning algorithms, we find that it is difficult to integrate on a basic UAV model and often lacks of real-time collision detection optimizer. Therefore, we explore a practical benefit from this approach using on-board Arduino and Ardupilot controllers by manually emulating the motion of an actual UAV model prior to test on the flying site. The result showed that the range finder sensor provides a real-time data to the algorithm to find a collision-free path and eventually optimized the route successfully.
International Nuclear Information System (INIS)
Kawashima, T
2016-01-01
To reduce the risk of injury to an infant in an in-car crib (or in a child safety bed) collision shock during a car crash, it is necessary to maintain a constant force acting on the crib below a certain allowable value. To realize this objective, we propose a semi-active in-car crib system with the joint application of regular and inverted pendulum mechanisms. The arms of the proposed crib system support the crib like a pendulum while the pendulum system itself is supported like an inverted pendulum by the arms. In addition, the friction torque of each arm is controlled using a brake mechanism that enables the proposed in-car crib to decrease the acceleration of the crib gradually and maintain it around the target value. This system not only reduces the impulsive force but also transfers the force to the infant's back using a spin control system, i.e., the impulse force acts is made to act perpendicularly on the crib. The spin control system was developed in our previous work. This work focuses on the acceleration control system. A semi-active control law with acceleration feedback is introduced, and the effectiveness of the system is demonstrated using numerical simulation and model experiment. (paper)
Kawashima, T.
2016-09-01
To reduce the risk of injury to an infant in an in-car crib (or in a child safety bed) collision shock during a car crash, it is necessary to maintain a constant force acting on the crib below a certain allowable value. To realize this objective, we propose a semi-active in-car crib system with the joint application of regular and inverted pendulum mechanisms. The arms of the proposed crib system support the crib like a pendulum while the pendulum system itself is supported like an inverted pendulum by the arms. In addition, the friction torque of each arm is controlled using a brake mechanism that enables the proposed in-car crib to decrease the acceleration of the crib gradually and maintain it around the target value. This system not only reduces the impulsive force but also transfers the force to the infant's back using a spin control system, i.e., the impulse force acts is made to act perpendicularly on the crib. The spin control system was developed in our previous work. This work focuses on the acceleration control system. A semi-active control law with acceleration feedback is introduced, and the effectiveness of the system is demonstrated using numerical simulation and model experiment.
A semi-active suspension control algorithm for vehicle comprehensive vertical dynamics performance
Nie, Shida; Zhuang, Ye; Liu, Weiping; Chen, Fan
2017-08-01
Comprehensive performance of the vehicle, including ride qualities and road-holding, is essentially of great value in practice. Many up-to-date semi-active control algorithms improve vehicle dynamics performance effectively. However, it is hard to improve comprehensive performance for the conflict between ride qualities and road-holding around the second-order resonance. Hence, a new control algorithm is proposed to achieve a good trade-off between ride qualities and road-holding. In this paper, the properties of the invariant points are analysed, which gives an insight into the performance conflicting around the second-order resonance. Based on it, a new control algorithm is proposed. The algorithm employs a novel frequency selector to balance suspension ride and handling performance by adopting a medium damping around the second-order resonance. The results of this study show that the proposed control algorithm could improve the performance of ride qualities and suspension working space up to 18.3% and 8.2%, respectively, with little loss of road-holding compared to the passive suspension. Consequently, the comprehensive performance can be improved by 6.6%. Hence, the proposed algorithm is of great potential to be implemented in practice.
Semi-active control of monopile offshore wind turbines under multi-hazards
Sun, C.
2018-01-01
The present paper studies the control of monopile offshore wind turbines subjected to multi-hazards consisting of wind, wave and earthquake. A Semi-active tuned mass damper (STMD) with tunable natural frequency and damping ratio is introduced to control the dynamic response. A new fully coupled analytical model of the monopile offshore wind turbine with an STMD is established. The aerodynamic, hydrodynamic and seismic loading models are derived. Soil effects and damage are considered. The National Renewable Energy Lab monopile 5 MW baseline wind turbine model is employed to examine the performance of the STMD. A passive tuned mass damper (TMD) is utilized for comparison. Through numerical simulation, it is found that before damage occurs, the wind and wave induced response is more dominant than the earthquake induced response. With damage presence in the tower and the foundation, the nacelle and the tower response is increased dramatically and the natural frequency is decreased considerably. As a result, the passive TMD with fixed parameters becomes off-tuned and loses its effectiveness. In comparison, the STMD retuned in real-time demonstrates consistent effectiveness in controlling the dynamic response of the monopile offshore wind turbines under multi-hazards and damage with a smaller stroke.
Energy Technology Data Exchange (ETDEWEB)
Bai, Xian-Xu, E-mail: bai@hfut.edu.cn [Department of Vehicle Engineering, Hefei University of Technology, Hefei 230009 (China); Wereley, Norman M.; Hu, Wei [Department of Aerospace Engineering, University of Maryland, College Park, Maryland 20742 (United States)
2015-05-07
A single-degree-of-freedom (SDOF) semi-active vibration control system based on a magnetorheological (MR) damper with an inner bypass is investigated in this paper. The MR damper employing a pair of concentric tubes, between which the key structure, i.e., the inner bypass, is formed and MR fluids are energized, is designed to provide large dynamic range (i.e., ratio of field-on damping force to field-off damping force) and damping force range. The damping force performance of the MR damper is modeled using phenomenological model and verified by the experimental tests. In order to assess its feasibility and capability in vibration control systems, the mathematical model of a SDOF semi-active vibration control system based on the MR damper and skyhook control strategy is established. Using an MTS 244 hydraulic vibration exciter system and a dSPACE DS1103 real-time simulation system, experimental study for the SDOF semi-active vibration control system is also conducted. Simulation results are compared to experimental measurements.
Soft Computing Optimizer For Intelligent Control Systems Design: The Structure And Applications
Directory of Open Access Journals (Sweden)
Sergey A. Panfilov
2003-10-01
Full Text Available Soft Computing Optimizer (SCO as a new software tool for design of robust intelligent control systems is described. It is based on the hybrid methodology of soft computing and stochastic simulation. It uses as an input the measured or simulated data about the modeled system. SCO is used to design an optimal fuzzy inference system, which approximates a random behavior of control object with the certain accuracy. The task of the fuzzy inference system construction is reduced to the subtasks such as forming of the linguistic variables for each input and output variable, creation of rule data base, optimization of rule data base and refinement of the parameters of the membership functions. Each task by the corresponding genetic algorithm (with an appropriate fitness function is solved. The result of SCO application is the design of Knowledge Base of a Fuzzy Controller, which contains the value information about developed fuzzy inference system. Such value information can be downloaded into the actual fuzzy controller to perform online fuzzy control. Simulations results of robust fuzzy control of nonlinear dynamic systems and experimental results of application on automotive semi-active suspension control are demonstrated.
Design and optimization of mixed flow pump impeller blades by varying semi-cone angle
Dash, Nehal; Roy, Apurba Kumar; Kumar, Kaushik
2018-03-01
The mixed flow pump is a cross between the axial and radial flow pump. These pumps are used in a large number of applications in modern fields. For the designing of these mixed flow pump impeller blades, a lot number of design parameters are needed to be considered which makes this a tedious task for which fundamentals of turbo-machinery and fluid mechanics are always prerequisites. The semi-cone angle of mixed flow pump impeller blade has a specified range of variations generally between 45o to 60o. From the literature review done related to this topic researchers have considered only a particular semi-cone angle and all the calculations are based on this very same semi-cone angle. By varying this semi-cone angle in the specified range, it can be verified if that affects the designing of the impeller blades for a mixed flow pump. Although a lot of methods are available for designing of mixed flow pump impeller blades like inverse time marching method, the pseudo-stream function method, Fourier expansion singularity method, free vortex method, mean stream line theory method etc. still the optimized design of the mixed flow pump impeller blade has been a cumbersome work. As stated above since all the available research works suggest or propose the blade designs with constant semi-cone angle, here the authors have designed the impeller blades by varying the semi-cone angle in a particular range with regular intervals for a Mixed-Flow pump. Henceforth several relevant impeller blade designs are obtained and optimization is carried out to obtain the optimized design (blade with optimal geometry) of impeller blade.
International Nuclear Information System (INIS)
Chigbu, P.E.; Ukekwe, E.C.; Ikekeonwu, G.A.M.
2006-12-01
There is a special family of the (n x n)/k semi-Latin squares called the Trojan squares which are optimal among semi-Latin squares of equivalent sizes. Unfortunately, Trojan squares do not exist for all k; for instance, there is no Trojan square for k ≥ n. However, the need usually arises for constructing optimal semi-Latin squares where no Trojan squares exist. Bailey made a conjecture on optimal semi-Latin squares for k ≥ n and based on this conjecture, optimal non-Trojan semi-Latin squares are here constructed for k = n, considering the inherent Trojan squares for k < n. A lemma substantiating this conjecture for k = n is given and proved. In addition, the properties for the admissible permutation sets used in constructing these optimal squares are made evident based on the systematic-group-theoretic algorithm of Bailey and Chigbu. Algorithms for identifying the admissible permutations as well as constructing the optimal non-Trojan (n x n)/k = n semi-Latin squares for odd n and n = 4 are given. (author)
Energy Technology Data Exchange (ETDEWEB)
Poure, P. [Laboratoire d' Instrumentation Electronique de Nancy LIEN, EA 3440, Nancy-Universite, Faculte des Sciences et Techniques, BP 239, 54506 Vandoeuvre Cedex (France); Weber, P.; Theilliol, D. [Centre de Recherche en Automatique de Nancy UMR 7039, Nancy-Universite, CNRS, Faculte des Sciences et Techniques, BP 239, 54506 Vandoeuvre Cedex (France); Saadate, S. [Groupe de Recherches en Electrotechnique et Electronique de Nancy UMR 7037, Nancy-Universite, CNRS, Faculte des Sciences et Techniques, BP 239, 54506 Vandoeuvre Cedex (France)
2009-02-15
This paper deals with fault tolerant shunt three-phase three-wire active filter topologies for which reliability is very important in industry applications. The determination of the optimal reconfiguration structure among various ones with or without redundant components is discussed based on reliability criteria. First, the reconfiguration of the inverter is detailed and a fast fault diagnosis method for power semi-conductor or driver fault detection and compensation is presented. This method avoids false fault detection due to power semi-conductors switching. The control architecture and algorithm are studied and a fault tolerant control strategy is considered. Simulation results in open and short circuit cases validate the theoretical study. Finally, the reliability of the studied three-phase three-wire filter shunt active topologies is analyzed to determine the optimal one. (author)
Semi-definite relaxations for optimal control problems with oscillation and concentration effects
Czech Academy of Sciences Publication Activity Database
Claeys, M.; Henrion, D.; Kružík, Martin
2017-01-01
Roč. 23, č. 1 (2017), s. 95-117 ISSN 1292-8119 Institutional support: RVO:67985556 Keywords : optimal control * impulsive control * semidefinite programming Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 1.540, year: 2016 http://library.utia.cas.cz/separaty/2017/MTR/kruzik-0470207.pdf
Control Chart on Semi Analytical Weighting
Miranda, G. S.; Oliveira, C. C.; Silva, T. B. S. C.; Stellato, T. B.; Monteiro, L. R.; Marques, J. R.; Faustino, M. G.; Soares, S. M. V.; Ulrich, J. C.; Pires, M. A. F.; Cotrim, M. E. B.
2018-03-01
Semi-analytical balance verification intends to assess the balance performance using graphs that illustrate measurement dispersion, trough time, and to demonstrate measurements were performed in a reliable manner. This study presents internal quality control of a semi-analytical balance (GEHAKA BG400) using control charts. From 2013 to 2016, 2 weight standards were monitored before any balance operation. This work intended to evaluate if any significant difference or bias were presented on weighting procedure over time, to check the generated data reliability. This work also exemplifies how control intervals are established.
5th International Conference on Optimization and Control with Applications
Teo, Kok; Zhang, Yi
2014-01-01
This book presents advances in state-of-the-art solution methods and their applications to real life practical problems in optimization, control and operations research. Contributions from world-class experts in the field are collated here in two parts, dealing first with optimization and control theory and then with techniques and applications. Topics covered in the first part include control theory on infinite dimensional Banach spaces, history-dependent inclusion and linear programming complexity theory. Chapters also explore the use of approximations of Hamilton-Jacobi-Bellman inequality for solving periodic optimization problems and look at multi-objective semi-infinite optimization problems, and production planning problems. In the second part, the authors address techniques and applications of optimization and control in a variety of disciplines, such as chaos synchronization, facial expression recognition and dynamic input-output economic models. Other applications considered here include image retr...
Nonlinear damping based semi-active building isolation system
Ho, Carmen; Zhu, Yunpeng; Lang, Zi-Qiang; Billings, Stephen A.; Kohiyama, Masayuki; Wakayama, Shizuka
2018-06-01
Many buildings in Japan currently have a base-isolation system with a low stiffness that is designed to shift the natural frequency of the building below the frequencies of the ground motion due to earthquakes. However, the ground motion observed during the 2011 Tohoku earthquake contained strong long-period waves that lasted for a record length of 3 min. To provide a novel and better solution against the long-period waves while maintaining the performance of the standard isolation range, the exploitation of the characteristics of nonlinear damping is proposed in this paper. This is motivated by previous studies of the authors, which have demonstrated that nonlinear damping can achieve desired performance over both low and high frequency regions and the optimal nonlinear damping force can be realized by closed loop controlled semi-active dampers. Simulation results have shown strong vibration isolation performance on a building model with identified parameters and have indicated that nonlinear damping can achieve low acceleration transmissibilities round the structural natural frequency as well as the higher ground motion frequencies that have been frequently observed during most earthquakes in Japan. In addition, physical building model based laboratory experiments are also conducted, The results demonstrate the advantages of the proposed nonlinear damping technologies over both traditional linear damping and more advanced Linear-Quadratic Gaussian (LQG) feedback control which have been used in practice to address building isolation system design and implementation problems. In comparison with the tuned-mass damper and other active control methods, the proposed solution offers a more pragmatic, low-cost, robust and effective alternative that can be readily installed into the base-isolation system of most buildings.
Numerical solution of the controlled Duffing oscillator by semi-orthogonal spline wavelets
International Nuclear Information System (INIS)
Lakestani, M; Razzaghi, M; Dehghan, M
2006-01-01
This paper presents a numerical method for solving the controlled Duffing oscillator. The method can be extended to nonlinear calculus of variations and optimal control problems. The method is based upon compactly supported linear semi-orthogonal B-spline wavelets. The differential and integral expressions which arise in the system dynamics, the performance index and the boundary conditions are converted into some algebraic equations which can be solved for the unknown coefficients. Illustrative examples are included to demonstrate the validity and applicability of the technique
International Nuclear Information System (INIS)
Du, Haiping; Li, Weihua; Zhang, Nong
2011-01-01
This paper presents a study on continuously variable stiffness control of vehicle seat suspension using a magnetorheological elastomer (MRE) isolator. A concept design for an MRE isolator is proposed in the paper and its behavior is experimentally evaluated. An integrated seat suspension model, which includes a quarter-car suspension and a seat suspension with a driver body model, is used to design a sub-optimal H ∞ controller for an active isolator. The desired control force generated by this active isolator is then emulated by the MRE isolator through its continuously variable stiffness property when the actuating condition is met. The vibration control effect of the MRE isolator is evaluated in terms of driver body acceleration responses under both bump and random road conditions. The results show that the proposed control strategy achieves better vibration reduction performance than conventional on–off control
Semi-empirical neural network models of controlled dynamical systems
Directory of Open Access Journals (Sweden)
Mihail V. Egorchev
2017-12-01
Full Text Available A simulation approach is discussed for maneuverable aircraft motion as nonlinear controlled dynamical system under multiple and diverse uncertainties including knowledge imperfection concerning simulated plant and its environment exposure. The suggested approach is based on a merging of theoretical knowledge for the plant with training tools of artificial neural network field. The efficiency of this approach is demonstrated using the example of motion modeling and the identification of the aerodynamic characteristics of a maneuverable aircraft. A semi-empirical recurrent neural network based model learning algorithm is proposed for multi-step ahead prediction problem. This algorithm sequentially states and solves numerical optimization subproblems of increasing complexity, using each solution as initial guess for subsequent subproblem. We also consider a procedure for representative training set acquisition that utilizes multisine control signals.
Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory
Energy Technology Data Exchange (ETDEWEB)
Gregor P. Henze; Moncef Krarti
2005-09-30
Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulation research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very
International Nuclear Information System (INIS)
Ashokkumar, Veeramuthu; Agila, Elango; Sivakumar, Pandian; Salam, Zainal; Rengasamy, Ramasamy; Ani, Farid Nasir
2014-01-01
Highlights: • Bioprospecting for Botryococcus in upstream and downstream process for bioenergy production. • Large scale cultivation of B. braunii at semi-continuous system under open raceway system. • The biomass was harvested 99.5% successfully by Poly-(D)glucosamine and ferric iron. • Botryococcus biodiesel was characterized and found within ASTM standards. • Under semi-continuous mode, the alga B. braunii produces 101 tons ha −1 year −1 . - Abstract: The indigenous strain Botryococcus braunii TN101 was isolated and acclimatized under laboratory condition. Upstream and downstream process was thoroughly explored for biofuel production. During semi-continuous cultivation, the alga was grown under batch mode for 6 days; thereafter 40% of algal culture was harvested at every three days interval. At semi-continuous system, the indigenous strain grows well and produces high biomass productivity of 33.8 g m −3 day −1 . A two step combined harvesting process was designed using ferric iron and organic polymer Poly-(D)glucosamine and harvested 99.5% of biomass. Lipid extraction was optimized using different solvents, cyclohexane and methanol at 3:1 ratio supported for maximum extraction of lipids in Botryococcus up to 26.3%. Physicochemical properties of lipid was analyzed and found, saponification values 184, ester values 164, iodine values 92 and the average molecular weight of the lipids are 920 g mol −1 . The lipid contains 9.7% of FFA level, therefore, a simultaneous esterification and transesterification of free fatty acids and triacylglycerides were optimized for biodiesel production and the methyl ester yield was recorded up to 84%. In addition, an optimization study was carried out for the removal of pigments present in the biodiesel; the result revealed that 99% of pigments were removed from the biodiesel using activated charcoal. The biodiesel profile was analyzed by 1 H and 13 C NMR and GC–MS analyzer, methyl palmitate and methyl oleate
DEFF Research Database (Denmark)
Caterino, Nicola; Georgakis, Christos T.; Spizzuoco, Mariacristina
2016-01-01
The design of a semi-active (SA) control system addressed to mitigate wind induced structural demand to high wind turbine towers is discussed herein. Actually, the remarkable growth in height of wind turbines in the last decades, for a higher production of electricity, makes this issue pressing....../20 scale model of a real, one hundred meters tall wind turbine has been assumed as case study for shaking table tests. A special control algorithm has been purposely designed to drive MR dampers. Starting from the results of preliminary laboratory tests, a finite element model of such structure has been...... calibrated so as to develop several numerical simulations addressed to calibrate the controller, i.e., to achieve as much as possible different, even conflicting, structural goals. The results are definitely encouraging, since the best configuration of the controller leaded to about 80% of reduction of base...
Directory of Open Access Journals (Sweden)
Guo Jiuwang
2015-01-01
Full Text Available Because of the randomness and fluctuation of wind energy, as well as the impact of strongly nonlinear characteristic of variable speed constant frequency (VSCF wind power generation system with doubly fed induction generators (DFIG, traditional active power control strategies are difficult to achieve high precision control and the output power of wind turbines is more fluctuated. In order to improve the quality of output electric energy of doubly fed wind turbines, on the basis of analyzing the operating principles and dynamic characteristics of doubly fed wind turbines, this paper proposes a new active power optimal control method of doubly fed wind turbines based on predictive control theory. This method uses state space model of wind turbines, based on the prediction of the future state of wind turbines, moves horizon optimization, and meanwhile, gets the control signals of pitch angle and generator torque. Simulation results show that the proposed control strategies can guarantee the utilization efficiency for wind energy. Simultaneously, they can improve operation stability of wind turbines and the quality of electric energy.
Road maintenance optimization through a discrete-time semi-Markov decision process
International Nuclear Information System (INIS)
Zhang Xueqing; Gao Hui
2012-01-01
Optimization models are necessary for efficient and cost-effective maintenance of a road network. In this regard, road deterioration is commonly modeled as a discrete-time Markov process such that an optimal maintenance policy can be obtained based on the Markov decision process, or as a renewal process such that an optimal maintenance policy can be obtained based on the renewal theory. However, the discrete-time Markov process cannot capture the real time at which the state transits while the renewal process considers only one state and one maintenance action. In this paper, road deterioration is modeled as a semi-Markov process in which the state transition has the Markov property and the holding time in each state is assumed to follow a discrete Weibull distribution. Based on this semi-Markov process, linear programming models are formulated for both infinite and finite planning horizons in order to derive optimal maintenance policies to minimize the life-cycle cost of a road network. A hypothetical road network is used to illustrate the application of the proposed optimization models. The results indicate that these linear programming models are practical for the maintenance of a road network having a large number of road segments and that they are convenient to incorporate various constraints on the decision process, for example, performance requirements and available budgets. Although the optimal maintenance policies obtained for the road network are randomized stationary policies, the extent of this randomness in decision making is limited. The maintenance actions are deterministic for most states and the randomness in selecting actions occurs only for a few states.
Directory of Open Access Journals (Sweden)
Byung-Keun Song
2017-10-01
Full Text Available This paper presents a new fuzzy sliding mode controller (FSMC to improve control performances in the presence of uncertainties related to model errors and external disturbance (UAD. As a first step, an adaptive control law is designed using Lyapunov stability analysis. The control law can update control parameters of the FSMC with a disturbance estimator (DE in which the closed-loop stability and finite-time convergence of tracking error are guaranteed. A solution for estimating the compensative quantity of the impact of UAD on a control system and a set of solutions are then presented in order to avoid the singular cases of the fuzzy-based function approximation, increase convergence ability, and reduce the calculating cost. Subsequently, the effectiveness of the proposed controller is verified through the investigation of vibration control performances of a semi-active vehicle suspension system featuring a magnetorheological damper (MRD. It is shown that the proposed controller can provide better control ability of vibration control with lower consumed power compared with two existing fuzzy sliding mode controllers.
Optimal treatment interruptions control of TB transmission model
Nainggolan, Jonner; Suparwati, Titik; Kawuwung, Westy B.
2018-03-01
A tuberculosis model which incorporates treatment interruptions of infectives is established. Optimal control of individuals infected with active TB is given in the model. It is obtained that the control reproduction numbers is smaller than the reproduction number, this means treatment controls could optimize the decrease in the spread of active TB. For this model, controls on treatment of infection individuals to reduce the actively infected individual populations, by application the Pontryagins Maximum Principle for optimal control. The result further emphasized the importance of controlling disease relapse in reducing the number of actively infected and treatment interruptions individuals with tuberculosis.
Multi-Objective Optimization Control for the Aerospace Dual-Active Bridge Power Converter
Directory of Open Access Journals (Sweden)
Tao Lei
2018-05-01
Full Text Available With the development of More Electrical Aircraft (MEA, the electrification of secondary power systems in aircraft is becoming more and more common. As the key power conversion device, the dual active bridge (DAB converter is the power interface for the energy storage system with the high voltage direct current (HVDC bus in aircraft electrical power systems. In this paper, a DAB DC-DC converter is designed to meet aviation requirements. The extended dual phase shifted control strategy is adopted, and a multi-objective genetic algorithm is applied to optimize its operating performance. Considering the three indicators of inductance current root mean square root (RMS value, negative reverse power and direct current (DC bias component of the current for the high frequency transformer as the optimization objectives, the DAB converter’s optimization model is derived to achieve soft switching as the main constraint condition. Optimized methods of controlling quantity for the DAB based on the evolution and genetic algorithm is used to solve the model, and a number of optimal control parameters are obtained under different load conditions. The results of digital, hard-in-loop simulation and hardware prototype experiments show that the three performance indexes are all suppressed greatly, and the optimization method proposed in this paper is reasonable. The work of this paper provides a theoretical basis and researching method for the multi-objective optimization of the power converter in the aircraft electrical power system.
Lu, Lyan-Ywan; Lin, Tzu-Kang; Jheng, Rong-Jie; Wu, Hsin-Hsien
2018-01-01
A semi-active friction damper (SAFD) can be employed for the seismic protection of structural systems. The effectiveness of an SAFD in absorbing seismic energy is usually superior to that of its passive counterpart, since its slip force can be altered in real time according to structural response and excitation. Most existing SAFDs are controlled by adjusting the clamping force applied on the friction interface. Thus, the implementation of SAFDs in practice requires precision control of the clamping force, which is usually substantially larger than the slip force. This may increase the implementation complexity and cost of SAFDs. To avoid this problem, this study proposes a novel position-controlled SAFD, named the leverage-type controllable friction damper (LCFD). The LCFD system combines a traditional passive friction damper and a leverage mechanism with a movable central pivot. By simply controlling the pivot position, the damping force generated by the LCFD system can be adjusted in real time. In order to verify the feasibility of the proposed SAFD, a prototype LCFD was tested by using a shaking table. The test results demonstrate that the equivalent friction force and hysteresis loop of the LCFD can be regulated by controlling the pivot position. By considering 16 ground motions with two different intensities, the adaptive feature of the LCFD for seismic structural control is further demonstrated numerically.
Constrained Optimization and Optimal Control for Partial Differential Equations
Leugering, Günter; Griewank, Andreas
2012-01-01
This special volume focuses on optimization and control of processes governed by partial differential equations. The contributors are mostly participants of the DFG-priority program 1253: Optimization with PDE-constraints which is active since 2006. The book is organized in sections which cover almost the entire spectrum of modern research in this emerging field. Indeed, even though the field of optimal control and optimization for PDE-constrained problems has undergone a dramatic increase of interest during the last four decades, a full theory for nonlinear problems is still lacking. The cont
Directory of Open Access Journals (Sweden)
Olga Kostyukova
2017-11-01
Full Text Available The paper is devoted to study of a special class of semi-infinite problems arising in nonlinear parametric Semi-infinite Programming, when the differential properties of the solutions are being studied. These problems are convex and possess noncompact index sets. In the paper, we present conditions guaranteeing the existence of optimal solutions, and prove new optimality criterion. An example illustrating the obtained results is presented.
Virtual prototyping of a semi-active transfemoral prosthetic leg.
Lui, Zhen Wei; Awad, Mohammed I; Abouhossein, Alireza; Dehghani-Sanij, Abbas A; Messenger, Neil
2015-05-01
This article presents a virtual prototyping study of a semi-active lower limb prosthesis to improve the functionality of an amputee during prosthesis-environment interaction for level ground walking. Articulated ankle-foot prosthesis and a single-axis semi-active prosthetic knee with active and passive operating modes were considered. Data for level ground walking were collected using a photogrammetric method in order to develop a base-line simulation model and with the hip kinematics input to verify the proposed design. The simulated results show that the semi-active lower limb prosthesis is able to move efficiently in passive mode, and the activation time of the knee actuator can be reduced by approximately 50%. Therefore, this semi-active system has the potential to reduce the energy consumption of the actuators required during level ground walking and requires less compensation from the amputee due to lower deviation of the vertical excursion of body centre of mass. © IMechE 2015.
Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control
Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.
2016-02-01
A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.
Demayo, Trevor Nat
Criteria pollutant regulations, climate change concerns, and energy conservation efforts are placing strict constraints in the design and operation of advanced, stationary combustion systems. To ensure minimal pollutant emissions and maximal efficiency at every instant of operation while preventing reaction blowout, combustion systems need to react and adapt in real-time to external changes. This study describes the development, demonstration, and evaluation of a multivariable feedback control system, designed to maximize the performance of natural gas-fired combustion systems. A feedback sensor array was developed to monitor reaction stability and measure combustion performance as a function of NOx, CO, and O, emissions. Acoustic and UV chemiluminescent emissions were investigated for use as stability indicators. Modulated signals of CH* and CO2* chemiluminescence were found to correlate well with the onset of lean blowout. A variety of emissions sensors were tested and evaluated, including conventional CEMS', micro-fuel cells, a zirconia NOx transducer, and a rapid response predictive NOx sensor based on UV flame chemiluminescence. A dual time-scale controller was designed to actively optimize operating conditions by maximizing a multivariable performance function J using a linear direction set search algorithm. The controller evaluated J under slow, quasi steady-state conditions, while dynamically monitoring the reaction zone at high speed for pre-blowout instabilities or boundary condition violations. To establish the input control parameters, two burner systems were selected: a 30 kW air-swirl, generic research burner, and a 120 kW scaled, fuel-staged, industrial boiler burner. The parameters, chosen to most affect burner performance, consisted of air swirl intensity and excess air for the generic burner, and fuel-staging and excess air for the boiler burner. A set of optimization parameters was also established to ensure efficient and deterministic
Yang, Qidong; Zuo, Hongchao; Li, Weidong
2016-01-01
Improving the capability of land-surface process models to simulate soil moisture assists in better understanding the atmosphere-land interaction. In semi-arid regions, due to limited near-surface observational data and large errors in large-scale parameters obtained by the remote sensing method, there exist uncertainties in land surface parameters, which can cause large offsets between the simulated results of land-surface process models and the observational data for the soil moisture. In this study, observational data from the Semi-Arid Climate Observatory and Laboratory (SACOL) station in the semi-arid loess plateau of China were divided into three datasets: summer, autumn, and summer-autumn. By combing the particle swarm optimization (PSO) algorithm and the land-surface process model SHAW (Simultaneous Heat and Water), the soil and vegetation parameters that are related to the soil moisture but difficult to obtain by observations are optimized using three datasets. On this basis, the SHAW model was run with the optimized parameters to simulate the characteristics of the land-surface process in the semi-arid loess plateau. Simultaneously, the default SHAW model was run with the same atmospheric forcing as a comparison test. Simulation results revealed the following: parameters optimized by the particle swarm optimization algorithm in all simulation tests improved simulations of the soil moisture and latent heat flux; differences between simulated results and observational data are clearly reduced, but simulation tests involving the adoption of optimized parameters cannot simultaneously improve the simulation results for the net radiation, sensible heat flux, and soil temperature. Optimized soil and vegetation parameters based on different datasets have the same order of magnitude but are not identical; soil parameters only vary to a small degree, but the variation range of vegetation parameters is large.
Optimal Vibration Control for Tracked Vehicle Suspension Systems
Directory of Open Access Journals (Sweden)
Yan-Jun Liang
2013-01-01
Full Text Available Technique of optimal vibration control with exponential decay rate and simulation for vehicle active suspension systems is developed. Mechanical model and dynamic system for a class of tracked vehicle suspension vibration control is established and the corresponding system of state space form is described. In order to prolong the working life of suspension system and improve ride comfort, based on the active suspension vibration control devices and using optimal control approach, an optimal vibration controller with exponential decay rate is designed. Numerical simulations are carried out, and the control effects of the ordinary optimal controller and the proposed controller are compared. Numerical simulation results illustrate the effectiveness of the proposed technique.
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai
2016-01-01
This paper presents the Distributed Model Predictive Control (D-MPC) of a wind farm equipped with fast and short-term Energy Storage System (ESS) for optimal active power control using the fast gradient method via dual decomposition. The primary objective of the D-MPC control of the wind farm...... is power reference tracking from system operators. Besides, by optimal distribution of the power references to individual wind turbines and the ESS unit, the wind turbine mechanical loads are alleviated. With the fast gradient method, the convergence rate of the DMPC is significantly improved which leads...
Irrigation management to optimize controlled drainage in a semi-arid area
Soppe, R.W.O.; Ayars, J.E.; Christen, E.W.; Shouse, P.J.
2003-01-01
On the west side of the San Joaquin Valley, California, groundwater tables have risen after several decades of irrigation. A regional semi-permeable layer at 100 m depth (Corcoran Clay) combined with over-irrigation and leaching is the major cause of the groundwater rise. Subsurface drain systems
Directory of Open Access Journals (Sweden)
Zhi-Jun Fu
2017-01-01
Full Text Available In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP. Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.
Cody, B. M.; Gonzalez-Nicolas, A.; Bau, D. A.
2011-12-01
of CO2 sequestered. This heuristic optimization method is chosen because of its robustness in optimizing large-scale, highly non-linear problems. Trade-off curves are developed for multiple fictional sites with the intent of clarifying how variations in domain characteristics (aquifer thickness, aquifer and weak cap rock permeability, the number of weak cap rock areas, and the number of aquifer-cap rock layers) affect Pareto-optimal fronts. Computational benefits of using semi-analytical leakage models are explored and discussed. [1] Birkholzer, J. (2008) "Research Project on CO2 Geological Storage and Groundwater Resources: Water Quality Effects Caused by CO2 Intrusion into Shallow Groundwater" Berkeley (CA): Lawrence Berkeley National Laboratory (US); 2008 Oct. 473 p. Report No.: 510-486-7134. [2] Celia, M.A. and Nordbotten, J.M. (2011) "Field-scale application of a semi-analytical model for estimation of CO2 and brine leakage along old wells" International Journal of Greenhouse Gas Control, 5 (2011), 257-269. [3] Nordbotten, J.M. and Celia, M.A. (2009) "Model for CO2 leakage including multiple geological layers and multiple leaky wells" Environ. Sci. Technol., 43, 743-749.
Optimal control of raw timber production processes
Ivan Kolenka
1978-01-01
This paper demonstrates the possibility of optimal planning and control of timber harvesting activ-ities with mathematical optimization models. The separate phases of timber harvesting are represented by coordinated models which can be used to select the optimal decision for the execution of any given phase. The models form a system whose components are connected and...
Control and filtering for semi-Markovian jump systems
Li, Fanbiao; Wu, Ligang
2017-01-01
This book presents up-to-date research developments and novel methodologies on semi-Markovian jump systems (S-MJS). It presents solutions to a series of problems with new approaches for the control and filtering of S-MJS, including stability analysis, sliding mode control, dynamic output feedback control, robust filter design, and fault detection. A set of newly developed techniques such as piecewise analysis method, positively invariant set approach, event-triggered method, and cone complementary linearization approaches are presented. Control and Filtering for Semi-Markovian Jump Systems is a comprehensive reference for researcher and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.
Optimal management strategies in variable environments: Stochastic optimal control methods
Williams, B.K.
1985-01-01
Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both
Optimization and Optimal Control
Chinchuluun, Altannar; Enkhbat, Rentsen; Tseveendorj, Ider
2010-01-01
During the last four decades there has been a remarkable development in optimization and optimal control. Due to its wide variety of applications, many scientists and researchers have paid attention to fields of optimization and optimal control. A huge number of new theoretical, algorithmic, and computational results have been observed in the last few years. This book gives the latest advances, and due to the rapid development of these fields, there are no other recent publications on the same topics. Key features: Provides a collection of selected contributions giving a state-of-the-art accou
Semi-automatic tool to ease the creation and optimization of GPU programs
DEFF Research Database (Denmark)
Jepsen, Jacob
2014-01-01
We present a tool that reduces the development time of GPU-executable code. We implement a catalogue of common optimizations specific to the GPU architecture. Through the tool, the programmer can semi-automatically transform a computationally-intensive code section into GPU-executable form...... of the transformations can be performed automatically, which makes the tool usable for both novices and experts in GPU programming....
GEOMETRICAL OPTIMIZATION OF VEHICLE SHOCK ABSORBERS WITH MR FLUID
ENGIN, Tahsin; PARLAK, Zekeriya; ŞAHIN, Ismail; ÇALLI, Ismail
2016-01-01
Magnetorheological (MR) shock absorber have received remarkable attention in the last decade due to being a potential technology to conduct semi-active control in structures and mechanical systems in order to effectively suppress vibration. To develop performance of MR shock absorbers, optimal design of the dampers should be considered. The present study deals with optimal geometrical modeling of a MR shock absorber. Optimal design of the present shock absorber was carried out by using Taguch...
Optimizing the construction of devices to control inaccesible surfaces - case study
Niţu, E. L.; Costea, A.; Iordache, M. D.; Rizea, A. D.; Babă, Al
2017-10-01
The modern concept for the evolution of manufacturing systems requires multi-criteria optimization of technological processes and equipments, prioritizing associated criteria according to their importance. Technological preparation of the manufacturing can be developed, depending on the volume of production, to the limit of favourable economical effects related to the recovery of the costs for the design and execution of the technological equipment. Devices, as subsystems of the technological system, in the general context of modernization and diversification of machines, tools, semi-finished products and drives, are made in a multitude of constructive variants, which in many cases do not allow their identification, study and improvement. This paper presents a case study in which the multi-criteria analysis of some structures, based on a general optimization method, of novelty character, is used in order to determine the optimal construction variant of a control device. The rational construction of the control device confirms that the optimization method and the proposed calculation methods are correct and determine a different system configuration, new features and functions, and a specific method of working to control inaccessible surfaces.
Janke, Leandro; Weinrich, Sören; Leite, Athaydes F; Schüch, Andrea; Nikolausz, Marcell; Nelles, Michael; Stinner, Walter
2017-12-01
Anaerobic digestion of sugarcane straw co-digested with sugarcane filter cake was investigated with a special focus on macronutrients supplementation for an optimized conversion process. Experimental data from batch tests and a semi-continuous experiment operated in different supplementation phases were used for modeling the conversion kinetics based on continuous stirred-tank reactors. The semi-continuous experiment showed an overall decrease in the performance along the inoculum washout from the reactors. By supplementing nitrogen alone or in combination to phosphorus and sulfur the specific methane production significantly increased (P0.99), the use of the depicted kinetics did not provide a good estimation for process simulation of the semi-continuous process (in any supplementation phase), possibly due to the different feeding modes and inoculum source, activity and adaptation. Copyright © 2017 Elsevier Ltd. All rights reserved.
An optimal control model for reducing and trading of carbon emissions
Guo, Huaying; Liang, Jin
2016-03-01
A stochastic optimal control model of reducing and trading for carbon emissions is established in this paper. With considerations of reducing the carbon emission growth and the price of the allowances in the market, an optimal policy is searched to have the minimum total costs to achieve the agreement of emission reduction targets. The model turns to a two-dimension HJB equation problem. By the methods of reducing dimension and Cole-Hopf transformation, a semi-closed form solution of the corresponding HJB problem under some assumptions is obtained. For more general cases, the numerical calculations, analysis and comparisons are presented.
Infinite horizon optimal impulsive control with applications to Internet congestion control
Avrachenkov, Konstantin; Habachi, Oussama; Piunovskiy, Alexey; Zhang, Yi
2015-04-01
We investigate infinite-horizon deterministic optimal control problems with both gradual and impulsive controls, where any finitely many impulses are allowed simultaneously. Both discounted and long-run time-average criteria are considered. We establish very general and at the same time natural conditions, under which the dynamic programming approach results in an optimal feedback policy. The established theoretical results are applied to the Internet congestion control, and by solving analytically and nontrivially the underlying optimal control problems, we obtain a simple threshold-based active queue management scheme, which takes into account the main parameters of the transmission control protocols, and improves the fairness among the connections in a given network.
Directory of Open Access Journals (Sweden)
Marcelo Perencin de Arruda Ribeiro
2005-06-01
Full Text Available In this work, optimal control techniques were used to optimize the feed of reactants during the enzymatic synthesis of ampicillin in a semi-batch reactor. Simulation results showed that a semi-batch integrated reactor (with product crystallization might achieve 88% 6-APA (6-aminepenicillanic acid conversion and 92% of PGME (phenylglycine methyl ester yield, with a productivity between 3.5 and 5.5 mM min-1.A síntese enzimática de ampicilina oferece menor impacto ambiental em relação ao processo utilizado atualmente pela indústria farmacêutica. Mas seu rendimento e produtividade devem ser melhorados para tornar essa rota competitiva. Alguns estudos empíricos para otimizar a rota enzimática de síntese de antibióticos beta-lactâmicos vêm sendo realizados. Entretanto, a utilização sistemática de métodos matemáticos de otimização nesse processo não é encontrada na literatura. Neste trabalho, utilizaram-se técnicas de controle ótimo para otimizar a alimentação de reagentes na síntese enzimática de ampicilina em reator operando em batelada alimentada. Resultados simulados mostram que, em reator integrado (com precipitação dos produtos operado em batelada alimentada, conversões de 6-APA e rendimento de EMFG de 88% a 92% são factíveis, assim como produtividades entre 3,5 e 5,5 mM.min-1.
Semi-Markov models control of restorable systems with latent failures
Obzherin, Yuriy E
2015-01-01
Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes valuable methodology which can be used by readers to build mathematical models of a wide class of systems for various applications. In particular, this information can be applied to build models of reliability, queuing systems, and technical control. Beginning with a brief introduction to the area, the book covers semi-Markov models for different control strategies in one-component systems, defining their stationary characteristics of reliability and efficiency, and uti
CALIBRATION OF SEMI-ANALYTIC MODELS OF GALAXY FORMATION USING PARTICLE SWARM OPTIMIZATION
International Nuclear Information System (INIS)
Ruiz, Andrés N.; Domínguez, Mariano J.; Yaryura, Yamila; Lambas, Diego García; Cora, Sofía A.; Martínez, Cristian A. Vega-; Gargiulo, Ignacio D.; Padilla, Nelson D.; Tecce, Tomás E.; Orsi, Álvaro; Arancibia, Alejandra M. Muñoz
2015-01-01
We present a fast and accurate method to select an optimal set of parameters in semi-analytic models of galaxy formation and evolution (SAMs). Our approach compares the results of a model against a set of observables applying a stochastic technique called Particle Swarm Optimization (PSO), a self-learning algorithm for localizing regions of maximum likelihood in multidimensional spaces that outperforms traditional sampling methods in terms of computational cost. We apply the PSO technique to the SAG semi-analytic model combined with merger trees extracted from a standard Lambda Cold Dark Matter N-body simulation. The calibration is performed using a combination of observed galaxy properties as constraints, including the local stellar mass function and the black hole to bulge mass relation. We test the ability of the PSO algorithm to find the best set of free parameters of the model by comparing the results with those obtained using a MCMC exploration. Both methods find the same maximum likelihood region, however, the PSO method requires one order of magnitude fewer evaluations. This new approach allows a fast estimation of the best-fitting parameter set in multidimensional spaces, providing a practical tool to test the consequences of including other astrophysical processes in SAMs
CALIBRATION OF SEMI-ANALYTIC MODELS OF GALAXY FORMATION USING PARTICLE SWARM OPTIMIZATION
Energy Technology Data Exchange (ETDEWEB)
Ruiz, Andrés N.; Domínguez, Mariano J.; Yaryura, Yamila; Lambas, Diego García [Instituto de Astronomía Teórica y Experimental, CONICET-UNC, Laprida 854, X5000BGR, Córdoba (Argentina); Cora, Sofía A.; Martínez, Cristian A. Vega-; Gargiulo, Ignacio D. [Consejo Nacional de Investigaciones Científicas y Técnicas, Rivadavia 1917, C1033AAJ Buenos Aires (Argentina); Padilla, Nelson D.; Tecce, Tomás E.; Orsi, Álvaro; Arancibia, Alejandra M. Muñoz, E-mail: andresnicolas@oac.uncor.edu [Instituto de Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, Santiago (Chile)
2015-03-10
We present a fast and accurate method to select an optimal set of parameters in semi-analytic models of galaxy formation and evolution (SAMs). Our approach compares the results of a model against a set of observables applying a stochastic technique called Particle Swarm Optimization (PSO), a self-learning algorithm for localizing regions of maximum likelihood in multidimensional spaces that outperforms traditional sampling methods in terms of computational cost. We apply the PSO technique to the SAG semi-analytic model combined with merger trees extracted from a standard Lambda Cold Dark Matter N-body simulation. The calibration is performed using a combination of observed galaxy properties as constraints, including the local stellar mass function and the black hole to bulge mass relation. We test the ability of the PSO algorithm to find the best set of free parameters of the model by comparing the results with those obtained using a MCMC exploration. Both methods find the same maximum likelihood region, however, the PSO method requires one order of magnitude fewer evaluations. This new approach allows a fast estimation of the best-fitting parameter set in multidimensional spaces, providing a practical tool to test the consequences of including other astrophysical processes in SAMs.
Irrigation management to optimize controlled drainage in a semi-arid area
Soppe, R.W.O.; Ayars, J.E.; Christen, E.W.; Shouse, P.J.
2003-01-01
On the west side of the San Joaquin Valley, California, groundwater tables have risen after several decades of irrigation. A regional semi-permeable layer at 100 m depth (Corcoran Clay) combined with over-irrigation and leaching is the major cause of the groundwater rise. Subsurface drain systems were installed from the 60¿s to the 80¿s to remove excess water and maintain an aerated root zone. However, drainage water resulting from these subsurface systems contained trace elements like seleni...
Semi-decentralized Strategies in Structural Vibration Control
Directory of Open Access Journals (Sweden)
F. Palacios-Quiñonero
2011-04-01
Full Text Available In this work, the main ideas involved in the design of overlapping and multi-overlapping controllers via the Inclusion Principle are discussed and illustrated in the context of the Structural Vibration Control of tall buildings under seismic excitation. A detailed theoretical background on the Inclusion Principle and the design of overlapping controllers is provided. Overlapping and multi-overlapping LQR controllers are designed for a simplified five-story building model. Numerical simulations are conducted to asses the performance of the proposed semi-decentralized controllers with positive results.
Ka, Hyun W; Chung, Cheng-Shiu; Ding, Dan; James, Khara; Cooper, Rory
2018-02-01
We developed a 3D vision-based semi-autonomous control interface for assistive robotic manipulators. It was implemented based on one of the most popular commercially available assistive robotic manipulator combined with a low-cost depth-sensing camera mounted on the robot base. To perform a manipulation task with the 3D vision-based semi-autonomous control interface, a user starts operating with a manual control method available to him/her. When detecting objects within a set range, the control interface automatically stops the robot, and provides the user with possible manipulation options through audible text output, based on the detected object characteristics. Then, the system waits until the user states a voice command. Once the user command is given, the control interface drives the robot autonomously until the given command is completed. In the empirical evaluations conducted with human subjects from two different groups, it was shown that the semi-autonomous control can be used as an alternative control method to enable individuals with impaired motor control to more efficiently operate the robot arms by facilitating their fine motion control. The advantage of semi-autonomous control was not so obvious for the simple tasks. But, for the relatively complex real-life tasks, the 3D vision-based semi-autonomous control showed significantly faster performance. Implications for Rehabilitation A 3D vision-based semi-autonomous control interface will improve clinical practice by providing an alternative control method that is less demanding physically as well cognitively. A 3D vision-based semi-autonomous control provides the user with task specific intelligent semiautonomous manipulation assistances. A 3D vision-based semi-autonomous control gives the user the feeling that he or she is still in control at any moment. A 3D vision-based semi-autonomous control is compatible with different types of new and existing manual control methods for ARMs.
Ionospheric F2-Layer Semi-Annual Variation in Middle Latitude by Solar Activity
Directory of Open Access Journals (Sweden)
Yoon-Kyung Park
2010-12-01
Full Text Available We examine the ionospheric F2-layer electron density variation by solar activity in middle latitude by using foF2 observed at the Kokubunji ionosonde station in Japan for the period from 1997 to 2008. The semi-annual variation of foF2 shows obviously in high solar activity (2000-2002 than low solar activity (2006-2008. It seems that variation of geomagnetic activity by solar activity influences on the semi-annual variation of the ionospheric F2-layer electron density. According to the Lomb-Scargle periodogram analysis of foF2 and Ap index, interplanetary magnetic field (IMF Bs (IMF Bz <0 component, solar wind speed, solar wind number density and flow pressure which influence the geomagnetic activity, we examine how the geomagnetic activity affects the ionospheric F2-layer electron density variation. We find that the semi-annual variation of daily foF2, Ap index and IMF Bs appear clearly during the high solar activity. It suggests that the semi-annual variation of geomagnetic activity, caused by Russell-McPherron effect, contributes greatly to the ionospheric F2-layer semi-annual electron density variation, except dynamical effects in the thermosphere.
Directory of Open Access Journals (Sweden)
Mohsen Einan
2017-08-01
Full Text Available This paper presents a new control strategy for isolated micro-grids including wind turbines (WT, fuel cells (FC, photo-voltaic (PV and battery energy storage systems (BESS. FC have been used in parallel with BESSs in order to increase their lifetime and efficiency. The changes in some parameters such as wind speed, sunlight, and consumption, lead to improper performance of droop. To overcome this challenge, a new intelligent method using a combination of fuzzy controller and cuckoo optimization algorithm (COA techniques for active power controllers in isolated networks is proposed. In this paper, COA is compared with genetic algorithm (GA and particles swarm optimization algorithm (PSO. In order to show efficiency of the proposed controller, this optimal controller has been compared with droop, optimized droop, and conventional fuzzy methods, the dynamic analysis of the island is implemented to assess the behavior of isolated generations accurately and simulation results are reported.
Semi-annual Sq-variation in solar activity cycle
Pogrebnoy, V.; Malosiev, T.
The peculiarities of semi-annual variation in solar activity cycle have been studied. The data from observatories having long observational series and located in different latitude zones were used. The following observatories were selected: Huancayo (magnetic equator), from 1922 to 1959; Apia (low latitudes), from 1912 to 1961; Moscow (middle latitudes), from 1947 to 1965. Based on the hourly values of H-components, the average monthly diurnal amplitudes (a difference between midday and midnight values), according to five international quiet days, were computed. Obtained results were compared with R (relative sunspot numbers) in the ranges of 0-30R, 40-100R, and 140-190R. It was shown, that the amplitude of semi-annual variation increases with R, from minimum to maximum values, on average by 45%. At equatorial Huancayo observatory, the semi-annual Sq(H)-variation appears especially clearly: its maximums take place at periods of equinoxes (March-April, September-October), and minimums -- at periods of solstices (June-July, December-January). At low (Apia observatory) and middle (Moscow observatory) latitudes, the character of semi-annual variation is somewhat different: it appears during the periods of equinoxes, but considerably less than at equator. Besides, with the growth of R, semi-annual variation appears against a background of annual variation, in the form of second peaks (maximum in June). At observatories located in low and middle latitudes, second peaks become more appreciable with an increase of R (March-April and September-October). During the periods of low solar activity, they are insignificant. This work has been carried out with the support from International Scientific and Technology Center (Project #KR-214).
Oil Reservoir Production Optimization using Optimal Control
DEFF Research Database (Denmark)
Völcker, Carsten; Jørgensen, John Bagterp; Stenby, Erling Halfdan
2011-01-01
Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using the adjo...... reservoir using water ooding and smart well technology. Compared to the uncontrolled case, the optimal operation increases the Net Present Value of the oil field by 10%.......Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using...
The Design and Semi-Physical Simulation Test of Fault-Tolerant Controller for Aero Engine
Liu, Yuan; Zhang, Xin; Zhang, Tianhong
2017-11-01
A new fault-tolerant control method for aero engine is proposed, which can accurately diagnose the sensor fault by Kalman filter banks and reconstruct the signal by real-time on-board adaptive model combing with a simplified real-time model and an improved Kalman filter. In order to verify the feasibility of the method proposed, a semi-physical simulation experiment has been carried out. Besides the real I/O interfaces, controller hardware and the virtual plant model, semi-physical simulation system also contains real fuel system. Compared with the hardware-in-the-loop (HIL) simulation, semi-physical simulation system has a higher degree of confidence. In order to meet the needs of semi-physical simulation, a rapid prototyping controller with fault-tolerant control ability based on NI CompactRIO platform is designed and verified on the semi-physical simulation test platform. The result shows that the controller can realize the aero engine control safely and reliably with little influence on controller performance in the event of fault on sensor.
Quantum demolition filtering and optimal control of unstable systems.
Belavkin, V P
2012-11-28
A brief account of the quantum information dynamics and dynamical programming methods for optimal control of quantum unstable systems is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme, we exploit the separation theorem of filtering and control aspects as in the usual case of quantum stable systems with non-demolition observation. This allows us to start with the Belavkin quantum filtering equation generalized to demolition observations and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to Hamiltonian terms in the filtering equation. An unstable controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one.
Design and experiment study of a semi-active energy-regenerative suspension system
International Nuclear Information System (INIS)
Shi, Dehua; Chen, Long; Wang, Ruochen; Jiang, Haobin; Shen, Yujie
2015-01-01
A new kind of semi-active energy-regenerative suspension system is proposed to recover suspension vibration energy, as well as to reduce the suspension cost and demands for the motor-rated capacity. The system consists of an energy-regenerative damper and a DC-DC converter-based energy-regenerative circuit. The energy-regenerative damper is composed of an electromagnetic linear motor and an adjustable shock absorber with three regulating levels. The linear motor just works as the generator to harvest the suspension vibration energy. The circuit can be used to improve the system’s energy-regenerative performance and to continuously regulate the motor’s electromagnetic damping force. Therefore, although the motor works as a generator and damps the isolation without an external power source, the motor damping force is controllable. The damping characteristics of the system are studied based on a two degrees of freedom vehicle vibration model. By further analyzing the circuit operation characteristics under different working modes, the double-loop controller is designed to track the desired damping force. The external-loop is a fuzzy controller that offers the desired equivalent damping. The inner-loop controller, on one hand, is used to generate the pulse number and the frequency to control the angle and the rotational speed of the step motor; on the other hand, the inner-loop is used to offer the duty cycle of the energy-regenerative circuit. Simulations and experiments are conducted to validate such a new suspension system. The results show that the semi-active energy-regenerative suspension can improve vehicle ride comfort with the controllable damping characteristics of the linear motor. Meanwhile, it also ensures energy regeneration. (paper)
Optimal Control Surface Layout for an Aeroservoelastic Wingbox
Stanford, Bret K.
2017-01-01
This paper demonstrates a technique for locating the optimal control surface layout of an aeroservoelastic Common Research Model wingbox, in the context of maneuver load alleviation and active utter suppression. The combinatorial actuator layout design is solved using ideas borrowed from topology optimization, where the effectiveness of a given control surface is tied to a layout design variable, which varies from zero (the actuator is removed) to one (the actuator is retained). These layout design variables are optimized concurrently with a large number of structural wingbox sizing variables and control surface actuation variables, in order to minimize the sum of structural weight and actuator weight. Results are presented that demonstrate interdependencies between structural sizing patterns and optimal control surface layouts, for both static and dynamic aeroelastic physics.
Verguet, Stéphane; Johri, Mira; Morris, Shaun K; Gauvreau, Cindy L; Jha, Prabhat; Jit, Mark
2015-03-03
The Measles & Rubella Initiative, a broad consortium of global health agencies, has provided support to measles-burdened countries, focusing on sustaining high coverage of routine immunization of children and supplementing it with a second dose opportunity for measles vaccine through supplemental immunization activities (SIAs). We estimate optimal scheduling of SIAs in countries with the highest measles burden. We develop an age-stratified dynamic compartmental model of measles transmission. We explore the frequency of SIAs in order to achieve measles control in selected countries and two Indian states with high measles burden. Specifically, we compute the maximum allowable time period between two consecutive SIAs to achieve measles control. Our analysis indicates that a single SIA will not control measles transmission in any of the countries with high measles burden. However, regular SIAs at high coverage levels are a viable strategy to prevent measles outbreaks. The periodicity of SIAs differs between countries and even within a single country, and is determined by population demographics and existing routine immunization coverage. Our analysis can guide country policymakers deciding on the optimal scheduling of SIA campaigns and the best combination of routine and SIA vaccination to control measles. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
Optimization of end-pumped, actively Q-switched quasi-III-level lasers.
Jabczynski, Jan K; Gorajek, Lukasz; Kwiatkowski, Jacek; Kaskow, Mateusz; Zendzian, Waldemar
2011-08-15
The new model of end-pumped quasi-III-level laser considering transient pumping processes, ground-state-depletion and up-conversion effects was developed. The model consists of two parts: pumping stage and Q-switched part, which can be separated in a case of active Q-switching regime. For pumping stage the semi-analytical model was developed, enabling the calculations for final occupation of upper laser level for given pump power and duration, spatial profile of pump beam, length and dopant level of gain medium. For quasi-stationary inversion, the optimization procedure of Q-switching regime based on Lagrange multiplier technique was developed. The new approach for optimization of CW regime of quasi-three-level lasers was developed to optimize the Q-switched lasers operating with high repetition rates. Both methods of optimizations enable calculation of optimal absorbance of gain medium and output losses for given pump rate. © 2011 Optical Society of America
International Nuclear Information System (INIS)
Dong Xiaomin; Yu Miao; Liao Changrong; Chen Weimin; Li Zushu
2009-01-01
This study presents a new intelligent control method, human-simulated intelligent control (HSIC) based on the sensory motor intelligent schema (SMIS), for a magneto-rheological (MR) suspension system considering the time delay uncertainty of MR dampers. After formulating the full car dynamic model featuring four MR dampers, the HSIC based on eight SMIS is derived. A neural network model is proposed to compensate for the uncertain time delay of the MR dampers. The HSIC based on SMIS is then experimentally realized for the manufactured full vehicle MR suspension system on the basis of the dSPACE platform. Its performance is evaluated and compared under various road conditions and presented in both time and frequency domains. The results show that significant gains are made in the improvement of vehicle performance. Results include a reduction of over 35% in the acceleration peak-to-peak value of a sprung mass over a bumpy road and a reduction of over 24% in the root-mean-square (RMS) sprung mass acceleration over a random road as compared to passive suspension with typical original equipment (OE) shock absorbers. In addition, the semi-active full vehicle system via HSIC based on SMIS provides better isolation than that via the original HSIC, which can avoid the effect of the time delay uncertainty of the MR dampers
Kucukgoz, Mehmet; Harmanci, Oztan; Mihcak, Mehmet K.; Venkatesan, Ramarathnam
2005-03-01
In this paper, we propose a novel semi-blind video watermarking scheme, where we use pseudo-random robust semi-global features of video in the three dimensional wavelet transform domain. We design the watermark sequence via solving an optimization problem, such that the features of the mark-embedded video are the quantized versions of the features of the original video. The exact realizations of the algorithmic parameters are chosen pseudo-randomly via a secure pseudo-random number generator, whose seed is the secret key, that is known (resp. unknown) by the embedder and the receiver (resp. by the public). We experimentally show the robustness of our algorithm against several attacks, such as conventional signal processing modifications and adversarial estimation attacks.
Cartmell, Matthew P.
2016-09-01
The Editor wishes to make the reader aware that the paper "Semi-active control of the rocking motion of monolithic art objects" by R. Ceravolo, M.L. Pecorelli, and L.Z. Fragonara, did not contain a direct citation of the fundamental and original work by D. Konstantinidis and N. Makris entitled "Experimental and analytical studies on the seismic response of free-standing and anchored laboratory equipment", Report No. PEER 2005/07. Pacific Earthquake Engineering Research (PEER) Center, University of California, Berkeley, 2005. The Editor regrets that this omission was not noted at the time that the above paper was accepted and published.
Semi-active engine mount design using auxiliary magneto-rheological fluid compliance chamber
Mansour, H.; Arzanpour, S.; Golnaraghi, M. F.; Parameswaran, A. M.
2011-03-01
Engine mounts are used in the automotive industry to isolate engine and chassis by reducing the noise and vibration imposed from one to the other. This paper describes modelling, simulation and design of a semi-active engine mount that is designed specifically to address the complicated vibration pattern of variable displacement engines (VDE). The ideal isolation for VDE requires the stiffness to be switchable upon cylinder activation/deactivation operating modes. In order to have a modular design, the same hydraulic engine mount components are maintained and a novel auxiliary magneto-rheological (MR) fluid chamber is developed and retrofitted inside the pumping chamber. The new compliance chamber is a controllable pressure regulator, which can effectively alter the dynamic performance of the mount. Switching between different modes happens by turning the electrical current to the MR chamber magnetic coil on and off. A model has been developed for the passive hydraulic mount and then it is extended to include the MR auxiliary chamber as well. A proof-of-concept prototype of the design has been fabricated which validates the mathematical model. The results demonstrate unique capability of the developed semi-active mount to be used for VDE application.
Nguyen, Sy Dzung; Choi, Seung-Bok; Nguyen, Quoc Hung
2018-05-01
Semi-active train-car suspensions are always impacted negatively by uncertainty and disturbance (UAD). In order to deal with this, we propose a novel optimal fuzzy disturbance observer-enhanced sliding mode controller (FDO-SMC) for magneto-rheological damper (MRD)-based semi-active train-car suspensions subjected to UAD whose variability rate may be high but bounded. The two main parts of the FDO-SMC are an adaptive sliding mode controller (ad-SMC) and an optimal fuzzy disturbance observer (op-FDO). As the first step, the initial structures of the sliding mode controller (SMC) and disturbance observer (DO) are built. Adaptive update laws for the SMC and DO are then set up synchronously via Lyapunov stability analysis. Subsequently, an optimal fuzzy system (op-FS) is designed to fully implement a parameter constraint mechanism so as to guarantee the system stability converging to the desired state even if the UAD variability rate increases in a given range. As a result, both the ad-SMC and op-FDO are formulated. It is shown from the comparative work with existing controllers that the proposed method provides the best vibration control capability with relatively low consumed power.
Shukla, Chitra; Thapliyal, Kishore; Pathak, Anirban
2017-12-01
Semi-quantum protocols that allow some of the users to remain classical are proposed for a large class of problems associated with secure communication and secure multiparty computation. Specifically, first-time semi-quantum protocols are proposed for key agreement, controlled deterministic secure communication and dialogue, and it is shown that the semi-quantum protocols for controlled deterministic secure communication and dialogue can be reduced to semi-quantum protocols for e-commerce and private comparison (socialist millionaire problem), respectively. Complementing with the earlier proposed semi-quantum schemes for key distribution, secret sharing and deterministic secure communication, set of schemes proposed here and subsequent discussions have established that almost every secure communication and computation tasks that can be performed using fully quantum protocols can also be performed in semi-quantum manner. Some of the proposed schemes are completely orthogonal-state-based, and thus, fundamentally different from the existing semi-quantum schemes that are conjugate coding-based. Security, efficiency and applicability of the proposed schemes have been discussed with appropriate importance.
Development and Optimization of controlled drug release ...
African Journals Online (AJOL)
The aim of this study is to develop and optimize an osmotically controlled drug delivery system of diclofenac sodium. Osmotically controlled oral drug delivery systems utilize osmotic pressure for controlled delivery of active drugs. Drug delivery from these systems, to a large extent, is independent of the physiological factors ...
Optimal control for chemical engineers
Upreti, Simant Ranjan
2013-01-01
Optimal Control for Chemical Engineers gives a detailed treatment of optimal control theory that enables readers to formulate and solve optimal control problems. With a strong emphasis on problem solving, the book provides all the necessary mathematical analyses and derivations of important results, including multiplier theorems and Pontryagin's principle.The text begins by introducing various examples of optimal control, such as batch distillation and chemotherapy, and the basic concepts of optimal control, including functionals and differentials. It then analyzes the notion of optimality, de
International Nuclear Information System (INIS)
Praveen Kumar; Jangid, R.S.; Reddy, G.R.
2013-01-01
Highlights: ► Piping system with semi-active variable stiffness damper is investigated under different seismic excitations. ► Switching control law and modified switching control law are adopted. ► There exist an optimum parameters of the SAVSD. ► Substantial reduction of the seismic response of piping system with SAVSD is observed. ► Good amount of energy dissipation is observed. -- Abstract: Seismic loads on piping system due to earthquakes can cause excessive vibrations, which can lead to serious instability resulting in damage or complete failure. In this paper, semi-active variable stiffness dampers (SAVSDs) have been studied to mitigate seismic response and vibration control of piping system used in the process industries, fossil and fissile fuel power plant. The SAVSD changes its stiffness depending upon the piping response and accordingly adds the control forces in the piping system. A study is conducted on the performance of SAVSD due to variation in device stiffness ratios in the switching control law and modified switching control law, which plays an important role in the present control algorithm of the damper. The effectiveness of the SAVSD in terms of reduction in the responses, namely, displacements, accelerations and base shear of the piping system is investigated by comparing uncontrolled responses under four different artificial earthquake motions with increasing amplitudes. The analytical results demonstrate that the SAVSDs under particular optimum parameters are very effective and practically implementable for the seismic response mitigation, vibration control and seismic requalification of piping systems
Energy Technology Data Exchange (ETDEWEB)
Praveen Kumar, E-mail: praveen@barc.gov.in [Department of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076 (India); Bhabha Atomic Research Centre, Trombay, Mumbai 400085 (India); Jangid, R.S. [Department of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076 (India); Reddy, G.R. [Bhabha Atomic Research Centre, Trombay, Mumbai 400085 (India)
2013-05-15
Highlights: ► Piping system with semi-active variable stiffness damper is investigated under different seismic excitations. ► Switching control law and modified switching control law are adopted. ► There exist an optimum parameters of the SAVSD. ► Substantial reduction of the seismic response of piping system with SAVSD is observed. ► Good amount of energy dissipation is observed. -- Abstract: Seismic loads on piping system due to earthquakes can cause excessive vibrations, which can lead to serious instability resulting in damage or complete failure. In this paper, semi-active variable stiffness dampers (SAVSDs) have been studied to mitigate seismic response and vibration control of piping system used in the process industries, fossil and fissile fuel power plant. The SAVSD changes its stiffness depending upon the piping response and accordingly adds the control forces in the piping system. A study is conducted on the performance of SAVSD due to variation in device stiffness ratios in the switching control law and modified switching control law, which plays an important role in the present control algorithm of the damper. The effectiveness of the SAVSD in terms of reduction in the responses, namely, displacements, accelerations and base shear of the piping system is investigated by comparing uncontrolled responses under four different artificial earthquake motions with increasing amplitudes. The analytical results demonstrate that the SAVSDs under particular optimum parameters are very effective and practically implementable for the seismic response mitigation, vibration control and seismic requalification of piping systems.
A semi-physical simulation platform of attitude determination and control system for satellite
Directory of Open Access Journals (Sweden)
Yuanjin Yu
2016-05-01
Full Text Available A semi-physical simulation platform for attitude determination and control system is proposed to verify the attitude estimator and controller on ground. A simulation target, a host PC, many attitude sensors, and actuators compose the simulation platform. The simulation target is composed of a central processing unit board with VxWorks operating system and many input/output boards connected via Compact Peripheral Component Interconnect bus. The executable programs in target are automatically generated from the simulation models in Simulink based on Real-Time Workshop of MATLAB. A three-axes gyroscope, a three-axes magnetometer, a sun sensor, a star tracer, three flywheels, and a Global Positioning System receiver are connected to the simulation target, which formulates the attitude control cycle of a satellite. The simulation models of the attitude determination and control system are described in detail. Finally, the semi-physical simulation platform is used to demonstrate the availability and rationality of the control scheme of a micro-satellite. Comparing the results between the numerical simulation in Simulink and the semi-physical simulation, the semi-physical simulation platform is available and the control scheme successfully achieves three-axes stabilization.
Feedback optimal control of dynamic stochastic two-machine flowshop with a finite buffer
Directory of Open Access Journals (Sweden)
Thang Diep
2010-06-01
Full Text Available This paper examines the optimization of production involving a tandem two-machine system producing a single part type, with each machine being subject to random breakdowns and repairs. An analytical model is formulated with a view to solving an optimal stochastic production problem of the system with machines having up-downtime non-exponential distributions. The model developed is obtained by using a dynamic programming approach and a semi-Markov process. The control problem aims to find the production rates needed by the machines to meet the demand rate, through a minimization of the inventory/shortage cost. Using the Bellman principle, the optimality conditions obtained satisfy the Hamilton-Jacobi-Bellman equation, which depends on time and system states, and ultimately, leads to a feedback control. Consequently, the new model enables us to improve the coefficient of variation (CVup/down to be less than one while it is equal to one in Markov model. Heuristics methods are used to involve the problem because of the difficulty of the analytical model using several states, and to show what control law should be used in each system state (i.e., including Kanban, feedback and CONWIP control. Numerical methods are used to solve the optimality conditions and to show how a machine should produce.
Active semi-supervised learning method with hybrid deep belief networks.
Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong
2014-01-01
In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.
High-Reynolds Number Active Blowing Semi-Span Force Measurement System Development
Lynn, Keith C.; Rhew, Ray D.; Acheson, Michael J.; Jones, Gregory S.; Milholen, William E.; Goodliff, Scott L.
2012-01-01
Recent wind-tunnel tests at the NASA Langley Research Center National Transonic Facility utilized high-pressure bellows to route air to the model for evaluating aircraft circulation control. The introduction of these bellows within the Sidewall Model Support System significantly impacted the performance of the external sidewall mounted semi-span balance. As a result of this impact on the semi-span balance measurement performance, it became apparent that a new capability needed to be built into the National Transonic Facility s infrastructure to allow for performing pressure tare calibrations on the balance in order to properly characterize its performance under the influence of static bellows pressure tare loads and bellows thermal effects. The objective of this study was to design both mechanical calibration hardware and an experimental calibration design that can be employed at the facility in order to efficiently and precisely perform the necessary loadings in order to characterize the semi-span balance under the influence of multiple calibration factors (balance forces/moments and bellows pressure/temperature). Using statistical design of experiments, an experimental design was developed allowing for strategically characterizing the behavior of the semi-span balance for use in circulation control and propulsion-type flow control testing at the National Transonic Facility.
Magneto Rheological Semi-Active Damper with External By-pass Circuit in Modular Structure
Directory of Open Access Journals (Sweden)
Alexandru Boltoşi
2010-10-01
Full Text Available In order to perform experimentally studies, in the paper it is presented a simple method which was elaborated to realize reliable, at low cost and reproducible semi-active dampers with magnetorheological fluids, having external magnetic circuit. The main components are common constitutive elements of industrial hydraulic and pneumatic drivers, having the supplementary advantages being manufactured in a large scale of overall dimensions and demanding minimal modifications. As accumulator, a similar type of hydraulic or pneumatic cylinder was used. The work of the whole damper can be optimized by modifying the nitrogen pressure and interior volume of accumulator. Another important advantage of this conception is the possibility to realize a modular structure composed by the damper, accumulator and magnetic field generator, interconnected by flexible elements.
Semi-passive, Chemical Oxidation Schemes for the Long-term Treatment of Contaminants
Energy Technology Data Exchange (ETDEWEB)
Frank W. Schwartz
2005-12-13
This research involves a combined experimental and modeling study that builds on our previous DOE-sponsored work in investigating how KMnO{sub 4} can be better used with in situ remediation of groundwater contaminated by chlorinated ethylenes (e.g., PCE, TCE, DCE). This study aims to provide scientific basis for developing a new long-term, semi-passive ISCO scheme that uses controlled release KMnO{sub 4} as a reactive barrier component. Specific objectives of the study are (1) to construct controlled release KMnO{sub 4} as a new reactive barrier component that could deliver permanganate at a controlled rate over long time periods of years, (2) to quantitatively describe release mechanisms associated with the controlled release KMnO{sub 4}, (3) to demonstrate efficacy of the new remediation scheme using proof-of-concept experiments, and (4) to design advanced forms of controlled release systems through numerical optimization. The new scheme operates in a long-term, semi-passive manner to control spreading of a dissolved contaminant plume with periodic replacement of the controlled release KMnO{sub 4} installed in the subsurface. As a first step in developing this remedial concept, we manufactured various prototype controlled release KMnO{sub 4} forms. Then we demonstrated using column experiments that the controlled release KMnO{sub 4} could deliver small amount of permanganate into flowing water at controlled rates over long time periods of years. An analytical model was also used to estimate the diffusivities and durations of the controlled release KMnO{sub 4}. Finally, proof-of-concept flow-tank experiments were performed to demonstrate the efficacy of the controlled release KMnO{sub 4} scheme in controlling dissolved TCE plume in a long-term, semi-passive manner. Another important thrust of our research effort involved numerical optimization of controlled release systems. This study used a numerical model that is capable of describing release patterns of active
Directory of Open Access Journals (Sweden)
Ušćumlić Gordana S.
2009-01-01
Full Text Available This paper is concerned on the development of the optimal laboratory procedure for the synthesis of calcium lactate pentahydrate and the application of obtained results in a project for a semi-industrial installation for its production. Calcium lactate is used as an additive in numerous food and pharmaceutical products. Basically, it has to satisfy quality requirements. That was the reason why the procedure for its synthesis had to be optimized in aspects of selection of reactants, their molar ratio, necessary laboratory equipment, reactant addition order, working temperature, isolation of final product from the reaction mixture, yield and product quality. A semi-industrial installation for the production of calcium lactate pentahydrate is projected on the basis of the results of this investigation. The importance of this investigation arises from the fact that this salt is not produced in Serbia and the complete quantity (about 20 t per year is imported.
Smart helicopter rotors optimization and piezoelectric vibration control
Ganguli, Ranjan; Viswamurthy, Sathyamangalam Ramanarayanan
2016-01-01
Exploiting the properties of piezoelectric materials to minimize vibration in rotor-blade actuators, this book demonstrates the potential of smart helicopter rotors to achieve the smoothness of ride associated with jet-engined, fixed-wing aircraft. Vibration control is effected using the concepts of trailing-edge flaps and active-twist. The authors’ optimization-based approach shows the advantage of multiple trailing-edge flaps and algorithms for full-authority control of dual trailing-edge-flap actuators are presented. Hysteresis nonlinearity in piezoelectric stack actuators is highlighted and compensated by use of another algorithm. The idea of response surfaces provides for optimal placement of trailing-edge flaps. The concept of active twist involves the employment of piezoelectrically induced shear actuation in rotating beams. Shear is then demonstrated for a thin-walled aerofoil-section rotor blade under feedback-control vibration minimization. Active twist is shown to be significant in reducing vibra...
Aschepkov, Leonid T; Kim, Taekyun; Agarwal, Ravi P
2016-01-01
This book is based on lectures from a one-year course at the Far Eastern Federal University (Vladivostok, Russia) as well as on workshops on optimal control offered to students at various mathematical departments at the university level. The main themes of the theory of linear and nonlinear systems are considered, including the basic problem of establishing the necessary and sufficient conditions of optimal processes. In the first part of the course, the theory of linear control systems is constructed on the basis of the separation theorem and the concept of a reachability set. The authors prove the closure of a reachability set in the class of piecewise continuous controls, and the problems of controllability, observability, identification, performance and terminal control are also considered. The second part of the course is devoted to nonlinear control systems. Using the method of variations and the Lagrange multipliers rule of nonlinear problems, the authors prove the Pontryagin maximum principle for prob...
Analysis of secretome of breast cancer cell line with an optimized semi-shotgun method
International Nuclear Information System (INIS)
Tang Xiaorong; Yao Ling; Chen Keying; Hu Xiaofang; Xu Lisa; Fan Chunhai
2009-01-01
Secretome, the totality of secreted proteins, is viewed as a promising pool of candidate cancer biomarkers. Simple and reliable methods for identifying secreted proteins are highly desired. We used an optimized semi-shotgun liquid chromatography followed by tandem mass spectrometry (LC-MS/MS) method to analyze the secretome of breast cancer cell line MDA-MB-231. A total of 464 proteins were identified. About 63% of the proteins were classified as secreted proteins, including many promising breast cancer biomarkers, which were thought to be correlated with tumorigenesis, tumor development and metastasis. These results suggest that the optimized method may be a powerful strategy for cell line secretome profiling, and can be used to find potential cancer biomarkers with great clinical significance. (authors)
Optimal Control of Mechanical Systems
Directory of Open Access Journals (Sweden)
Vadim Azhmyakov
2007-01-01
Full Text Available In the present work, we consider a class of nonlinear optimal control problems, which can be called “optimal control problems in mechanics.” We deal with control systems whose dynamics can be described by a system of Euler-Lagrange or Hamilton equations. Using the variational structure of the solution of the corresponding boundary-value problems, we reduce the initial optimal control problem to an auxiliary problem of multiobjective programming. This technique makes it possible to apply some consistent numerical approximations of a multiobjective optimization problem to the initial optimal control problem. For solving the auxiliary problem, we propose an implementable numerical algorithm.
Introduction to optimal control theory
International Nuclear Information System (INIS)
Agrachev, A.A.
2002-01-01
These are lecture notes of the introductory course in Optimal Control theory treated from the geometric point of view. Optimal Control Problem is reduced to the study of controls (and corresponding trajectories) leading to the boundary of attainable sets. We discuss Pontryagin Maximum Principle, basic existence results, and apply these tools to concrete simple optimal control problems. Special sections are devoted to the general theory of linear time-optimal problems and linear-quadratic problems. (author)
PointCom: semi-autonomous UGV control with intuitive interface
Rohde, Mitchell M.; Perlin, Victor E.; Iagnemma, Karl D.; Lupa, Robert M.; Rohde, Steven M.; Overholt, James; Fiorani, Graham
2008-04-01
Unmanned ground vehicles (UGVs) will play an important role in the nation's next-generation ground force. Advances in sensing, control, and computing have enabled a new generation of technologies that bridge the gap between manual UGV teleoperation and full autonomy. In this paper, we present current research on a unique command and control system for UGVs named PointCom (Point-and-Go Command). PointCom is a semi-autonomous command system for one or multiple UGVs. The system, when complete, will be easy to operate and will enable significant reduction in operator workload by utilizing an intuitive image-based control framework for UGV navigation and allowing a single operator to command multiple UGVs. The project leverages new image processing algorithms for monocular visual servoing and odometry to yield a unique, high-performance fused navigation system. Human Computer Interface (HCI) techniques from the entertainment software industry are being used to develop video-game style interfaces that require little training and build upon the navigation capabilities. By combining an advanced navigation system with an intuitive interface, a semi-autonomous control and navigation system is being created that is robust, user friendly, and less burdensome than many current generation systems. mand).
Computational study of smoke flow control in garage fires and optimization of the ventilation system
Directory of Open Access Journals (Sweden)
Banjac Miloš J.
2009-01-01
Full Text Available With the aim of evaluating capabilities of a ventilation system to control the spread of smoke in the emergency operating mode, thereby providing conditions for safe evacuation of people from a fire-struck area, computational fluid dynamics simulation of a fire in a semi-bedded garage was conducted. Using the experimental results of combustion dynamics of a passenger car on fire, optimal positions of ventilation openings were determined. According to recommendations by DIN EN 12101 standard, the operating modes of a ventilation system were verified and optimal start time of the smoke extraction system was defined.
Optimal Control and Optimization of Stochastic Supply Chain Systems
Song, Dong-Ping
2013-01-01
Optimal Control and Optimization of Stochastic Supply Chain Systems examines its subject in the context of the presence of a variety of uncertainties. Numerous examples with intuitive illustrations and tables are provided, to demonstrate the structural characteristics of the optimal control policies in various stochastic supply chains and to show how to make use of these characteristics to construct easy-to-operate sub-optimal policies. In Part I, a general introduction to stochastic supply chain systems is provided. Analytical models for various stochastic supply chain systems are formulated and analysed in Part II. In Part III the structural knowledge of the optimal control policies obtained in Part II is utilized to construct easy-to-operate sub-optimal control policies for various stochastic supply chain systems accordingly. Finally, Part IV discusses the optimisation of threshold-type control policies and their robustness. A key feature of the book is its tying together of ...
Control parameter optimization for AP1000 reactor using Particle Swarm Optimization
International Nuclear Information System (INIS)
Wang, Pengfei; Wan, Jiashuang; Luo, Run; Zhao, Fuyu; Wei, Xinyu
2016-01-01
Highlights: • The PSO algorithm is applied for control parameter optimization of AP1000 reactor. • Key parameters of the MSHIM control system are optimized. • Optimization results are evaluated though simulations and quantitative analysis. - Abstract: The advanced mechanical shim (MSHIM) core control strategy is implemented in the AP1000 reactor for core reactivity and axial power distribution control simultaneously. The MSHIM core control system can provide superior reactor control capabilities via automatic rod control only. This enables the AP1000 to perform power change operations automatically without the soluble boron concentration adjustments. In this paper, the Particle Swarm Optimization (PSO) algorithm has been applied for the parameter optimization of the MSHIM control system to acquire better reactor control performance for AP1000. System requirements such as power control performance, control bank movement and AO control constraints are reflected in the objective function. Dynamic simulations are performed based on an AP1000 reactor simulation platform in each iteration of the optimization process to calculate the fitness values of particles in the swarm. The simulation platform is developed in Matlab/Simulink environment with implementation of a nodal core model and the MSHIM control strategy. Based on the simulation platform, the typical 10% step load decrease transient from 100% to 90% full power is simulated and the objective function used for control parameter tuning is directly incorporated in the simulation results. With successful implementation of the PSO algorithm in the control parameter optimization of AP1000 reactor, four key parameters of the MSHIM control system are optimized. It has been demonstrated by the calculation results that the optimized MSHIM control system parameters can improve the reactor power control capability and reduce the control rod movement without compromising AO control. Therefore, the PSO based optimization
Control strategy optimization of HVAC plants
Energy Technology Data Exchange (ETDEWEB)
Facci, Andrea Luigi; Zanfardino, Antonella [Department of Engineering, University of Napoli “Parthenope” (Italy); Martini, Fabrizio [Green Energy Plus srl (Italy); Pirozzi, Salvatore [SIAT Installazioni spa (Italy); Ubertini, Stefano [School of Engineering (DEIM) University of Tuscia (Italy)
2015-03-10
In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting.
Control strategy optimization of HVAC plants
International Nuclear Information System (INIS)
Facci, Andrea Luigi; Zanfardino, Antonella; Martini, Fabrizio; Pirozzi, Salvatore; Ubertini, Stefano
2015-01-01
In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components and energy systems, and is sufficiently fast to make it applicable to real-time setting
Towards Quantum Cybernetics:. Optimal Feedback Control in Quantum Bio Informatics
Belavkin, V. P.
2009-02-01
A brief account of the quantum information dynamics and dynamical programming methods for the purpose of optimal control in quantum cybernetics with convex constraints and cońcave cost and bequest functions of the quantum state is given. Consideration is given to both open loop and feedback control schemes corresponding respectively to deterministic and stochastic semi-Markov dynamics of stable or unstable systems. For the quantum feedback control scheme with continuous observations we exploit the separation theorem of filtering and control aspects for quantum stochastic micro-dynamics of the total system. This allows to start with the Belavkin quantum filtering equation and derive the generalized Hamilton-Jacobi-Bellman equation using standard arguments of classical control theory. This is equivalent to a Hamilton-Jacobi equation with an extra linear dissipative term if the control is restricted to only Hamiltonian terms in the filtering equation. A controlled qubit is considered as an example throughout the development of the formalism. Finally, we discuss optimum observation strategies to obtain a pure quantum qubit state from a mixed one.
Depletion of forest resources in Sudan. Intervention options for optimal control
International Nuclear Information System (INIS)
Hassan, Rashid; Hertzler, Greg; Benhin, James K.A.
2009-01-01
Agricultural expansion and over-cutting of trees for fuelwood are important causes of deforestation in arid and semi-arid countries such as Sudan. The consequence is increased desertification and high erosion and loss of soil nutrients leading to declining agricultural productivity. However, the social costs of the deforestation externality are not taken into account in present forest management and land use planning in Sudan leading to under-pricing and over-exploitation of the country's forest resources. This study evaluated the suitability of approaches commonly used by most forest resource management agencies for prediction of the state and control of harvesting of forest resources against alternative empirical simulation models using relevant information about economic behaviour of trading agents in the fuelwood market. Results showed the clear superiority of models integrating market behaviour over current approaches in the ability to better simulate real trends of wood consumption and hence depletion rates. The study also adopted an optimal control model to derive socially optimal forest harvesting regimes. The results showed that current rates of forest resource rent recovery and reforestation efforts are very far from optimal. Results also suggest that, in addition to optimal pricing and higher reforestation efforts, promotion and availability of fuel substitutes and investment in wood energy conversion efficiencies have a strong potential for curbing the problem of deforestation in Sudan. (author)
Depletion of forest resources in Sudan. Intervention options for optimal control
Energy Technology Data Exchange (ETDEWEB)
Hassan, Rashid [Centre for Environmental Economics and Policy in Africa (CEEPA), Faculty of Natural and Agricultural Sciences, University of Pretoria, 0002 Pretoria (South Africa); Hertzler, Greg [Agricultural and Resource Economics, Faculty of Agriculture, Food and Natural Resources, The University of Sydney, Sydney, NSW 2006 (Australia); Benhin, James K.A. [Marine and Coastal Environmental Economics, Business School, University of Plymouth, Drake Circus, Plymouth, Devon PL4 8AA (United Kingdom)
2009-04-15
Agricultural expansion and over-cutting of trees for fuelwood are important causes of deforestation in arid and semi-arid countries such as Sudan. The consequence is increased desertification and high erosion and loss of soil nutrients leading to declining agricultural productivity. However, the social costs of the deforestation externality are not taken into account in present forest management and land use planning in Sudan leading to under-pricing and over-exploitation of the country's forest resources. This study evaluated the suitability of approaches commonly used by most forest resource management agencies for prediction of the state and control of harvesting of forest resources against alternative empirical simulation models using relevant information about economic behaviour of trading agents in the fuelwood market. Results showed the clear superiority of models integrating market behaviour over current approaches in the ability to better simulate real trends of wood consumption and hence depletion rates. The study also adopted an optimal control model to derive socially optimal forest harvesting regimes. The results showed that current rates of forest resource rent recovery and reforestation efforts are very far from optimal. Results also suggest that, in addition to optimal pricing and higher reforestation efforts, promotion and availability of fuel substitutes and investment in wood energy conversion efficiencies have a strong potential for curbing the problem of deforestation in Sudan. (author)
Depletion of forest resources in Sudan: Intervention options for optimal control
Energy Technology Data Exchange (ETDEWEB)
Hassan, Rashid [Centre for Environmental Economics and Policy in Africa (CEEPA), Faculty of Natural and Agricultural Sciences, University of Pretoria, 0002 Pretoria (South Africa)], E-mail: rashid.hassan@up.ac.za; Hertzler, Greg [Agricultural and Resource Economics, Faculty of Agriculture, Food and Natural Resources, University of Sydney, Sydney, NSW 2006 (Australia); Benhin, James K.A. [Marine and Coastal Environmental Economics, Business School, University of Plymouth, Drake Circus, Plymouth, Devon PL4 8AA (United Kingdom)
2009-04-15
Agricultural expansion and over-cutting of trees for fuelwood are important causes of deforestation in arid and semi-arid countries such as Sudan. The consequence is increased desertification and high erosion and loss of soil nutrients leading to declining agricultural productivity. However, the social costs of the deforestation externality are not taken into account in present forest management and land use planning in Sudan leading to under-pricing and over-exploitation of the country's forest resources. This study evaluated the suitability of approaches commonly used by most forest resource management agencies for prediction of the state and control of harvesting of forest resources against alternative empirical simulation models using relevant information about economic behaviour of trading agents in the fuelwood market. Results showed the clear superiority of models integrating market behaviour over current approaches in the ability to better simulate real trends of wood consumption and hence depletion rates. The study also adopted an optimal control model to derive socially optimal forest harvesting regimes. The results showed that current rates of forest resource rent recovery and reforestation efforts are very far from optimal. Results also suggest that, in addition to optimal pricing and higher reforestation efforts, promotion and availability of fuel substitutes and investment in wood energy conversion efficiencies have a strong potential for curbing the problem of deforestation in Sudan.
Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.
Wei, Qinglai; Liu, Derong; Lin, Hanquan
2016-03-01
In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.
Optimal integral force feedback for active vibration control
Teo, Yik R.; Fleming, Andrew J.
2015-11-01
This paper proposes an improvement to Integral Force Feedback (IFF), which is a popular method for active vibration control of structures and mechanical systems. Benefits of IFF include robustness, guaranteed stability and simplicity. However, the maximum damping performance is dependent on the stiffness of the system; hence, some systems cannot be adequately controlled. In this paper, an improvement to the classical force feedback control scheme is proposed. The improved method achieves arbitrary damping for any mechanical system by introducing a feed-through term. The proposed improvement is experimentally demonstrated by actively damping an objective lens assembly for a high-speed confocal microscope.
a Method for Preview Vibration Control of Systems Having Forcing Inputs and Rapidly-Switched Dampers
ElBeheiry, E. M.
1998-07-01
In a variety of applications, especially in large scale dynamic systems, the mechanization of different vibration control elements in different locations would be decided by limitations placed on the modal vibration of the system and the inherent dynamic coupling between its modes. Also, the quality of vibration control to the economy of producing the whole system would be another trade-off leading to a mix of passive, active and semi-active vibration control elements in one system. This termactiveis limited to externally powered vibration control inputs and the termsemi-activeis limited to rapidly switched dampers. In this article, an optimal preview control method is developed for application to dynamic systems having active and semi-active vibration control elements mechanized at different locations in one system. The system is then a piecewise (bilinear) controller in which two independent sets of control inputs appear additively and multiplicatively. Calculus of variations along with the Hamiltonian approach are employed for the derivation of this method. In essence, it requires the active elements to be ideal force generators and the switched dampers to have the property of on-line variation of the damping characteristics to pre-determined limits. As the dampers switch during operation the whole system's structure differs, and then values of the active forcing inputs are adapted to match these rapid changes. Strictly speaking, each rapidly switched damper has pre-known upper and lower damping levels and it can take on any in-between value. This in-between value is to be determined by the method as long as the damper tracks a pre-known fully active control demand. In every damping state of each semi-active damper the method provides the optimal matching values of the active forcing inputs. The method is shown to have the feature of solving simple standard matrix equations to obtain closed form solutions. A comprehensive 9-DOF tractor semi-trailer model is used
Nonlinear optimal control theory
Berkovitz, Leonard David
2012-01-01
Nonlinear Optimal Control Theory presents a deep, wide-ranging introduction to the mathematical theory of the optimal control of processes governed by ordinary differential equations and certain types of differential equations with memory. Many examples illustrate the mathematical issues that need to be addressed when using optimal control techniques in diverse areas. Drawing on classroom-tested material from Purdue University and North Carolina State University, the book gives a unified account of bounded state problems governed by ordinary, integrodifferential, and delay systems. It also dis
Emerging trends in vibration control of wind turbines: a focus on a dual control strategy.
Staino, Andrea; Basu, Biswajit
2015-02-28
The paper discusses some of the recent developments in vibration control strategies for wind turbines, and in this context proposes a new dual control strategy based on the combination and modification of two recently proposed control schemes. Emerging trends in the vibration control of both onshore and offshore wind turbines are presented. Passive, active and semi-active structural vibration control algorithms have been reviewed. Of the existing controllers, two control schemes, active pitch control and active tendon control, have been discussed in detail. The proposed new control scheme is a merger of active tendon control with passive pitch control, and is designed using a Pareto-optimal problem formulation. This combination of controllers is the cornerstone of a dual strategy with the feature of decoupling vibration control from optimal power control as one of its main advantages, in addition to reducing the burden on the pitch demand. This dual control strategy will bring in major benefits to the design of modern wind turbines and is expected to play a significant role in the advancement of offshore wind turbine technologies. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Analysis and control of Boolean networks a semi-tensor product approach
Cheng, Daizhan; Li, Zhiqiang
2010-01-01
This book presents a new approach to the investigation of Boolean control networks, using the semi-tensor product (STP), which can express a logical function as a conventional discrete-time linear system. This makes it possible to analyze basic control problems.
Concepts of real time and semi-real time material control
International Nuclear Information System (INIS)
Lovett, J.E.
1975-01-01
After a brief consideration of the traditional material balance accounting on an MBA basis, this paper explores the basic concepts of real time and semi-real time material control, together with some of the major problems to be solved. Three types of short-term material control are discussed: storage, batch processing, and continuous processing. (DLC)
Active control of noise radiation from vibrating structures
DEFF Research Database (Denmark)
Mørkholt, Jakob
developed, based on the theory of radiation filters for estimating the sound radiation from multimodal vibrations. This model has then been used in simulations of optimal feedback control, with special emphasis of the stability margins of the optimal control scheme. Two different methods of designing...... optimal and robust discrete-time feedback controllers for active vibration control of multimodal structures have been compared. They have been showed to yield controllers with identical frequency response characteristics, even though they employ completely different methods of numerical solutions...... and result in different representations of the controllers. The Internal Model Control structure combined with optimal filtering is suggested as an alternative to state space optimal control techniques for designing robust optimal controllers for audio frequency vibration control of resonant structures....
Adaptive optimization for active queue management supporting TCP flows
Baldi, S.; Kosmatopoulos, Elias B.; Pitsillides, Andreas; Lestas, Marios; Ioannou, Petros A.; Wan, Y.; Chiu, George; Johnson, Katie; Abramovitch, Danny
2016-01-01
An adaptive decentralized strategy for active queue management of TCP flows over communication networks is presented. The proposed strategy solves locally, at each link, an optimal control problem, minimizing a cost composed of residual capacity and buffer queue size. The solution of the optimal
Land cover controls on summer discharge and runoff solution chemistry of semi-arid urban catchments
Gallo, Erika L.; Brooks, Paul D.; Lohse, Kathleen A.; McLain, Jean E. T.
2013-04-01
SummaryRecharge of urban runoff to groundwater as a stormwater management practice has gained importance in semi-arid regions where water resources are scarce and urban centers are growing. Despite this trend, the importance of land cover in controlling semi-arid catchment runoff quantity and quality remains unclear. Here we address the question: How do land cover characteristics control the amount and quality of storm runoff in semi-arid urban catchments? We monitored summertime runoff quantity and quality from five catchments dominated by distinct urban land uses: low, medium, and high density residential, mixed use, and commercial. Increasing urban land cover increased runoff duration and the likelihood that a rainfall event would result in runoff, but did not increase the time to peak discharge of episodic runoff. The effect of urban land cover on hydrologic responses was tightly coupled to the magnitude of rainfall. At distinct rainfall thresholds, roads, percent impervious cover and the stormwater drainage network controlled runoff frequency, runoff depth and runoff ratios. Contrary to initial expectations, runoff quality did not vary in repose to impervious cover or land use. We identified four major mechanisms controlling runoff quality: (1) variable solute sourcing due to land use heterogeneity and above ground catchment connectivity; (2) the spatial extent of pervious and biogeochemically active areas; (3) the efficiency of overland flow and runoff mobilization; and (4) solute flushing and dilution. Our study highlights the importance of the stormwater drainage systems characteristics in controlling urban runoff quantity and quality; and suggests that enhanced wetting and in-stream processes may control solute sourcing and retention. Finally, we suggest that the characteristics of the stormwater drainage system should be integrated into stormwater management approaches.
Design considerations for a semi-active electromagnetic suspension system
Paulides, J.J.H.; Encica, L.; Lomonova, E.A.; Vandenput, A.J.A.
2006-01-01
Vehicle manufacturers always strive to improve the vehicle handling and passenger safety and comfort. One of the focus points for the automotive industry is the (semi-)active suspension system for which various commercial technologies are existing, varying from pneumatic to hydraulic. This paper
Directory of Open Access Journals (Sweden)
Denise Tourino Rezende de Cerqueira
Full Text Available ABSTRACT: Improved spray deposition can be attained by electrostatically charging spray droplets, which increases the attraction of droplets to plants and decreases operator exposure to pesticide and losses to the environment. However, this technique alone is not sufficient to achieve desirable penetration of the spray solution into the crop canopy; thus, air assistance can be added to the electrostatic spraying to further improve spray deposition. This study was conducted to compare different spraying technologies on spray deposition and two-spotted spider mite control in cut chrysanthemum. Treatments included in the study were: conventional TJ 8003 double flat fan nozzles, conventional TXVK-3 hollow cone nozzles, semi-stationary motorized jet launched spray with electrostatic spray system (ESS and air assistance (AA, and semi-stationary motorized jet launched spray with AA only (no ESS. To evaluate the effect of these spraying technologies on the control of two-spotted spider mite, a control treatment was included that did not receive an acaricide application. The AA spraying technology, with or without ESS, optimized spray deposition and provided satisfactory two-spotted spider mite control up to 4 days after application.
Process control and optimization with simple interval calculation method
DEFF Research Database (Denmark)
Pomerantsev, A.; Rodionova, O.; Høskuldsson, Agnar
2006-01-01
for the quality improvement in the course of production. The latter is an active quality optimization, which takes into account the actual history of the process. The advocate approach is allied to the conventional method of multivariate statistical process control (MSPC) as it also employs the historical process......Methods of process control and optimization are presented and illustrated with a real world example. The optimization methods are based on the PLS block modeling as well as on the simple interval calculation methods of interval prediction and object status classification. It is proposed to employ...... the series of expanding PLS/SIC models in order to support the on-line process improvements. This method helps to predict the effect of planned actions on the product quality and thus enables passive quality control. We have also considered an optimization approach that proposes the correcting actions...
Guglielmi, Y.; Cappa, F.; Nussbaum, C.
2015-12-01
The appreciation of the sensitivity of fractures and fault zones to fluid-induced-deformations in the subsurface is a key question in predicting the reservoir/caprock system integrity around fluid manipulations with applications to reservoir leakage and induced seismicity. It is also a question of interest in understanding earthquakes source, and recently the hydraulic behavior of clay faults under a potential reactivation around nuclear underground depository sites. Fault and fractures dynamics studies face two key problems (1) the up-scaling of laboratory determined properties and constitutive laws to the reservoir scale which is not straightforward when considering faults and fractures heterogeneities, (2) the difficulties to control both the induced seismicity and the stimulated zone geometry when a fault is reactivated. Using instruments dedicated to measuring coupled pore pressures and deformations downhole, we conducted field academic experiments to characterize fractures and fault zones hydromechanical properties as a function of their multi-scale architecture, and to monitor their dynamic behavior during the earthquake nucleation process. We show experiments on reservoir or cover rocks analogues in underground research laboratories where experimental conditions can be optimized. Key result of these experiments is to highlight how important the aseismic fault activation is compared to the induced seismicity. We show that about 80% of the fault kinematic moment is aseismic and discuss the complex associated fault friction coefficient variations. We identify that the slip stability and the slip velocity are mainly controlled by the rate of the permeability/porosity increase, and discuss the conditions for slip nucleation leading to seismic instability.
Semi-supervised learning via regularized boosting working on multiple semi-supervised assumptions.
Chen, Ke; Wang, Shihai
2011-01-01
Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learning with various strategies. To our knowledge, however, none of them takes all three semi-supervised assumptions, i.e., smoothness, cluster, and manifold assumptions, together into account during boosting learning. In this paper, we propose a novel cost functional consisting of the margin cost on labeled data and the regularization penalty on unlabeled data based on three fundamental semi-supervised assumptions. Thus, minimizing our proposed cost functional with a greedy yet stagewise functional optimization procedure leads to a generic boosting framework for semi-supervised learning. Extensive experiments demonstrate that our algorithm yields favorite results for benchmark and real-world classification tasks in comparison to state-of-the-art semi-supervised learning algorithms, including newly developed boosting algorithms. Finally, we discuss relevant issues and relate our algorithm to the previous work.
Near optimal decentralized H_inf control
DEFF Research Database (Denmark)
Stoustrup, J.; Niemann, Hans Henrik
It is shown that foir a class of decentralized control problems there does not exist a sequence of controllers of bounded order which obtains near optimal control. Neither does there exist an infinity dimentional optimal controller. Using the insight of the line of proof of these results, a heuri......It is shown that foir a class of decentralized control problems there does not exist a sequence of controllers of bounded order which obtains near optimal control. Neither does there exist an infinity dimentional optimal controller. Using the insight of the line of proof of these results...
Miller, Christopher J.; Goodrick, Dan
2017-01-01
The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads. The subject of this paper is the design of the optimal control architecture, and provides the reader with some techniques for tailoring the architecture, along with detailed simulation results.
Consensus of satellite cluster flight using an energy-matching optimal control method
Luo, Jianjun; Zhou, Liang; Zhang, Bo
2017-11-01
This paper presents an optimal control method for consensus of satellite cluster flight under a kind of energy matching condition. Firstly, the relation between energy matching and satellite periodically bounded relative motion is analyzed, and the satellite energy matching principle is applied to configure the initial conditions. Then, period-delayed errors are adopted as state variables to establish the period-delayed errors dynamics models of a single satellite and the cluster. Next a novel satellite cluster feedback control protocol with coupling gain is designed, so that the satellite cluster periodically bounded relative motion consensus problem (period-delayed errors state consensus problem) is transformed to the stability of a set of matrices with the same low dimension. Based on the consensus region theory in the research of multi-agent system consensus issues, the coupling gain can be obtained to satisfy the requirement of consensus region and decouple the satellite cluster information topology and the feedback control gain matrix, which can be determined by Linear quadratic regulator (LQR) optimal method. This method can realize the consensus of satellite cluster period-delayed errors, leading to the consistency of semi-major axes (SMA) and the energy-matching of satellite cluster. Then satellites can emerge the global coordinative cluster behavior. Finally the feasibility and effectiveness of the present energy-matching optimal consensus for satellite cluster flight is verified through numerical simulations.
Design of a semi-custom integrated circuit for the SLAC SLC timing control system
International Nuclear Information System (INIS)
Linstadt, E.
1984-10-01
A semi-custom (gate array) integrated circuit has been designed for use in the SLAC Linear Collider timing and control system. The design process and SLAC's experiences during the phases of the design cycle are described. Issues concerning the partitioning of the design into semi-custom and standard components are discussed. Functional descriptions of the semi-custom integrated circuit and the timing module in which it is used are given
Discriminative semi-supervised feature selection via manifold regularization.
Xu, Zenglin; King, Irwin; Lyu, Michael Rung-Tsong; Jin, Rong
2010-07-01
Feature selection has attracted a huge amount of interest in both research and application communities of data mining. We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number of labeled samples are usually insufficient for identifying the relevant features, the critical problem arising from semi-supervised feature selection is how to take advantage of the information underneath the unlabeled data. To address this problem, we propose a novel discriminative semi-supervised feature selection method based on the idea of manifold regularization. The proposed approach selects features through maximizing the classification margin between different classes and simultaneously exploiting the geometry of the probability distribution that generates both labeled and unlabeled data. In comparison with previous semi-supervised feature selection algorithms, our proposed semi-supervised feature selection method is an embedded feature selection method and is able to find more discriminative features. We formulate the proposed feature selection method into a convex-concave optimization problem, where the saddle point corresponds to the optimal solution. To find the optimal solution, the level method, a fairly recent optimization method, is employed. We also present a theoretic proof of the convergence rate for the application of the level method to our problem. Empirical evaluation on several benchmark data sets demonstrates the effectiveness of the proposed semi-supervised feature selection method.
International Nuclear Information System (INIS)
Sugny, D.; Bomble, L.; Ribeyre, T.; Dulieu, O.; Desouter-Lecomte, M.
2009-01-01
Implementation of quantum controlled-NOT (CNOT) gates in realistic molecular systems is studied using stimulated Raman adiabatic passage (STIRAP) techniques optimized in the time domain by genetic algorithms or coupled with optimal control theory. In the first case, with an adiabatic solution (a series of STIRAP processes) as starting point, we optimize in the time domain different parameters of the pulses to obtain a high fidelity in two realistic cases under consideration. A two-qubit CNOT gate constructed from different assignments in rovibrational states is considered in diatomic (NaCs) or polyatomic (SCCl 2 ) molecules. The difficulty of encoding logical states in pure rotational states with STIRAP processes is illustrated. In such circumstances, the gate can be implemented by optimal control theory and the STIRAP sequence can then be used as an interesting trial field. We discuss the relative merits of the two methods for rovibrational computing (structure of the control field, duration of the control, and efficiency of the optimization).
Preconditioning for partial differential equation constrained optimization with control constraints
Stoll, Martin
2011-10-18
Optimal control problems with partial differential equations play an important role in many applications. The inclusion of bound constraints for the control poses a significant additional challenge for optimization methods. In this paper, we propose preconditioners for the saddle point problems that arise when a primal-dual active set method is used. We also show for this method that the same saddle point system can be derived when the method is considered as a semismooth Newton method. In addition, the projected gradient method can be employed to solve optimization problems with simple bounds, and we discuss the efficient solution of the linear systems in question. In the case when an acceleration technique is employed for the projected gradient method, this again yields a semismooth Newton method that is equivalent to the primal-dual active set method. We also consider the Moreau-Yosida regularization method for control constraints and efficient preconditioners for this technique. Numerical results illustrate the competitiveness of these approaches. © 2011 John Wiley & Sons, Ltd.
Preconditioning for partial differential equation constrained optimization with control constraints
Stoll, Martin; Wathen, Andy
2011-01-01
Optimal control problems with partial differential equations play an important role in many applications. The inclusion of bound constraints for the control poses a significant additional challenge for optimization methods. In this paper, we propose preconditioners for the saddle point problems that arise when a primal-dual active set method is used. We also show for this method that the same saddle point system can be derived when the method is considered as a semismooth Newton method. In addition, the projected gradient method can be employed to solve optimization problems with simple bounds, and we discuss the efficient solution of the linear systems in question. In the case when an acceleration technique is employed for the projected gradient method, this again yields a semismooth Newton method that is equivalent to the primal-dual active set method. We also consider the Moreau-Yosida regularization method for control constraints and efficient preconditioners for this technique. Numerical results illustrate the competitiveness of these approaches. © 2011 John Wiley & Sons, Ltd.
Optimal control in thermal engineering
Badescu, Viorel
2017-01-01
This book is the first major work covering applications in thermal engineering and offering a comprehensive introduction to optimal control theory, which has applications in mechanical engineering, particularly aircraft and missile trajectory optimization. The book is organized in three parts: The first part includes a brief presentation of function optimization and variational calculus, while the second part presents a summary of the optimal control theory. Lastly, the third part describes several applications of optimal control theory in solving various thermal engineering problems. These applications are grouped in four sections: heat transfer and thermal energy storage, solar thermal engineering, heat engines and lubrication.Clearly presented and easy-to-use, it is a valuable resource for thermal engineers and thermal-system designers as well as postgraduate students.
Optimal Adaptive Droop Control for Effective Load Sharing in AC Microgrids
DEFF Research Database (Denmark)
Anvari-Moghaddam, Amjad; Shafiee, Qobad; Quintero, Juan Carlos Vasquez
2016-01-01
During the past few years, microgrids (MGs) have been becoming more attractive as effective means to integrate different distributed energy resources (DERs). To coordinate active and reactive power sharing among DERs, conventional droop control method is widely used as a decentralized control...... control strategy is developed in two levels. The upper control level is a mixed-objective optimization algorithm that provides optimal set-points for power generations considering system’s constraints and goals, while the lower control level is responsible for tracking the reference signals coming from...
Activity and heart rate in semi-domesticated reindeer during adaptation to emergency feeding.
Nilsson, A; Ahman, B; Norberg, H; Redbo, I; Eloranta, E; Olsson, K
2006-06-15
Although reindeer are well adapted to limited food resources during winter, semi-domesticated reindeer are regularly fed when snow conditions are bad in order to prevent starvation. Feeding sometimes results in health problems and loss of animals. This study was made to assess if activity pattern in reindeer could be used as a tool for the reindeer herder in early detection of animals that are not adapting to feeding. The frequency of 10 behavioural categories was recorded in five groups of penned, eight-month-old, female semi-domesticated reindeer. Three reindeer per group were fitted with heart rate monitors. Lying was the most frequent behaviour, whilst there were few cases of agonistic behaviour. Heart rate varied during the day, with peaks during feeding and low heart rates in the early morning. Restricted feed intake resulted in more locomotion and seeking but less ruminating compared to feeding ad libitum. This was followed by a generally lower heart rate in reindeer in the restricted groups compared to controls. Subsequent feeding with different combinations of lichens, silage and pellets ad libitum resulted initially in significantly more of the animals lying curled up, compared to controls, combined with increased heart rates. As the experiment continued the general activity pattern, as well as the heart rate, gradually became more similar in all groups. Lying curled was the behavioural indicator most consistently affected by feed deprivation and adaptation to feeding and may thus be a useful indicator to distinguish individual reindeer that are not adjusting to feeding.
Fuzzy logic control and optimization system
Lou, Xinsheng [West Hartford, CT
2012-04-17
A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Multi-component controllers in reactor physics optimality analysis
International Nuclear Information System (INIS)
Aldemir, T.
1978-01-01
An algorithm is developed for the optimality analysis of thermal reactor assemblies with multi-component control vectors. The neutronics of the system under consideration is assumed to be described by the two-group diffusion equations and constraints are imposed upon the state and control variables. It is shown that if the problem is such that the differential and algebraic equations describing the system can be cast into a linear form via a change of variables, the optimal control components are piecewise constant functions and the global optimal controller can be determined by investigating the properties of the influence functions. Two specific problems are solved utilizing this approach. A thermal reactor consisting of fuel, burnable poison and moderator is found to yield maximal power when the assembly consists of two poison zones and the power density is constant throughout the assembly. It is shown that certain variational relations have to be considered to maintain the activeness of the system equations as differential constraints. The problem of determining the maximum initial breeding ratio for a thermal reactor is solved by treating the fertile and fissile material absorption densities as controllers. The optimal core configurations are found to consist of three fuel zones for a bare assembly and two fuel zones for a reflected assembly. The optimum fissile material density is determined to be inversely proportional to the thermal flux
Analysis and Optimal Condition of the Rear-Sound-Aided Control Source in Active Noise Control
Directory of Open Access Journals (Sweden)
Karel Kreuter
2011-01-01
Full Text Available An active noise control scenario of simple ducts is considered. The previously suggested technique of using an single loudspeaker and its rear sound to cancel the upstream sound is further examined and compared to the bidirectional solution in order to give theoretical proof of its advantage. Firstly, a model with a new approach for taking damping effects into account is derived based on the electrical transmission line theory. By comparison with the old model, the new approach is validated, and occurring differences are discussed. Moreover, a numerical application with the consideration of damping is implemented for confirmation. The influence of the rear sound strength on the feedback-path system is investigated, and the optimal condition is determined. Finally, it is proven that the proposed source has an advantage of an extended phase lag and a time delay in the feedback-path system by both frequency-response analysis and numerical calculation of the time response.
Optimal detection and control strategies for invasive species management
Shefali V. Mehta; Robert G. Haight; Frances R. Homans; Stephen Polasky; Robert C. Venette
2007-01-01
The increasing economic and environmental losses caused by non-native invasive species amplify the value of identifying and implementing optimal management options to prevent, detect, and control invasive species. Previous literature has focused largely on preventing introductions of invasive species and post-detection control activities; few have addressed the role of...
Directory of Open Access Journals (Sweden)
Zhixiang Ling
2016-09-01
Full Text Available The three-port converter has three H-bridge ports that can interface with three different energy sources and offers the advantages of flexible power transmission, galvanic isolation ability and high power density. The three-port full-bridge converter can be used in electric vehicles as a combined charger that consists of a battery charger and a DC-DC converter. Power transfer occurs between two ports while the third port is isolated, i.e., the average power is zero. The purpose of this paper is to apply an optimal phase shift strategy in isolation control and provide a detailed comparison between traditional phase shift control and optimal phase shift control under the proposed isolation control scheme, including comparison of the zero-voltage-switching range and the root mean square current for the two methods. Based on this analysis, the optimal parameters are selected. The results of simulations and experiments are given to verify the advantages of dual-phase-shift control in isolation control.
Chen, Xiangqun; Huang, Rui; Shen, Liman; chen, Hao; Xiong, Dezhi; Xiao, Xiangqi; Liu, Mouhai; Xu, Renheng
2018-03-01
In this paper, the semi-active RFID watt-hour meter is applied to automatic test lines and intelligent warehouse management, from the transmission system, test system and auxiliary system, monitoring system, realize the scheduling of watt-hour meter, binding, control and data exchange, and other functions, make its more accurate positioning, high efficiency of management, update the data quickly, all the information at a glance. Effectively improve the quality, efficiency and automation of verification, and realize more efficient data management and warehouse management.
Time-optimal control with finite bandwidth
Hirose, M.; Cappellaro, P.
2018-04-01
Time-optimal control theory provides recipes to achieve quantum operations with high fidelity and speed, as required in quantum technologies such as quantum sensing and computation. While technical advances have achieved the ultrastrong driving regime in many physical systems, these capabilities have yet to be fully exploited for the precise control of quantum systems, as other limitations, such as the generation of higher harmonics or the finite response time of the control apparatus, prevent the implementation of theoretical time-optimal control. Here we present a method to achieve time-optimal control of qubit systems that can take advantage of fast driving beyond the rotating wave approximation. We exploit results from time-optimal control theory to design driving protocols that can be implemented with realistic, finite-bandwidth control fields, and we find a relationship between bandwidth limitations and achievable control fidelity.
Fuzzy Controller for Automatic Steering in Heavy Vehicle Semi-Trailers
Directory of Open Access Journals (Sweden)
Herrera-Ruíz G.
2013-01-01
Full Text Available Los camiones con semi-remolques son ampliamente utilizados para el transporte de mercancías debido a su bajo costo de operación, sino inherentes a estos vehículos son algunos problemas como una mala maniobrabilidad. Para minimizar los efectos de esta desventaja, entre otras soluciones, la incorporación de ejes orientables en los semirremolques se ha propuesto. Este artículo presenta una ecuación de dirección, y un controlador de lógica difusa para un semi-remolque automático forzado sistema de dirección para reducir al mínimo el apagado de seguimiento y la anchura total en curva, lo que resulta en una mejora de la maniobrabilidad del vehículo a baja velocidad. Para lograr esto, el algoritmo de control propuesto considera el ángulo de articulación y parámetros tales como la velocidad y dirección del vehículo. El sistema se probó en un instrumentada experimental semi-remolque durante varias maniobras de prueba predeterminados.
Semi-parametrical NAA method for paper analysis
International Nuclear Information System (INIS)
Medeiros, Ilca M.M.A.; Zamboni, Cibele B.; Cruz, Manuel T.F. da; Morel, Jose C.O.; Park, Song W.
2007-01-01
The semi-parametric Neutron Activation Analysis technique, using Au as flux monitor, was applied to determine element concentrations in white paper, usually commercialized, aiming to check the quality control of its production in industrial process. (author)
The design of a semi-custom intergrated circuit for the SLAC SLC timing control system
International Nuclear Information System (INIS)
Linstadt, E.
1985-01-01
A semi-custom (gate array) integrated circuit has been designed for use in the SLAC Linear Collider timing and control system. The design process and SLAC's experiences during the phases of the design cycle are described. Issues concerning the partitioning of the design into semi-custom and standard components are discussed. Functional descriptions of the semi-custom integrated circuit and the timing module in which it is used are given
Wang, D.; Cui, Y.
2015-12-01
The objectives of this paper are to validate the applicability of a multi-band quasi-analytical algorithm (QAA) in retrieval absorption coefficients of optically active constituents in turbid coastal waters, and to further improve the model using a proposed semi-analytical model (SAA). The ap(531) and ag(531) semi-analytically derived using SAA model are quite different from the retrievals procedures of QAA model that ap(531) and ag(531) are semi-analytically derived from the empirical retrievals results of a(531) and a(551). The two models are calibrated and evaluated against datasets taken from 19 independent cruises in West Florida Shelf in 1999-2003, provided by SeaBASS. The results indicate that the SAA model produces a superior performance to QAA model in absorption retrieval. Using of the SAA model in retrieving absorption coefficients of optically active constituents from West Florida Shelf decreases the random uncertainty of estimation by >23.05% from the QAA model. This study demonstrates the potential of the SAA model in absorption coefficients of optically active constituents estimating even in turbid coastal waters. Keywords: Remote sensing; Coastal Water; Absorption Coefficient; Semi-analytical Model
Optimization of accelerator control
International Nuclear Information System (INIS)
Vasiljev, N.D.; Mozin, I.V.; Shelekhov, V.A.; Efremov, D.V.
1992-01-01
Expensive exploitation of charged particle accelerators is inevitably concerned with requirements of effectively obtaining of the best characteristics of accelerated beams for physical experiments. One of these characteristics is intensity. Increase of intensity is hindered by a number of effects, concerned with the influence of the volume charge field on a particle motion dynamics in accelerator's chamber. However, ultimate intensity, determined by a volume charge, is almost not achieved for the most of the operating accelerators. This fact is caused by losses of particles during injection, at the initial stage of acceleration and during extraction. These losses are caused by deviations the optimal from real characteristics of the accelerating and magnetic system. This is due to a number of circumstances, including technological tolerances on structural elements of systems, influence of measuring and auxiliary equipment and beam consumers' installations, placed in the closed proximity to magnets, and instability in operation of technological systems of accelerator. Control task consists in compensation of deviations of characteristics of magnetic and electric fields by optimal selection of control actions. As for technical means, automatization of modern accelerators allows to solve optimal control problems in real time. Therefore, the report is devoted to optimal control methods and experimental results. (J.P.N.)
PI Stabilization for Congestion Control of AQM Routers with Tuning Parameter Optimization
Directory of Open Access Journals (Sweden)
S. Chebli
2016-09-01
Full Text Available In this paper, we consider the problem of stabilizing network using a new proportional- integral (PI based congestion controller in active queue management (AQM router; with appropriate model approximation in the first order delay systems, we seek a stability region of the controller by using the Hermite- Biehler theorem, which isapplicable to quasipolynomials. A Genetic Algorithm technique is employed to derive optimal or near optimal PI controller parameters.
Intelligent, Semi-Automated Procedure Aid (ISAPA) for ISS Flight Control, Phase II
National Aeronautics and Space Administration — We propose to develop the Intelligent, Semi-Automated Procedure Aid (ISAPA) intended for use by International Space Station (ISS) ground controllers to increase the...
Gradient Optimization for Analytic conTrols - GOAT
Assémat, Elie; Machnes, Shai; Tannor, David; Wilhelm-Mauch, Frank
Quantum optimal control becomes a necessary step in a number of studies in the quantum realm. Recent experimental advances showed that superconducting qubits can be controlled with an impressive accuracy. However, most of the standard optimal control algorithms are not designed to manage such high accuracy. To tackle this issue, a novel quantum optimal control algorithm have been introduced: the Gradient Optimization for Analytic conTrols (GOAT). It avoids the piecewise constant approximation of the control pulse used by standard algorithms. This allows an efficient implementation of very high accuracy optimization. It also includes a novel method to compute the gradient that provides many advantages, e.g. the absence of backpropagation or the natural route to optimize the robustness of the control pulses. This talk will present the GOAT algorithm and a few applications to transmons systems.
Semi-Supervised Learning of Lift Optimization of Multi-Element Three-Segment Variable Camber Airfoil
Kaul, Upender K.; Nguyen, Nhan T.
2017-01-01
This chapter describes a new intelligent platform for learning optimal designs of morphing wings based on Variable Camber Continuous Trailing Edge Flaps (VCCTEF) in conjunction with a leading edge flap called the Variable Camber Krueger (VCK). The new platform consists of a Computational Fluid Dynamics (CFD) methodology coupled with a semi-supervised learning methodology. The CFD component of the intelligent platform comprises of a full Navier-Stokes solution capability (NASA OVERFLOW solver with Spalart-Allmaras turbulence model) that computes flow over a tri-element inboard NASA Generic Transport Model (GTM) wing section. Various VCCTEF/VCK settings and configurations were considered to explore optimal design for high-lift flight during take-off and landing. To determine globally optimal design of such a system, an extremely large set of CFD simulations is needed. This is not feasible to achieve in practice. To alleviate this problem, a recourse was taken to a semi-supervised learning (SSL) methodology, which is based on manifold regularization techniques. A reasonable space of CFD solutions was populated and then the SSL methodology was used to fit this manifold in its entirety, including the gaps in the manifold where there were no CFD solutions available. The SSL methodology in conjunction with an elastodynamic solver (FiDDLE) was demonstrated in an earlier study involving structural health monitoring. These CFD-SSL methodologies define the new intelligent platform that forms the basis for our search for optimal design of wings. Although the present platform can be used in various other design and operational problems in engineering, this chapter focuses on the high-lift study of the VCK-VCCTEF system. Top few candidate design configurations were identified by solving the CFD problem in a small subset of the design space. The SSL component was trained on the design space, and was then used in a predictive mode to populate a selected set of test points outside
Near Optimal Decentralized H-infinity Control: Bounded vs. Unbounded Controller Order
DEFF Research Database (Denmark)
Stoustrup, Jakob; Niemann, H.H.
1997-01-01
It is shown that for a class of decentralized control problems there does not exist a sequence of controllers of bounded order which obtains near optimal control. Neither does there exist an infinite dimensional optimal controller. Using the insight of the line of proof of these results, a heuris......It is shown that for a class of decentralized control problems there does not exist a sequence of controllers of bounded order which obtains near optimal control. Neither does there exist an infinite dimensional optimal controller. Using the insight of the line of proof of these results...
Robust Semi-Supervised Manifold Learning Algorithm for Classification
Directory of Open Access Journals (Sweden)
Mingxia Chen
2018-01-01
Full Text Available In the recent years, manifold learning methods have been widely used in data classification to tackle the curse of dimensionality problem, since they can discover the potential intrinsic low-dimensional structures of the high-dimensional data. Given partially labeled data, the semi-supervised manifold learning algorithms are proposed to predict the labels of the unlabeled points, taking into account label information. However, these semi-supervised manifold learning algorithms are not robust against noisy points, especially when the labeled data contain noise. In this paper, we propose a framework for robust semi-supervised manifold learning (RSSML to address this problem. The noisy levels of the labeled points are firstly predicted, and then a regularization term is constructed to reduce the impact of labeled points containing noise. A new robust semi-supervised optimization model is proposed by adding the regularization term to the traditional semi-supervised optimization model. Numerical experiments are given to show the improvement and efficiency of RSSML on noisy data sets.
Active link selection for efficient semi-supervised community detection
Yang, Liang; Jin, Di; Wang, Xiao; Cao, Xiaochun
2015-01-01
Several semi-supervised community detection algorithms have been proposed recently to improve the performance of traditional topology-based methods. However, most of them focus on how to integrate supervised information with topology information; few of them pay attention to which information is critical for performance improvement. This leads to large amounts of demand for supervised information, which is expensive or difficult to obtain in most fields. For this problem we propose an active link selection framework, that is we actively select the most uncertain and informative links for human labeling for the efficient utilization of the supervised information. We also disconnect the most likely inter-community edges to further improve the efficiency. Our main idea is that, by connecting uncertain nodes to their community hubs and disconnecting the inter-community edges, one can sharpen the block structure of adjacency matrix more efficiently than randomly labeling links as the existing methods did. Experiments on both synthetic and real networks demonstrate that our new approach significantly outperforms the existing methods in terms of the efficiency of using supervised information. It needs ~13% of the supervised information to achieve a performance similar to that of the original semi-supervised approaches. PMID:25761385
System for optimizing activation measurements
International Nuclear Information System (INIS)
Antonov, V.A.
1993-01-01
Optimization procedures make it possible to perform committed activation investigations, reduce the number of experiments, make them less laborious, and increase their productivity. Separate mathematical functions were investigated for given optimization conditions, and these enable numerical optimal parameter values to be established only in the particular cases of specific techniques and mathematical computer programs. In the known mathematical models insufficient account is taken of the variety and complexity of real nuclide mixtures, the influence of background radiation, and the wide diversity of activation measurement conditions, while numerical methods for solving the optimization problem fail to reveal the laws governing the variations of the activation parameters and their functional interdependences. An optimization method was proposed in which was mainly used to estimate the time intervals for activation measurements of a mononuclide, binary or ternary nuclide mixture. However, by forming a mathematical model of activation processes it becomes possible to extend the number of nuclides in the mixture and to take account of the influence of background radiation and the diversity of the measurement alternatives. The analytical expressions and nomograms obtained can be used to determine the number of measurements, their minimum errors, their sensitivities when estimating the quantity of the tracer nuclide, the permissible quantity of interfering nuclides, the permissible background radiation intensity, and the flux of activating radiation. In the worker described herein these investigations are generalized to include spectrally resolved detection of the activation effect in the presence of the tracer and the interfering nuclides. The analytical expressions are combined into a system from which the optimal activation parameters can be found under different given conditions
Optimal control of a CSTR process
Directory of Open Access Journals (Sweden)
A. Soukkou
2008-12-01
Full Text Available Designing an effective criterion and learning algorithm for find the best structure is a major problem in the control design process. In this paper, the fuzzy optimal control methodology is applied to the design of the feedback loops of an Exothermic Continuous Stirred Tank Reactor system. The objective of design process is to find an optimal structure/gains of the Robust and Optimal Takagi Sugeno Fuzzy Controller (ROFLC. The control signal thus obtained will minimize a performance index, which is a function of the tracking/regulating errors, the quantity of the energy of the control signal applied to the system, and the number of fuzzy rules. The genetic learning is proposed for constructing the ROFLC. The chromosome genes are arranged into two parts, the binary-coded part contains the control genes and the real-coded part contains the genes parameters representing the fuzzy knowledge base. The effectiveness of this chromosome formulation enables the fuzzy sets and rules to be optimally reduced. The performances of the ROFLC are compared to these found by the traditional PD controller with Genetic Optimization (PD_GO. Simulations demonstrate that the proposed ROFLC and PD_GO has successfully met the design specifications.
Optimal decoupling controllers revisited
Czech Academy of Sciences Publication Activity Database
Kučera, Vladimír
2013-01-01
Roč. 42, č. 1 (2013), s. 1-16 ISSN 0324-8569 R&D Projects: GA TA ČR(CZ) TE01020197 Institutional support: RVO:67985556 Keywords : linear systems * fractional representations * decoupling control lers * stabilizing control lers * optimal control lers Subject RIV: BC - Control Systems Theory
International Nuclear Information System (INIS)
Sarrafan, Atabak; Zareh, Seiyed Hamid; Khayyat, Amir Ali Akbar; Zabihollah, Abolghassem
2012-01-01
Magnetorheological (MR) damper is a prominent semi-active control device to vibrate mitigation of structures. Due to the inherent non-linear nature of MR damper, an intelligent non-linear neuro-fuzzy control strategy is designed to control wave-induced vibration of an offshore steel jacket platform equipped with MR dampers. In the proposed control system, a dynamic-feedback neural network is adapted to model non-linear dynamic system, and the fuzzy logic controller is used to determine the control forces of MR dampers. By use of two feed forward neural networks required voltages and actual MR damper forces are obtained, in which the first neural network and the second one acts as the inverse dynamics model, and the forward dynamics model of the MR dampers, respectively. The most important characteristic of the proposed intelligent control strategy is its inherent robustness and its ability to handle the non-linear behavior of the system. Besides, no mathematical model needed to calculate forces produced by MR dampers. According to linearized Morison equation, wave-induced forces are determined. The performance of the proposed neuro-fuzzy control system is compared with that of a traditional semi-active control strategy, i.e., clipped optimal control system with LQG-target controller, through computer simulations, while the uncontrolled system response is used as the baseline. It is demonstrated that the design of proposed control system framework is more effective than that of the clipped optimal control scheme with LQG-target controller to reduce the vibration of offshore structure. Furthermore, the control strategy is very important for semi-active control
Symposium on Optimal Control Theory
1987-01-01
Control theory can be roughly classified as deterministic or stochastic. Each of these can further be subdivided into game theory and optimal control theory. The central problem of control theory is the so called constrained maximization (which- with slight modifications--is equivalent to minimization). One can then say, heuristically, that the major problem of control theory is to find the maximum of some performance criterion (or criteria), given a set of constraints. The starting point is, of course, a mathematical representation of the performance criterion (or criteria)- sometimes called the objective functional--along with the constraints. When the objective functional is single valued (Le. , when there is only one objective to be maximized), then one is dealing with optimal control theory. When more than one objective is involved, and the objectives are generally incompatible, then one is dealing with game theory. The first paper deals with stochastic optimal control, using the dynamic programming ...
Semi-infinite fractional programming
Verma, Ram U
2017-01-01
This book presents a smooth and unified transitional framework from generalised fractional programming, with a finite number of variables and a finite number of constraints, to semi-infinite fractional programming, where a number of variables are finite but with infinite constraints. It focuses on empowering graduate students, faculty and other research enthusiasts to pursue more accelerated research advances with significant interdisciplinary applications without borders. In terms of developing general frameworks for theoretical foundations and real-world applications, it discusses a number of new classes of generalised second-order invex functions and second-order univex functions, new sets of second-order necessary optimality conditions, second-order sufficient optimality conditions, and second-order duality models for establishing numerous duality theorems for discrete minmax (or maxmin) semi-infinite fractional programming problems. In the current interdisciplinary supercomputer-oriented research envi...
Integrated cable vibration control system using wireless sensors
Jeong, Seunghoo; Cho, Soojin; Sim, Sung-Han
2017-04-01
As the number of long-span bridges is increasing worldwide, maintaining their structural integrity and safety become an important issue. Because the stay cable is a critical member in most long-span bridges and vulnerable to wind-induced vibrations, vibration mitigation has been of interest both in academia and practice. While active and semi-active control schemes are known to be quite effective in vibration reduction compared to the passive control, requirements for equipment including data acquisition, control devices, and power supply prevent a widespread adoption in real-world applications. This study develops an integrated system for vibration control of stay-cables using wireless sensors implementing a semi-active control. Arduino, a low-cost single board system, is employed with a MEMS digital accelerometer and a Zigbee wireless communication module to build the wireless sensor. The magneto-rheological (MR) damper is selected as a damping device, controlled by an optimal control algorithm implemented on the Arduino sensing system. The developed integrated system is tested in a laboratory environment using a cable to demonstrate the effectiveness of the proposed system on vibration reduction. The proposed system is shown to reduce the vibration of stay-cables with low operating power effectively.
Control of polymer network topology in semi-batch systems
Wang, Rui; Olsen, Bradley; Johnson, Jeremiah
Polymer networks invariably possess topological defects: loops of different orders. Since small loops (primary loops and secondary loops) both lower the modulus of network and lead to stress concentration that causes material failure at low deformation, it is desirable to greatly reduce the loop fraction. We have shown that achieving loop fraction close to zero is extremely difficult in the batch process due to the slow decay of loop fraction with the polymer concentration and chain length. Here, we develop a modified kinetic graph theory that can model network formation reactions in semi-batch systems. We demonstrate that the loop fraction is not sensitive to the feeding policy if the reaction volume maintains constant during the network formation. However, if we initially put concentrated solution of small junction molecules in the reactor and continuously adding polymer solutions, the fractions of both primary loop and higher-order loops will be significantly reduced. There is a limiting value (nonzero) of loop fraction that can be achieved in the semi-batch system in condition of extremely slow feeding rate. This minimum loop fraction only depends on a single dimensionless variable, the product of concentration and with single chain pervaded volume, and defines an operating zone in which the loop fraction of polymer networks can be controlled through adjusting the feeding rate of the semi-batch process.
Controllable outrigger damping system for high rise building with MR dampers
Wang, Zhihao; Chang, Chia-Ming; Spencer, Billie F., Jr.; Chen, Zhengqing
2010-04-01
A novel energy dissipation system that can achieve the amplified damping ratio for a frame-core tube structures is explored, where vertical dampers are equipped between the outrigger and perimeter columns. The modal characteristics of the structural system with linear viscous dampers are theoretically analyzed from the simplified finite element model by parametric analysis. The result shows that modal damping ratios of the first several modes can increase a lot with this novel damping system. To improve the control performance of system, the semi-active control devices, magnetorheological (MR) dampers, are adopted to develop a controllable outrigger damping system. The clipped optimal control with the linear-quadratic Gaussian (LQG) acceleration feedback is adopted in this paper. The effectiveness of both passive and semi-active control outrigger damping systems is evaluated through the numerical simulation of a representative tall building subjected to two typical earthquake records.
PID control design for chaotic synchronization using a tribes optimization approach
Energy Technology Data Exchange (ETDEWEB)
Santos Coelho, Leandro dos [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: leandro.coelho@pucpr.br; Andrade Bernert, Diego Luis de [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: dbernert@gmail.com
2009-10-15
Recently, the investigation of synchronization and control problems for discrete chaotic systems has stimulated a wide range of research activity including both theoretical studies and practical applications. This paper deals with the tuning of a proportional-integral-derivative (PID) controller using a modified Tribes optimization algorithm based on truncated chaotic Zaslavskii map (MTribes) for synchronization of two identical discrete chaotic systems subject the different initial conditions. The Tribes algorithm is inspired by the social behavior of bird flocking and is also an optimization adaptive procedure that does not require sociometric or swarm size parameter tuning. Numerical simulations are given to show the effectiveness of the proposed synchronization method. In addition, some comparisons of the MTribes optimization algorithm with other continuous optimization methods, including classical Tribes algorithm and particle swarm optimization approaches, are presented.
PID control design for chaotic synchronization using a tribes optimization approach
International Nuclear Information System (INIS)
Santos Coelho, Leandro dos; Andrade Bernert, Diego Luis de
2009-01-01
Recently, the investigation of synchronization and control problems for discrete chaotic systems has stimulated a wide range of research activity including both theoretical studies and practical applications. This paper deals with the tuning of a proportional-integral-derivative (PID) controller using a modified Tribes optimization algorithm based on truncated chaotic Zaslavskii map (MTribes) for synchronization of two identical discrete chaotic systems subject the different initial conditions. The Tribes algorithm is inspired by the social behavior of bird flocking and is also an optimization adaptive procedure that does not require sociometric or swarm size parameter tuning. Numerical simulations are given to show the effectiveness of the proposed synchronization method. In addition, some comparisons of the MTribes optimization algorithm with other continuous optimization methods, including classical Tribes algorithm and particle swarm optimization approaches, are presented.
Optimal Power Flow Control by Rotary Power Flow Controller
Directory of Open Access Journals (Sweden)
KAZEMI, A.
2011-05-01
Full Text Available This paper presents a new power flow model for rotary power flow controller (RPFC. RPFC injects a series voltage into the transmission line and provides series compensation and phase shifting simultaneously. Therefore, it is able to control the transmission line impedance and the active power flow through it. An RPFC is composed mainly of two rotary phase shifting transformers (RPST and two conventional (series and shunt transformers. Structurally, an RPST consists of two windings (stator and rotor windings. The rotor windings of the two RPSTs are connected in parallel and their stator windings are in series. The injected voltage is proportional to the vector sum of the stator voltages and so its amplitude and angle are affected by the rotor position of the two RPSTs. This paper, describes the steady state operation and single-phase equivalent circuit of the RPFC. Also in this paper, a new power flow model, based on power injection model of flexible ac transmission system (FACTS controllers, suitable for the power flow analysis is introduced. Proposed model is used to solve optimal power flow (OPF problem in IEEE standard test systems incorporating RPFC and the optimal settings and location of the RPFC is determined.
DEFF Research Database (Denmark)
Christiansen, Pia
Growth of Clostridium, originating mainly from silage, may cause serious late blowing defects in semi-hard cheeses during ripening. In the present project, the possibilities were investigated to use anticlostridial non-starter Lactobacillus (mainly Lb. paracasei), isolated from Danish semi......-hard cheeses of high quality, as protective adjunct cultures against clostridia activities in silage and cheese. Screening for anticlostridial activity among non-starter Lactobacillus isolates against selected Clostridium strains showed that almost half (44%) of the naturally occurring non......-starter Lactobacillus in Danish semi-hard cheeses possessed anticlostridial activities and 10% possessed a broad anticlostridial activity, and these were selected for further investigations. Antagonistic antimicrobial interactions between some of the selected anticlostridial Lactobacillus strains were demonstrated...
Optimal control theory an introduction
Kirk, Donald E
2004-01-01
Optimal control theory is the science of maximizing the returns from and minimizing the costs of the operation of physical, social, and economic processes. Geared toward upper-level undergraduates, this text introduces three aspects of optimal control theory: dynamic programming, Pontryagin's minimum principle, and numerical techniques for trajectory optimization.Chapters 1 and 2 focus on describing systems and evaluating their performances. Chapter 3 deals with dynamic programming. The calculus of variations and Pontryagin's minimum principle are the subjects of chapters 4 and 5, and chapter
Networked and Distributed Control Method with Optimal Power Dispatch for Islanded Microgrids
DEFF Research Database (Denmark)
Li, Qiang; Peng, Congbo; Chen, Minyou
2017-01-01
of controllable agents. The distributed control laws derived from the first subgraph guarantee the supply-demand balance, while further control laws from the second subgraph reassign the outputs of controllable distributed generators, which ensure active and reactive power are dispatched optimally. However...... according to our proposition. Finally, the method is evaluated over seven cases via simulation. The results show that the system performs as desired, even if environmental conditions and load demand fluctuate significantly. In summary, the method can rapidly respond to fluctuations resulting in optimal...
Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO
Directory of Open Access Journals (Sweden)
Adel Taieb
2017-01-01
Full Text Available This paper introduces a new development for designing a Multi-Input Multi-Output (MIMO Fuzzy Optimal Model Predictive Control (FOMPC using the Adaptive Particle Swarm Optimization (APSO algorithm. The aim of this proposed control, called FOMPC-APSO, is to develop an efficient algorithm that is able to have good performance by guaranteeing a minimal control. This is done by determining the optimal weights of the objective function. Our method is considered an optimization problem based on the APSO algorithm. The MIMO system to be controlled is modeled by a Takagi-Sugeno (TS fuzzy system whose parameters are identified using weighted recursive least squares method. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, Continuous Stirred Tank Reactor (CSTR and Tank system, where the proposed approach provides better performances compared with other methods.
Wang, Lu; Albera, Laurent; Kachenoura, Amar; Shu, Huazhong; Senhadji, Lotfi
2014-12-01
Semi-symmetric three-way arrays are essential tools in blind source separation (BSS) particularly in independent component analysis (ICA). These arrays can be built by resorting to higher order statistics of the data. The canonical polyadic (CP) decomposition of such semi-symmetric three-way arrays allows us to identify the so-called mixing matrix, which contains the information about the intensities of some latent source signals present in the observation channels. In addition, in many applications, such as the magnetic resonance spectroscopy (MRS), the columns of the mixing matrix are viewed as relative concentrations of the spectra of the chemical components. Therefore, the two loading matrices of the three-way array, which are equal to the mixing matrix, are nonnegative. Most existing CP algorithms handle the symmetry and the nonnegativity separately. Up to now, very few of them consider both the semi-nonnegativity and the semi-symmetry structure of the three-way array. Nevertheless, like all the methods based on line search, trust region strategies, and alternating optimization, they appear to be dependent on initialization, requiring in practice a multi-initialization procedure. In order to overcome this drawback, we propose two new methods, called [InlineEquation not available: see fulltext.] and [InlineEquation not available: see fulltext.], to solve the problem of CP decomposition of semi-nonnegative semi-symmetric three-way arrays. Firstly, we rewrite the constrained optimization problem as an unconstrained one. In fact, the nonnegativity constraint of the two symmetric modes is ensured by means of a square change of variable. Secondly, a Jacobi-like optimization procedure is adopted because of its good convergence property. More precisely, the two new methods use LU and QR matrix factorizations, respectively, which consist in formulating high-dimensional optimization problems into several sequential polynomial and rational subproblems. By using both LU
Feed Forward Neural Network and Optimal Control Problem with Control and State Constraints
Kmet', Tibor; Kmet'ová, Mária
2009-09-01
A feed forward neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The paper extends adaptive critic neural network architecture proposed by [5] to the optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.
Optimal, real-time control--colliders
International Nuclear Information System (INIS)
Spencer, J.E.
1991-05-01
With reasonable definitions, optimal control is possible for both classical and quantal systems with new approaches called PISC(Parallel) and NISC(Neural) from analogy with RISC (Reduced Instruction Set Computing). If control equals interaction, observation and comparison to some figure of merit with interaction via external fields, then optimization comes from varying these fields to give design or operating goals. Structural stability can then give us tolerance and design constraints. But simulations use simplified models, are not in real-time and assume fixed or stationary conditions, so optimal control goes far beyond convergence rates of algorithms. It is inseparable from design and this has many implications for colliders. 12 refs., 3 figs
Factors influencing the profitability of optimizing control systems
International Nuclear Information System (INIS)
Broussaud, A.; Guyot, O.
1999-01-01
Optimizing control systems supplement conventional Distributed Control Systems and Programmable Logic Controllers. They continuously implement set points, which aim at maximizing the profitability of plant operation. They are becoming an integral part of modern mineral processing plants. This trend is justified by economic considerations, optimizing control being among the most cost-effective methods of improving metallurgical plant performance. The paper successively analyzes three sets of factors, which influence the profitability of optimizing control systems, and provides guidelines for analyzing the potential value of an optimizing control system at a given operation: external factors, such as economic factors and factors related to plant feed; features of the optimizing control system; and subsequent maintenance of the optimizing control system. It is shown that pay back times for optimization control projects are typically measured in days. The OCS software used by the authors for their applications is described briefly. (author)
Integrated production planning and control: A multi-objective optimization model
Directory of Open Access Journals (Sweden)
Cheng Wang
2013-09-01
Full Text Available Purpose: Production planning and control has crucial impact on the production and business activities of enterprise. Enterprise Resource Planning (ERP is the most popular resources planning and management system, however there are some shortcomings and deficiencies in the production planning and control because its core component is still the Material Requirements Planning (MRP. For the defects of ERP system, many local improvement and optimization schemes have been proposed, and improve the feasibility and practicality of the plan in some extent, but study considering the whole planning system optimization in the multiple performance management objectives and achieving better application performance is less. The purpose of this paper is to propose a multi-objective production planning optimization model Based on the point of view of the integration of production planning and control, in order to achieve optimization and control of enterprise manufacturing management. Design/methodology/approach: On the analysis of ERP planning system’s defects and disadvantages, and related research and literature, a multi-objective production planning optimization model is proposed, in addition to net demand and capacity, multiple performance management objectives, such as on-time delivery, production balance, inventory, overtime production, are considered incorporating into the examination scope of the model, so that the manufacturing process could be management and controlled Optimally between multiple objectives. The validity and practicability of the model will be verified by the instance in the last part of the paper. Findings: The main finding is that production planning management of manufacturing enterprise considers not only the capacity and materials, but also a variety of performance management objectives in the production process, and building a multi-objective optimization model can effectively optimize the management and control of enterprise
Role of controllability in optimizing quantum dynamics
International Nuclear Information System (INIS)
Wu Rebing; Hsieh, Michael A.; Rabitz, Herschel
2011-01-01
This paper reveals an important role that controllability plays in the complexity of optimizing quantum control dynamics. We show that the loss of controllability generally leads to multiple locally suboptimal controls when gate fidelity in a quantum control system is maximized, which does not happen if the system is controllable. Such local suboptimal controls may attract an optimization algorithm into a local trap when a global optimal solution is sought, even if the target gate can be perfectly realized. This conclusion results from an analysis of the critical topology of the corresponding quantum control landscape, which refers to the gate fidelity objective as a functional of the control fields. For uncontrollable systems, due to SU(2) and SU(3) dynamical symmetries, the control landscape corresponding to an implementable target gate is proven to possess multiple locally optimal critical points, and its ruggedness can be further increased if the target gate is not realizable. These results imply that the optimization of quantum dynamics can be seriously impeded when operating with local search algorithms under these conditions, and thus full controllability is demanded.
External and semi-internal controls for PCR amplification of homologous sequences in mixed templates
DEFF Research Database (Denmark)
Kalle, Elena; Gulevich, Alexander; Rensing, Christopher Günther T
2013-01-01
as an acceptable alternative. In order to evaluate the effects of inhibitors, a model multi-template mix was amplified in a mixture with DNAse-treated sample. Semi-internal control allowed establishment of intervals for robust PCR performance for different samples, thus enabling correct comparison of the samples......In a mixed template, the presence of homologous target DNA sequences creates environments that almost inevitably give rise to artifacts and biases during PCR. Heteroduplexes, chimeras, and skewed template-to-product ratios are the exclusive attributes of mixed template PCR and never occur....... This study demonstrated the efficiency of a model mixed template as an adequate external amplification control for a particular PCR application. The conditions of multi-template PCR do not allow implementation of a classic internal control; therefore we developed a convenient semi-internal control...
Thermodynamic framework for discrete optimal control in multiphase flow systems
Sieniutycz, Stanislaw
1999-08-01
Bellman's method of dynamic programming is used to synthesize diverse optimization approaches to active (work producing) and inactive (entropy generating) multiphase flow systems. Thermal machines, optimally controlled unit operations, nonlinear heat conduction, spontaneous relaxation processes, and self-propagating wave fronts are all shown to satisfy a discrete Hamilton-Jacobi-Bellman equation and a corresponding discrete optimization algorithm of Pontryagin's type, with the maximum principle for a Hamiltonian. The extremal structures are always canonical. A common unifying criterion is set for all considered systems, which is the criterion of a minimum generated entropy. It is shown that constraints can modify the entropy functionals in a different way for each group of the processes considered; thus the resulting structures of these functionals may differ significantly. Practical conclusions are formulated regarding the energy savings and energy policy in optimally controlled systems.
Operator support through modern optimal estimation and control
International Nuclear Information System (INIS)
Burdick, G.R.
1980-01-01
Applications of Modern Optimal Estimation and Control Theories are late in coming to the nuclear industry. Some features of the theories that might be exploited in nuclear systems applications are described. Activities at the Idaho National Engineering Laboratory relating to operator support using those theories are identified and some implementation challenges are discussed
Time-optimal feedback control for linear systems
International Nuclear Information System (INIS)
Mirica, S.
1976-01-01
The paper deals with the results of qualitative investigations of the time-optimal feedback control for linear systems with constant coefficients. In the first section, after some definitions and notations, two examples are given and it is shown that even the time-optimal control problem for linear systems with constant coefficients which looked like ''completely solved'' requires a further qualitative investigation of the stability to ''permanent perturbations'' of optimal feedback control. In the second section some basic results of the linear time-optimal control problem are reviewed. The third section deals with the definition of Boltyanskii's ''regular synthesis'' and its connection to Filippov's theory of right-hand side discontinuous differential equations. In the fourth section a theorem is proved concerning the stability to perturbations of time-optimal feedback control for linear systems with scalar control. In the last two sections it is proved that, if the matrix which defines the system has only real eigenvalues or is three-dimensional, the time-optimal feedback control defines a regular synthesis and therefore is stable to perturbations. (author)
Optimal control of compressible Navier-Stokes equations
International Nuclear Information System (INIS)
Ito, K.; Ravindran, S.S.
1994-01-01
Optimal control for the viscous incompressible flows, which are governed by incompressible Navier-Stokes equations, has been the subject of extensive study in recent years, see, e.g., [AT], [GHS], [IR], and [S]. In this paper we consider the optimal control of compressible isentropic Navier-Stokes equations. We develop the weak variational formulation and discuss the existence and necessary optimality condition characterizing the optimal control. A numerical method based on the mixed-finite element method is also discussed to compute the control and numerical results are presented
Optimal control of quantum measurement
Energy Technology Data Exchange (ETDEWEB)
Egger, Daniel; Wilhelm, Frank [Theoretical Physics, Saarland University, 66123 Saarbruecken (Germany)
2015-07-01
Pulses to steer the time evolution of quantum systems can be designed with optimal control theory. In most cases it is the coherent processes that can be controlled and one optimizes the time evolution towards a target unitary process, sometimes also in the presence of non-controllable incoherent processes. Here we show how to extend the GRAPE algorithm in the case where the incoherent processes are controllable and the target time evolution is a non-unitary quantum channel. We perform a gradient search on a fidelity measure based on Choi matrices. We illustrate our algorithm by optimizing a measurement pulse for superconducting phase qubits. We show how this technique can lead to large measurement contrast close to 99%. We also show, within the validity of our model, that this algorithm can produce short 1.4 ns pulses with 98.2% contrast.
Optimal control of hybrid vehicles
Jager, Bram; Kessels, John
2013-01-01
Optimal Control of Hybrid Vehicles provides a description of power train control for hybrid vehicles. The background, environmental motivation and control challenges associated with hybrid vehicles are introduced. The text includes mathematical models for all relevant components in the hybrid power train. The power split problem in hybrid power trains is formally described and several numerical solutions detailed, including dynamic programming and a novel solution for state-constrained optimal control problems based on Pontryagin’s maximum principle. Real-time-implementable strategies that can approximate the optimal solution closely are dealt with in depth. Several approaches are discussed and compared, including a state-of-the-art strategy which is adaptive for vehicle conditions like velocity and mass. Two case studies are included in the book: · a control strategy for a micro-hybrid power train; and · experimental results obtained with a real-time strategy implemented in...
Solving Optimal Control Problem of Monodomain Model Using Hybrid Conjugate Gradient Methods
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Kin Wei Ng
2012-01-01
Full Text Available We present the numerical solutions for the PDE-constrained optimization problem arising in cardiac electrophysiology, that is, the optimal control problem of monodomain model. The optimal control problem of monodomain model is a nonlinear optimization problem that is constrained by the monodomain model. The monodomain model consists of a parabolic partial differential equation coupled to a system of nonlinear ordinary differential equations, which has been widely used for simulating cardiac electrical activity. Our control objective is to dampen the excitation wavefront using optimal applied extracellular current. Two hybrid conjugate gradient methods are employed for computing the optimal applied extracellular current, namely, the Hestenes-Stiefel-Dai-Yuan (HS-DY method and the Liu-Storey-Conjugate-Descent (LS-CD method. Our experiment results show that the excitation wavefronts are successfully dampened out when these methods are used. Our experiment results also show that the hybrid conjugate gradient methods are superior to the classical conjugate gradient methods when Armijo line search is used.
Reliability-based optimization of an active vibration controller using evolutionary algorithms
Saraygord Afshari, Sajad; Pourtakdoust, Seid H.
2017-04-01
Many modern industrialized systems such as aircrafts, rotating turbines, satellite booms, etc. cannot perform their desired tasks accurately if their uninhibited structural vibrations are not controlled properly. Structural health monitoring and online reliability calculations are emerging new means to handle system imposed uncertainties. As stochastic forcing are unavoidable, in most engineering systems, it is often needed to take them into the account for the control design process. In this research, smart material technology is utilized for structural health monitoring and control in order to keep the system in a reliable performance range. In this regard, a reliability-based cost function is assigned for both controller gain optimization as well as sensor placement. The proposed scheme is implemented and verified for a wing section. Comparison of results for the frequency responses is considered to show potential applicability of the presented technique.
Energy extraction from a semi-passive flapping-foil turbine with active heave and passive pitch
Boudreau, Matthieu; Dumas, Guy; Gunther, Kevin; CFD Laboratory LMFN Team
2017-11-01
Due to the inherent complexity of the mechanisms needed to prescribe the heaving and the pitching motions of optimal flapping-foil turbines, several research groups are now investigating the potential of using unconstrained passive motions. The amplitude, the phase and the frequency of such free motions are thus the result of the interaction of the blade with the flow and its elastic supports, namely springs and dampers. In parallel with our current study on fully-passive flapping-foil turbines, we investigate in this work the possibility of using a semi-passive turbine. Unlike previous semi-passive turbines studied in the literature, we propose a turbine with a passive pitching motion and an active heaving motion constrained to be a sine wave with desired amplitude and frequency. As most of the energy extracted by flapping-foil turbines comes from the heaving motion, it is natural to connect an electric generator to this degree of freedom, thereby allowing one to constrain this motion. It is found that large-amplitude pitching motions leading to a considerable energy extraction can arise under different circumstances and mechanisms, either forced by the heaving motion or driven by an instability of the pitching motion itself. The authors gratefully acknowledge the support from the Natural Sciences and Engineering Research Council of Canada (NSERC), the Tyler Lewis Clean Energy Research Foundation, Calcul Québec and Compute Canada.
Direct Optimal Control of Duffing Dynamics
Oz, Hayrani; Ramsey, John K.
2002-01-01
The "direct control method" is a novel concept that is an attractive alternative and competitor to the differential-equation-based methods. The direct method is equally well applicable to nonlinear, linear, time-varying, and time-invariant systems. For all such systems, the method yields explicit closed-form control laws based on minimization of a quadratic control performance measure. We present an application of the direct method to the dynamics and optimal control of the Duffing system where the control performance measure is not restricted to a quadratic form and hence may include a quartic energy term. The results we present in this report also constitute further generalizations of our earlier work in "direct optimal control methodology." The approach is demonstrated for the optimal control of the Duffing equation with a softening nonlinear stiffness.
Kalle, Elena; Gulevich, Alexander; Rensing, Christopher
2013-11-01
In a mixed template, the presence of homologous target DNA sequences creates environments that almost inevitably give rise to artifacts and biases during PCR. Heteroduplexes, chimeras, and skewed template-to-product ratios are the exclusive attributes of mixed template PCR and never occur in a single template assay. Yet, multi-template PCR has been used without appropriate attention to quality control and assay validation, in spite of the fact that such practice diminishes the reliability of results. External and internal amplification controls became obligatory elements of good laboratory practice in different PCR assays. We propose the inclusion of an analogous approach as a quality control system for multi-template PCR applications. The amplification controls must take into account the characteristics of multi-template PCR and be able to effectively monitor particular assay performance. This study demonstrated the efficiency of a model mixed template as an adequate external amplification control for a particular PCR application. The conditions of multi-template PCR do not allow implementation of a classic internal control; therefore we developed a convenient semi-internal control as an acceptable alternative. In order to evaluate the effects of inhibitors, a model multi-template mix was amplified in a mixture with DNAse-treated sample. Semi-internal control allowed establishment of intervals for robust PCR performance for different samples, thus enabling correct comparison of the samples. The complexity of the external and semi-internal amplification controls must be comparable with the assumed complexity of the samples. We also emphasize that amplification controls should be applied in multi-template PCR regardless of the post-assay method used to analyze products. © 2013 Elsevier B.V. All rights reserved.
Optimal Control Development System for Electrical Drives
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Marian GAICEANU
2008-08-01
Full Text Available In this paper the optimal electrical drive development system is presented. It consists of both electrical drive types: DC and AC. In order to implement the optimal control for AC drive system an Altivar 71 inverter, a Frato magnetic particle brake (as load, three-phase induction machine, and dSpace 1104 controller have been used. The on-line solution of the matrix Riccati differential equation (MRDE is computed by dSpace 1104 controller, based on the corresponding feedback signals, generating the optimal speed reference for the AC drive system. The optimal speed reference is tracked by Altivar 71 inverter, conducting to energy reduction in AC drive. The classical control (consisting of rotor field oriented control with PI controllers and the optimal one have been implemented by designing an adequate ControlDesk interface. The three-phase induction machine (IM is controlled at constant flux. Therefore, the linear dynamic mathematical model of the IM has been obtained. The optimal control law provides transient regimes with minimal energy consumption. The obtained solution by integration of the MRDE is orientated towards the numerical implementation-by using a zero order hold. The development system is very useful for researchers, doctoral students or experts training in electrical drive. The experimental results are shown.
Turnpike phenomenon and infinite horizon optimal control
Zaslavski, Alexander J
2014-01-01
This book is devoted to the study of the turnpike phenomenon and describes the existence of solutions for a large variety of infinite horizon optimal control classes of problems. Chapter 1 provides introductory material on turnpike properties. Chapter 2 studies the turnpike phenomenon for discrete-time optimal control problems. The turnpike properties of autonomous problems with extended-value intergrands are studied in Chapter 3. Chapter 4 focuses on large classes of infinite horizon optimal control problems without convexity (concavity) assumptions. In Chapter 5, the turnpike results for a class of dynamic discrete-time two-player zero-sum game are proven. This thorough exposition will be very useful for mathematicians working in the fields of optimal control, the calculus of variations, applied functional analysis, and infinite horizon optimization. It may also be used as a primary text in a graduate course in optimal control or as supplementary text for a variety of courses in other disciplines. Resea...
Research on LQR optimal control method of active engine mount
Huan, Xie; Yu, Duan
2018-04-01
In this paper, the LQR control method is applied to the active mount of the engine, and a six-cylinder engine excitation model is established. Through the joint simulation of AMESim and MATLAB, the vibration isolation performance of the active mount system and the passive mount system is analyzed. Excited by the multi-engine operation, the simulation results of the vertical displacement, acceleration and dynamic deflection of the vehicle body show that the vibration isolation capability of the active mount system is superior to that of the passive mount system. It shows that compared with the passive mount, LQR active mount can greatly improve the vibration isolation performance, which proves the feasibility and effectiveness of the LQR control method.
Euler's fluid equations: Optimal control vs optimization
International Nuclear Information System (INIS)
Holm, Darryl D.
2009-01-01
An optimization method used in image-processing (metamorphosis) is found to imply Euler's equations for incompressible flow of an inviscid fluid, without requiring that the Lagrangian particle labels exactly follow the flow lines of the Eulerian velocity vector field. Thus, an optimal control problem and an optimization problem for incompressible ideal fluid flow both yield the same Euler fluid equations, although their Lagrangian parcel dynamics are different. This is a result of the gauge freedom in the definition of the fluid pressure for an incompressible flow, in combination with the symmetry of fluid dynamics under relabeling of their Lagrangian coordinates. Similar ideas are also illustrated for SO(N) rigid body motion.
Predictive Duty Cycle Control of Three-Phase Active-Front-End Rectifiers
DEFF Research Database (Denmark)
Song, Zhanfeng; Tian, Yanjun; Chen, Wei
2016-01-01
This paper proposed an on-line optimizing duty cycle control approach for three-phase active-front-end rectifiers, aiming to obtain the optimal control actions under different operating conditions. Similar to finite control set model predictive control strategy, a cost function previously...
A Semi-Automatic, Remote-Controlled Video Observation System for Transient Luminous Events
DEFF Research Database (Denmark)
Allin, Thomas Højgaard; Neubert, Torsten; Laursen, Steen
2003-01-01
In support for global ELF/VLF observations, HF measurements in France, and conjugate photometry/VLF observations in South Africa, we developed and operated a semi-automatic, remotely controlled video system for the observation of middle-atmospheric transient luminous events (TLEs). Installed...
Developments in model-based optimization and control distributed control and industrial applications
Grancharova, Alexandra; Pereira, Fernando
2015-01-01
This book deals with optimization methods as tools for decision making and control in the presence of model uncertainty. It is oriented to the use of these tools in engineering, specifically in automatic control design with all its components: analysis of dynamical systems, identification problems, and feedback control design. Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classical feedback design objectives as stability, performance and feasibility, afforded by the established body of results and methodologies constituting optimal control theory. It makes particular use of the popular formulation known as predictive control or receding-horizon optimization. The individual contributions in this volume are wide-ranging in subject matter but coordinated within a five-part structure covering material on: · complexity and structure in model predictive control (MPC); · collaborative MPC; · distributed MPC; · optimization-based analysis and desi...
Ji, Yu; Sheng, Wanxing; Jin, Wei; Wu, Ming; Liu, Haitao; Chen, Feng
2018-02-01
A coordinated optimal control method of active and reactive power of distribution network with distributed PV cluster based on model predictive control is proposed in this paper. The method divides the control process into long-time scale optimal control and short-time scale optimal control with multi-step optimization. The models are transformed into a second-order cone programming problem due to the non-convex and nonlinear of the optimal models which are hard to be solved. An improved IEEE 33-bus distribution network system is used to analyse the feasibility and the effectiveness of the proposed control method
Presentation of Malaria Epidemics Using Multiple Optimal Controls
Directory of Open Access Journals (Sweden)
Abid Ali Lashari
2012-01-01
Full Text Available An existing model is extended to assess the impact of some antimalaria control measures, by re-formulating the model as an optimal control problem. This paper investigates the fundamental role of three type of controls, personal protection, treatment, and mosquito reduction strategies in controlling the malaria. We work in the nonlinear optimal control framework. The existence and the uniqueness results of the solution are discussed. A characterization of the optimal control via adjoint variables is established. The optimality system is solved numerically by a competitive Gauss-Seidel-like implicit difference method. Finally, numerical simulations of the optimal control problem, using a set of reasonable parameter values, are carried out to investigate the effectiveness of the proposed control measures.
Optimization analysis of propulsion motor control efficiency
Directory of Open Access Journals (Sweden)
CAI Qingnan
2017-12-01
Full Text Available [Objectives] This paper aims to strengthen the control effect of propulsion motors and decrease the energy used during actual control procedures.[Methods] Based on the traditional propulsion motor equivalence circuit, we increase the iron loss current component, introduce the definition of power matching ratio, calculate the highest efficiency of a motor at a given speed and discuss the flux corresponding to the power matching ratio with the highest efficiency. In the original motor vector efficiency optimization control module, an efficiency optimization control module is added so as to achieve motor efficiency optimization and energy conservation.[Results] MATLAB/Simulink simulation data shows that the efficiency optimization control method is suitable for most conditions. The operation efficiency of the improved motor model is significantly higher than that of the original motor model, and its dynamic performance is good.[Conclusions] Our motor efficiency optimization control method can be applied in engineering to achieve energy conservation.
Design and modeling of semi-active squeeze film dampers using magneto-rheological fluids
International Nuclear Information System (INIS)
Kim, Keun-Joo; Lee, Chong-Won; Koo, Jeong-Hoi
2008-01-01
Conventional squeeze film dampers (SFDs) have shown their effectiveness in suppressing unbalanced vibrations in rotor systems, particularly supported by rolling element bearings. Recently, there is an increasing demand for 'controllable' SFDs to meet the need of modern rotating machinery, characterized by high operating speed and high load capacity. Thus, this paper presents a controllable semi-active SFD using magneto-rheological (MR) fluids, focusing on its design and modeling. It offers a comprehensive design method and an innovative experimental identification and modeling technique for MR-SFDs. The primary goal of the MR-SFD design is set to maximize its dynamic control bandwidth, and the design method includes the material selection, magnetic circuit analysis and sealing element design. After constructing a prototype MR-SFD based on the final design, this work investigated how some of the critical design parameters affect the performance of the MR-SFD (i.e. its dynamic control bandwidth change). Furthermore, it characterized the damper's dynamic behavior experimentally using a novel excitation method that adopts active magnetic bearing (AMB) units. Unlike conventional methods, the AMB system was able to precisely control the amplitude and frequency of the input excitation, enabling us to obtain the nonlinear dynamic stiffness properties of the MR-SFD with varying input current. In modeling the dynamic behavior of the MR-SFD, this study employed the describing function method. The describing function analysis effectively captured the nonlinear dynamic behavior of the MR-SFD
Halim, Dunant; Cheng, Li; Su, Zhongqing
2011-04-01
The work proposed an optimization approach for structural sensor placement to improve the performance of vibro-acoustic virtual sensor for active noise control applications. The vibro-acoustic virtual sensor was designed to estimate the interior sound pressure of an acoustic-structural coupled enclosure using structural sensors. A spectral-spatial performance metric was proposed, which was used to quantify the averaged structural sensor output energy of a vibro-acoustic system excited by a spatially varying point source. It was shown that (i) the overall virtual sensing error energy was contributed additively by the modal virtual sensing error and the measurement noise energy; (ii) each of the modal virtual sensing error system was contributed by both the modal observability levels for the structural sensing and the target acoustic virtual sensing; and further (iii) the strength of each modal observability level was influenced by the modal coupling and resonance frequencies of the associated uncoupled structural/cavity modes. An optimal design of structural sensor placement was proposed to achieve sufficiently high modal observability levels for certain important panel- and cavity-controlled modes. Numerical analysis on a panel-cavity system demonstrated the importance of structural sensor placement on virtual sensing and active noise control performance, particularly for cavity-controlled modes.
Pla, F. G.; Rajiyah, H.
1995-01-01
The feasibility of using acoustic plate radiators powered by piezoceramic thin sheets as canceling sources for active control of aircraft engine fan noise is demonstrated. Analytical and numerical models of actuated beams and plates are developed and validated. An optimization study is performed to identify the optimum combination of design parameters that maximizes the plate volume velocity for a given resonance frequency. Fifteen plates with various plate and actuator sizes, thicknesses, and bonding layers were fabricated and tested using results from the optimization study. A maximum equivalent piston displacement of 0.39 mm was achieved with the optimized plate samples tested with only one actuator powered, corresponding to a plate deflection at the center of over 1 millimeter. This is very close to the deflection required for a full size engine application and represents a 160-fold improvement over previous work. Experimental results further show that performance is limited by the critical stress of the piezoceramic actuator and bonding layer rather than by the maximum moment available from the actuator. Design enhancements are described in detail that will lead to a flight-worthy acoustic plate radiator by minimizing actuator tensile stresses and reducing nonlinear effects. Finally, several adaptive tuning methods designed to increase the bandwidth of acoustic plate radiators are analyzed including passive, active, and semi-active approaches. The back chamber pressurization and volume variation methods are investigated experimentally and shown to be simple and effective ways to obtain substantial control over the resonance frequency of a plate radiator. This study shows that piezoceramic-based plate radiators can be a viable acoustic source for active control of aircraft engine fan noise.
Modulation of microRNA activity by semi-microRNAs (smiRNAs
Directory of Open Access Journals (Sweden)
Isabelle ePlante
2012-06-01
Full Text Available The ribonuclease Dicer plays a central role in the microRNA pathway by catalyzing the formation of 19 to 24-nucleotide (nt long microRNAs. Subsequently incorporated into Ago2 effector complexes, microRNAs are known to regulate messenger RNA (mRNA translation. Whether shorter RNA species derived from microRNAs exist and play a role in mRNA regulation remains unknown. Here, we report the serendipitous discovery of a 12-nt long RNA species corresponding to the 5’ region of the microRNA let-7, and tentatively termed semi-microRNA, or smiRNA. Using a smiRNA derived from the precursor of miR-223 as a model, we show that 12-nt long smiRNA species are devoid of any direct mRNA regulatory activity, as assessed in a reporter gene activity assay in transfected cultured human cells. However, smiR-223 was found to modulate the ability of the microRNA from which it derives to mediate translational repression or cleavage of reporter mRNAs. Our findings suggest that smiRNAs may be generated along the microRNA pathway and participate to the control of gene expression by regulating the activity of the related full-length mature microRNA in vivo.
Directory of Open Access Journals (Sweden)
Ruisheng Sun
2016-01-01
Full Text Available This paper presents a new parametric optimization approach based on a modified particle swarm optimization (PSO to design a class of impulsive-correction projectiles with discrete, flexible-time interval, and finite-energy control. In terms of optimal control theory, the task is described as the formulation of minimum working number of impulses and minimum control error, which involves reference model linearization, boundary conditions, and discontinuous objective function. These result in difficulties in finding the global optimum solution by directly utilizing any other optimization approaches, for example, Hp-adaptive pseudospectral method. Consequently, PSO mechanism is employed for optimal setting of impulsive control by considering the time intervals between two neighboring lateral impulses as design variables, which makes the briefness of the optimization process. A modification on basic PSO algorithm is developed to improve the convergence speed of this optimization through linearly decreasing the inertial weight. In addition, a suboptimal control and guidance law based on PSO technique are put forward for the real-time consideration of the online design in practice. Finally, a simulation case coupled with a nonlinear flight dynamic model is applied to validate the modified PSO control algorithm. The results of comparative study illustrate that the proposed optimal control algorithm has a good performance in obtaining the optimal control efficiently and accurately and provides a reference approach to handling such impulsive-correction problem.
Dynamic optimization and adaptive controller design
Inamdar, S. R.
2010-10-01
In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.
Optimization of boundary controls of string vibrations
Energy Technology Data Exchange (ETDEWEB)
Il' in, V A; Moiseev, E I [Department of Computing Mathematics and Cybernetics, M.V. Lomonosov Moscow State University, Moscow (Russian Federation)
2005-12-31
For a large time interval T boundary controls of string vibrations are optimized in the following seven boundary-control problems: displacement control at one end (with the other end fixed or free); displacement control at both ends; elastic force control at one end (with the other end fixed or free); elastic force control at both ends; combined control (displacement control at one end and elastic force control at the other). Optimal boundary controls in each of these seven problems are sought as functions minimizing the corresponding boundary-energy integral under the constraints following from the initial and terminal conditions for the string at t=0 and t=T, respectively. For all seven problems, the optimal boundary controls are written out in closed analytic form.
Doroodgar, Barzin; Liu, Yugang; Nejat, Goldie
2014-12-01
Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing a human operator to cooperate and share such tasks with a rescue robot as navigation, exploration, and victim identification. In this paper, we present a unique hierarchical reinforcement learning-based semi-autonomous control architecture for rescue robots operating in cluttered and unknown urban search and rescue (USAR) environments. The aim of the controller is to enable a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A direction-based exploration technique is integrated in the controller to expand the search area of the robot via the classification of regions and the rubble piles within these regions. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed HRL-based semi-autonomous controller to unknown cluttered scenes with different sizes and varying types of configurations.
A Higher Harmonic Optimal Controller to Optimise Rotorcraft Aeromechanical Behaviour
Leyland, Jane Anne
1996-01-01
Three methods to optimize rotorcraft aeromechanical behavior for those cases where the rotorcraft plant can be adequately represented by a linear model system matrix were identified and implemented in a stand-alone code. These methods determine the optimal control vector which minimizes the vibration metric subject to constraints at discrete time points, and differ from the commonly used non-optimal constraint penalty methods such as those employed by conventional controllers in that the constraints are handled as actual constraints to an optimization problem rather than as just additional terms in the performance index. The first method is to use a Non-linear Programming algorithm to solve the problem directly. The second method is to solve the full set of non-linear equations which define the necessary conditions for optimality. The third method is to solve each of the possible reduced sets of equations defining the necessary conditions for optimality when the constraints are pre-selected to be either active or inactive, and then to simply select the best solution. The effects of maneuvers and aeroelasticity on the systems matrix are modelled by using a pseudo-random pseudo-row-dependency scheme to define the systems matrix. Cases run to date indicate that the first method of solution is reliable, robust, and easiest to use, and that it was superior to the conventional controllers which were considered.
Optimal control novel directions and applications
Aronna, Maria; Kalise, Dante
2017-01-01
Focusing on applications to science and engineering, this book presents the results of the ITN-FP7 SADCO network’s innovative research in optimization and control in the following interconnected topics: optimality conditions in optimal control, dynamic programming approaches to optimal feedback synthesis and reachability analysis, and computational developments in model predictive control. The novelty of the book resides in the fact that it has been developed by early career researchers, providing a good balance between clarity and scientific rigor. Each chapter features an introduction addressed to PhD students and some original contributions aimed at specialist researchers. Requiring only a graduate mathematical background, the book is self-contained. It will be of particular interest to graduate and advanced undergraduate students, industrial practitioners and to senior scientists wishing to update their knowledge.
Wu, Xin; Wu, Bin; Zheng, Yi; Tian, Yong; Liu, Jie; Zheng, Chunmiao
2015-04-01
In arid and semi-arid agricultural areas, groundwater (GW) is an important water source of irrigation, in addition to surface water (SW). Groundwater pumping would significantly alter the regional hydrological regime, and therefore complicate the water resources management process. This study explored how to optimize the conjunctive use of SW and GW for agricultural irrigation at a basin scale, based on integrated SW-GW modeling and global optimization methods. The improved GSFLOW model was applied to the Heihe River Basin, the second largest inland river basin in China. Two surrogate-based global optimization approaches were implemented and compared, including the well-established DYCORS algorithm and a new approach we proposed named as SOIM, which takes radial basis function (RBF) and support vector machine (SVM) as the surrogate model, respectively. Both temporal and spatial optimizations were performed, aiming at maximizing saturated storage change of midstream part conditioned on non-reduction of irrigation demand, constrained by certain annual discharge for the downstream part. Several scenarios for different irrigation demand and discharge flow are designed. The main study results include the following. First, the integrated modeling not only provides sufficient flexibility to formulation of optimization problems, but also makes the optimization results more physically interpretable and managerially meaningful. Second, the surrogate-based optimization approach was proved to be effective and efficient for the complex, time-consuming modeling, and is quite promising for decision-making. Third, the strong and complicated SW-GW interactions in the study area allow significant water resources conservation, even if neither irrigation demand nor discharge for the downstream part decreases. Under the optimal strategy, considerable part of surface water division is replaced by 'Stream leakage-Pump' process to avoid non-beneficial evaporation via canals. Spatially
Bulgakov, V. K.; Strigunov, V. V.
2009-05-01
The Pontryagin maximum principle is used to prove a theorem concerning optimal control in regional macroeconomics. A boundary value problem for optimal trajectories of the state and adjoint variables is formulated, and optimal curves are analyzed. An algorithm is proposed for solving the boundary value problem of optimal control. The performance of the algorithm is demonstrated by computing an optimal control and the corresponding optimal trajectories.
Wang, Y. M.; Xu, W. C.; Wu, S. Q.; Chai, C. W.; Liu, X.; Wang, S. H.
2018-03-01
The torsional oscillation is the dominant vibration form for the impression cylinder of printing machine (printing cylinder for short), directly restricting the printing speed up and reducing the quality of the prints. In order to reduce torsional vibration, the active control method for the printing cylinder is obtained. Taking the excitation force and moment from the cylinder gap and gripper teeth open & closing cam mechanism as variable parameters, authors establish the dynamic mathematical model of torsional vibration for the printing cylinder. The torsional active control method is based on Particle Swarm Optimization(PSO) algorithm to optimize input parameters for the serve motor. Furthermore, the input torque of the printing cylinder is optimized, and then compared with the numerical simulation results. The conclusions are that torsional vibration active control based on PSO is an availability method to the torsional vibration of printing cylinder.
Optimal design of distributed control and embedded systems
Çela, Arben; Li, Xu-Guang; Niculescu, Silviu-Iulian
2014-01-01
Optimal Design of Distributed Control and Embedded Systems focuses on the design of special control and scheduling algorithms based on system structural properties as well as on analysis of the influence of induced time-delay on systems performances. It treats the optimal design of distributed and embedded control systems (DCESs) with respect to communication and calculation-resource constraints, quantization aspects, and potential time-delays induced by the associated communication and calculation model. Particular emphasis is put on optimal control signal scheduling based on the system state. In order to render this complex optimization problem feasible in real time, a time decomposition is based on periodicity induced by the static scheduling is operated. The authors present a co-design approach which subsumes the synthesis of the optimal control laws and the generation of an optimal schedule of control signals on real-time networks as well as the execution of control tasks on a single processor. The a...
Asgharnia, Amirhossein; Shahnazi, Reza; Jamali, Ali
2018-05-11
The most studied controller for pitch control of wind turbines is proportional-integral-derivative (PID) controller. However, due to uncertainties in wind turbine modeling and wind speed profiles, the need for more effective controllers is inevitable. On the other hand, the parameters of PID controller usually are unknown and should be selected by the designer which is neither a straightforward task nor optimal. To cope with these drawbacks, in this paper, two advanced controllers called fuzzy PID (FPID) and fractional-order fuzzy PID (FOFPID) are proposed to improve the pitch control performance. Meanwhile, to find the parameters of the controllers the chaotic evolutionary optimization methods are used. Using evolutionary optimization methods not only gives us the unknown parameters of the controllers but also guarantees the optimality based on the chosen objective function. To improve the performance of the evolutionary algorithms chaotic maps are used. All the optimization procedures are applied to the 2-mass model of 5-MW wind turbine model. The proposed optimal controllers are validated using simulator FAST developed by NREL. Simulation results demonstrate that the FOFPID controller can reach to better performance and robustness while guaranteeing fewer fatigue damages in different wind speeds in comparison to FPID, fractional-order PID (FOPID) and gain-scheduling PID (GSPID) controllers. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Fatigue Load Sensitivity Based Optimal Active Power Dispatch For Wind Farms
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Huang, Shaojun
2017-01-01
This paper proposes an optimal active power dispatch algorithm for wind farms based on Wind Turbine (WT) load sensitivity. The control objectives include tracking power references from the system operator and minimizing fatigue loads experienced by WTs. The sensitivity of WT fatigue loads to power...... sensitivity are derived, which significantly improves the computation efficiency of the local WT controller. The proposed algorithm can be implemented in different active power control schemes. Case studies were conducted with a wind farm under balance control for both low and high wind conditions...
Optimal Operation and Stabilising Control of the Concentric Heat-Integrated Distillation Column
DEFF Research Database (Denmark)
Bisgaard, Thomas; Skogestad, Sigurd; Huusom, Jakob Kjøbsted
2016-01-01
A systematic control structure design method is applied on the concentric heat integrated distillation column (HIDiC) separating benzene and toluene. A degrees of freedom analysis is provided for identifying potential manipulated and controlled variables. Optimal operation is mapped and active...
Optimal control of hydroelectric facilities
Zhao, Guangzhi
This thesis considers a simple yet realistic model of pump-assisted hydroelectric facilities operating in a market with time-varying but deterministic power prices. Both deterministic and stochastic water inflows are considered. The fluid mechanical and engineering details of the facility are described by a model containing several parameters. We present a dynamic programming algorithm for optimizing either the total energy produced or the total cash generated by these plants. The algorithm allows us to give the optimal control strategy as a function of time and to see how this strategy, and the associated plant value, varies with water inflow and electricity price. We investigate various cases. For a single pumped storage facility experiencing deterministic power prices and water inflows, we investigate the varying behaviour for an oversimplified constant turbine- and pump-efficiency model with simple reservoir geometries. We then generalize this simple model to include more realistic turbine efficiencies, situations with more complicated reservoir geometry, and the introduction of dissipative switching costs between various control states. We find many results which reinforce our physical intuition about this complicated system as well as results which initially challenge, though later deepen, this intuition. One major lesson of this work is that the optimal control strategy does not differ much between two differing objectives of maximizing energy production and maximizing its cash value. We then turn our attention to the case of stochastic water inflows. We present a stochastic dynamic programming algorithm which can find an on-average optimal control in the face of this randomness. As the operator of a facility must be more cautious when inflows are random, the randomness destroys facility value. Following this insight we quantify exactly how much a perfect hydrological inflow forecast would be worth to a dam operator. In our final chapter we discuss the
Optimal control for Malaria disease through vaccination
Munzir, Said; Nasir, Muhammad; Ramli, Marwan
2018-01-01
Malaria is a disease caused by an amoeba (single-celled animal) type of plasmodium where anopheles mosquito serves as the carrier. This study examines the optimal control problem of malaria disease spread based on Aron and May (1982) SIR type models and seeks the optimal solution by minimizing the prevention of the spreading of malaria by vaccine. The aim is to investigate optimal control strategies on preventing the spread of malaria by vaccination. The problem in this research is solved using analytical approach. The analytical method uses the Pontryagin Minimum Principle with the symbolic help of MATLAB software to obtain optimal control result and to analyse the spread of malaria with vaccination control.
Energy Technology Data Exchange (ETDEWEB)
Yang, Weiwei; Li, Chunhu, E-mail: lichunhu@ouc.edu.cn; Wang, Liang; Sun, ShengNan; Yan, Xin
2015-10-30
Highlights: • Activated semi-coke supported TiO{sub 2}-rGO photocatalysts were fabricated by one-step solvothermal method. • The photocatalytic performance for NO removal was studied under visible light irradiation. • The introduction of rGO is responsible for superior photocatalytic activity. • Optimum operational parameters at 70 °C, with 8% O{sub 2} and 8% relative humidity were obtained. • Thermal vapor regeneration is the most suitable generation method. - Abstract: The photocatalysts of activated semi-coke supported TiO{sub 2}-rGO nanocomposite (TiO{sub 2}-rGO/ASC) with different contents of reduced graphene oxide were fabricated by one-step solvothermal method for NO removal under visible light irradiation. It was confirmed that 8% content of reduced graphene oxide presented the best NO photooxidation performance under visible light irradiation at 70 °C with 350–400 mg/m{sup 3} NO,5% O{sub 2} and 5% relative humidity. The reasons for improved activity were discussed, alloyed with the mechanism of producing CO. Detailed structural information of TiO{sub 2}-rGO/ASC photocatalysts was characterized by scanning electron microscope (SEM), energy dispersive X-ray Spectroscopy (EDX), X-ray diffraction analysis (XRD), UV–Vis diffuse reflectance spectra (UV–Vis DRS) and photoluminescence (PL), which indicated that the introduction of rGO was responsible for well dispersion, smaller crystalline size, red shift of absorption band and suppressing quick photo-induced charges recombination of TiO{sub 2}-rGO/ASC photocatalysts. Optimization of operational parameters with 70 °C, 8% O{sub 2} and 8% relative humidity were also obtained. Deactivation of TiO{sub 2}-rGO/ASC photocatalysts for NO removal was investigated by Fourier-transform infrared (FTIR) analysis. Regeneration experiments showed that thermal vapor regeneration would be optimal method owing to excellent regenerative capacity and inexpensive procedure.
Optimal control of native predators
Martin, Julien; O'Connell, Allan F.; Kendall, William L.; Runge, Michael C.; Simons, Theodore R.; Waldstein, Arielle H.; Schulte, Shiloh A.; Converse, Sarah J.; Smith, Graham W.; Pinion, Timothy; Rikard, Michael; Zipkin, Elise F.
2010-01-01
We apply decision theory in a structured decision-making framework to evaluate how control of raccoons (Procyon lotor), a native predator, can promote the conservation of a declining population of American Oystercatchers (Haematopus palliatus) on the Outer Banks of North Carolina. Our management objective was to maintain Oystercatcher productivity above a level deemed necessary for population recovery while minimizing raccoon removal. We evaluated several scenarios including no raccoon removal, and applied an adaptive optimization algorithm to account for parameter uncertainty. We show how adaptive optimization can be used to account for uncertainties about how raccoon control may affect Oystercatcher productivity. Adaptive management can reduce this type of uncertainty and is particularly well suited for addressing controversial management issues such as native predator control. The case study also offers several insights that may be relevant to the optimal control of other native predators. First, we found that stage-specific removal policies (e.g., yearling versus adult raccoon removals) were most efficient if the reproductive values among stage classes were very different. Second, we found that the optimal control of raccoons would result in higher Oystercatcher productivity than the minimum levels recommended for this species. Third, we found that removing more raccoons initially minimized the total number of removals necessary to meet long term management objectives. Finally, if for logistical reasons managers cannot sustain a removal program by removing a minimum number of raccoons annually, managers may run the risk of creating an ecological trap for Oystercatchers.
Directory of Open Access Journals (Sweden)
Hui Yu
2013-01-01
Full Text Available Identifying potent drug combination from a herbal mixture is usually quite challenging, due to a large number of possible trials. Using an engineering approach of the feedback system control (FSC scheme, we identified the potential best combinations of four flavonoids, including formononetin, ononin, calycosin, and calycosin-7-O-β-D-glucoside deriving from Astragali Radix (AR; Huangqi, which provided the best biological action at minimal doses. Out of more than one thousand possible combinations, only tens of trials were required to optimize the flavonoid combinations that stimulated a maximal transcriptional activity of hypoxia response element (HRE, a critical regulator for erythropoietin (EPO transcription, in cultured human embryonic kidney fibroblast (HEK293T. By using FSC scheme, 90% of the work and time can be saved, and the optimized flavonoid combinations increased the HRE mediated transcriptional activity by ~3-fold as compared with individual flavonoid, while the amount of flavonoids was reduced by ~10-fold. Our study suggests that the optimized combination of flavonoids may have strong effect in activating the regulatory element of erythropoietin at very low dosage, which may be used as new source of natural hematopoietic agent. The present work also indicates that the FSC scheme is able to serve as an efficient and model-free approach to optimize the drug combination of different ingredients within a herbal decoction.
Optimal Control for the Degenerate Elliptic Logistic Equation
International Nuclear Information System (INIS)
Delgado, M.; Montero, J.A.; Suarez, A.
2002-01-01
We consider the optimal control of harvesting the diffusive degenerate elliptic logistic equation. Under certain assumptions, we prove the existence and uniqueness of an optimal control. Moreover, the optimality system and a characterization of the optimal control are also derived. The sub-supersolution method, the singular eigenvalue problem and differentiability with respect to the positive cone are the techniques used to obtain our results
Optimization Control of Bidirectional Cascaded DC-AC Converter Systems
DEFF Research Database (Denmark)
Tian, Yanjun
in bidirectional cascaded converter. This research work analyses the control strategies based on the topology of dual active bridges converter cascaded with a three phase inverter. It firstly proposed a dc link voltage and active power coordinative control method for this cascaded topology, and it can reduce dc....... The connections of the renewable energy sources to the power system are mostly through the power electronic converters. Moreover, for high controllability and flexibility, power electronic devices are gradually acting as the interface between different networks in power systems, promoting conventional power...... the bidirectional power flow in the distribution level of power systems. Therefore direct contact of converters introduces significant uncertainties to power system, especially for the stability and reliability. This dissertation studies the optimization control of the two stages directly connected converters...
Optimal control systems in hydro power plants
International Nuclear Information System (INIS)
Babunski, Darko L.
2012-01-01
The aim of the research done in this work is focused on obtaining the optimal models of hydro turbine including auxiliary equipment, analysis of governors for hydro power plants and analysis and design of optimal control laws that can be easily applicable in real hydro power plants. The methodology of the research and realization of the set goals consist of the following steps: scope of the models of hydro turbine, and their modification using experimental data; verification of analyzed models and comparison of advantages and disadvantages of analyzed models, with proposal of turbine model for design of control low; analysis of proportional-integral-derivative control with fixed parameters and gain scheduling and nonlinear control; analysis of dynamic characteristics of turbine model including control and comparison of parameters of simulated system with experimental data; design of optimal control of hydro power plant considering proposed cost function and verification of optimal control law with load rejection measured data. The hydro power plant models, including model of power grid are simulated in case of island ing and restoration after breakup and load rejection with consideration of real loading and unloading of hydro power plant. Finally, simulations provide optimal values of control parameters, stability boundaries and results easily applicable to real hydro power plants. (author)
Optimal control with aerospace applications
Longuski, James M; Prussing, John E
2014-01-01
Want to know not just what makes rockets go up but how to do it optimally? Optimal control theory has become such an important field in aerospace engineering that no graduate student or practicing engineer can afford to be without a working knowledge of it. This is the first book that begins from scratch to teach the reader the basic principles of the calculus of variations, develop the necessary conditions step-by-step, and introduce the elementary computational techniques of optimal control. This book, with problems and an online solution manual, provides the graduate-level reader with enough introductory knowledge so that he or she can not only read the literature and study the next level textbook but can also apply the theory to find optimal solutions in practice. No more is needed than the usual background of an undergraduate engineering, science, or mathematics program: namely calculus, differential equations, and numerical integration. Although finding optimal solutions for these problems is a...
Genetic Algorithm Optimizes Q-LAW Control Parameters
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
A Feedback Optimal Control Algorithm with Optimal Measurement Time Points
Directory of Open Access Journals (Sweden)
Felix Jost
2017-02-01
Full Text Available Nonlinear model predictive control has been established as a powerful methodology to provide feedback for dynamic processes over the last decades. In practice it is usually combined with parameter and state estimation techniques, which allows to cope with uncertainty on many levels. To reduce the uncertainty it has also been suggested to include optimal experimental design into the sequential process of estimation and control calculation. Most of the focus so far was on dual control approaches, i.e., on using the controls to simultaneously excite the system dynamics (learning as well as minimizing a given objective (performing. We propose a new algorithm, which sequentially solves robust optimal control, optimal experimental design, state and parameter estimation problems. Thus, we decouple the control and the experimental design problems. This has the advantages that we can analyze the impact of measurement timing (sampling independently, and is practically relevant for applications with either an ethical limitation on system excitation (e.g., chemotherapy treatment or the need for fast feedback. The algorithm shows promising results with a 36% reduction of parameter uncertainties for the Lotka-Volterra fishing benchmark example.
Optimal Control Problems for Nonlinear Variational Evolution Inequalities
Directory of Open Access Journals (Sweden)
Eun-Young Ju
2013-01-01
Full Text Available We deal with optimal control problems governed by semilinear parabolic type equations and in particular described by variational inequalities. We will also characterize the optimal controls by giving necessary conditions for optimality by proving the Gâteaux differentiability of solution mapping on control variables.
Adaptive optimization and control using neural networks
Energy Technology Data Exchange (ETDEWEB)
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
1993-10-22
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Optimization-Based Approaches to Control of Probabilistic Boolean Networks
Directory of Open Access Journals (Sweden)
Koichi Kobayashi
2017-02-01
Full Text Available Control of gene regulatory networks is one of the fundamental topics in systems biology. In the last decade, control theory of Boolean networks (BNs, which is well known as a model of gene regulatory networks, has been widely studied. In this review paper, our previously proposed methods on optimal control of probabilistic Boolean networks (PBNs are introduced. First, the outline of PBNs is explained. Next, an optimal control method using polynomial optimization is explained. The finite-time optimal control problem is reduced to a polynomial optimization problem. Furthermore, another finite-time optimal control problem, which can be reduced to an integer programming problem, is also explained.
Adaptive hybrid optimal quantum control for imprecisely characterized systems.
Egger, D J; Wilhelm, F K
2014-06-20
Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful.
Modified Newton-Raphson GRAPE methods for optimal control of spin systems
International Nuclear Information System (INIS)
Goodwin, D. L.; Kuprov, Ilya
2016-01-01
Quadratic convergence throughout the active space is achieved for the gradient ascent pulse engineering (GRAPE) family of quantum optimal control algorithms. We demonstrate in this communication that the Hessian of the GRAPE fidelity functional is unusually cheap, having the same asymptotic complexity scaling as the functional itself. This leads to the possibility of using very efficient numerical optimization techniques. In particular, the Newton-Raphson method with a rational function optimization (RFO) regularized Hessian is shown in this work to require fewer system trajectory evaluations than any other algorithm in the GRAPE family. This communication describes algebraic and numerical implementation aspects (matrix exponential recycling, Hessian regularization, etc.) for the RFO Newton-Raphson version of GRAPE and reports benchmarks for common spin state control problems in magnetic resonance spectroscopy.
Modified Newton-Raphson GRAPE methods for optimal control of spin systems
Energy Technology Data Exchange (ETDEWEB)
Goodwin, D. L.; Kuprov, Ilya, E-mail: i.kuprov@soton.ac.uk [School of Chemistry, University of Southampton, Highfield Campus, Southampton SO17 1BJ (United Kingdom)
2016-05-28
Quadratic convergence throughout the active space is achieved for the gradient ascent pulse engineering (GRAPE) family of quantum optimal control algorithms. We demonstrate in this communication that the Hessian of the GRAPE fidelity functional is unusually cheap, having the same asymptotic complexity scaling as the functional itself. This leads to the possibility of using very efficient numerical optimization techniques. In particular, the Newton-Raphson method with a rational function optimization (RFO) regularized Hessian is shown in this work to require fewer system trajectory evaluations than any other algorithm in the GRAPE family. This communication describes algebraic and numerical implementation aspects (matrix exponential recycling, Hessian regularization, etc.) for the RFO Newton-Raphson version of GRAPE and reports benchmarks for common spin state control problems in magnetic resonance spectroscopy.
A path-following driver/vehicle model with optimized lateral dynamic controller
Directory of Open Access Journals (Sweden)
Behrooz Mashadi
Full Text Available Reduction in traffic congestion and overall number of accidents, especially within the last decade, can be attributed to the enormous progress in active safety. Vehicle path following control with the presence of driver commands can be regarded as one of the important issues in vehicle active safety systems development and more realistic explanation of vehicle path tracking problem. In this paper, an integrated driver/DYC control system is presented that regulates the steering angle and yaw moment, considering driver previewed path. Thus, the driver previewed distance, the heading error and the lateral deviation between the vehicle and desired path are used as inputs. Then, the controller determines and applies a corrective steering angle and a direct yaw moment to make the vehicle follow the desired path. A PID controller with optimized gains is used for the control of integrated driver/DYC system. Genetic Algorithm as an intelligent optimization method is utilized to adapt PID controller gains for various working situations. Proposed integrated driver/DYC controller is examined on lane change manuvers andthe sensitivity of the control system is investigated through the changes in the driver model and vehicle parameters. Simulation results show the pronounced effectiveness of the controller in vehicle path following and stability.
Time-optimal control of reactor power
International Nuclear Information System (INIS)
Bernard, J.A.
1987-01-01
Control laws that permit adjustments in reactor power to be made in minimum time and without overshoot have been formulated and demonstrated. These control laws which are derived from the standard and alternate dynamic period equations, are closed-form expressions of general applicability. These laws were deduced by noting that if a system is subject to one or more operating constraints, then the time-optimal response is to move the system along these constraints. Given that nuclear reactors are subject to limitations on the allowed reactor period, a time-optimal control law would step the period from infinity to the minimum allowed value, hold the period at that value for the duration of the transient, and then step the period back to infinity. The change in reactor would therefore be accomplished in minimum time. The resulting control laws are superior to other forms of time-optimal control because they are general-purpose, closed-form expressions that are both mathematically tractable and readily implanted. Moreover, these laws include provisions for the use of feedback. The results of simulation studies and actual experiments on the 5 MWt MIT Research Reactor in which these time-optimal control laws were used successfully to adjust the reactor power are presented
Simulation Research on Vehicle Active Suspension Controller Based on G1 Method
Li, Gen; Li, Hang; Zhang, Shuaiyang; Luo, Qiuhui
2017-09-01
Based on the order relation analysis method (G1 method), the optimal linear controller of vehicle active suspension is designed. The system of the main and passive suspension of the single wheel vehicle is modeled and the system input signal model is determined. Secondly, the system motion state space equation is established by the kinetic knowledge and the optimal linear controller design is completed with the optimal control theory. The weighting coefficient of the performance index coefficients of the main passive suspension is determined by the relational analysis method. Finally, the model is simulated in Simulink. The simulation results show that: the optimal weight value is determined by using the sequence relation analysis method under the condition of given road conditions, and the vehicle acceleration, suspension stroke and tire motion displacement are optimized to improve the comprehensive performance of the vehicle, and the active control is controlled within the requirements.
Optimal Model-Based Control in HVAC Systems
DEFF Research Database (Denmark)
Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik
2008-01-01
is developed. Then the optimal control structure is designed and implemented. The HVAC system is splitted into two subsystems. By selecting the right set-points and appropriate cost functions for each subsystem controller the optimal control strategy is respected to gaurantee the minimum thermal and electrical......This paper presents optimal model-based control of a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger (a rotary wheel heat recovery) and a water-to- air heat exchanger. First dynamic model of the HVAC system...... energy consumption. Finally, the controller is applied to control the mentioned HVAC system and the results show that the expected goals are fulfilled....
Optimal coordination and control of posture and movements.
Johansson, Rolf; Fransson, Per-Anders; Magnusson, Måns
2009-01-01
This paper presents a theoretical model of stability and coordination of posture and locomotion, together with algorithms for continuous-time quadratic optimization of motion control. Explicit solutions to the Hamilton-Jacobi equation for optimal control of rigid-body motion are obtained by solving an algebraic matrix equation. The stability is investigated with Lyapunov function theory and it is shown that global asymptotic stability holds. It is also shown how optimal control and adaptive control may act in concert in the case of unknown or uncertain system parameters. The solution describes motion strategies of minimum effort and variance. The proposed optimal control is formulated to be suitable as a posture and movement model for experimental validation and verification. The combination of adaptive and optimal control makes this algorithm a candidate for coordination and control of functional neuromuscular stimulation as well as of prostheses. Validation examples with experimental data are provided.
Optimally Controlled Flexible Fuel Powertrain System
Energy Technology Data Exchange (ETDEWEB)
Hakan Yilmaz; Mark Christie; Anna Stefanopoulou
2010-12-31
The primary objective of this project was to develop a true Flex Fuel Vehicle capable of running on any blend of ethanol from 0 to 85% with reduced penalty in usable vehicle range. A research and development program, targeting 10% improvement in fuel economy using a direct injection (DI) turbocharged spark ignition engine was conducted. In this project a gasoline-optimized high-technology engine was considered and the hardware and configuration modifications were defined for the engine, fueling system, and air path. Combined with a novel engine control strategy, control software, and calibration this resulted in a highly efficient and clean FFV concept. It was also intended to develop robust detection schemes of the ethanol content in the fuel integrated with adaptive control algorithms for optimized turbocharged direct injection engine combustion. The approach relies heavily on software-based adaptation and optimization striving for minimal modifications to the gasoline-optimized engine hardware system. Our ultimate objective was to develop a compact control methodology that takes advantage of any ethanol-based fuel mixture and not compromise the engine performance under gasoline operation.
OPTIMAL CONTROL FOR ELECTRIC VEHICLE STABILIZATION
Directory of Open Access Journals (Sweden)
MARIAN GAICEANU
2016-01-01
Full Text Available This main objective of the paper is to stabilize an electric vehicle in optimal manner to a step lane change maneuver. To define the mathematical model of the vehicle, the rigid body moving on a plane is taken into account. An optimal lane keeping controller delivers the adequate angles in order to stabilize the vehicle’s trajectory in an optimal way. Two degree of freedom linear bicycle model is adopted as vehicle model, consisting of lateral and yaw motion equations. The proposed control maintains the lateral stability by taking the feedback information from the vehicle transducers. In this way only the lateral vehicle’s dynamics are enough to considerate. Based on the obtained linear mathematical model the quadratic optimal control is designed in order to maintain the lateral stability of the electric vehicle. The numerical simulation results demonstrate the feasibility of the proposed solution.
Geladé, Katleen; Janssen, Tieme W P; Bink, Marleen; van Mourik, Rosa; Maras, Athanasios; Oosterlaan, Jaap
2016-10-01
The efficacy of neurofeedback as a treatment for attention-deficit/hyperactivity disorder (ADHD), and whether neurofeedback is a viable alternative for stimulant medication, is still an intensely debated subject. The current randomized controlled trial compared neurofeedback to (1) optimally titrated methylphenidate and (2) a semi-active control intervention, physical activity, to account for nonspecific effects. A multicenter 3-way parallel-group study with balanced randomization was conducted. Children with a DSM-IV-TR diagnosis of ADHD, aged 7-13 years, were randomly allocated to receive neurofeedback (n = 39), methylphenidate (n = 36), or physical activity (n = 37) over a period of 10-12 weeks. Neurofeedback comprised theta/beta training on the vertex (Cz). Physical activity consisted of moderate to vigorous intensity exercises. Neurofeedback and physical activity were balanced in terms of number (~30) and duration of sessions. A double-blind pseudorandomized placebo-controlled crossover titration procedure was used to determine an optimal dose in the methylphenidate intervention. Parent and teacher ratings on the Strengths and Difficulties Questionnaire (SDQ) and Strengths and Weaknesses of ADHD Symptoms and Normal Behavior (SWAN) were used to assess intervention outcomes. Data collection took place between September 2010 and March 2014. Intention-to-treat analyses revealed an improvement in parent-reported behavior on the SDQ and the SWAN Hyperactivity/Impulsivity scale, irrespective of received intervention (ηp² = 0.21-0.22, P ≤ .001), whereas the SWAN Inattention scale revealed more improvement in children who received methylphenidate than neurofeedback and physical activity (ηp² = 0.13, P ≤ .001). Teachers reported a decrease of ADHD symptoms on all measures for methylphenidate, but not for neurofeedback or physical activity (range of ηp² = 0.14-0.29, P ADHD symptoms in children with ADHD. ClinicalTrials.gov identifier: NCT01363544. © Copyright
Optimal Investment Control of Macroeconomic Systems
Institute of Scientific and Technical Information of China (English)
ZHAO Ke-jie; LIU Chuan-zhe
2006-01-01
Economic growth is always accompanied by economic fluctuation. The target of macroeconomic control is to keep a basic balance of economic growth, accelerate the optimization of economic structures and to lead a rapid, sustainable and healthy development of national economies, in order to propel society forward. In order to realize the above goal, investment control must be regarded as the most important policy for economic stability. Readjustment and control of investment includes not only control of aggregate investment, but also structural control which depends on economic-technology relationships between various industries of a national economy. On the basis of the theory of a generalized system, an optimal investment control model for government has been developed. In order to provide a scientific basis for government to formulate a macroeconomic control policy, the model investigates the balance of total supply and aggregate demand through an adjustment in investment decisions realizes a sustainable and stable growth of the national economy. The optimal investment decision function proposed by this study has a unique and specific expression, high regulating precision and computable characteristics.
Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty
Nguyen, Nhan T.
2012-01-01
This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.
A model of optimal voluntary muscular control.
FitzHugh, R
1977-07-19
In the absence of detailed knowledge of how the CNS controls a muscle through its motor fibers, a reasonable hypothesis is that of optimal control. This hypothesis is studied using a simplified mathematical model of a single muscle, based on A.V. Hill's equations, with series elastic element omitted, and with the motor signal represented by a single input variable. Two cost functions were used. The first was total energy expended by the muscle (work plus heat). If the load is a constant force, with no inertia, Hill's optimal velocity of shortening results. If the load includes a mass, analysis by optimal control theory shows that the motor signal to the muscle consists of three phases: (1) maximal stimulation to accelerate the mass to the optimal velocity as quickly as possible, (2) an intermediate level of stimulation to hold the velocity at its optimal value, once reached, and (3) zero stimulation, to permit the mass to slow down, as quickly as possible, to zero velocity at the specified distance shortened. If the latter distance is too small, or the mass too large, the optimal velocity is not reached, and phase (2) is absent. For lengthening, there is no optimal velocity; there are only two phases, zero stimulation followed by maximal stimulation. The second cost function was total time. The optimal control for shortening consists of only phases (1) and (3) above, and is identical to the minimal energy control whenever phase (2) is absent from the latter. Generalization of this model to include viscous loads and a series elastic element are discussed.
Automated beam steering using optimal control
Energy Technology Data Exchange (ETDEWEB)
Allen, C. K. (Christopher K.)
2004-01-01
We present a steering algorithm which, with the aid of a model, allows the user to specify beam behavior throughout a beamline, rather than just at specified beam position monitor (BPM) locations. The model is used primarily to compute the values of the beam phase vectors from BPM measurements, and to define cost functions that describe the steering objectives. The steering problem is formulated as constrained optimization problem; however, by applying optimal control theory we can reduce it to an unconstrained optimization whose dimension is the number of control signals.
Semi-autonomous unmanned ground vehicle control system
Anderson, Jonathan; Lee, Dah-Jye; Schoenberger, Robert; Wei, Zhaoyi; Archibald, James
2006-05-01
Unmanned Ground Vehicles (UGVs) have advantages over people in a number of different applications, ranging from sentry duty, scouting hazardous areas, convoying goods and supplies over long distances, and exploring caves and tunnels. Despite recent advances in electronics, vision, artificial intelligence, and control technologies, fully autonomous UGVs are still far from being a reality. Currently, most UGVs are fielded using tele-operation with a human in the control loop. Using tele-operations, a user controls the UGV from the relative safety and comfort of a control station and sends commands to the UGV remotely. It is difficult for the user to issue higher level commands such as patrol this corridor or move to this position while avoiding obstacles. As computer vision algorithms are implemented in hardware, the UGV can easily become partially autonomous. As Field Programmable Gate Arrays (FPGAs) become larger and more powerful, vision algorithms can run at frame rate. With the rapid development of CMOS imagers for consumer electronics, frame rate can reach as high as 200 frames per second with a small size of the region of interest. This increase in the speed of vision algorithm processing allows the UGVs to become more autonomous, as they are able to recognize and avoid obstacles in their path, track targets, or move to a recognized area. The user is able to focus on giving broad supervisory commands and goals to the UGVs, allowing the user to control multiple UGVs at once while still maintaining the convenience of working from a central base station. In this paper, we will describe a novel control system for the control of semi-autonomous UGVs. This control system combines a user interface similar to a simple tele-operation station along with a control package, including the FPGA and multiple cameras. The control package interfaces with the UGV and provides the necessary control to guide the UGV.
Energy Technology Data Exchange (ETDEWEB)
De Choudens, H.; Rage, P. [Commissariat a l' energie atomique et aux energies alternatives - CEA, Centre d' Etudes Nucleaires de Grenoble (France)
1963-07-01
As the number of electronic semi-portable health measurement devices is (was) increasing, it appears (appeared) important to organise their maintenance. In this report, the authors describe the implemented organisation. They indicate how a device is identified, which are the performed tests, and discuss results which have been obtained during the first year of implementation of this maintenance organisation. Then, they present the control bench, its operation (supply, measurement circuits), its use (control process for different devices, performed measurements and controls)
Optimal identification of semi-rigid domains in macromolecules from molecular dynamics simulation.
Directory of Open Access Journals (Sweden)
Stefan Bernhard
Full Text Available Biological function relies on the fact that biomolecules can switch between different conformations and aggregation states. Such transitions involve a rearrangement of parts of the biomolecules involved that act as dynamic domains. The reliable identification of such domains is thus a key problem in biophysics. In this work we present a method to identify semi-rigid domains based on dynamical data that can be obtained from molecular dynamics simulations or experiments. To this end the average inter-atomic distance-deviations are computed. The resulting matrix is then clustered by a constrained quadratic optimization problem. The reliability and performance of the method are demonstrated for two artificial peptides. Furthermore we correlate the mechanical properties with biological malfunction in three variants of amyloidogenic transthyretin protein, where the method reveals that a pathological mutation destabilizes the natural dimer structure of the protein. Finally the method is used to identify functional domains of the GroEL-GroES chaperone, thus illustrating the efficiency of the method for large biomolecular machines.
In-flight performance optimization for rotorcraft with redundant controls
Ozdemir, Gurbuz Taha
A conventional helicopter has limits on performance at high speeds because of the limitations of main rotor, such as compressibility issues on advancing side or stall issues on retreating side. Auxiliary lift and thrust components have been suggested to improve performance of the helicopter substantially by reducing the loading on the main rotor. Such a configuration is called the compound rotorcraft. Rotor speed can also be varied to improve helicopter performance. In addition to improved performance, compound rotorcraft and variable RPM can provide a much larger degree of control redundancy. This additional redundancy gives the opportunity to further enhance performance and handling qualities. A flight control system is designed to perform in-flight optimization of redundant control effectors on a compound rotorcraft in order to minimize power required and extend range. This "Fly to Optimal" (FTO) control law is tested in simulation using the GENHEL model. A model of the UH-60, a compound version of the UH-60A with lifting wing and vectored thrust ducted propeller (VTDP), and a generic compound version of the UH-60A with lifting wing and propeller were developed and tested in simulation. A model following dynamic inversion controller is implemented for inner loop control of roll, pitch, yaw, heave, and rotor RPM. An outer loop controller regulates airspeed and flight path during optimization. A Golden Section search method was used to find optimal rotor RPM on a conventional helicopter, where the single redundant control effector is rotor RPM. The FTO builds off of the Adaptive Performance Optimization (APO) method of Gilyard by performing low frequency sweeps on a redundant control for a fixed wing aircraft. A method based on the APO method was used to optimize trim on a compound rotorcraft with several redundant control effectors. The controller can be used to optimize rotor RPM and compound control effectors through flight test or simulations in order to
Frankowska, Hélène; Hoehener, Daniel
2017-06-01
This paper is devoted to pointwise second-order necessary optimality conditions for the Mayer problem arising in optimal control theory. We first show that with every optimal trajectory it is possible to associate a solution p (ṡ) of the adjoint system (as in the Pontryagin maximum principle) and a matrix solution W (ṡ) of an adjoint matrix differential equation that satisfy a second-order transversality condition and a second-order maximality condition. These conditions seem to be a natural second-order extension of the maximum principle. We then prove a Jacobson like necessary optimality condition for general control systems and measurable optimal controls that may be only ;partially singular; and may take values on the boundary of control constraints. Finally we investigate the second-order sensitivity relations along optimal trajectories involving both p (ṡ) and W (ṡ).
An exercise in nostalgia: Nostalgia promotes health optimism and physical activity.
Kersten, Mike; Cox, Cathy R; Van Enkevort, Erin A
2016-10-01
Previous research has shown that nostalgia, a sentimental longing for the past, leads to greater feelings of optimism, with other work demonstrating that optimistic thinking (general & health-orientated) is associated with better physical and psychological health. Integrating these two lines of research, the current studies examined whether nostalgia-induced health optimism promotes attitudes and behaviours associated with better physical well-being. Participants, in three experiments, were randomly assigned to write about either a nostalgic or ordinary event. Following this, everyone completed a measure of health optimism (Studies 1-3), measures of health attitudes (Study 2) and had their physical activity monitored over the course of 2 weeks (Study 3). The results revealed that, in comparison to control conditions, nostalgic reverie led to greater health optimism (Studies 1-3). Further, heightened health optimism following nostalgic reflection led to more positive health attitudes (Study 2), and increased physical activity over a two-week period (i.e. Fitbit activity trackers; Study 3). These findings highlight the importance of nostalgia on health attitudes and behaviours. Specifically, this work suggests that nostalgia can be used as a mechanism to increase the importance, perceived efficacy and behaviour associated with better physical health.
Optimization and control of the activated sludge process by adaptation of aeration tank volume
Energy Technology Data Exchange (ETDEWEB)
Staud, R
1982-04-01
Purpose of full scale studies conducted at a municipal wastewater treatment plant at Schwetzingen, Germany, was to optimize the activated sludge treatment process. Influent loading fluctuations were answered by operating a distinct number of the four parallel treatment plant units (aeration tank/clarifier) present. During the intermediate period of time the aerators were also switched off, and the activated sludge was kept anaerobically. The purpose of this particular technique is to equalize the nutrient supply of the microorganisms to gain an improved metabolic potential, as well as to decrease the energy demand for aeration. A mathematical algorithm for process control was developed to accomplish this technique. Initial parameters are inflow rate, MLSS and plateau-BOD to evaluate the substrate concentration. The results of the full scale studies prove the practicability of this concept. Equalization of the F:M ratio fluctuations leads to an increase of the average substrate loading but not to any decrease in the overall process efficiency. Anaerobic sludge storage did not cause any problem. Odor problems could be handled by limitation of the storage period to 24 hours. As far as energy consumption for aeration is concerned a decrease by 47% percent could be achieved.
Deterministic methods for multi-control fuel loading optimization
Rahman, Fariz B. Abdul
We have developed a multi-control fuel loading optimization code for pressurized water reactors based on deterministic methods. The objective is to flatten the fuel burnup profile, which maximizes overall energy production. The optimal control problem is formulated using the method of Lagrange multipliers and the direct adjoining approach for treatment of the inequality power peaking constraint. The optimality conditions are derived for a multi-dimensional multi-group optimal control problem via calculus of variations. Due to the Hamiltonian having a linear control, our optimal control problem is solved using the gradient method to minimize the Hamiltonian and a Newton step formulation to obtain the optimal control. We are able to satisfy the power peaking constraint during depletion with the control at beginning of cycle (BOC) by building the proper burnup path forward in time and utilizing the adjoint burnup to propagate the information back to the BOC. Our test results show that we are able to achieve our objective and satisfy the power peaking constraint during depletion using either the fissile enrichment or burnable poison as the control. Our fuel loading designs show an increase of 7.8 equivalent full power days (EFPDs) in cycle length compared with 517.4 EFPDs for the AP600 first cycle.
Optimal Control for Stochastic Delay Evolution Equations
Energy Technology Data Exchange (ETDEWEB)
Meng, Qingxin, E-mail: mqx@hutc.zj.cn [Huzhou University, Department of Mathematical Sciences (China); Shen, Yang, E-mail: skyshen87@gmail.com [York University, Department of Mathematics and Statistics (Canada)
2016-08-15
In this paper, we investigate a class of infinite-dimensional optimal control problems, where the state equation is given by a stochastic delay evolution equation with random coefficients, and the corresponding adjoint equation is given by an anticipated backward stochastic evolution equation. We first prove the continuous dependence theorems for stochastic delay evolution equations and anticipated backward stochastic evolution equations, and show the existence and uniqueness of solutions to anticipated backward stochastic evolution equations. Then we establish necessary and sufficient conditions for optimality of the control problem in the form of Pontryagin’s maximum principles. To illustrate the theoretical results, we apply stochastic maximum principles to study two examples, an infinite-dimensional linear-quadratic control problem with delay and an optimal control of a Dirichlet problem for a stochastic partial differential equation with delay. Further applications of the two examples to a Cauchy problem for a controlled linear stochastic partial differential equation and an optimal harvesting problem are also considered.
Optimal control linear quadratic methods
Anderson, Brian D O
2007-01-01
This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory from an engineering viewpoint, with step-by-step explanations that show clearly how to make practical use of the material.The three-part treatment begins with the basic theory of the linear regulator/tracker for time-invariant and time-varying systems. The Hamilton-Jacobi equation is introduced using the Principle of Optimality, and the infinite-time problem is considered. The second part outlines the
Engineering applications of discrete-time optimal control
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui; Ravn, Hans V.
1990-01-01
Many problems of design and operation of engineering systems can be formulated as optimal control problems where time has been discretisized. This is also true even if 'time' is not involved in the formulation of the problem, but rather another one-dimensional parameter. This paper gives a review...... of some well-known and new results in discrete time optimal control methods applicable to practical problem solving within engineering. Emphasis is placed on dynamic programming, the classical maximum principle and generalized versions of the maximum principle for optimal control of discrete time systems...
Development of the Circulation Control Flow Scheme Used in the NTF Semi-Span FAST-MAC Model
Jones, Gregory S.; Milholen, William E., II; Chan, David T.; Allan, Brian G.; Goodliff, Scott L.; Melton, Latunia P.; Anders, Scott G.; Carter, Melissa B.; Capone, Francis J.
2013-01-01
The application of a circulation control system for high Reynolds numbers was experimentally validated with the Fundamental Aerodynamic Subsonic Transonic Modular Active Control semi-span model in the NASA Langley National Transonic Facility. This model utilized four independent flow paths to modify the lift and thrust performance of a representative advanced transport type of wing. The design of the internal flow paths highlights the challenges associated with high Reynolds number testing in a cryogenic pressurized wind tunnel. Weight flow boundaries for the air delivery system were identified at mildly cryogenic conditions ranging from 0.1 to 10 lbm/sec. Results from the test verified system performance and identified solutions associated with the weight-flow metering system that are linked to internal perforated plates used to achieve flow uniformity at the jet exit.
Semi-definite Programming: methods and algorithms for energy management
International Nuclear Information System (INIS)
Gorge, Agnes
2013-01-01
The present thesis aims at exploring the potentialities of a powerful optimization technique, namely Semi-definite Programming, for addressing some difficult problems of energy management. We pursue two main objectives. The first one consists of using SDP to provide tight relaxations of combinatorial and quadratic problems. A first relaxation, called 'standard' can be derived in a generic way but it is generally desirable to reinforce them, by means of tailor-made tools or in a systematic fashion. These two approaches are implemented on different models of the Nuclear Outages Scheduling Problem, a famous combinatorial problem. We conclude this topic by experimenting the Lasserre's hierarchy on this problem, leading to a sequence of semi-definite relaxations whose optimal values tends to the optimal value of the initial problem. The second objective deals with the use of SDP for the treatment of uncertainty. We investigate an original approach called 'distributionally robust optimization', that can be seen as a compromise between stochastic and robust optimization and admits approximations under the form of a SDP. We compare the benefits of this method w.r.t classical approaches on a demand/supply equilibrium problem. Finally, we propose a scheme for deriving SDP relaxations of MISOCP and we report promising computational results indicating that the semi-definite relaxation improves significantly the continuous relaxation, while requiring a reasonable computational effort. SDP therefore proves to be a promising optimization method that offers great opportunities for innovation in energy management. (author)
Semi-polar GaN materials technology for high IQE green LEDs.
Energy Technology Data Exchange (ETDEWEB)
Koleske, Daniel; Lee, Stephen Roger; Crawford, Mary H; Coltrin, Michael Elliott; Fini, Paul
2013-06-01
The goal of this NETL funded program was to improve the IQE in green (and longer wavelength) nitride- based LEDs structures by using semi-polar GaN planar orientations for InGaN multiple quantum well (MQW) growth. These semi-polar orientations have the advantage of significantly reducing the piezoelectric fields that distort the QW band structure and decrease electron-hole overlap. In addition, semipolar surfaces potentially provide a more open surface bonding environment for indium incorporation, thus enabling higher indium concentrations in the InGaN MQW. The goal of the proposed work was to select the optimal semi-polar orientation and explore wafer miscuts around this orientation that produced the highest quantum efficiency LEDs. At the end of this program we had hoped to have MQWs active regions at 540 nm with an IQE of 50% and an EQE of 40%, which would be approximately twice the estimated current state-of-the-art.
Reynoso Meza, Gilberto; Sanchis Saez, Javier; Herrero Durá, Juan Manuel
2017-01-01
This book is devoted to Multiobjective Optimization Design (MOOD) procedures for controller tuning applications, by means of Evolutionary Multiobjective Optimization (EMO). It presents developments in tools, procedures and guidelines to facilitate this process, covering the three fundamental steps in the procedure: problem definition, optimization and decision-making. The book is divided into four parts. The first part, Fundamentals, focuses on the necessary theoretical background and provides specific tools for practitioners. The second part, Basics, examines a range of basic examples regarding the MOOD procedure for controller tuning, while the third part, Benchmarking, demonstrates how the MOOD procedure can be employed in several control engineering problems. The fourth part, Applications, is dedicated to implementing the MOOD procedure for controller tuning in real processes.
Optimal Bilinear Control of Gross--Pitaevskii Equations
Hintermü ller, Michael; Marahrens, Daniel; Markowich, Peter A.; Sparber, Christof
2013-01-01
A mathematical framework for optimal bilinear control of nonlinear Schrödinger equations of Gross--Pitaevskii type arising in the description of Bose--Einstein condensates is presented. The obtained results generalize earlier efforts found in the literature in several aspects. In particular, the cost induced by the physical workload over the control process is taken into account rather than the often used L^2- or H^1-norms for the cost of the control action. Well-posedness of the problem and existence of an optimal control are proved. In addition, the first order optimality system is rigorously derived. Also a numerical solution method is proposed, which is based on a Newton-type iteration, and used to solve several coherent quantum control problems.
Directory of Open Access Journals (Sweden)
Mun-Kyeom Kim
2017-09-01
Full Text Available This study introduces a frequency regulation strategy to enable the participation of wind turbines with permanent magnet synchronous generators (PMSGs. The optimal strategy focuses on developing the frequency support capability of PMSGs connected to the power system. Active power control is performed using maximum power point tracking (MPPT and de-loaded control to supply the required power reserve following a disturbance. A kinetic energy (KE reserve control is developed to enhance the frequency regulation capability of wind turbines. The coordination with the de-loaded control prevents instability in the PMSG wind system due to excessive KE discharge. A KE optimization method that maximizes the sum of the KE reserves at wind farms is also adopted to determine the de-loaded power reference for each PMSG wind turbine using the particle swarm optimization (PSO algorithm. To validate the effectiveness of the proposed optimal control and operation strategy, three different case studies are conducted using the PSCAD/EMTDC simulation tool. The results demonstrate that the optimal strategy enhances the frequency support contribution from PMSG wind turbines.
Biologically active compounds of semi-metals
Czech Academy of Sciences Publication Activity Database
Řezanka, Tomáš; Sigler, Karel
2008-01-01
Roč. 69, č. 3 (2008), s. 585-606 ISSN 0031-9422 Institutional research plan: CEZ:AV0Z50200510 Keywords : semi-metals * boron * silicon Subject RIV: CE - Biochemistry Impact factor: 2.946, year: 2008
Control Methods Utilizing Energy Optimizing Schemes in Refrigeration Systems
DEFF Research Database (Denmark)
Larsen, L.S; Thybo, C.; Stoustrup, Jakob
2003-01-01
The potential energy savings in refrigeration systems using energy optimal control has been proved to be substantial. This however requires an intelligent control that drives the refrigeration systems towards the energy optimal state. This paper proposes an approach for a control, which drives th...... the condenser pressure towards an optimal state. The objective of this is to present a feasible method that can be used for energy optimizing control. A simulation model of a simple refrigeration system will be used as basis for testing the control method....
Lipid-lowering Activity of Natural and Semi-Synthetic Sterols and Stanols.
Taha, Dhiaa A; Wasan, Ellen K; Wasan, Kishor M; Gershkovich, Pavel
2015-01-01
Consumption of plant sterols/ stanols has long been demonstrated to reduce plasma cholesterol levels. The objective of this review is to demonstrate the lipid-lowering activity and anti-atherogenic effects of natural and semi-synthetic plant sterols/ stanols based on evidence from cell-culture studies, animal studies and clinical trials. Additionally, this review highlights certain molecular mechanisms by which plant sterols/ stanols lower plasma cholesterol levels with a special emphasis on factors that affect the cholesterol-lowering activity of plant sterols/stanols. The crystalline nature and the poor oil solubility of these natural products could be important factors that limit their cholesterol-lowering efficiency. Several attempts have been made to improve the cholesterol-lowering activity by enhancing the bioavailability of crystalline sterols and stanols. Approaches involved reduction of the crystal size and/or esterification with fatty acids from vegetable or fish oils. However, the most promising approach in this context is the chemical modification of plant sterols /stanols into water soluble disodium ascorbyl phytostanyl phosphates analogue by esterification with ascorbic acid. This novel semi-synthetic stanol derivative has improved efficacy over natural plant sterols/ stanols and can provide additional benefits by combining the cholesterol-lowering properties of plant stanols with the antioxidant potential of ascorbic acid. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
Scalable algorithms for optimal control of stochastic PDEs
Ghattas, Omar
2016-01-07
We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.
Scalable algorithms for optimal control of stochastic PDEs
Ghattas, Omar; Alexanderian, Alen; Petra, Noemi; Stadler, Georg
2016-01-01
We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.
Management of nuclear PRs activity with optimal conditions
International Nuclear Information System (INIS)
Ohnishi, Teruaki
1997-01-01
A methodology is proposed to derive optimal conditions for the activity of nuclear public relations (PRs). With the use of data-bases available at present, expressions were derived which connect the budget allocated for the PRs activity with the intensity of stimulus for four types of activity of the advertisement in the press, the exclusive publicity, the pamphlet and the advertisement on television. Optimal conditions for the activity were determined by introducing a model describing a relation between the intensity of stimulus and the extent of the change of public's attitude to nuclear energy, namely the effect of PRs activity, and also by giving the optimal ratio of allocation of the budget among the four types of activity as a function of cost versus effectiveness of each type. Those optimal conditions, being for the ratio of allocation of the budget, the execution time and the intensity of each type of activity at that time, vary depending on the number of household in a target region, the target class of demography, the duration time of activity, and the amount of budget for the activity. It becomes clear from numerical calculation that the optimal conditions and the effect of activity show quite strong non-linearity with respect to the variation of those variables, and that the effect of PRs activity averaged over all public in the target region becomes to be maximum, in Japan, when the activity is executed with the optimal conditions determined for the target class of middle- and advanced-aged women. The management of nuclear PRs activity becomes possible by introducing such a method of fixation of optimal conditions for the activity as described here. (author)
Reference-shaping adaptive control by using gradient descent optimizers.
Directory of Open Access Journals (Sweden)
Baris Baykant Alagoz
Full Text Available This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC method for several test scenarios. An experimental study demonstrates application of method for rotor control.
Optimal control problem for the extended Fisher–Kolmogorov equation
Indian Academy of Sciences (India)
In this paper, the optimal control problem for the extended Fisher–Kolmogorov equation is studied. The optimal control under boundary condition is given, the existence of optimal solution to the equation is proved and the optimality system is established.
International Nuclear Information System (INIS)
Chenel, A.; Meier, C.; Dive, G.; Desouter-Lecomte, M.
2015-01-01
We compare the strategy found by the optimal control theory in a complex molecular system according to the active subspace coupled to the field. The model is the isomerization during a Cope rearrangement of Thiele’s ester that is the most stable dimer obtained by the dimerization of methyl-cyclopentadienenylcarboxylate. The crudest partitioning consists in retaining in the active space only the reaction coordinate, coupled to a dissipative bath of harmonic oscillators which are not coupled to the field. The control then fights against dissipation by accelerating the passage across the transition region which is very wide and flat in a Cope reaction. This mechanism has been observed in our previous simulations [Chenel et al., J. Phys. Chem. A 116, 11273 (2012)]. We compare here, the response of the control field when the reaction path is coupled to a second active mode. Constraints on the integrated intensity and on the maximum amplitude of the fields are imposed limiting the control landscape. Then, optimum field from one-dimensional simulation cannot provide a very high yield. Better guess fields based on the two-dimensional model allow the control to exploit different mechanisms providing a high control yield. By coupling the reaction surface to a bath, we confirm the link between the robustness of the field against dissipation and the time spent in the delocalized states above the transition barrier
Control and optimal control theories with applications
Burghes, D N
2004-01-01
This sound introduction to classical and modern control theory concentrates on fundamental concepts. Employing the minimum of mathematical elaboration, it investigates the many applications of control theory to varied and important present-day problems, e.g. economic growth, resource depletion, disease epidemics, exploited population, and rocket trajectories. An original feature is the amount of space devoted to the important and fascinating subject of optimal control. The work is divided into two parts. Part one deals with the control of linear time-continuous systems, using both transfer fun
Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu
2017-05-24
In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.
Optimal estimation and control in nuclear power plants
International Nuclear Information System (INIS)
Purviance, J.E.; Tylee, J.L.
1982-08-01
Optimal estimation and control theories offer the potential for more precise control and diagnosis of nuclear power plants. The important element of these theories is that a mathematical plant model is used in conjunction with the actual plant data to optimize some performance criteria. These criteria involve important plant variables and incorporate a sense of the desired plant performance. Several applications of optimal estimation and control to nuclear systems are discussed
Correlations in state space can cause sub-optimal adaptation of optimal feedback control models.
Aprasoff, Jonathan; Donchin, Opher
2012-04-01
Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to 're-tune' the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.
Neural Network for Optimization of Existing Control Systems
DEFF Research Database (Denmark)
Madsen, Per Printz
1995-01-01
The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems.......The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems....
Optimal control of a wave energy converter
Hendrikx, R.W.M.; Leth, J.; Andersen, P; Heemels, W.P.M.H.
2017-01-01
The optimal control strategy for a wave energy converter (WEC) with constraints on the control torque is investigated. The goal is to optimize the total energy delivered to the electricity grid. Using Pontryagin's maximum principle, the solution is found to be singular-bang. Using higher order
Optimization and control methods in industrial engineering and construction
Wang, Xiangyu
2014-01-01
This book presents recent advances in optimization and control methods with applications to industrial engineering and construction management. It consists of 15 chapters authored by recognized experts in a variety of fields including control and operation research, industrial engineering, and project management. Topics include numerical methods in unconstrained optimization, robust optimal control problems, set splitting problems, optimum confidence interval analysis, a monitoring networks optimization survey, distributed fault detection, nonferrous industrial optimization approaches, neural networks in traffic flows, economic scheduling of CCHP systems, a project scheduling optimization survey, lean and agile construction project management, practical construction projects in Hong Kong, dynamic project management, production control in PC4P, and target contracts optimization. The book offers a valuable reference work for scientists, engineers, researchers and practitioners in industrial engineering and c...
Optimal Sliding Mode Controllers for Attitude Stabilization of Flexible Spacecraft
Directory of Open Access Journals (Sweden)
Chutiphon Pukdeboon
2011-01-01
Full Text Available The robust optimal attitude control problem for a flexible spacecraft is considered. Two optimal sliding mode control laws that ensure the exponential convergence of the attitude control system are developed. Integral sliding mode control (ISMC is applied to combine the first-order sliding mode with optimal control and is used to control quaternion-based spacecraft attitude manoeuvres with external disturbances and an uncertainty inertia matrix. For the optimal control part the state-dependent Riccati equation (SDRE and optimal Lyapunov techniques are employed to solve the infinite-time nonlinear optimal control problem. The second method of Lyapunov is used to guarantee the stability of the attitude control system under the action of the proposed control laws. An example of multiaxial attitude manoeuvres is presented and simulation results are included to verify the usefulness of the developed controllers.
Rapid Optimal Generation Algorithm for Terrain Following Trajectory Based on Optimal Control
Institute of Scientific and Technical Information of China (English)
杨剑影; 张海; 谢邦荣; 尹健
2004-01-01
Based on the optimal control theory, a 3-dimensionnal direct generation algorithm is proposed for anti-ground low altitude penetration tasks under complex terrain. By optimizing the terrain following(TF) objective function,terrain coordinate system, missile dynamic model and control vector, the TF issue is turning into the improved optimal control problem whose mathmatical model is simple and need not solve the second order terrain derivative. Simulation results prove that this method is reasonable and feasible. The TF precision is in the scope from 0.3 m to 3.0 m,and the planning time is less than 30 min. This method have the strongpionts such as rapidness, precision and has great application value.
An optimal control problem for controlling the cell volume in dehydration and rehydration process
Energy Technology Data Exchange (ETDEWEB)
Chenghung Huang; Tetsung Chen [National Cheng Kung Univ., Dept. of Systems and Naval Mechatronic Engineering, Tainan (Taiwan)
2004-08-01
An optimal control algorithm utilizing the conjugate gradient method (CGM) of minimization is applied successfully in the present study in determining the optimal boundary control function for a diffusion-limited cell model based on the desired cell volume. The validity of the present optimal control analysis is examined by means of numerical experiments. Different desired cell volume for dehydration, rehydration and their combination are given in three test cases with different weighting coefficients and the corresponding optimal control functions are determined. The results show that the optimal boundary control functions can be obtained with an arbitrary initial guess within one second CPU time on a Pentium III-600 MHz PC. (Author)
Optimal control of HIV/AIDS dynamic: Education and treatment
Sule, Amiru; Abdullah, Farah Aini
2014-07-01
A mathematical model which describes the transmission dynamics of HIV/AIDS is developed. The optimal control representing education and treatment for this model is explored. The existence of optimal Control is established analytically by the use of optimal control theory. Numerical simulations suggest that education and treatment for the infected has a positive impact on HIV/AIDS control.
An optimized one-tube, semi-nested PCR assay for Paracoccidioides brasiliensis detection.
Pitz, Amanda de Faveri; Koishi, Andrea Cristine; Tavares, Eliandro Reis; Andrade, Fábio Goulart de; Loth, Eduardo Alexandre; Gandra, Rinaldo Ferreira; Venancio, Emerson José
2013-01-01
Herein, we report a one-tube, semi-nested-polymerase chain reaction (OTsn-PCR) assay for the detection of Paracoccidioides brasiliensis. We developed the OTsn-PCR assay for the detection of P. brasiliensis in clinical specimens and compared it with other PCR methods. The OTsn-PCR assay was positive for all clinical samples, and the detection limit was better or equivalent to the other nested or semi-nested PCR methods for P. brasiliensis detection. The OTsn-PCR assay described in this paper has a detection limit similar to other reactions for the molecular detection of P. brasiliensis, but this approach is faster and less prone to contamination than other conventional nested or semi-nested PCR assays.
Optimal control of inverted pendulum system using PID controller, LQR and MPC
Varghese, Elisa Sara; Vincent, Anju K.; Bagyaveereswaran, V.
2017-11-01
Inverted pendulum is a highly nonlinear system. Here we propose an optimal control technique for the control of an inverted Pendulum - cart system. The system is modeled, linearized and controlled. Here, the control objective is to control the system such that when the cart reaches a desired position the inverted pendulum stabilizes in the upright position. Initially PID controller is used to control the system. Later, Linear Quadratic Regulator (LQR) a well-known optimal control technique which makes use of the states of the dynamical system and control input to frame the optimal control decision is used. Various combinations of both PID and LQR controllers are implemented. To validate the robustness of the controller, the system is simulated with and without disturbance. Finally the system is also controlled using Model Predictive controller (MPC). MPC has well predictive ability to calculate future events and implement necessary control actions. The performance of the system is compared and analyzed.
Safranski, David L.; Weiss, Daiana; Clark, J. Brian; Taylor, W.R.; Gall, Ken
2014-01-01
Biodegradable polymers are clinically used in numerous biomedical applications, and classically show a loss in mechanical properties within weeks of implantation. This work demonstrates a new class of semi-degradable polymers that show an increase in mechanical properties through degradation via a controlled shift in a thermal transition. Semi-degradable polymer networks, poly(β-amino ester)-co-methyl methacrylate, were formed from a low glass transition temperature crosslinker, poly(β-amino ester), and high glass transition temperature monomer, methyl methacrylate, which degraded in a manner dependent upon the crosslinker chemical structure. In vitro and in vivo degradation revealed changes in mechanical behavior due to the degradation of the crosslinker from the polymer network. This novel polymer system demonstrates a strategy to temporally control the mechanical behavior of polymers and to enhance the initial performance of smart biomedical devices. PMID:24769113
Optimal Control for a Class of Chaotic Systems
Directory of Open Access Journals (Sweden)
Jianxiong Zhang
2012-01-01
Full Text Available This paper proposes the optimal control methods for a class of chaotic systems via state feedback. By converting the chaotic systems to the form of uncertain piecewise linear systems, we can obtain the optimal controller minimizing the upper bound on cost function by virtue of the robust optimal control method of piecewise linear systems, which is cast as an optimization problem under constraints of bilinear matrix inequalities (BMIs. In addition, the lower bound on cost function can be achieved by solving a semidefinite programming (SDP. Finally, numerical examples are given to illustrate the results.
Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System
Directory of Open Access Journals (Sweden)
Qiang Gao
2013-01-01
Full Text Available Motion control of gun barrels is an ongoing topic for the development of gun control equipments possessing excellent performances. In this paper, a typical fractional order PID control strategy is employed for the gun control system. To obtain optimal parameters of the controller, a multiobjective optimization scheme is developed from the loop-shaping perspective. To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. To enhance the robustness of the algorithm for different problems, an adapting scheme of the mutation operation is further employed. With assistance of the evolutionary algorithm, the optimal solution for the specified problem is selected. The numerical simulation results show that the control system can rapidly follow the demand signal with high accuracy and high robustness, demonstrating the efficiency of the proposed controller parameter tuning method.
Wells, James W; Cowled, Chris J; Darling, David; Guinn, Barbara-Ann; Farzaneh, Farzin; Noble, Alistair; Galea-Lauri, Joanna
2007-12-01
Alloreactive T-cell responses are known to result in the production of large amounts of proinflammatory cytokines capable of activating and maturing dendritic cells (DC). However, it is unclear whether these allogeneic responses could also act as an adjuvant for concurrent antigen-specific responses. To examine effects of simultaneous alloreactive and antigen-specific T-cell responses induced by semi-allogeneic DC. Semi-allogeneic DC were generated from the F(1) progeny of inbred strains of mice (C57BL/6 and C3H, or C57BL/6 and DBA). We directly primed antigen-specific CD8(+) and CD4(+) T-cells from OT-I and OT-II mice, respectively, in the absence of allogeneic responses, in vitro, and in the presence or absence of alloreactivity in vivo. In vitro, semi-allogeneic DC cross-presented ovalbumin (OVA) to naïve CD8(+) OT-I transgenic T-cells, primed naïve CD4(+) OT-II transgenic T-cells and could stimulate strong alloreactive T-cell proliferation in a primary mixed lymphocyte reaction (MLR). In vivo, semi-allogeneic DC migrated efficiently to regional lymph nodes but did not survive there as long as autologous DC. In addition, they were not able to induce cytotoxic T-lymphocyte (CTL) activity to a target peptide, and only weakly stimulated adoptively transferred OT-II cells. The CD4(+) response was unchanged in allo-tolerized mice, indicating that alloreactive T-cell responses could not provide help for concurrently activated antigen-specific responses. In an EL4 tumour-treatment model, vaccination with semi-allogeneic DC/EL4 fusion hybrids, but not allogeneic DC/EL4 hybrids, significantly increased mouse survival. Expression of self-Major histocompatibility complex (MHC) by semi-allogeneic DC can cause the induction of antigen-specific immunity, however, concurrently activated allogeneic bystander responses do not provide helper or adjuvant effects.
Optimal Control Inventory Stochastic With Production Deteriorating
Affandi, Pardi
2018-01-01
In this paper, we are using optimal control approach to determine the optimal rate in production. Most of the inventory production models deal with a single item. First build the mathematical models inventory stochastic, in this model we also assume that the items are in the same store. The mathematical model of the problem inventory can be deterministic and stochastic models. In this research will be discussed how to model the stochastic as well as how to solve the inventory model using optimal control techniques. The main tool in the study problems for the necessary optimality conditions in the form of the Pontryagin maximum principle involves the Hamilton function. So we can have the optimal production rate in a production inventory system where items are subject deterioration.
International Nuclear Information System (INIS)
Medeiros, Jose Antonio Carlos Canedo; Machado, Marcelo Dornellas; Lima, Alan Miranda M. de; Schirru, Roberto
2007-01-01
Predictive control systems are control systems that use a model of the controlled system (plant), used to predict the future behavior of the plant allowing the establishment of an anticipative control based on a future condition of the plant, and an optimizer that, considering a future time horizon of the plant output and a recent horizon of the control action, determines the controller's outputs to optimize a performance index of the controlled plant. The predictive control system does not require analytical models of the plant; the model of predictor of the plant can be learned from historical data of operation of the plant. The optimizer of the predictive controller establishes the strategy of the control: the minimization of a performance index (objective function) is done so that the present and future control actions are computed in such a way to minimize the objective function. The control strategy, implemented by the optimizer, induces the formation of an optimal control mechanism whose effect is to reduce the stabilization time, the 'overshoot' and 'undershoot', minimize the control actuation so that a compromise among those objectives is attained. The optimizer of the predictive controller is usually implemented using gradient-based algorithms. In this work we use the Particle Swarm Optimization algorithm (PSO) in the optimizer component of a predictive controller applied in the control of the xenon oscillation of a pressurized water reactor (PWR). The PSO is a stochastic optimization technique applied in several disciplines, simple and capable of providing a global optimal for high complexity problems and difficult to be optimized, providing in many cases better results than those obtained by other conventional and/or other artificial optimization techniques. (author)
Energy Technology Data Exchange (ETDEWEB)
Dulikravich, George S.; Sikka, Vinod K.; Muralidharan, G.
2006-06-01
The goal of this project was to adapt and use an advanced semi-stochastic algorithm for constrained multiobjective optimization and combine it with experimental testing and verification to determine optimum concentrations of alloying elements in heat-resistant and corrosion-resistant H-series stainless steel alloys that will simultaneously maximize a number of alloy's mechanical and corrosion properties.
Optimization strategy for actuator and sensor placement in active structural acoustic control
Oude nijhuis, M.H.H.; de Boer, Andries
2003-01-01
In active structural acoustic control the goal is to reduce the sound radiation of a structure by means of changing the vibrational behaviour of that structure. The performance of such an active control system is to a large extent determined by the locations of the actuators and sensors. In this
Energy Optimal Control of Induction Motor Drives
DEFF Research Database (Denmark)
Abrahamsen, Flemming
This thesis deals with energy optimal control of small and medium-size variable speed induction motor drives for especially Heating, Ventilation and Air-Condition (HVAC) applications. Optimized efficiency is achieved by adapting the magnetization level in the motor to the load, and the basic...... demonstrated that energy optimal control will sometimes improve and sometimes deteriorate the stability. Comparison of small and medium-size induction motor drives with permanent magnet motor drives indicated why, and in which applications, PM motors are especially good. Calculations of economical aspects...... improvement by energy optimal control for any standard induction motor drive between 2.2 kW and 90 kW. A simple method to evaluate the robustness against load disturbances was developed and used to compare the robustness of different motor types and sizes. Calculation of the oscillatory behavior of a motor...
Particle control in the DIII-D advanced divertor
International Nuclear Information System (INIS)
Schaffer, M.J.; Lippmann, S.I.; Mahdavi, M.A.; Petrie, T.W.; Stambaugh, R.D.; Hogan, J.; Klepper, C.C.; Mioduszewski, P.; Owen, L.; Hill, D.N.; Rensink, M.; Buchenauer, D.
1991-11-01
A new, electrically biasable, semi-closed divertor was installed and operated in the D3-D lower outside divertor location. The semi-closed divertor has yielded static gas pressure buildups in the pumping plenum in excess of 10 mtorr. (The planned cryogenic pumping is not yet installed). Electrical bias controls the distribution of particle recycle between the inner and outer divertors by rvec E x rvec B drifts. Depending on sign, bias increases or decreases the plenum gas pressure. Bias greatly reduce the sensitivity of plenum pressure to separatrix position. In particular, rvec E x rvec B drifts in the D3-D geometry can direct plasma across a divertor target and then optimally into the pumping aperture. Bias, even without active pumping, has also demonstrated a limited control of ELMing H-mode plasma density. 5 refs., 8 figs
Combined Optimal Control System for excavator electric drive
Kurochkin, N. S.; Kochetkov, V. P.; Platonova, E. V.; Glushkin, E. Y.; Dulesov, A. S.
2018-03-01
The article presents a synthesis of the combined optimal control algorithms of the AC drive rotation mechanism of the excavator. Synthesis of algorithms consists in the regulation of external coordinates - based on the theory of optimal systems and correction of the internal coordinates electric drive using the method "technical optimum". The research shows the advantage of optimal combined control systems for the electric rotary drive over classical systems of subordinate regulation. The paper presents a method for selecting the optimality criterion of coefficients to find the intersection of the range of permissible values of the coordinates of the control object. There is possibility of system settings by choosing the optimality criterion coefficients, which allows one to select the required characteristics of the drive: the dynamic moment (M) and the time of the transient process (tpp). Due to the use of combined optimal control systems, it was possible to significantly reduce the maximum value of the dynamic moment (M) and at the same time - reduce the transient time (tpp).
Defending against the Advanced Persistent Threat: An Optimal Control Approach
Directory of Open Access Journals (Sweden)
Pengdeng Li
2018-01-01
Full Text Available The new cyberattack pattern of advanced persistent threat (APT has posed a serious threat to modern society. This paper addresses the APT defense problem, that is, the problem of how to effectively defend against an APT campaign. Based on a novel APT attack-defense model, the effectiveness of an APT defense strategy is quantified. Thereby, the APT defense problem is modeled as an optimal control problem, in which an optimal control stands for a most effective APT defense strategy. The existence of an optimal control is proved, and an optimality system is derived. Consequently, an optimal control can be figured out by solving the optimality system. Some examples of the optimal control are given. Finally, the influence of some factors on the effectiveness of an optimal control is examined through computer experiments. These findings help organizations to work out policies of defending against APTs.
Practical synchronization on complex dynamical networks via optimal pinning control
Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu
2015-07-01
We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.
Design optimization for active twist rotor blades
Mok, Ji Won
This dissertation introduces the process of optimizing active twist rotor blades in the presence of embedded anisotropic piezo-composite actuators. Optimum design of active twist blades is a complex task, since it involves a rich design space with tightly coupled design variables. The study presents the development of an optimization framework for active helicopter rotor blade cross-sectional design. This optimization framework allows for exploring a rich and highly nonlinear design space in order to optimize the active twist rotor blades. Different analytical components are combined in the framework: cross-sectional analysis (UM/VABS), an automated mesh generator, a beam solver (DYMORE), a three-dimensional local strain recovery module, and a gradient based optimizer within MATLAB. Through the mathematical optimization problem, the static twist actuation performance of a blade is maximized while satisfying a series of blade constraints. These constraints are associated with locations of the center of gravity and elastic axis, blade mass per unit span, fundamental rotating blade frequencies, and the blade strength based on local three-dimensional strain fields under worst loading conditions. Through pre-processing, limitations of the proposed process have been studied. When limitations were detected, resolution strategies were proposed. These include mesh overlapping, element distortion, trailing edge tab modeling, electrode modeling and foam implementation of the mesh generator, and the initial point sensibility of the current optimization scheme. Examples demonstrate the effectiveness of this process. Optimization studies were performed on the NASA/Army/MIT ATR blade case. Even though that design was built and shown significant impact in vibration reduction, the proposed optimization process showed that the design could be improved significantly. The second example, based on a model scale of the AH-64D Apache blade, emphasized the capability of this framework to
The Contributions of Physical Activity and Fitness to Optimal Health and Wellness
Ohuruogu, Ben
2016-01-01
The paper examined the role of physical activity and fitness more especially in the area of disease prevention and control by looking at the major ways by which regular physical activity and fitness contributes to optimal health and wellness. The Surgeor General's Report (1996), stressed that physical inactivity is a national problem which…
Optimal control of quantum systems: Origins of inherent robustness to control field fluctuations
International Nuclear Information System (INIS)
Rabitz, Herschel
2002-01-01
The impact of control field fluctuations on the optimal manipulation of quantum dynamics phenomena is investigated. The quantum system is driven by an optimal control field, with the physical focus on the evolving expectation value of an observable operator. A relationship is shown to exist between the system dynamics and the control field fluctuations, wherein the process of seeking optimal performance assures an inherent degree of system robustness to such fluctuations. The presence of significant field fluctuations breaks down the evolution of the observable expectation value into a sequence of partially coherent robust steps. Robustness occurs because the optimization process reduces sensitivity to noise-driven quantum system fluctuations by taking advantage of the observable expectation value being bilinear in the evolution operator and its adjoint. The consequences of this inherent robustness are discussed in the light of recent experiments and numerical simulations on the optimal control of quantum phenomena. The analysis in this paper bodes well for the future success of closed-loop quantum optimal control experiments, even in the presence of reasonable levels of field fluctuations
Directory of Open Access Journals (Sweden)
Carlos Villaseñor
2017-12-01
Full Text Available Nowadays, there are several meta-heuristics algorithms which offer solutions for multi-variate optimization problems. These algorithms use a population of candidate solutions which explore the search space, where the leadership plays a big role in the exploration-exploitation equilibrium. In this work, we propose to use a Germinal Center Optimization algorithm (GCO which implements temporal leadership through modeling a non-uniform competitive-based distribution for particle selection. GCO is used to find an optimal set of parameters for a neural inverse optimal control applied to all-terrain tracked robot. In the Neural Inverse Optimal Control (NIOC scheme, a neural identifier, based on Recurrent High Orden Neural Network (RHONN trained with an extended kalman filter algorithm, is used to obtain a model of the system, then, a control law is design using such model with the inverse optimal control approach. The RHONN identifier is developed without knowledge of the plant model or its parameters, on the other hand, the inverse optimal control is designed for tracking velocity references. Applicability of the proposed scheme is illustrated using simulations results as well as real-time experimental results with an all-terrain tracked robot.
An optimized one-tube, semi-nested PCR assay for Paracoccidioides brasiliensis detection
Directory of Open Access Journals (Sweden)
Amanda de Faveri Pitz
2013-12-01
Full Text Available Introduction Herein, we report a one-tube, semi-nested-polymerase chain reaction (OTsn-PCR assay for the detection of Paracoccidioides brasiliensis. Methods We developed the OTsn-PCR assay for the detection of P. brasiliensis in clinical specimens and compared it with other PCR methods. Results The OTsn-PCR assay was positive for all clinical samples, and the detection limit was better or equivalent to the other nested or semi-nested PCR methods for P. brasiliensis detection. Conclusions The OTsn-PCR assay described in this paper has a detection limit similar to other reactions for the molecular detection of P. brasiliensis, but this approach is faster and less prone to contamination than other conventional nested or semi-nested PCR assays.
Optimization of microgrids based on controller designing for ...
African Journals Online (AJOL)
The power quality of microgrid during islanded operation is strongly related with the controller performance of DGs. Therefore a new optimal control strategy for distributed generation based inverter to connect to the generalized microgrid is proposed. This work shows developing optimal control algorithms for the DG ...
Martis, Ruth; Brown, Julie; McAra-Couper, Judith; Crowther, Caroline A
2018-04-11
Glycaemic target recommendations vary widely between international professional organisations for women with gestational diabetes mellitus (GDM). Some studies have reported women's experiences of having GDM, but little is known how this relates to their glycaemic targets. The aim of this study was to identify enablers and barriers for women with GDM to achieve optimal glycaemic control. Women with GDM were recruited from two large, geographically different, hospitals in New Zealand to participate in a semi-structured interview to explore their views and experiences focusing on enablers and barriers to achieving optimal glycaemic control. Final thematic analysis was performed using the Theoretical Domains Framework. Sixty women participated in the study. Women reported a shift from their initial negative response to accepting their diagnosis but disliked the constant focus on numbers. Enablers and barriers were categorised into ten domains across the three study questions. Enablers included: the ability to attend group teaching sessions with family and hear from women who have had GDM; easy access to a diabetes dietitian with diet recommendations tailored to a woman's context including ethnic food and financial considerations; free capillary blood glucose (CBG) monitoring equipment, health shuttles to take women to appointments; child care when attending clinic appointments; and being taught CBG testing by a community pharmacist. Barriers included: lack of health information, teaching sessions, consultations, and food diaries in a woman's first language; long waiting times at clinic appointments; seeing a different health professional every clinic visit; inconsistent advice; no tailored physical activities assessments; not knowing where to access appropriate information on the internet; unsupportive partners, families, and workplaces; and unavailability of social media or support groups for women with GDM. Perceived judgement by others led some women only to share
Active learning for semi-supervised clustering based on locally linear propagation reconstruction.
Chang, Chin-Chun; Lin, Po-Yi
2015-03-01
The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.
Advanced Process Control Application and Optimization in Industrial Facilities
Directory of Open Access Journals (Sweden)
Howes S.
2015-01-01
Full Text Available This paper describes application of the new method and tool for system identification and PID tuning/advanced process control (APC optimization using the new 3G (geometric, gradient, gravity optimization method. It helps to design and implement control schemes directly inside the distributed control system (DCS or programmable logic controller (PLC. Also, the algorithm helps to identify process dynamics in closed-loop mode, optimizes controller parameters, and helps to develop adaptive control and model-based control (MBC. Application of the new 3G algorithm for designing and implementing APC schemes is presented. Optimization of primary and advanced control schemes stabilizes the process and allows the plant to run closer to process, equipment and economic constraints. This increases production rates, minimizes operating costs and improves product quality.
Optimization and control of a continuous polymerization reactor
Directory of Open Access Journals (Sweden)
L. A. Alvarez
2012-12-01
Full Text Available This work studies the optimization and control of a styrene polymerization reactor. The proposed strategy deals with the case where, because of market conditions and equipment deterioration, the optimal operating point of the continuous reactor is modified significantly along the operation time and the control system has to search for this optimum point, besides keeping the reactor system stable at any possible point. The approach considered here consists of three layers: the Real Time Optimization (RTO, the Model Predictive Control (MPC and a Target Calculation (TC that coordinates the communication between the two other layers and guarantees the stability of the whole structure. The proposed algorithm is simulated with the phenomenological model of a styrene polymerization reactor, which has been widely used as a benchmark for process control. The complete optimization structure for the styrene process including disturbances rejection is developed. The simulation results show the robustness of the proposed strategy and the capability to deal with disturbances while the economic objective is optimized.
Semi-quantitative Data on Ethanol Consumption in 354 ET Cases and 370 Controls
Louis, Elan D.; Michalec, Monika
2014-01-01
The notion that there is an association between essential tremor (ET) and higher ethanol consumption has crept into the literature; however, the data are limited and conflicted. 354 ET cases and 370 matched controls were enrolled in a clinical-epidemiological study. Average current daily ethanol consumption was estimated using the Willett Semi-quantitative Food Frequency Questionnaire. The proportion of cases and controls who drank any ethanol was similar: 66.7% vs. 64.1%, p = 0.46, as was th...
Kumar, Girish; Jain, Vipul; Gandhi, O. P.
2018-03-01
Maintenance helps to extend equipment life by improving its condition and avoiding catastrophic failures. Appropriate model or mechanism is, thus, needed to quantify system availability vis-a-vis a given maintenance strategy, which will assist in decision-making for optimal utilization of maintenance resources. This paper deals with semi-Markov process (SMP) modeling for steady state availability analysis of mechanical systems that follow condition-based maintenance (CBM) and evaluation of optimal condition monitoring interval. The developed SMP model is solved using two-stage analytical approach for steady-state availability analysis of the system. Also, CBM interval is decided for maximizing system availability using Genetic Algorithm approach. The main contribution of the paper is in the form of a predictive tool for system availability that will help in deciding the optimum CBM policy. The proposed methodology is demonstrated for a centrifugal pump.
Force control of a tri-layer conducting polymer actuator using optimized fuzzy logic control
International Nuclear Information System (INIS)
Itik, Mehmet; Sabetghadam, Mohammadreza; Alici, Gursel
2014-01-01
Conducting polymers actuators (CPAs) are potential candidates for replacing conventional actuators in various fields, such as robotics and biomedical engineering, due to their advantageous properties, which includes their low cost, light weight, low actuation voltage and biocompatibility. As these actuators are very suitable for use in micro-nano manipulation and in injection devices in which the magnitude of the force applied to the target is of crucial importance, the force generated by CPAs needs to be accurately controlled. In this paper, a fuzzy logic (FL) controller with a Mamdani inference system is designed to control the blocking force of a trilayer CPA with polypyrrole electrodes, which operates in air. The particle swarm optimization (PSO) method is employed to optimize the controller’s membership function parameters and therefore enhance the performance of the FL controller. An adaptive neuro-fuzzy inference system model, which can capture the nonlinear dynamics of the actuator, is utilized in the optimization process. The optimized Mamdani FL controller is then implemented on the CPA experimentally, and its performance is compared with a non-optimized fuzzy controller as well as with those obtained from a conventional PID controller. The results presented indicate that the blocking force at the tip of the CPA can be effectively controlled by the optimized FL controller, which shows excellent transient and steady state characteristics but increases the control voltage compared to the non-optimized fuzzy controllers. (paper)
Stochastic optimal control of non-stationary response of a single-degree-of-freedom vehicle model
Narayanan, S.; Raju, G. V.
1990-09-01
An active suspension system to control the non-stationary response of a single-degree-of-freedom (sdf) vehicle model with variable velocity traverse over a rough road is investigated. The suspension is optimized with respect to ride comfort and road holding, using stochastic optimal control theory. The ground excitation is modelled as a spatial homogeneous random process, being the output of a linear shaping filter to white noise. The effect of the rolling contact of the tyre is considered by an additional filter in cascade. The non-stationary response with active suspension is compared with that of a passive system.
Development of a simulation model of semi-active suspension for monorail
Hasnan, K.; Didane, D. H.; Kamarudin, M. A.; Bakhsh, Qadir; Abdulmalik, R. E.
2016-11-01
The new Kuala Lumpur Monorail Fleet Expansion Project (KLMFEP) uses semiactive technology in its suspension system. It is recognized that the suspension system influences the ride quality. Thus, among the way to further improve the ride quality is by fine- tuning the semi-active suspension system on the new KL Monorail. The semi-active suspension for the monorail specifically in terms of improving ride quality could be exploited further. Hence a simulation model which will act as a platform to test the design of a complete suspension system particularly to investigate the ride comfort performance is required. MSC Adams software was considered as the tool to develop the simulation platform, where all parameters and data are represented by mathematical equations; whereas the new KL Monorail being the reference model. In the simulation, the model went through step disturbance on the guideway for stability and ride comfort analysis. The model has shown positive results where the monorail is in stable condition as an outcome from stability analysis. The model also scores a Rating 1 classification in ISO 2631 Ride Comfort performance which is very comfortable as an overall outcome from ride comfort analysis. The model is also adjustable, flexibile and understandable by the engineers within the field for the purpose of further development.
Safranski, David L; Weiss, Daiana; Clark, J Brian; Taylor, W Robert; Gall, Ken
2014-08-01
Biodegradable polymers are clinically used in numerous biomedical applications, and classically show a loss of mechanical properties within weeks of implantation. This work demonstrates a new class of semi-degradable polymers that show an increase in mechanical properties through degradation via a controlled shift in a thermal transition. Semi-degradable polymer networks, poly(β-amino ester)-co-methyl methacrylate, were formed from a low glass transition temperature crosslinker, poly(β-amino ester), and high glass transition temperature monomer, methyl methacrylate, which degraded in a manner dependent upon the crosslinker chemical structure. In vitro and in vivo degradation revealed changes in mechanical behavior due to the degradation of the crosslinker from the polymer network. This novel polymer system demonstrates a strategy to temporally control the mechanical behavior of polymers and to enhance the initial performance of smart biomedical devices. Copyright © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Semi-flocking algorithm for motion control of mobile sensors in large-scale surveillance systems.
Semnani, Samaneh Hosseini; Basir, Otman A
2015-01-01
The ability of sensors to self-organize is an important asset in surveillance sensor networks. Self-organize implies self-control at the sensor level and coordination at the network level. Biologically inspired approaches have recently gained significant attention as a tool to address the issue of sensor control and coordination in sensor networks. These approaches are exemplified by the two well-known algorithms, namely, the Flocking algorithm and the Anti-Flocking algorithm. Generally speaking, although these two biologically inspired algorithms have demonstrated promising performance, they expose deficiencies when it comes to their ability to maintain simultaneous robust dynamic area coverage and target coverage. These two coverage performance objectives are inherently conflicting. This paper presents Semi-Flocking, a biologically inspired algorithm that benefits from key characteristics of both the Flocking and Anti-Flocking algorithms. The Semi-Flocking algorithm approaches the problem by assigning a small flock of sensors to each target, while at the same time leaving some sensors free to explore the environment. This allows the algorithm to strike balance between robust area coverage and target coverage. Such balance is facilitated via flock-sensor coordination. The performance of the proposed Semi-Flocking algorithm is examined and compared with other two flocking-based algorithms once using randomly moving targets and once using a standard walking pedestrian dataset. The results of both experiments show that the Semi-Flocking algorithm outperforms both the Flocking algorithm and the Anti-Flocking algorithm with respect to the area of coverage and the target coverage objectives. Furthermore, the results show that the proposed algorithm demonstrates shorter target detection time and fewer undetected targets than the other two flocking-based algorithms.
Multiobjective optimization of low impact development stormwater controls
Eckart, Kyle; McPhee, Zach; Bolisetti, Tirupati
2018-07-01
Green infrastructure such as Low Impact Development (LID) controls are being employed to manage the urban stormwater and restore the predevelopment hydrological conditions besides improving the stormwater runoff water quality. Since runoff generation and infiltration processes are nonlinear, there is a need for identifying optimal combination of LID controls. A coupled optimization-simulation model was developed by linking the U.S. EPA Stormwater Management Model (SWMM) to the Borg Multiobjective Evolutionary Algorithm (Borg MOEA). The coupled model is capable of performing multiobjective optimization which uses SWMM simulations as a tool to evaluate potential solutions to the optimization problem. The optimization-simulation tool was used to evaluate low impact development (LID) stormwater controls. A SWMM model was developed, calibrated, and validated for a sewershed in Windsor, Ontario and LID stormwater controls were tested for three different return periods. LID implementation strategies were optimized using the optimization-simulation model for five different implementation scenarios for each of the three storm events with the objectives of minimizing peak flow in the stormsewers, reducing total runoff, and minimizing cost. For the sewershed in Windsor, Ontario, the peak run off and total volume of the runoff were found to reduce by 13% and 29%, respectively.
Tuning of active vibration controllers for ACTEX by genetic algorithm
Kwak, Moon K.; Denoyer, Keith K.
1999-06-01
This paper is concerned with the optimal tuning of digitally programmable analog controllers on the ACTEX-1 smart structures flight experiment. The programmable controllers for each channel include a third order Strain Rate Feedback (SRF) controller, a fifth order SRF controller, a second order Positive Position Feedback (PPF) controller, and a fourth order PPF controller. Optimal manual tuning of several control parameters can be a difficult task even though the closed-loop control characteristics of each controller are well known. Hence, the automatic tuning of individual control parameters using Genetic Algorithms is proposed in this paper. The optimal control parameters of each control law are obtained by imposing a constraint on the closed-loop frequency response functions using the ACTEX mathematical model. The tuned control parameters are then uploaded to the ACTEX electronic control electronics and experiments on the active vibration control are carried out in space. The experimental results on ACTEX will be presented.
Optimizing Active Cyber Defense
Lu, Wenlian; Xu, Shouhuai; Yi, Xinlei
2016-01-01
Active cyber defense is one important defensive method for combating cyber attacks. Unlike traditional defensive methods such as firewall-based filtering and anti-malware tools, active cyber defense is based on spreading "white" or "benign" worms to combat against the attackers' malwares (i.e., malicious worms) that also spread over the network. In this paper, we initiate the study of {\\em optimal} active cyber defense in the setting of strategic attackers and/or strategic defenders. Specific...
Optimal Semi-Adaptive Search With False Targets
2017-12-01
Kress, K. Y. Lin, and R. Szechtman, “Optimal discrete search with imperfect specificity,” Math Meth Oper Res, vol. 68, pp. 539–549, 2008. [16] L. D...constraints on employment of physical search assets will involve discrete approximations to the continuous solutions given by these techniques. These...model assumes. We optimize in the continuous case, to be able then to make the best possible discrete approximations if needed, given the constraints of a
Active Complementary Control for Affine Nonlinear Control Systems With Actuator Faults.
Fan, Quan-Yong; Yang, Guang-Hong
2017-11-01
This paper is concerned with the problem of active complementary control design for affine nonlinear control systems with actuator faults. The outage and loss of effectiveness fault cases are considered. In order to achieve the performance enhancement of the faulty control system, the complementary control scheme is designed in two steps. Firstly, a novel fault estimation scheme is developed. Then, by using the fault estimations to reconstruct the faulty system dynamics and introducing a cost function as the optimization objective, a nearly optimal complementary control is obtained online based on the adaptive dynamic programming (ADP) method. Unlike most of the previous ADP methods with the addition of a probing signal, new adaptive weight update laws are derived to guarantee the convergence of neural network weights and the stability of the closed-loop system, which strongly supports the online implementation of the ADP method. Finally, two simulation examples are given to illustrate the performance and effectiveness of the proposed method.
Directory of Open Access Journals (Sweden)
Francisco Palacios-Quiñonero
2014-01-01
Full Text Available We present a new design strategy that makes it possible to synthesize decentralized output-feedback controllers by solving two successive optimization problems with linear matrix inequality (LMI constraints. In the initial LMI optimization problem, two auxiliary elements are computed: a standard state-feedback controller, which can be taken as a reference in the performance assessment, and a matrix that facilitates a proper definition of the main LMI optimization problem. Next, by solving the second optimization problem, the output-feedback controller is obtained. The proposed strategy extends recent results in static output-feedback control and can be applied to design complex passive-damping systems for vibrational control of large structures. More precisely, by taking advantages of the existing link between fully decentralized velocity-feedback controllers and passive linear dampers, advanced active feedback control strategies can be used to design complex passive-damping systems, which combine the simplicity and robustness of passive control systems with the efficiency of active feedback control. To demonstrate the effectiveness of the proposed approach, a passive-damping system for the seismic protection of a five-story building is designed with excellent results.
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
Optimal control of switched systems arising in fermentation processes
Liu, Chongyang
2014-01-01
The book presents, in a systematic manner, the optimal controls under different mathematical models in fermentation processes. Variant mathematical models – i.e., those for multistage systems; switched autonomous systems; time-dependent and state-dependent switched systems; multistage time-delay systems and switched time-delay systems – for fed-batch fermentation processes are proposed and the theories and algorithms of their optimal control problems are studied and discussed. By putting forward novel methods and innovative tools, the book provides a state-of-the-art and comprehensive systematic treatment of optimal control problems arising in fermentation processes. It not only develops nonlinear dynamical system, optimal control theory and optimization algorithms, but can also help to increase productivity and provide valuable reference material on commercial fermentation processes.
Euler's fluid equations: Optimal control vs optimization
Energy Technology Data Exchange (ETDEWEB)
Holm, Darryl D., E-mail: d.holm@ic.ac.u [Department of Mathematics, Imperial College London, SW7 2AZ (United Kingdom)
2009-11-23
An optimization method used in image-processing (metamorphosis) is found to imply Euler's equations for incompressible flow of an inviscid fluid, without requiring that the Lagrangian particle labels exactly follow the flow lines of the Eulerian velocity vector field. Thus, an optimal control problem and an optimization problem for incompressible ideal fluid flow both yield the same Euler fluid equations, although their Lagrangian parcel dynamics are different. This is a result of the gauge freedom in the definition of the fluid pressure for an incompressible flow, in combination with the symmetry of fluid dynamics under relabeling of their Lagrangian coordinates. Similar ideas are also illustrated for SO(N) rigid body motion.
Robust output LQ optimal control via integral sliding modes
Fridman, Leonid; Bejarano, Francisco Javier
2014-01-01
Featuring original research from well-known experts in the field of sliding mode control, this monograph presents new design schemes for implementing LQ control solutions in situations where the output system is the only information provided about the state of the plant. This new design works under the restrictions of matched disturbances without losing its desirable features. On the cutting-edge of optimal control research, Robust Output LQ Optimal Control via Integral Sliding Modes is an excellent resource for both graduate students and professionals involved in linear systems, optimal control, observation of systems with unknown inputs, and automatization. In the theory of optimal control, the linear quadratic (LQ) optimal problem plays an important role due to its physical meaning, and its solution is easily given by an algebraic Riccati equation. This solution turns out to be restrictive, however, because of two assumptions: the system must be free from disturbances and the entire state vector must be kn...
Optimizing pipeline transportation using a fuzzy controller
Energy Technology Data Exchange (ETDEWEB)
Aramaki, Thiago L.; Correa, Joao L. L.; Montalvoa, Antonio F. F. [National Control and Operation Center Tranpetro, Rio de Janeiro, (Brazil)
2010-07-01
The optimization of pipeline transportation is a big concern for the transporter companies. This paper is the third of a series of three articles which investigated the application of a system to simulate the human ability to operate a pipeline in an optimized way. The present paper presents the development of a proportional integral (PI) fuzzy controller, in order to optimize pipeline transportation capacity. The fuzzy adaptive PI controller system was developed and tested with a hydraulic simulator. On-field data were used from the OSBRA pipeline. The preliminary tests showed that the performance of the software simulation was satisfactory. It varied the set-point of the conventional controller within the limits of flow meters. The transport capacity of the pipe was maximize without compromising the integrity of the commodities transported. The system developed proved that it can be easily deployed as a specialist optimizing system to be added to SCADA systems.
Semi-automated high-efficiency reflectivity chamber for vacuum UV measurements
Wiley, James; Fleming, Brian; Renninger, Nicholas; Egan, Arika
2017-08-01
This paper presents the design and theory of operation for a semi-automated reflectivity chamber for ultraviolet optimized optics. A graphical user interface designed in LabVIEW controls the stages, interfaces with the detector system, takes semi-autonomous measurements, and monitors the system in case of error. Samples and an optical photodiode sit on an optics plate mounted to a rotation stage in the middle of the vacuum chamber. The optics plate rotates the samples and diode between an incident and reflected position to measure the absolute reflectivity of the samples at wavelengths limited by the monochromator operational bandpass of 70 nm to 550 nm. A collimating parabolic mirror on a fine steering tip-tilt motor enables beam steering for detector peak-ups. This chamber is designed to take measurements rapidly and with minimal oversight, increasing lab efficiency for high cadence and high accuracy vacuum UV reflectivity measurements.
Optimal control of stochastic difference Volterra equations an introduction
Shaikhet, Leonid
2015-01-01
This book showcases a subclass of hereditary systems, that is, systems with behaviour depending not only on their current state but also on their past history; it is an introduction to the mathematical theory of optimal control for stochastic difference Volterra equations of neutral type. As such, it will be of much interest to researchers interested in modelling processes in physics, mechanics, automatic regulation, economics and finance, biology, sociology and medicine for all of which such equations are very popular tools. The text deals with problems of optimal control such as meeting given performance criteria, and stabilization, extending them to neutral stochastic difference Volterra equations. In particular, it contrasts the difference analogues of solutions to optimal control and optimal estimation problems for stochastic integral Volterra equations with optimal solutions for corresponding problems in stochastic difference Volterra equations. Optimal Control of Stochastic Difference Volterra Equation...
Optimization control of LNG regasification plant using Model Predictive Control
Wahid, A.; Adicandra, F. F.
2018-03-01
Optimization of liquified natural gas (LNG) regasification plant is important to minimize costs, especially operational costs. Therefore, it is important to choose optimum LNG regasification plant design and maintaining the optimum operating conditions through the implementation of model predictive control (MPC). Optimal tuning parameter for MPC such as P (prediction horizon), M (control of the horizon) and T (sampling time) are achieved by using fine-tuning method. The optimal criterion for design is the minimum amount of energy used and for control is integral of square error (ISE). As a result, the optimum design is scheme 2 which is developed by Devold with an energy savings of 40%. To maintain the optimum conditions, required MPC with P, M and T as follows: tank storage pressure: 90, 2, 1; product pressure: 95, 2, 1; temperature vaporizer: 65, 2, 2; and temperature heater: 35, 6, 5, with ISE value at set point tracking respectively 0.99, 1792.78, 34.89 and 7.54, or improvement of control performance respectively 4.6%, 63.5%, 3.1% and 58.2% compared to PI controller performance. The energy savings that MPC controllers can make when there is a disturbance in temperature rise 1°C of sea water is 0.02 MW.
Distributed Model Predictive Control for Active Power Control of Wind Farm
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard
2014-01-01
This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....
Optimal Control and Forecasting of Complex Dynamical Systems
Grigorenko, Ilya
2006-01-01
This important book reviews applications of optimization and optimal control theory to modern problems in physics, nano-science and finance. The theory presented here can be efficiently applied to various problems, such as the determination of the optimal shape of a laser pulse to induce certain excitations in quantum systems, the optimal design of nanostructured materials and devices, or the control of chaotic systems and minimization of the forecast error for a given forecasting model (for example, artificial neural networks). Starting from a brief review of the history of variational calcul
Discrete-time optimal control and games on large intervals
Zaslavski, Alexander J
2017-01-01
Devoted to the structure of approximate solutions of discrete-time optimal control problems and approximate solutions of dynamic discrete-time two-player zero-sum games, this book presents results on properties of approximate solutions in an interval that is independent lengthwise, for all sufficiently large intervals. Results concerning the so-called turnpike property of optimal control problems and zero-sum games in the regions close to the endpoints of the time intervals are the main focus of this book. The description of the structure of approximate solutions on sufficiently large intervals and its stability will interest graduate students and mathematicians in optimal control and game theory, engineering, and economics. This book begins with a brief overview and moves on to analyze the structure of approximate solutions of autonomous nonconcave discrete-time optimal control Lagrange problems.Next the structures of approximate solutions of autonomous discrete-time optimal control problems that are discret...
Robust and optimal control a two-port framework approach
Tsai, Mi-Ching
2014-01-01
A Two-port Framework for Robust and Optimal Control introduces an alternative approach to robust and optimal controller synthesis procedures for linear, time-invariant systems, based on the two-port system widespread in electrical engineering. The novel use of the two-port system in this context allows straightforward engineering-oriented solution-finding procedures to be developed, requiring no mathematics beyond linear algebra. A chain-scattering description provides a unified framework for constructing the stabilizing controller set and for synthesizing H2 optimal and H∞ sub-optimal controllers. Simple yet illustrative examples explain each step. A Two-port Framework for Robust and Optimal Control features: · a hands-on, tutorial-style presentation giving the reader the opportunity to repeat the designs presented and easily to modify them for their own programs; · an abundance of examples illustrating the most important steps in robust and optimal design; and · �...
Safety Impacts of the Actuated Signal Control at Urban Intersections
Directory of Open Access Journals (Sweden)
Sang Hyuk Lee
2016-02-01
Full Text Available To reduce travel time, the actuated signal controls have been implemented at urban intersections. However, the safety impacts of actuated signal controls thus far have rarely been examined. In this assessment of the safety impact of urban intersections with semi-actuated signal controls, the safety performance functions and EB approaches were applied. The semi-actuated signal controls have increased injuries and total crashes in all crash types by around 5.9% and 3.8%, respectively. Regarding the most common crash types, such as angle, sideswipe & rear-end, and head-on crashes, semi-actuated signal controls have been seen to decrease injuries by 7.7%. Total crashes have been reduced by over 9.2% through the use of semi-actuated signal controls. This may be result of optimal signal timings considering traffic conditions during peak time periods. In conclusion, safety impact factors which have been established in this study can be used to improve safety and minimize travel times using semi-actuated signal controls.
Self-optimizing Pitch Control for Large Scale Wind Turbine Based on ADRC
Xia, Anjun; Hu, Guoqing; Li, Zheng; Huang, Dongxiao; Wang, Fengxiang
2018-01-01
Since wind turbine is a complex nonlinear and strong coupling system, traditional PI control method can hardly achieve good control performance. A self-optimizing pitch control method based on the active-disturbance-rejection control theory is proposed in this paper. A linear model of the wind turbine is derived by linearizing the aerodynamic torque equation and the dynamic response of wind turbine is transformed into a first-order linear system. An expert system is designed to optimize the amplification coefficient according to the pitch rate and the speed deviation. The purpose of the proposed control method is to regulate the amplification coefficient automatically and keep the variations of pitch rate and rotor speed in proper ranges. Simulation results show that the proposed pitch control method has the ability to modify the amplification coefficient effectively, when it is not suitable, and keep the variations of pitch rate and rotor speed in proper ranges
Simulation and optimal control of wind-farm boundary layers
Meyers, Johan; Goit, Jay
2014-05-01
In large wind farms, the effect of turbine wakes, and their interaction leads to a reduction in farm efficiency, with power generated by turbines in a farm being lower than that of a lone-standing turbine by up to 50%. In very large wind farms or `deep arrays', this efficiency loss is related to interaction of the wind farms with the planetary boundary layer, leading to lower wind speeds at turbine level. Moreover, for these cases it has been demonstrated both in simulations and wind-tunnel experiments that the wind-farm energy extraction is dominated by the vertical turbulent transport of kinetic energy from higher regions in the boundary layer towards the turbine level. In the current study, we investigate the use of optimal control techniques combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large `infinite' wind farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with actuator-disk and actuator-line representations of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind that combines Fourier-spectral discretization in horizontal directions with a fourth-order finite-volume approach in the vertical direction. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in an actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. Optimal model-predictive control (or optimal receding horizon control) is used, where the model simply consists of the full LES equations, and the time horizon is approximately 280 seconds. The optimization is performed using a
Keulen, van T.A.C.; Gillot, J.; Jager, de A.G.; Steinbuch, M.
2014-01-01
This paper presents a numerical solution for scalar state constrained optimal control problems. The algorithm rewrites the constrained optimal control problem as a sequence of unconstrained optimal control problems which can be solved recursively as a two point boundary value problem. The solution
Skinner-Rusk unified formalism for optimal control systems and applications
International Nuclear Information System (INIS)
Barbero-Linan, MarIa; EcheverrIa-EnrIquez, Arturo; Diego, David MartIn de; Munoz-Lecanda, Miguel C; Roman-Roy, Narciso
2007-01-01
A geometric approach to time-dependent optimal control problems is proposed. This formulation is based on the Skinner and Rusk formalism for Lagrangian and Hamiltonian systems. The corresponding unified formalism developed for optimal control systems allows us to formulate geometrically the necessary conditions given by a weak form of Pontryagin's maximum principle, provided that the differentiability with respect to controls is assumed and the space of controls is open. Furthermore, our method is also valid for implicit optimal control systems and, in particular, for the so-called descriptor systems (optimal control problems including both differential and algebraic equations)
Directory of Open Access Journals (Sweden)
Saifullah Khalid
2016-09-01
Full Text Available Three conventional control constant instantaneous power control, sinusoidal current control, and synchronous reference frame techniques for extracting reference currents for shunt active power filters have been optimized using Fuzzy Logic control and Adaptive Tabu search Algorithm and their performances have been compared. Critical analysis of Comparison of the compensation ability of different control strategies based on THD and speed will be done, and suggestions will be given for the selection of technique to be used. The simulated results using MATLAB model are presented, and they will clearly prove the value of the proposed control method of aircraft shunt APF. The waveforms observed after the application of filter will be having the harmonics within the limits and the power quality will be improved.
Discrete-time inverse optimal control for nonlinear systems
Sanchez, Edgar N
2013-01-01
Discrete-Time Inverse Optimal Control for Nonlinear Systems proposes a novel inverse optimal control scheme for stabilization and trajectory tracking of discrete-time nonlinear systems. This avoids the need to solve the associated Hamilton-Jacobi-Bellman equation and minimizes a cost functional, resulting in a more efficient controller. Design More Efficient Controllers for Stabilization and Trajectory Tracking of Discrete-Time Nonlinear Systems The book presents two approaches for controller synthesis: the first based on passivity theory and the second on a control Lyapunov function (CLF). Th
Basso Moro, Sara; Carrieri, Marika; Avola, Danilo; Brigadoi, Sabrina; Lancia, Stefania; Petracca, Andrea; Spezialetti, Matteo; Ferrari, Marco; Placidi, Giuseppe; Quaresima, Valentina
2016-06-01
Objective. In the last few years, the interest in applying virtual reality systems for neurorehabilitation is increasing. Their compatibility with neuroimaging techniques, such as functional near-infrared spectroscopy (fNIRS), allows for the investigation of brain reorganization with multimodal stimulation and real-time control of the changes occurring in brain activity. The present study was aimed at testing a novel semi-immersive visuo-motor task (VMT), which has the features of being adopted in the field of neurorehabilitation of the upper limb motor function. Approach. A virtual environment was simulated through a three-dimensional hand-sensing device (the LEAP Motion Controller), and the concomitant VMT-related prefrontal cortex (PFC) response was monitored non-invasively by fNIRS. Upon the VMT, performed at three different levels of difficulty, it was hypothesized that the PFC would be activated with an expected greater level of activation in the ventrolateral PFC (VLPFC), given its involvement in the motor action planning and in the allocation of the attentional resources to generate goals from current contexts. Twenty-one subjects were asked to move their right hand/forearm with the purpose of guiding a virtual sphere over a virtual path. A twenty-channel fNIRS system was employed for measuring changes in PFC oxygenated-deoxygenated hemoglobin (O2Hb/HHb, respectively). Main results. A VLPFC O2Hb increase and a concomitant HHb decrease were observed during the VMT performance, without any difference in relation to the task difficulty. Significance. The present study has revealed a particular involvement of the VLPFC in the execution of the novel proposed semi-immersive VMT adoptable in the neurorehabilitation field.
International Nuclear Information System (INIS)
Rascovsky, Simon; Delgado, Jorge Andres; Sanz, Alexander
2008-01-01
To verify the reproducibility of word generation, text comprehension, antonyms generation and motor/somatosensory RMF protocols in a test-retest evaluation through a semiautomatic stereotaxical localization method for activation comparison. Methods: Word generation, text comprehension, antonyms generation and motor/somatosensory FMRI paradigms were applied on 8 healthy subjects on two separate sessions, performing the evaluation of inter-session activations through conjunction and cluster analysis. Results: Activations according to Brodmann areas were reproducible in 50%, 62.5% and 75% for word generation, text comprehension and antonyms generation respectively. For the motor paradigms, right motor conjoined activations were found in 86% of subjects and in 100% of subjects for left conjoined activations. Conclusions: The semi-automatic method of determining inter-session areas of common activation allows its use for functional cytoarchitectonic localization of fMRI activations with minimal intervention, and can be used as a quality control measure of the different paradigms used in RMF, minimizing observer bias.
Centralized Stochastic Optimal Control of Complex Systems
Energy Technology Data Exchange (ETDEWEB)
Malikopoulos, Andreas [ORNL
2015-01-01
In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain using the long-run expected average cost per unit time criterion, and we show that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.
Stochastic optimal control of single neuron spike trains
DEFF Research Database (Denmark)
Iolov, Alexandre; Ditlevsen, Susanne; Longtin, Andrë
2014-01-01
stimulation of a neuron to achieve a target spike train under the physiological constraint to not damage tissue. Approach. We pose a stochastic optimal control problem to precisely specify the spike times in a leaky integrate-and-fire (LIF) model of a neuron with noise assumed to be of intrinsic or synaptic...... origin. In particular, we allow for the noise to be of arbitrary intensity. The optimal control problem is solved using dynamic programming when the controller has access to the voltage (closed-loop control), and using a maximum principle for the transition density when the controller only has access...... to the spike times (open-loop control). Main results. We have developed a stochastic optimal control algorithm to obtain precise spike times. It is applicable in both the supra-threshold and sub-threshold regimes, under open-loop and closed-loop conditions and with an arbitrary noise intensity; the accuracy...
Control and Optimization Methods for Electric Smart Grids
Ilić, Marija
2012-01-01
Control and Optimization Methods for Electric Smart Grids brings together leading experts in power, control and communication systems,and consolidates some of the most promising recent research in smart grid modeling,control and optimization in hopes of laying the foundation for future advances in this critical field of study. The contents comprise eighteen essays addressing wide varieties of control-theoretic problems for tomorrow’s power grid. Topics covered include: Control architectures for power system networks with large-scale penetration of renewable energy and plug-in vehicles Optimal demand response New modeling methods for electricity markets Control strategies for data centers Cyber-security Wide-area monitoring and control using synchronized phasor measurements. The authors present theoretical results supported by illustrative examples and practical case studies, making the material comprehensible to a wide audience. The results reflect the exponential transformation that today’s grid is going...
Parametric optimal control of uncertain systems under an optimistic value criterion
Li, Bo; Zhu, Yuanguo
2018-01-01
It is well known that the optimal control of a linear quadratic model is characterized by the solution of a Riccati differential equation. In many cases, the corresponding Riccati differential equation cannot be solved exactly such that the optimal feedback control may be a complex time-oriented function. In this article, a parametric optimal control problem of an uncertain linear quadratic model under an optimistic value criterion is considered for simplifying the expression of optimal control. Based on the equation of optimality for the uncertain optimal control problem, an approximation method is presented to solve it. As an application, a two-spool turbofan engine optimal control problem is given to show the utility of the proposed model and the efficiency of the presented approximation method.
Optimal Trajectory Tracking Control for a Wheeled Mobile Robot Using Fractional Order PID Controller
Directory of Open Access Journals (Sweden)
Ameer L. Saleh
2018-02-01
Full Text Available This paper present an optimal Fractional Order PID (FOPID controller based on Particle Swarm Optimization (PSO for controlling the trajectory tracking of Wheeled Mobile Robot(WMR.The issue of trajectory tracking with given a desired reference velocity is minimized to get the distance and deviation angle equal to zero, to realize the objective of trajectory tracking a two FOPID controllers are used for velocity control and azimuth control to implement the trajectory tracking control. A path planning and path tracking methodologies are used to give different desired tracking trajectories. PSO algorithm is using to find the optimal parameters of FOPID controllers. The kinematic and dynamic models of wheeled mobile robot for desired trajectory tracking with PSO algorithm are simulated in Simulink-Matlab. Simulation results show that the optimal FOPID controllers are more effective and has better dynamic performance than the conventional methods.
Optimal control of a harmonic oscillator: Economic interpretations
Janová, Jitka; Hampel, David
2013-10-01
Optimal control is a popular technique for modelling and solving the dynamic decision problems in economics. A standard interpretation of the criteria function and Lagrange multipliers in the profit maximization problem is well known. On a particular example, we aim to a deeper understanding of the possible economic interpretations of further mathematical and solution features of the optimal control problem: we focus on the solution of the optimal control problem for harmonic oscillator serving as a model for Phillips business cycle. We discuss the economic interpretations of arising mathematical objects with respect to well known reasoning for these in other problems.
Spacecraft attitude control using neuro-fuzzy approximation of the optimal controllers
Kim, Sung-Woo; Park, Sang-Young; Park, Chandeok
2016-01-01
In this study, a neuro-fuzzy controller (NFC) was developed for spacecraft attitude control to mitigate large computational load of the state-dependent Riccati equation (SDRE) controller. The NFC was developed by training a neuro-fuzzy network to approximate the SDRE controller. The stability of the NFC was numerically verified using a Lyapunov-based method, and the performance of the controller was analyzed in terms of approximation ability, steady-state error, cost, and execution time. The simulations and test results indicate that the developed NFC efficiently approximates the SDRE controller, with asymptotic stability in a bounded region of angular velocity encompassing the operational range of rapid-attitude maneuvers. In addition, it was shown that an approximated optimal feedback controller can be designed successfully through neuro-fuzzy approximation of the optimal open-loop controller.
Assessment of semi-active friction dampers
dos Santos, Marcelo Braga; Coelho, Humberto Tronconi; Lepore Neto, Francisco Paulo; Mafhoud, Jarir
2017-09-01
The use of friction dampers has been widely proposed for a variety of mechanical systems for which applying viscoelastic materials, fluid based dampers or other viscous dampers is impossible. An important example is the application of friction dampers in aircraft engines to reduce the blades' vibration amplitudes. In most cases, friction dampers have been studied in a passive manner, but significant improvements can be achieved by controlling the normal force in the contact region. The aim of this paper is to present and study five control strategies for friction dampers based on three different hysteresis cycles by using the Harmonic Balance Method (HBM), a numerical and experimental analysis. The first control strategy uses the friction force as a resistance when the system is deviating from its equilibrium position. The second control strategy maximizes the energy removal in each harmonic oscillation cycle by calculating the optimal normal force based on the last displacement peak. The third control strategy combines the first strategy with the homogenous modulation of the friction force. Finally, the last two strategies attempt to predict the system's movement based on its velocity and acceleration and our knowledge of its physical properties. Numerical and experimental studies are performed with these five strategies, which define the performance metrics. The experimental testing rig is fully identified and its parameters are used for numerical simulations. The obtained results show the satisfactory performance of the friction damper and selected strategy and the suitable agreement between the numerical and experimental results.
A homotopy algorithm for digital optimal projection control GASD-HADOC
Collins, Emmanuel G., Jr.; Richter, Stephen; Davis, Lawrence D.
1993-01-01
The linear-quadratic-gaussian (LQG) compensator was developed to facilitate the design of control laws for multi-input, multi-output (MIMO) systems. The compensator is computed by solving two algebraic equations for which standard closed-loop solutions exist. Unfortunately, the minimal dimension of an LQG compensator is almost always equal to the dimension of the plant and can thus often violate practical implementation constraints on controller order. This deficiency is especially highlighted when considering control-design for high-order systems such as flexible space structures. This deficiency motivated the development of techniques that enable the design of optimal controllers whose dimension is less than that of the design plant. A homotopy approach based on the optimal projection equations that characterize the necessary conditions for optimal reduced-order control. Homotopy algorithms have global convergence properties and hence do not require that the initializing reduced-order controller be close to the optimal reduced-order controller to guarantee convergence. However, the homotopy algorithm previously developed for solving the optimal projection equations has sublinear convergence properties and the convergence slows at higher authority levels and may fail. A new homotopy algorithm for synthesizing optimal reduced-order controllers for discrete-time systems is described. Unlike the previous homotopy approach, the new algorithm is a gradient-based, parameter optimization formulation and was implemented in MATLAB. The results reported may offer the foundation for a reliable approach to optimal, reduced-order controller design.
Brinkman, Britney G; Khan, Aliya; Edner, Benjamin; Rosén, Lee A
2014-01-01
Recent research has suggested that vegetarians may be at an increased risk for developing disordered eating or body image issues when compared to non-vegetarians. However, the results of such studies are mixed, and no research has explored potential connections between vegetarianism and self-objectification. In the current study, the authors examine factors that predicted body surveillance, body shame, and appearance control beliefs; three aspects of self-objectification. Surveys were completed by 386 women from the United States who were categorized as vegetarian, semi-vegetarian, or non-vegetarian. The three groups differed regarding dietary motivations, levels of feminist activism, and body shame, but did not differ on their conformity to feminine norms. While conformity to feminine norms predicted body surveillance and body shame levels among all three groups of women, feminist activism predicted appearance control beliefs among non-vegetarians only. These findings suggest that it is important for researchers and clinicians to distinguish among these three groups when examining the relationship between vegetarianism and self-objectification. Copyright © 2013 Elsevier Ltd. All rights reserved.
Optimal control of a qubit in an optical cavity
International Nuclear Information System (INIS)
Deffner, Sebastian
2014-01-01
We study quantum information processing by means of optimal control theory. To this end, we analyze the damped Jaynes–Cummings model, and derive optimal control protocols that minimize the heating or energy dispersion rates, and controls that drive the system at the quantum speed limit. Special emphasis is put on analyzing the subtleties of optimal control theory for our system. In particular, it is shown how two fundamentally different approaches to the quantum speed limit can be reconciled by carefully formulating the problem. (paper)
Optimal control of quantum systems: a projection approach
International Nuclear Information System (INIS)
Cheng, C.-J.; Hwang, C.-C.; Liao, T.-L.; Chou, G.-L.
2005-01-01
This paper considers the optimal control of quantum systems. The controlled quantum systems are described by the probability-density-matrix-based Liouville-von Neumann equation. Using projection operators, the states of the quantum system are decomposed into two sub-spaces, namely the 'main state' space and the 'remaining state' space. Since the control energy is limited, a solution for optimizing the external control force is proposed in which the main state is brought to the desired main state at a certain target time, while the population of the remaining state is simultaneously suppressed in order to diminish its effects on the final population of the main state. The optimization problem is formulated by maximizing a general cost functional of states and control force. An efficient algorithm is developed to solve the optimization problem. Finally, using the hydrogen fluoride (HF) molecular population transfer problem as an illustrative example, the effectiveness of the proposed scheme for a quantum system initially in a mixed state or in a pure state is investigated through numerical simulations
Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui
2017-01-01
This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....
Directory of Open Access Journals (Sweden)
Karaba Adam
2016-01-01
Full Text Available Steam-cracking is energetically intensive large-scaled process which transforms a wide range of hydrocarbons feedstock to petrochemical products. The dependence of products yields on feedstock composition and reaction conditions has been successfully described by mathematical models which are very useful tools for the optimization of cracker operation. Remaining problem is to formulate objective function for such an optimization. Quantitative criterion based on the process economy is proposed in this paper. Previously developed and verified industrial steam-cracking semi-mechanistic model is utilized as supporting tool for economic evaluation of selected gasoline feedstock. Economic criterion is established as the difference between value of products obtained by cracking of studied feedstock under given conditions and the value of products obtained by cracking of reference feedstock under reference conditions. As an example of method utilization, optimal reaction conditions were searched for each of selected feedstock. Potential benefit of individual cracking and cracking of grouped feedstocks in the contrast to cracking under the middle of optimums is evaluated and also compared to cracking under usual conditions.
Numerical optimization of circulation control airfoils
Tai, T. C.; Kidwell, G. H., Jr.; Vanderplaats, G. N.
1981-01-01
A numerical procedure for optimizing circulation control airfoils, which consists of the coupling of an optimization scheme with a viscous potential flow analysis for blowing jet, is presented. The desired airfoil is defined by a combination of three baseline shapes (cambered ellipse, and cambered ellipse with drooped and spiralled trailing edges). The coefficients of these shapes are used as design variables in the optimization process. Under the constraints of lift augmentation and lift-to-drag ratios, the optimal airfoils are found to lie between those of cambered ellipse and the drooped trailing edge, towards the latter as the angle of attack increases. Results agree qualitatively with available experimental data.
Optimal control of operation efficiency of belt conveyor systems
International Nuclear Information System (INIS)
Zhang, Shirong; Xia, Xiaohua
2010-01-01
The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment or operation levels. Switching control and variable speed control are proposed in literature to improve energy efficiency of belt conveyors. The current implementations mostly focus on lower level control loops or an individual belt conveyor without operational considerations at the system level. In this paper, an optimal switching control and a variable speed drive (VSD) based optimal control are proposed to improve the energy efficiency of belt conveyor systems at the operational level, where time-of-use (TOU) tariff, ramp rate of belt speed and other system constraints are considered. A coal conveying system in a coal-fired power plant is taken as a case study, where great saving of energy cost is achieved by the two optimal control strategies. Moreover, considerable energy saving resulting from VSD based optimal control is also proved by the case study.
Optimal control of operation efficiency of belt conveyor systems
Energy Technology Data Exchange (ETDEWEB)
Zhang, Shirong [Department of Automation, Wuhan University, Wuhan 430072 (China); Xia, Xiaohua [Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002 (South Africa)
2010-06-15
The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment or operation levels. Switching control and variable speed control are proposed in literature to improve energy efficiency of belt conveyors. The current implementations mostly focus on lower level control loops or an individual belt conveyor without operational considerations at the system level. In this paper, an optimal switching control and a variable speed drive (VSD) based optimal control are proposed to improve the energy efficiency of belt conveyor systems at the operational level, where time-of-use (TOU) tariff, ramp rate of belt speed and other system constraints are considered. A coal conveying system in a coal-fired power plant is taken as a case study, where great saving of energy cost is achieved by the two optimal control strategies. Moreover, considerable energy saving resulting from VSD based optimal control is also proved by the case study. (author)
Optimal Control of Wind Power Generation
Directory of Open Access Journals (Sweden)
Pawel Pijarski
2018-03-01
Full Text Available Power system control is a complex task, which is strongly related to the number and kind of generating units as well as to the applied technologies, such as conventional coal fired power plants or wind and photovoltaic farms. Fast development of wind generation that is considered as unstable generation sets new strong requirements concerning remote control and data hubs cooperating with SCADA systems. Considering specific nature of the wind power generation, the authors analyze the problem of optimal control for wind power generation in farms located over a selected remote-controlled part of the Operator grid under advantageous wind conditions. This article presents an original stepwise method for tracing power flows that makes possible to eliminate current (power overloading of power grid branches. Its core idea is to consider the discussed problem as an optimization task.
Contour hedgerows and grass strips in erosion and runoff control in semi-arid Kenya
Kinama, J.M.; Stigter, C.J.; Ong, C.K.; Ng'ang'a, J.K.; Gichuki, F.N.
2007-01-01
Most early alley cropping studies in semi-arid Kenya were on fairly flat land while there is an increase in cultivated sloping land. The effectiveness of aging contour hedgerows and grass strips for erosion control on an about 15% slope of an Alfisol was compared. The five treatments were Senna
Smart Novel Semi-Active Tuned Mass Damper for Fixed-Bottom and Floating Offshore Wind (Presentation)
Energy Technology Data Exchange (ETDEWEB)
Rodriguez Tsouroukdissian, Arturo [Alstom Renewable US LLC
2016-05-02
The intention of this paper is to present the results of a novel smart semi-active tuned mass damper (SA-TMD), which mitigates unwanted loads for both fixed-bottom and floating offshore wind systems. (Presentation Format).
Design of Solar Harvested Semi Active RFID Transponder with Supercapacitor Storage
Gary Valentine; Lukas Vojtech; Marek Neruda
2015-01-01
This paper presents the analysis, design and manufacture of a low cost, low maintenance and long-range prototype of RFID transponder with continuous operability. A prototype of semi-active RFID transponder is produced with a range that can be extended via a DC input to allow all of the readers signal power to be reflected via backscatter modulation. The transponder is powered via solar harvested power which is selected over other energy harvesting technologies as it provides a greater energy ...
Hybrid intelligent control concepts for optimal data fusion
Llinas, James
1994-02-01
In the post-Cold War era, Naval surface ship operations will be largely conducted in littoral waters to support regional military missions of all types, including humanitarian and evacuation activities, and amphibious mission execution. Under these conditions, surface ships will be much more isolated and vulnerable to a variety of threats, including maneuvering antiship missiles. To deal with these threats, the optimal employment of multiple shipborne sensors for maximum vigilance is paramount. This paper characterizes the sensor management problem as one of intelligent control, identifies some of the key issues in controller design, and presents one approach to controller design which is soon to be implemented and evaluated. It is argued that the complexity and hierarchical nature of problem formulation demands a hybrid combination of knowledge-based methods and scheduling techniques from 'hard' real-time systems theory for its solution.
Extremum-Seeking Control and Applications A Numerical Optimization-Based Approach
Zhang, Chunlei
2012-01-01
Extremum seeking control tracks a varying maximum or minimum in a performance function such as a cost. It attempts to determine the optimal performance of a control system as it operates, thereby reducing downtime and the need for system analysis. Extremum Seeking Control and Applications is divided into two parts. In the first, the authors review existing analog optimization based extremum seeking control including gradient, perturbation and sliding mode based control designs. They then propose a novel numerical optimization based extremum seeking control based on optimization algorithms and state regulation. This control design is developed for simple linear time-invariant systems and then extended for a class of feedback linearizable nonlinear systems. The two main optimization algorithms – line search and trust region methods – are analyzed for robustness. Finite-time and asymptotic state regulators are put forward for linear and nonlinear systems respectively. Further design flexibility is achieved u...
A history of semi-active laser dome and window materials
Sullivan, Roger M.
2014-05-01
Semi-Active Laser (SAL) guidance systems were developed starting in the mid-1960's and today form an important class of precision guided weapons. The laser wavelengths generally fall in the short wave infrared region of the spectrum. Relative to passive, image based, infrared seekers the optical demands placed on the domes or windows of SAL seekers is very modest, allowing the use of low cost, easily manufactured materials, such as polycarbonate. This paper will examine the transition of SAL window and dome science and technology from the laboratory to battlefield, with special emphasis on the story of polycarbonate domes.
Exploring the complexity of quantum control optimization trajectories.
Nanduri, Arun; Shir, Ofer M; Donovan, Ashley; Ho, Tak-San; Rabitz, Herschel
2015-01-07
The control of quantum system dynamics is generally performed by seeking a suitable applied field. The physical objective as a functional of the field forms the quantum control landscape, whose topology, under certain conditions, has been shown to contain no critical point suboptimal traps, thereby enabling effective searches for fields that give the global maximum of the objective. This paper addresses the structure of the landscape as a complement to topological critical point features. Recent work showed that landscape structure is highly favorable for optimization of state-to-state transition probabilities, in that gradient-based control trajectories to the global maximum value are nearly straight paths. The landscape structure is codified in the metric R ≥ 1.0, defined as the ratio of the length of the control trajectory to the Euclidean distance between the initial and optimal controls. A value of R = 1 would indicate an exactly straight trajectory to the optimal observable value. This paper extends the state-to-state transition probability results to the quantum ensemble and unitary transformation control landscapes. Again, nearly straight trajectories predominate, and we demonstrate that R can take values approaching 1.0 with high precision. However, the interplay of optimization trajectories with critical saddle submanifolds is found to influence landscape structure. A fundamental relationship necessary for perfectly straight gradient-based control trajectories is derived, wherein the gradient on the quantum control landscape must be an eigenfunction of the Hessian. This relation is an indicator of landscape structure and may provide a means to identify physical conditions when control trajectories can achieve perfect linearity. The collective favorable landscape topology and structure provide a foundation to understand why optimal quantum control can be readily achieved.
Exploring quantum control landscapes: Topology, features, and optimization scaling
International Nuclear Information System (INIS)
Moore, Katharine W.; Rabitz, Herschel
2011-01-01
Quantum optimal control experiments and simulations have successfully manipulated the dynamics of systems ranging from atoms to biomolecules. Surprisingly, these collective works indicate that the effort (i.e., the number of algorithmic iterations) required to find an optimal control field appears to be essentially invariant to the complexity of the system. The present work explores this matter in a series of systematic optimizations of the state-to-state transition probability on model quantum systems with the number of states N ranging from 5 through 100. The optimizations occur over a landscape defined by the transition probability as a function of the control field. Previous theoretical studies on the topology of quantum control landscapes established that they should be free of suboptimal traps under reasonable physical conditions. The simulations in this work include nearly 5000 individual optimization test cases, all of which confirm this prediction by fully achieving optimal population transfer of at least 99.9% on careful attention to numerical procedures to ensure that the controls are free of constraints. Collectively, the simulation results additionally show invariance of required search effort to system dimension N. This behavior is rationalized in terms of the structural features of the underlying control landscape. The very attractive observed scaling with system complexity may be understood by considering the distance traveled on the control landscape during a search and the magnitude of the control landscape slope. Exceptions to this favorable scaling behavior can arise when the initial control field fluence is too large or when the target final state recedes from the initial state as N increases.
Optimal control methods for rapidly time-varying Hamiltonians
International Nuclear Information System (INIS)
Motzoi, F.; Merkel, S. T.; Wilhelm, F. K.; Gambetta, J. M.
2011-01-01
In this article, we develop a numerical method to find optimal control pulses that accounts for the separation of timescales between the variation of the input control fields and the applied Hamiltonian. In traditional numerical optimization methods, these timescales are treated as being the same. While this approximation has had much success, in applications where the input controls are filtered substantially or mixed with a fast carrier, the resulting optimized pulses have little relation to the applied physical fields. Our technique remains numerically efficient in that the dimension of our search space is only dependent on the variation of the input control fields, while our simulation of the quantum evolution is accurate on the timescale of the fast variation in the applied Hamiltonian.
Directory of Open Access Journals (Sweden)
Qijia Yao
2017-07-01
Full Text Available The optimal control of multibody spacecraft during the stretching process of solar arrays is investigated, and a hybrid optimization strategy based on Gauss pseudospectral method (GPM and direct shooting method (DSM is presented. First, the elastic deformation of flexible solar arrays was described approximately by the assumed mode method, and a dynamic model was established by the second Lagrangian equation. Then, the nonholonomic motion planning problem is transformed into a nonlinear programming problem by using GPM. By giving fewer LG points, initial values of the state variables and control variables were obtained. A serial optimization framework was adopted to obtain the approximate optimal solution from a feasible solution. Finally, the control variables were discretized at LG points, and the precise optimal control inputs were obtained by DSM. The optimal trajectory of the system can be obtained through numerical integration. Through numerical simulation, the stretching process of solar arrays is stable with no detours, and the control inputs match the various constraints of actual conditions. The results indicate that the method is effective with good robustness. Keywords: Motion planning, Multibody spacecraft, Optimal control, Gauss pseudospectral method, Direct shooting method
On a Highly Nonlinear Self-Obstacle Optimal Control Problem
Energy Technology Data Exchange (ETDEWEB)
Di Donato, Daniela, E-mail: daniela.didonato@unitn.it [University of Trento, Department of Mathematics (Italy); Mugnai, Dimitri, E-mail: dimitri.mugnai@unipg.it [Università di Perugia, Dipartimento di Matematica e Informatica (Italy)
2015-10-15
We consider a non-quadratic optimal control problem associated to a nonlinear elliptic variational inequality, where the obstacle is the control itself. We show that, fixed a desired profile, there exists an optimal solution which is not far from it. Detailed characterizations of the optimal solution are given, also in terms of approximating problems.
2016 Network Games, Control, and Optimization Conference
Jimenez, Tania; Solan, Eilon
2017-01-01
This contributed volume offers a collection of papers presented at the 2016 Network Games, Control, and Optimization conference (NETGCOOP), held at the University of Avignon in France, November 23-25, 2016. These papers highlight the increasing importance of network control and optimization in many networking application domains, such as mobile and fixed access networks, computer networks, social networks, transportation networks, and, more recently, electricity grids and biological networks. Covering a wide variety of both theoretical and applied topics in the areas listed above, the authors explore several conceptual and algorithmic tools that are needed for efficient and robust control operation, performance optimization, and better understanding the relationships between entities that may be acting cooperatively or selfishly in uncertain and possibly adversarial environments. As such, this volume will be of interest to applied mathematicians, computer scientists, engineers, and researchers in other relate...
Semi-solid electrodes having high rate capability
Energy Technology Data Exchange (ETDEWEB)
Chiang, Yet-Ming; Duduta, Mihai; Holman, Richard; Limthongkul, Pimpa; Tan, Taison
2017-11-28
Embodiments described herein relate generally to electrochemical cells having high rate capability, and more particularly to devices, systems and methods of producing high capacity and high rate capability batteries having relatively thick semi-solid electrodes. In some embodiments, an electrochemical cell includes an anode and a semi-solid cathode. The semi-solid cathode includes a suspension of an active material of about 35% to about 75% by volume of an active material and about 0.5% to about 8% by volume of a conductive material in a non-aqueous liquid electrolyte. An ion-permeable membrane is disposed between the anode and the semi-solid cathode. The semi-solid cathode has a thickness of about 250 .mu.m to about 2,000 .mu.m, and the electrochemical cell has an area specific capacity of at least about 7 mAh/cm.sup.2 at a C-rate of C/4. In some embodiments, the semi-solid cathode slurry has a mixing index of at least about 0.9.
Schlegel, Lisa B; Schubert-Zsilavecz, Manfred; Abdel-Tawab, Mona
2017-08-05
Near infrared (NIR) spectroscopy is increasingly gaining significance in the pharmaceutical industry for quality and in-process control. However, the potential of this method for quantitative quality control in pharmacies has long been neglected and little data is available on its application in analysis of creams and ointments. This study evaluated the applicability of NIR spectrometer with limited wavelength range (1000-1900nm) for quantitative quality control of six different dermatological semi-solid pharmaceutical preparations. Each contained a frequently used active ingredient in a common concentration either in a water-free lipid base or in an aqueous cream matrix. Based on direct NIR transflectance measurements through standardized glass beakers and partial least squares (PLS) multivariate calibration, quantitative models were generated comparing several data pre-processing methods Whereas difficulties were observed for mixtures containing 2% (w/w) metronidazole or 4% (w/w) erythromycin, content determination was possible with sufficient accuracy for salicylic acid (5 % (w/w)) and urea (10% (w/w)) in hydrophilic as well as in lipophilic formulations meeting the limit of a maximum deviation of±5% (relative) from the reference values. Exemplarily, one of the methods was successfully validated according to the EMA Guideline, determining several figures of merit such as specificity, linearity, accuracy, precision and robustness. Copyright © 2017 Elsevier B.V. All rights reserved.
Dynamic optimization the calculus of variations and optimal control in economics and management
Kamien, Morton I
2012-01-01
Since its initial publication, this text has defined courses in dynamic optimization taught to economics and management science students. The two-part treatment covers the calculus of variations and optimal control. 1998 edition.
Applications of functional analysis to optimal control problems
International Nuclear Information System (INIS)
Mizukami, K.
1976-01-01
Some basic concepts in functional analysis, a general norm, the Hoelder inequality, functionals and the Hahn-Banach theorem are described; a mathematical formulation of two optimal control problems is introduced by the method of functional analysis. The problem of time-optimal control systems with both norm constraints on control inputs and on state variables at discrete intermediate times is formulated as an L-problem in the theory of moments. The simplex method is used for solving a non-linear minimizing problem inherent in the functional analysis solution to this problem. Numerical results are presented for a train operation. The second problem is that of optimal control of discrete linear systems with quadratic cost functionals. The problem is concerned with the case of unconstrained control and fixed endpoints. This problem is formulated in terms of norms of functionals on suitable Banach spaces. (author)
Engineering to Control Noise, Loading, and Optimal Operating Points
International Nuclear Information System (INIS)
Mitchell R. Swartz
2000-01-01
Successful engineering of low-energy nuclear systems requires control of noise, loading, and optimum operating point (OOP) manifolds. The latter result from the biphasic system response of low-energy nuclear reaction (LENR)/cold fusion systems, and their ash production rate, to input electrical power. Knowledge of the optimal operating point manifold can improve the reproducibility and efficacy of these systems in several ways. Improved control of noise, loading, and peak production rates is available through the study, and use, of OOP manifolds. Engineering of systems toward the OOP-manifold drive-point peak may, with inclusion of geometric factors, permit more accurate uniform determinations of the calibrated activity of these materials/systems
Infinite-horizon optimal control problems in economics
International Nuclear Information System (INIS)
Aseev, Sergei M; Besov, Konstantin O; Kryazhimskii, Arkadii V
2012-01-01
This paper extends optimal control theory to a class of infinite-horizon problems that arise in studying models of optimal dynamic allocation of economic resources. In a typical problem of this sort the initial state is fixed, no constraints are imposed on the behaviour of the admissible trajectories at large times, and the objective functional is given by a discounted improper integral. We develop the method of finite-horizon approximations in a broad context and use it to derive complete versions of the Pontryagin maximum principle for such problems. We provide sufficient conditions for the normality of infinite-horizon optimal control problems and for the validity of the 'standard' limit transversality conditions with time going to infinity. As a meaningful example, we consider a new two-sector model of optimal economic growth subject to a random jump in prices. Bibliography: 53 titles.
Combined Optimal Sizing and Control for a Hybrid Tracked Vehicle
Directory of Open Access Journals (Sweden)
Huei Peng
2012-11-01
Full Text Available The optimal sizing and control of a hybrid tracked vehicle is presented and solved in this paper. A driving schedule obtained from field tests is used to represent typical tracked vehicle operations. Dynamics of the diesel engine-permanent magnetic AC synchronous generator set, the lithium-ion battery pack, and the power split between them are modeled and validated through experiments. Two coupled optimizations, one for the plant parameters, forming the outer optimization loop and one for the control strategy, forming the inner optimization loop, are used to achieve minimum fuel consumption under the selected driving schedule. The dynamic programming technique is applied to find the optimal controller in the inner loop while the component parameters are optimized iteratively in the outer loop. The results are analyzed, and the relationship between the key parameters is observed to keep the optimal sizing and control simultaneously.
Existence and characterization of optimal control in mathematics model of diabetics population
Permatasari, A. H.; Tjahjana, R. H.; Udjiani, T.
2018-03-01
Diabetes is a chronic disease with a huge burden affecting individuals and the whole society. In this paper, we constructed the optimal control mathematical model by applying a strategy to control the development of diabetic population. The constructed mathematical model considers the dynamics of disabled people due to diabetes. Moreover, an optimal control approach is proposed in order to reduce the burden of pre-diabetes. Implementation of control is done by preventing the pre-diabetes develop into diabetics with and without complications. The existence of optimal control and characterization of optimal control is discussed in this paper. Optimal control is characterized by applying the Pontryagin minimum principle. The results indicate that there is an optimal control in optimization problem in mathematics model of diabetic population. The effect of the optimal control variable (prevention) is strongly affected by the number of healthy people.
On a multi-channel transportation loss system with controlled input and controlled service
Directory of Open Access Journals (Sweden)
Jewgeni Dshalalow
1987-01-01
Full Text Available A multi-channel loss queueing system is investigated. The input stream is a controlled point process. The service in each of m parallel channels depends on the state of the system at certain moments of time when input and service may be controlled. To obtain explicitly the limiting distribution of the main process (Zt (the number of busy channels in equilibrium, an auxiliary three dimensional process with two additional components (one of them is a semi-Markov process is treated as semi-regenerative process. An optimization problem is discussed. Simple expressions for an objective function are derived.
Existence of optimal controls for systems governed by mean-field ...
African Journals Online (AJOL)
In this paper, we study the existence of an optimal control for systems, governed by stochastic dierential equations of mean-eld type. For non linear systems, we prove the existence of an optimal relaxed control, by using tightness techniques and Skorokhod selection theorem. The optimal control is a measure valued process ...
International Nuclear Information System (INIS)
Berrazouane, S.; Mohammedi, K.
2014-01-01
Highlights: • Optimized fuzzy logic controller (FLC) for operating a standalone hybrid power system based on cuckoo search algorithm. • Comparison between optimized fuzzy logic controller based on cuckoo search and swarm intelligent. • Loss of power supply probability and levelized energy cost are introduced. - Abstract: This paper presents the development of an optimized fuzzy logic controller (FLC) for operating a standalone hybrid power system based on cuckoo search algorithm. The FLC inputs are batteries state of charge (SOC) and net power flow, FLC outputs are the power rate of batteries, photovoltaic and diesel generator. Data for weekly solar irradiation, ambient temperature and load profile are used to tune the proposed controller by using cuckoo search algorithm. The optimized FLC is able to minimize loss of power supply probability (LPSP), excess energy (EE) and levelized energy cost (LEC). Moreover, the results of CS optimization are better than of particle swarm optimization PSO for fuzzy system controller
Optimal control theory applied to fusion plasma thermal stabilization
International Nuclear Information System (INIS)
Sager, G.; Miley, G.; Maya, I.
1985-01-01
Many authors have investigated stability characteristics and performance of various burn control schemes. The work presented here represents the first application of optimal control theory to the problem of fusion plasma thermal stabilization. The objectives of this initial investigation were to develop analysis methods, demonstrate tractability, and present some preliminary results of optimal control theory in burn control research
Optimization of preservation activities and preservation engineering (1)
International Nuclear Information System (INIS)
Aoki, Takayuki; Mimaki, Hidehito; Oda, Mitsuyuki
2004-01-01
In order to deal with the optimization of preservation activities and 'preservation engineering' which makes it possible, the relation between general society and preservation, the content and the structure of preservation activities, and the viewpoint and the approach of the optimization of the preventive preservation are described. The optimization of the preventive preservation is shown respectively in the four stages of planning, implementation, result evaluation and countermeasure. (K. Kato)
PID control for chaotic synchronization using particle swarm optimization
International Nuclear Information System (INIS)
Chang, W.-D.
2009-01-01
In this paper, we attempt to use the proportional-integral-derivative (PID) controller to achieve the chaos synchronization for delayed discrete chaotic systems. Three PID control gains can be optimally determined by means of using a novel optimization algorithm, called the particle swarm optimization (PSO). The algorithm is motivated from the organism behavior of fish schooling and bird flocking, and involves the social psychology principles in socio-cognition human agents and evolutionary computations. It has a good numerical convergence for solving optimization problem. To show the validity of the PSO-based PID control for chaos synchronization, several cases with different initial populations are considered and some simulation results are shown.
PID control for chaotic synchronization using particle swarm optimization
Energy Technology Data Exchange (ETDEWEB)
Chang, W.-D. [Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan (China)], E-mail: wdchang@mail.stu.edu.tw
2009-01-30
In this paper, we attempt to use the proportional-integral-derivative (PID) controller to achieve the chaos synchronization for delayed discrete chaotic systems. Three PID control gains can be optimally determined by means of using a novel optimization algorithm, called the particle swarm optimization (PSO). The algorithm is motivated from the organism behavior of fish schooling and bird flocking, and involves the social psychology principles in socio-cognition human agents and evolutionary computations. It has a good numerical convergence for solving optimization problem. To show the validity of the PSO-based PID control for chaos synchronization, several cases with different initial populations are considered and some simulation results are shown.
Farjoud, Alireza; Taylor, Russell; Schumann, Eric; Schlangen, Timothy
2014-02-01
This paper is focused on modelling, design, and testing of semi-active magneto-rheological (MR) engine and transmission mounts used in the automotive industry. The purpose is to develop a complete analysis, synthesis, design, and tuning tool that reduces the need for expensive and time-consuming laboratory and field tests. A detailed mathematical model of such devices is developed using multi-physics modelling techniques for physical systems with various energy domains. The model includes all major features of an MR mount including fluid dynamics, fluid track, elastic components, decoupler, rate-dip, gas-charged chamber, MR fluid rheology, magnetic circuit, electronic driver, and control algorithm. Conventional passive hydraulic mounts can also be studied using the same mathematical model. The model is validated using standard experimental procedures. It is used for design and parametric study of mounts; effects of various geometric and material parameters on dynamic response of mounts can be studied. Additionally, this model can be used to test various control strategies to obtain best vibration isolation performance by tuning control parameters. Another benefit of this work is that nonlinear interactions between sub-components of the mount can be observed and investigated. This is not possible by using simplified linear models currently available.
Intermediate levels of hippocampal activity appear optimal for associative memory formation.
Directory of Open Access Journals (Sweden)
Xiao Liu
Full Text Available BACKGROUND: It is well established that hippocampal activity is positively related to effective associative memory formation. However, in biological systems often optimal levels of activity are contrasted by both sub- and supra-optimal levels. Sub-optimal levels of hippocampal activity are commonly attributed to unsuccessful memory formation, whereas the supra-optimal levels of hippocampal activity related to unsuccessful memory formation have been rarely studied. It is still unclear under what circumstances such supra-optimal levels of hippocampal activity occur. To clarify this issue, we aimed at creating a condition, in which supra-optimal hippocampal activity is associated with encoding failure. We assumed that such supra-optimal activity occurs when task-relevant information is embedded in task-irrelevant, distracting information, which can be considered as noise. METHODOLOGY/PRINCIPAL FINDINGS: In the present fMRI study, we probed neural correlates of associative memory formation in a full-factorial design with associative memory (subsequently remembered versus forgotten and noise (induced by high versus low distraction as factors. Results showed that encoding failure was associated with supra-optimal activity in the high-distraction condition and with sub-optimal activity in the low distraction condition. Thus, we revealed evidence for a bell-shape function relating hippocampal activity with associative encoding success. CONCLUSIONS/SIGNIFICANCE: Our findings indicate that intermediate levels of hippocampal activity are optimal while both too low and too high levels appear detrimental for associative memory formation. Supra-optimal levels of hippocampal activity seem to occur when task-irrelevant information is added to task-relevant signal. If such task-irrelevant noise is reduced adequately, hippocampal activity is lower and thus optimal for associative memory formation.
Controlling active cabin suspensions in commercial vehicles
Evers, W.J.E.; Besselink, I.J.M.; Teerhuis, A.P.; Knaap, van der A.C.M.; Nijmeijer, H.
2009-01-01
The field of automotive suspensions is changing. Semi-active and active suspensions are starting to become viable options for vehicle designers. Suspension design for commercial vehicles is especially interesting given its potential. An active cabin suspension for a heavy-duty truck is considered,
Optimal hysteretic control for a BMAP/SM/1/N queue with two operation modes
Directory of Open Access Journals (Sweden)
Alexander N. Dudin
2000-01-01
Full Text Available We consider BMAP/SM/1 type queueing system with finite buffer of size N. The system has two operation modes, which are characterized by the matrix generating function of BMAP-input, the kernel of the semi-Markovian service process, and utilization cost. An algorithm for determining the optimal hysteresis strategy is presented.
The Optimization of power reactor control system
International Nuclear Information System (INIS)
Danupoyo, S.D.
1997-01-01
A power reactor is an important part in nuclear powered electrical plant systems. Success in controlling the power reactor will establish safety of the whole power plant systems. Until now, the power reactor has been controlled by a classical control system that was designed based on output feedback method. To meet the safety requirements that are now more restricted, the recently used power reactor control system should be modified. this paper describes a power reactor control system that is designed based on a state feedback method optimized with LQG (Linear-quadrature-gaussian) method and equipped with a state estimator. A pressurized-water type reactor has been used as the model. by using a point kinetics method with one group delayed neutrons. the result of simulation testing shows that the optimized control system can control the power reactor more effective and efficient than the classical control system
Directory of Open Access Journals (Sweden)
Patrícia dos Santos Costa
Full Text Available Abstract The optimization of culture medium with statistical methods is widely used in filamentous fungi glycosyl hydrolase production. The implementation of such methodology in bioreactors is very expensive as it requires several pH-controlled systems operating in parallel in order to test a large number of culture media components. The objective of this study was to evaluate potassium biphthalate buffer for pH control, which allows the optimization studies to be performed in shake flasks.The results have shown that buffering the culture medium with 0.1 M potassium biphthalate allowed pH control, resulting in a decrease of the standard deviation of triplicates for pH and activities of glycosyl hydrolase measurements. The use of this buffer allowed shake flask culture media optimization of enzyme production by Trichoderma harzianum, increasing the cellulase activity by more than 2 times compared to standard unbuffered culture medium. The same buffer can be used for culture media optimization of other fungi, such as Penicillium echinulatum.
Neutron density optimal control of A-1 reactor analoque model
International Nuclear Information System (INIS)
Grof, V.
1975-01-01
Two applications are described of the optimal control of a reactor analog model. Both cases consider the control of neutron density. Control loops containing the on-line controlled process, the reactor of the first Czechoslovak nuclear power plant A-1, are simulated on an analog computer. Two versions of the optimal control algorithm are derived using modern control theory (Pontryagin's maximum principle, the calculus of variations, and Kalman's estimation theory), the minimum time performance index, and the quadratic performance index. The results of the optimal control analysis are compared with the A-1 reactor conventional control. (author)
Optimal Sizing and Control Strategy Design for Heavy Hybrid Electric Truck
Directory of Open Access Journals (Sweden)
Yuan Zou
2012-01-01
Full Text Available Due to the complexity of the hybrid powertrain, the control is highly involved to improve the collaborations of the different components. For the specific powertrain, the components' sizing just gives the possibility to propel the vehicle and the control will realize the function of the propulsion. Definitely the components' sizing also gives the constraints to the control design, which cause a close coupling between the sizing and control strategy design. This paper presents a parametric study focused on sizing of the powertrain components and optimization of the power split between the engine and electric motor for minimizing the fuel consumption. A framework is put forward to accomplish the optimal sizing and control design for a heavy parallel pre-AMT hybrid truck under the natural driving schedule. The iterative plant-controller combined optimization methodology is adopted to optimize the key parameters of the plant and control strategy simultaneously. A scalable powertrain model based on a bilevel optimization framework is built. Dynamic programming is applied to find the optimal control in the inner loop with a prescribed cycle. The parameters are optimized in the outer loop. The results are analysed and the optimal sizing and control strategy are achieved simultaneously.
Robust Optimal Adaptive Control Method with Large Adaptive Gain
Nguyen, Nhan T.
2009-01-01
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.
Two-phase strategy of controlling motor coordination determined by task performance optimality.
Shimansky, Yury P; Rand, Miya K
2013-02-01
A quantitative model of optimal coordination between hand transport and grip aperture has been derived in our previous studies of reach-to-grasp movements without utilizing explicit knowledge of the optimality criterion or motor plant dynamics. The model's utility for experimental data analysis has been demonstrated. Here we show how to generalize this model for a broad class of reaching-type, goal-directed movements. The model allows for measuring the variability of motor coordination and studying its dependence on movement phase. The experimentally found characteristics of that dependence imply that execution noise is low and does not affect motor coordination significantly. From those characteristics it is inferred that the cost of neural computations required for information acquisition and processing is included in the criterion of task performance optimality as a function of precision demand for state estimation and decision making. The precision demand is an additional optimized control variable that regulates the amount of neurocomputational resources activated dynamically. It is shown that an optimal control strategy in this case comprises two different phases. During the initial phase, the cost of neural computations is significantly reduced at the expense of reducing the demand for their precision, which results in speed-accuracy tradeoff violation and significant inter-trial variability of motor coordination. During the final phase, neural computations and thus motor coordination are considerably more precise to reduce the cost of errors in making a contact with the target object. The generality of the optimal coordination model and the two-phase control strategy is illustrated on several diverse examples.
Optimal control and quantum simulations in superconducting quantum devices
Energy Technology Data Exchange (ETDEWEB)
Egger, Daniel J.
2014-10-31
Quantum optimal control theory is the science of steering quantum systems. In this thesis we show how to overcome the obstacles in implementing optimal control for superconducting quantum bits, a promising candidate for the creation of a quantum computer. Building such a device will require the tools of optimal control. We develop pulse shapes to solve a frequency crowding problem and create controlled-Z gates. A methodology is developed for the optimisation towards a target non-unitary process. We show how to tune-up control pulses for a generic quantum system in an automated way using a combination of open- and closed-loop optimal control. This will help scaling of quantum technologies since algorithms can calibrate control pulses far more efficiently than humans. Additionally we show how circuit QED can be brought to the novel regime of multi-mode ultrastrong coupling using a left-handed transmission line coupled to a right-handed one. We then propose to use this system as an analogue quantum simulator for the Spin-Boson model to show how dissipation arises in quantum systems.
Fahmy, Hesham; Zjawiony, Jordan K.; Konoshima, Takao; Tokuda, Harukuni; Khan, Shabana; Khalifa, Sherief
2006-01-01
Abstract: In the course of our continuing research in development and evaluation of novel skin cancer chemopreventive agents from marine sources, five semi-synthetic cembranoids derived from the marine natural product sarcophine, isolated from the soft coral Sarcophyton glaucum, were synthesized and shown to exhibit a remarkable chemopreventive activity in the in-vitro Epstein Barr Virus Early Antigen (EBV-EA) activation assay. These compounds were assayed in vivo using the two-stage carcinog...
Optimization and control of metal forming processes
Havinga, Gosse Tjipke
2016-01-01
Inevitable variations in process and material properties limit the accuracy of metal forming processes. Robust optimization methods or control systems can be used to improve the production accuracy. Robust optimization methods are used to design production processes with low sensitivity to the
Parameters control in GAs for dynamic optimization
Directory of Open Access Journals (Sweden)
Khalid Jebari
2013-02-01
Full Text Available The Control of Genetic Algorithms parameters allows to optimize the search process and improves the performance of the algorithm. Moreover it releases the user to dive into a game process of trial and failure to find the optimal parameters.
Optimal Control of Interdependent Epidemics in Complex Networks
Chen, Juntao; Zhang, Rui; Zhu, Quanyan
2017-01-01
Optimal control of interdependent epidemics spreading over complex networks is a critical issue. We first establish a framework to capture the coupling between two epidemics, and then analyze the system's equilibrium states by categorizing them into three classes, and deriving their stability conditions. The designed control strategy globally optimizes the trade-off between the control cost and the severity of epidemics in the network. A gradient descent algorithm based on a fixed point itera...
Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control
Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.
2015-01-01
The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.
An approach of optimal sensitivity applied in the tertiary loop of the automatic generation control
Energy Technology Data Exchange (ETDEWEB)
Belati, Edmarcio A. [CIMATEC - SENAI, Salvador, BA (Brazil); Alves, Dilson A. [Electrical Engineering Department, FEIS, UNESP - Sao Paulo State University (Brazil); da Costa, Geraldo R.M. [Electrical Engineering Department, EESC, USP - Sao Paulo University (Brazil)
2008-09-15
This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (author)
Infinite-horizon optimal control problems in economics
Energy Technology Data Exchange (ETDEWEB)
Aseev, Sergei M; Besov, Konstantin O; Kryazhimskii, Arkadii V
2012-04-30
This paper extends optimal control theory to a class of infinite-horizon problems that arise in studying models of optimal dynamic allocation of economic resources. In a typical problem of this sort the initial state is fixed, no constraints are imposed on the behaviour of the admissible trajectories at large times, and the objective functional is given by a discounted improper integral. We develop the method of finite-horizon approximations in a broad context and use it to derive complete versions of the Pontryagin maximum principle for such problems. We provide sufficient conditions for the normality of infinite-horizon optimal control problems and for the validity of the 'standard' limit transversality conditions with time going to infinity. As a meaningful example, we consider a new two-sector model of optimal economic growth subject to a random jump in prices. Bibliography: 53 titles.
International Nuclear Information System (INIS)
Romero, Alberto; Millar, Dean; Carvalho, Monica; Maestre, José M.; Camacho, Eduardo F.
2015-01-01
Mine dewatering can represent up to 5% of the total energy demand of a mine, and is one of the mine systems that aim to guarantee safe operating conditions. As mines go deeper, dewatering pumping heads become bigger, potentially involving several lift stages. Greater depth does not only mean greater dewatering cost, but more complex systems that require more sophisticated control systems, especially if mine operators wish to gain benefits from demand response incentives that are becoming a routine part of electricity tariffs. This work explores a two stage economic optimization procedure of an underground mine dewatering system, comprising two lifting stages, each one including a pump station and a water reservoir. First, the system design is optimized considering hourly characteristic dewatering demands for twelve days, one day representing each month of the year to account for seasonal dewatering demand variations. This design optimization minimizes the annualized cost of the system, and therefore includes the investment costs in underground reservoirs. Reservoir size, as well as an hourly pumping operation plan are calculated for specific operating environments, defined by characteristic hourly electricity prices and water inflows (seepage and water use from production activities), at best known through historical observations for the previous year. There is no guarantee that the system design will remain optimal when it faces the water inflows and market determined electricity prices of the year ahead, or subsequent years ahead, because these remain unknown at design time. Consequently, the dewatering optimized system design is adopted subsequently as part of a Model Predictive Control (MPC) strategy that adaptively maintains optimality during the operations phase. Centralized, distributed and non-centralized MPC strategies are explored. Results show that the system can be reliably controlled using any of these control strategies proposed. Under the operating
A fractional optimal control problem for maximizing advertising efficiency
Igor Bykadorov; Andrea Ellero; Stefania Funari; Elena Moretti
2007-01-01
We propose an optimal control problem to model the dynamics of the communication activity of a firm with the aim of maximizing its efficiency. We assume that the advertising effort undertaken by the firm contributes to increase the firm's goodwill and that the goodwill affects the firm's sales. The aim is to find the advertising policies in order to maximize the firm's efficiency index which is computed as the ratio between "outputs" and "inputs" properly weighted; the outputs are represented...
Optimal robust control strategy of a solid oxide fuel cell system
Wu, Xiaojuan; Gao, Danhui
2018-01-01
Optimal control can ensure system safe operation with a high efficiency. However, only a few papers discuss optimal control strategies for solid oxide fuel cell (SOFC) systems. Moreover, the existed methods ignore the impact of parameter uncertainty on system instantaneous performance. In real SOFC systems, several parameters may vary with the variation of operation conditions and can not be identified exactly, such as load current. Therefore, a robust optimal control strategy is proposed, which involves three parts: a SOFC model with parameter uncertainty, a robust optimizer and robust controllers. During the model building process, boundaries of the uncertain parameter are extracted based on Monte Carlo algorithm. To achieve the maximum efficiency, a two-space particle swarm optimization approach is employed to obtain optimal operating points, which are used as the set points of the controllers. To ensure the SOFC safe operation, two feed-forward controllers and a higher-order robust sliding mode controller are presented to control fuel utilization ratio, air excess ratio and stack temperature afterwards. The results show the proposed optimal robust control method can maintain the SOFC system safe operation with a maximum efficiency under load and uncertainty variations.
Optimal control problem for the extended Fisher–Kolmogorov equation
Indian Academy of Sciences (India)
by methods of optimal control, such as chemical engineering and vehicle ... ern optimal control theories and applied models are not only represented by .... Obviously, equation (2.5) is an ordinary differential equation and according to ODE.
Directory of Open Access Journals (Sweden)
Kaewploy Somsak
2015-01-01
Full Text Available Liquid state welding techniques available are prone to gas porosity problems. To avoid this solid state bonding is usually an alternative of preference. Among solid state bonding techniques, diffusion bonding is often employed in aluminium alloy automotive parts welding in order to enhance their mechanical properties. However, there has been no standard procedure nor has there been any definitive criterion for judicious welding parameters setting. It is thus a matter of importance to find the set of optimal parameters for effective diffusion bonding. This work proposes the use of response surface methodology in determining such a set of optimal parameters. Response surface methodology is more efficient in dealing with complex process compared with other techniques available. There are two variations of response surface methodology. The one adopted in this work is the central composite design approach. This is because when the initial upper and lower bounds of the desired parameters are exceeded the central composite design approach is still capable of yielding the optimal values of the parameters that appear to be out of the initially preset range. Results from the experiments show that the pressing pressure and the holding time affect the tensile strength of jointing. The data obtained from the experiment fits well to a quadratic equation with high coefficient of determination (R2 = 94.21%. It is found that the optimal parameters in the process of jointing semi-solid casting aluminium alloy by using diffusion bonding are the pressing pressure of 2.06 MPa and 214 minutes of the holding time in order to achieve the highest tensile strength of 142.65 MPa
Time dependent optimal switching controls in online selling models
Energy Technology Data Exchange (ETDEWEB)
Bradonjic, Milan [Los Alamos National Laboratory; Cohen, Albert [MICHIGAN STATE UNIV
2010-01-01
We present a method to incorporate dishonesty in online selling via a stochastic optimal control problem. In our framework, the seller wishes to maximize her average wealth level W at a fixed time T of her choosing. The corresponding Hamilton-Jacobi-Bellmann (HJB) equation is analyzed for a basic case. For more general models, the admissible control set is restricted to a jump process that switches between extreme values. We propose a new approach, where the optimal control problem is reduced to a multivariable optimization problem.
Optimal control of nonlinear continuous-time systems in strict-feedback form.
Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani
2015-10-01
This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.
Directory of Open Access Journals (Sweden)
Maryam M Shanechi
Full Text Available Real-time brain-machine interfaces (BMI have focused on either estimating the continuous movement trajectory or target intent. However, natural movement often incorporates both. Additionally, BMIs can be modeled as a feedback control system in which the subject modulates the neural activity to move the prosthetic device towards a desired target while receiving real-time sensory feedback of the state of the movement. We develop a novel real-time BMI using an optimal feedback control design that jointly estimates the movement target and trajectory of monkeys in two stages. First, the target is decoded from neural spiking activity before movement initiation. Second, the trajectory is decoded by combining the decoded target with the peri-movement spiking activity using an optimal feedback control design. This design exploits a recursive Bayesian decoder that uses an optimal feedback control model of the sensorimotor system to take into account the intended target location and the sensory feedback in its trajectory estimation from spiking activity. The real-time BMI processes the spiking activity directly using point process modeling. We implement the BMI in experiments consisting of an instructed-delay center-out task in which monkeys are presented with a target location on the screen during a delay period and then have to move a cursor to it without touching the incorrect targets. We show that the two-stage BMI performs more accurately than either stage alone. Correct target prediction can compensate for inaccurate trajectory estimation and vice versa. The optimal feedback control design also results in trajectories that are smoother and have lower estimation error. The two-stage decoder also performs better than linear regression approaches in offline cross-validation analyses. Our results demonstrate the advantage of a BMI design that jointly estimates the target and trajectory of movement and more closely mimics the sensorimotor control system.
Optimization of feed water control for auxiliary boiler
International Nuclear Information System (INIS)
Li Lingmao
2004-01-01
This paper described the feed water control system of the auxiliary boiler steam drum in Qinshan Phase III Nuclear Power Plant, analyzed the deficiency of the original configuration, and proposed the optimized configuration. The optimized feed water control system can ensure the stable and safe operation of the auxiliary boiler, and the normal operation of the users. (author)
Relaxed error control in shape optimization that utilizes remeshing
CSIR Research Space (South Africa)
Wilke, DN
2013-02-01
Full Text Available Shape optimization strategies based on error indicators usually require strict error control for every computed design during the optimization run. The strict error control serves two purposes. Firstly, it allows for the accurate computation...
Real-Time Optimization and Control of Next-Generation Distribution
-Generation Distribution Infrastructure Real-Time Optimization and Control of Next-Generation Distribution developing a system-theoretic distribution network management framework that unifies real-time voltage and Infrastructure | Grid Modernization | NREL Real-Time Optimization and Control of Next
Sampled-data and discrete-time H2 optimal control
Trentelman, Harry L.; Stoorvogel, Anton A.
1993-01-01
This paper deals with the sampled-data H2 optimal control problem. Given a linear time-invariant continuous-time system, the problem of minimizing the H2 performance over all sampled-data controllers with a fixed sampling period can be reduced to a pure discrete-time H2 optimal control problem. This
Optimal Control of Evolution Mixed Variational Inclusions
Energy Technology Data Exchange (ETDEWEB)
Alduncin, Gonzalo, E-mail: alduncin@geofisica.unam.mx [Universidad Nacional Autónoma de México, Departamento de Recursos Naturales, Instituto de Geofísica (Mexico)
2013-12-15
Optimal control problems of primal and dual evolution mixed variational inclusions, in reflexive Banach spaces, are studied. The solvability analysis of the mixed state systems is established via duality principles. The optimality analysis is performed in terms of perturbation conjugate duality methods, and proximation penalty-duality algorithms to mixed optimality conditions are further presented. Applications to nonlinear diffusion constrained problems as well as quasistatic elastoviscoplastic bilateral contact problems exemplify the theory.
Optimal Control of Evolution Mixed Variational Inclusions
International Nuclear Information System (INIS)
Alduncin, Gonzalo
2013-01-01
Optimal control problems of primal and dual evolution mixed variational inclusions, in reflexive Banach spaces, are studied. The solvability analysis of the mixed state systems is established via duality principles. The optimality analysis is performed in terms of perturbation conjugate duality methods, and proximation penalty-duality algorithms to mixed optimality conditions are further presented. Applications to nonlinear diffusion constrained problems as well as quasistatic elastoviscoplastic bilateral contact problems exemplify the theory
Optimal Control Design for a Solar Greenhouse
Ooteghem, van R.J.C.
2010-01-01
Abstract: An optimal climate control has been designed for a solar greenhouse to achieve optimal crop production with sustainable instead of fossil energy. The solar greenhouse extends a conventional greenhouse with an improved roof cover, ventilation with heat recovery, a heat pump, a heat
A hybrid iterative scheme for optimal control problems governed by ...
African Journals Online (AJOL)
MRT
KEY WORDS: Optimal control problem; Fredholm integral equation; ... control problems governed by Fredholm integral and integro-differential equations is given in (Brunner and Yan, ..... The exact optimal trajectory and control functions are. 2.
Assuring robustness to noise in optimal quantum control experiments
International Nuclear Information System (INIS)
Bartelt, A.F.; Roth, M.; Mehendale, M.; Rabitz, H.
2005-01-01
Closed-loop optimal quantum control experiments operate in the inherent presence of laser noise. In many applications, attaining high quality results [i.e., a high signal-to-noise (S/N) ratio for the optimized objective] is as important as producing a high control yield. Enhancement of the S/N ratio will typically be in competition with the mean signal, however, the latter competition can be balanced by biasing the optimization experiments towards higher mean yields while retaining a good S/N ratio. Other strategies can also direct the optimization to reduce the standard deviation of the statistical signal distribution. The ability to enhance the S/N ratio through an optimized choice of the control is demonstrated for two condensed phase model systems: second harmonic generation in a nonlinear optical crystal and stimulated emission pumping in a dye solution
Directory of Open Access Journals (Sweden)
Weifeng Wang
2014-01-01
Full Text Available We study an optimal control problem governed by a semilinear parabolic equation, whose control variable is contained only in the boundary condition. An existence theorem for the optimal control is obtained.
Research on bathymetry estimation by Worldview-2 based with the semi-analytical model
Sheng, L.; Bai, J.; Zhou, G.-W.; Zhao, Y.; Li, Y.-C.
2015-04-01
South Sea Islands of China are far away from the mainland, the reefs takes more than 95% of south sea, and most reefs scatter over interested dispute sensitive area. Thus, the methods of obtaining the reefs bathymetry accurately are urgent to be developed. Common used method, including sonar, airborne laser and remote sensing estimation, are limited by the long distance, large area and sensitive location. Remote sensing data provides an effective way for bathymetry estimation without touching over large area, by the relationship between spectrum information and bathymetry. Aimed at the water quality of the south sea of China, our paper develops a bathymetry estimation method without measured water depth. Firstly the semi-analytical optimization model of the theoretical interpretation models has been studied based on the genetic algorithm to optimize the model. Meanwhile, OpenMP parallel computing algorithm has been introduced to greatly increase the speed of the semi-analytical optimization model. One island of south sea in China is selected as our study area, the measured water depth are used to evaluate the accuracy of bathymetry estimation from Worldview-2 multispectral images. The results show that: the semi-analytical optimization model based on genetic algorithm has good results in our study area;the accuracy of estimated bathymetry in the 0-20 meters shallow water area is accepted.Semi-analytical optimization model based on genetic algorithm solves the problem of the bathymetry estimation without water depth measurement. Generally, our paper provides a new bathymetry estimation method for the sensitive reefs far away from mainland.
Hybrid Quantum-Classical Approach to Quantum Optimal Control.
Li, Jun; Yang, Xiaodong; Peng, Xinhua; Sun, Chang-Pu
2017-04-14
A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal control problem. We show that the most computationally demanding part of gradient-based algorithms, namely, computing the fitness function and its gradient for a control input, can be accomplished by the process of evolution and measurement on a quantum simulator. By posing queries to and receiving answers from the quantum simulator, classical computing devices update the control parameters until an optimal control solution is found. To demonstrate the quantum-classical scheme in experiment, we use a seven-qubit nuclear magnetic resonance system, on which we have succeeded in optimizing state preparation without involving classical computation of the large Hilbert space evolution.
Xia, Yaping; Yin, Minghui; Zou, Yun
2018-01-01
In this paper, the relationship between the degree of controllability (DOC) of controlled plants and the corresponding quadratic optimal performance index in LQR control is investigated for the electro-hydraulic synchronising servo control systems and wind turbine systems, respectively. It is shown that for these two types of systems, the higher the DOC of a controlled plant is, the better the quadratic optimal performance index is. It implies that in some LQR controller designs, the measure of the DOC of a controlled plant can be used as an index for the optimisation of adjustable plant parameters, by which the plant can be controlled more effectively.
Sima, Wenxia; Jiang, Xiongwei; Peng, Qingjun; Sun, Potao
2018-05-01
Electrical breakdown is an important physical phenomenon in electrical equipment and electronic devices. Many related models and theories of electrical breakdown have been proposed. However, a widely recognized understanding on the following phenomenon is still lacking: impulse breakdown strength which varies with waveform parameters, decrease in the breakdown strength of AC voltage with increasing frequency, and higher impulse breakdown strength than that of AC. In this work, an improved model of activation energy absorption for different electrical breakdowns in semi-crystalline insulating polymers is proposed based on the Harmonic oscillator model. Simulation and experimental results show that, the energy of trapped charges obtained from AC stress is higher than that of impulse voltage, and the absorbed activation energy increases with the increase in the electric field frequency. Meanwhile, the frequency-dependent relative dielectric constant ε r and dielectric loss tanδ also affect the absorption of activation energy. The absorbed activation energy and modified trap level synergistically determine the breakdown strength. The mechanism analysis of breakdown strength under various voltage waveforms is consistent with the experimental results. Therefore, the proposed model of activation energy absorption in the present work may provide a new possible method for analyzing and explaining the breakdown phenomenon in semi-crystalline insulating polymers.
Desiccant wheel thermal performance modeling for indoor humidity optimal control
International Nuclear Information System (INIS)
Wang, Nan; Zhang, Jiangfeng; Xia, Xiaohua
2013-01-01
Highlights: • An optimal humidity control model is formulated to control the indoor humidity. • MPC strategy is used to implement the optimal operation solution. • Practical applications of the MPC strategy is illustrated by the case study. - Abstract: Thermal comfort is an important concern in the energy efficiency improvement of commercial buildings. Thermal comfort research focuses mostly on temperature control, but humidity control is an important aspect to maintain indoor comfort too. In this paper, an optimal humidity control model (OHCM) is presented. Model predictive control (MPC) strategy is applied to implement the optimal operation of the desiccant wheel during working hours of a commercial building. The OHCM is revised to apply the MPC strategy. A case is studied to illustrate the practical applications of the MPC strategy
Optimal control applications in electric power systems
Christensen, G S; Soliman, S A
1987-01-01
Significant advances in the field of optimal control have been made over the past few decades. These advances have been well documented in numerous fine publications, and have motivated a number of innovations in electric power system engineering, but they have not yet been collected in book form. Our purpose in writing this book is to provide a description of some of the applications of optimal control techniques to practical power system problems. The book is designed for advanced undergraduate courses in electric power systems, as well as graduate courses in electrical engineering, applied mathematics, and industrial engineering. It is also intended as a self-study aid for practicing personnel involved in the planning and operation of electric power systems for utilities, manufacturers, and consulting and government regulatory agencies. The book consists of seven chapters. It begins with an introductory chapter that briefly reviews the history of optimal control and its power system applications and also p...
Directory of Open Access Journals (Sweden)
Fengyong Sun
2017-04-01
Full Text Available In order to solve the aero-propulsion system acceleration optimal problem, the necessity of inlet control is discussed, and a fully new aero-propulsion system acceleration process control design including the inlet, engine, and nozzle is proposed in this paper. In the proposed propulsion system control scheme, the inlet, engine, and nozzle are simultaneously adjusted through the FSQP method. In order to implement the control scheme design, an aero-propulsion system component-level model is built to simulate the inlet working performance and the matching problems between the inlet and engine. Meanwhile, a stabilizing inlet control scheme is designed to solve the inlet control problems. In optimal control of the aero-propulsion system acceleration process, the inlet is an emphasized control unit in the optimal acceleration control system. Two inlet control patterns are discussed in the simulation. The simulation results prove that by taking the inlet ramp angle as an active control variable instead of being modulated passively, acceleration performance could be obviously enhanced. Acceleration objectives could be obtained with a faster acceleration time by 5%.
Self-optimizing robust nonlinear model predictive control
Lazar, M.; Heemels, W.P.M.H.; Jokic, A.; Thoma, M.; Allgöwer, F.; Morari, M.
2009-01-01
This paper presents a novel method for designing robust MPC schemes that are self-optimizing in terms of disturbance attenuation. The method employs convex control Lyapunov functions and disturbance bounds to optimize robustness of the closed-loop system on-line, at each sampling instant - a unique
International Nuclear Information System (INIS)
Minjarez-Sosa, J. Adolfo; Luque-Vasquez, Fernando
2008-01-01
This paper deals with two person zero-sum semi-Markov games with a possibly unbounded payoff function, under a discounted payoff criterion. Assuming that the distribution of the holding times H is unknown for one of the players, we combine suitable methods of statistical estimation of H with control procedures to construct an asymptotically discount optimal pair of strategies
Numerical aspects of optimal control of penicillin production
Czech Academy of Sciences Publication Activity Database
Pčolka, M.; Čelikovský, Sergej
2014-01-01
Roč. 37, č. 1 (2014), s. 71-81 ISSN 1615-7591 R&D Projects: GA ČR(CZ) GA13-20433S Institutional support: RVO:67985556 Keywords : Optimal control * Nonlinear systems * Fermentation process * Gradient method optimization * Antibiotics production Subject RIV: BC - Control Systems Theory Impact factor: 1.997, year: 2014 http://library.utia.cas.cz/separaty/2014/TR/celikovsky-0424718.pdf
Optimal Design and Real Time Implementation of Autonomous Microgrid Including Active Load
Directory of Open Access Journals (Sweden)
Mohamed A. Hassan
2018-05-01
Full Text Available Controller gains and power-sharing parameters are the main parameters affect the dynamic performance of the microgrid. Considering an active load to the autonomous microgrid, the stability problem will be more involved. In this paper, the active load effect on microgrid dynamic stability is explored. An autonomous microgrid including three inverter-based distributed generations (DGs with an active load is modeled and the associated controllers are designed. Controller gains of the inverters and active load as well as Phase Locked Loop (PLL parameters are optimally tuned to guarantee overall system stability. A weighted objective function is proposed to minimize the error in both measured active power and DC voltage based on time-domain simulations. Different AC and DC disturbances are applied to verify and assess the effectiveness of the proposed control strategy. The results demonstrate the potential of the proposed controller to enhance the microgrid stability and to provide efficient damping characteristics. Additionally, the proposed controller is compared with the literature to demonstrate its superiority. Finally, the microgrid considered has been established and implemented on real time digital simulator (RTDS. The experimental results validate the simulation results and approve the effectiveness of the proposed controllers to enrich the stability of the considered microgrid.
Model-based dynamic control and optimization of gas networks
Energy Technology Data Exchange (ETDEWEB)
Hofsten, Kai
2001-07-01
This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum
Variational reconstruction using subdivision surfaces with continuous sharpness control
Institute of Scientific and Technical Information of China (English)
Xiaoqun Wu; Jianmin Zheng; Yiyu Cai; Haisheng Li
2017-01-01
We present a variational method for subdivision surface reconstruction from a noisy dense mesh.A new set of subdivision rules with continuous sharpness control is introduced into Loop subdivision for better modeling subdivision surface features such as semi-sharp creases,creases,and corners.The key idea is to assign a sharpness value to each edge of the control mesh to continuously control the surface features.Based on the new subdivision rules,a variational model with L1 norm is formulated to find the control mesh and the corresponding sharpness values of the subdivision surface that best fits the input mesh.An iterative solver based on the augmented Lagrangian method and particle swarm optimization is used to solve the resulting non-linear,non-differentiable optimization problem.Our experimental results show that our method can handle meshes well with sharp/semi-sharp features and noise.
Optimizing human activity patterns using global sensitivity analysis.
Fairchild, Geoffrey; Hickmann, Kyle S; Mniszewski, Susan M; Del Valle, Sara Y; Hyman, James M
2014-12-01
Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule's regularity for a population. We show how to tune an activity's regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.
Parallel Optimization of Polynomials for Large-scale Problems in Stability and Control
Kamyar, Reza
In this thesis, we focus on some of the NP-hard problems in control theory. Thanks to the converse Lyapunov theory, these problems can often be modeled as optimization over polynomials. To avoid the problem of intractability, we establish a trade off between accuracy and complexity. In particular, we develop a sequence of tractable optimization problems --- in the form of Linear Programs (LPs) and/or Semi-Definite Programs (SDPs) --- whose solutions converge to the exact solution of the NP-hard problem. However, the computational and memory complexity of these LPs and SDPs grow exponentially with the progress of the sequence - meaning that improving the accuracy of the solutions requires solving SDPs with tens of thousands of decision variables and constraints. Setting up and solving such problems is a significant challenge. The existing optimization algorithms and software are only designed to use desktop computers or small cluster computers --- machines which do not have sufficient memory for solving such large SDPs. Moreover, the speed-up of these algorithms does not scale beyond dozens of processors. This in fact is the reason we seek parallel algorithms for setting-up and solving large SDPs on large cluster- and/or super-computers. We propose parallel algorithms for stability analysis of two classes of systems: 1) Linear systems with a large number of uncertain parameters; 2) Nonlinear systems defined by polynomial vector fields. First, we develop a distributed parallel algorithm which applies Polya's and/or Handelman's theorems to some variants of parameter-dependent Lyapunov inequalities with parameters defined over the standard simplex. The result is a sequence of SDPs which possess a block-diagonal structure. We then develop a parallel SDP solver which exploits this structure in order to map the computation, memory and communication to a distributed parallel environment. Numerical tests on a supercomputer demonstrate the ability of the algorithm to
Directory of Open Access Journals (Sweden)
Semenenko V.M.
2013-10-01
Full Text Available A highly sensitive and selective method of pyraclostrobin, boscalid, tebufenpyrad and prohexadione-calcium determination under their combined presence in water sample, using high-performance liquid chromatography was developed. On the base of mentioned active ingredients (combined fungicide Bellis, insecto-acaricide Masai and plant growth regulator Regalis pesticides may be used in one vegetation season for fruit trees protection. Method of co-determination of these substances is based on the preparation of water samples for extraction, extraction of pyraclostrobin, boscalid, tebufenpyrad and prohexadione-calcium, concentrating of extract of substances mixtures and chromatographic determination with ultraviolet detection. A distinctive feature of this method is changing of ratio of components of mobile phase (mixture of acetonitrile and 0,1 % aqueous solution of phosphoric acid in the process of chromatographic analysis, which allowed to clearly visualize test substances in case of their joint presence in one sample. Implementation of developed and patented method into practice optimizes control over application of pesticides in agriculture and their monitoring in reservoirs water by significant acceleration of analysis and reduction of expenses in its carying out.
Wind turbine optimal control during storms
International Nuclear Information System (INIS)
Petrović, V; Bottasso, C L
2014-01-01
This paper proposes a control algorithm that enables wind turbine operation in high winds. With this objective, an online optimization procedure is formulated that, based on the wind turbine state, estimates those extremal wind speed variations that would produce maximal allowable wind turbine loads. Optimization results are compared to the actual wind speed and, if there is a danger of excessive loading, the wind turbine power reference is adjusted to ensure that loads stay within allowed limits. This way, the machine can operate safely even above the cut-out wind speed, thereby realizing a soft envelope-protecting cut-out. The proposed control strategy is tested and verified using a high-fidelity aeroservoelastic simulation model
Two-objective on-line optimization of supervisory control strategy
Energy Technology Data Exchange (ETDEWEB)
Nassif, N.; Kajl, S.; Sabourin, R. [Ecole de Technologie Superieure, Montreal (Canada)
2004-09-01
The set points of supervisory control strategy are optimized with respect to energy use and thermal comfort for existing HVAC systems. The set point values of zone temperatures, supply duct static pressure, and supply air temperature are the problem variables, while energy use and thermal comfort are the objective functions. The HVAC system model includes all the individual component models developed and validated against the monitored data of an existing VAV system. It serves to calculate energy use during the optimization process, whereas the actual energy use is determined by using monitoring data and the appropriate validated component models. A comparison, done for one summer week, of actual and optimal energy use shows that the on-line implementation of a genetic algorithm optimization program to determine the optimal set points of supervisory control strategy could save energy by 19.5%, while satisfying the minimum zone airflow rates and the thermal comfort. The results also indicate that the application of the two-objective optimization problem can help control daily energy use or daily building thermal comfort, thus saving more energy than the application of the one-objective optimization problem. (Author)
Miller, Christopher J.; Goodrick, Dan
2017-01-01
The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads to specified values. This technique has been implemented and flown on the National Aeronautics and Space Administration Full-scale Advanced Systems Testbed aircraft. The flight tests illustrate that the approach achieves the desired performance and show promising potential benefits. The flights also uncovered some important issues that will need to be addressed for production application.
Lukasse, L.
1999-01-01
This thesis is about control and identification in activated sludge processes (ASP's). The chapters in this thesis are divided in two parts. Part I deals with the development of the best feasible, close-to-optimal adaptive receding horizon optimal controller (RHOC) for N-removal in a
Energy Technology Data Exchange (ETDEWEB)
Thu, Hien Cao Thi; Lee, Moonyong [Yeungnam University, Gyeongsan (Korea, Republic of)
2013-12-15
A novel analytical design method of industrial proportional-integral (PI) controllers was developed for the optimal control of first-order processes with operational constraints. The control objective was to minimize a weighted sum of the controlled variable error and the rate of change in the manipulated variable under the maximum allowable limits in the controlled variable, manipulated variable and the rate of change in the manipulated variable. The constrained optimal servo control problem was converted to an unconstrained optimization to obtain an analytical tuning formula. A practical shortcut procedure for obtaining optimal PI parameters was provided based on graphical analysis of global optimality. The proposed PI controller was found to guarantee global optimum and deal explicitly with the three important operational constraints.
Directory of Open Access Journals (Sweden)
Stefanie Zimmermann
2014-03-01
Full Text Available Sesquiterpene lactones (STLs are natural products that have potent antitrypanosomal activity in vitro and, in the case of cynaropicrin, also reduce parasitemia in the murine model of trypanosomiasis. To explore their structure-antitrypanosomal activity relationships, a set of 34 natural and semi-synthetic STLs and amino-STLs was tested in vitro against T. b. rhodesiense (which causes East African sleeping sickness and mammalian cancer cells (rat bone myoblast L6 cells. It was found that the α-methylene-γ-lactone moiety is necessary for both antitrypanosomal effects and cytotoxicity. Antitrypanosomal selectivity is facilitated by 2-(hydroxymethylacrylate or 3,4-dihydroxy-2-methylenebutylate side chains, and by the presence of cyclopentenone rings. Semi-synthetic STL amines with morpholino and dimethylamino groups showed improved in vitro activity over the native STLs. The dimethylamino derivative of cynaropicrin was prepared and tested orally in the T. b. rhodesiense acute mouse model, where it showed reduced toxicity over cynaropicrin, but also lost antitrypanosomal activity.
Optimal control of a waste water cleaning plant
Directory of Open Access Journals (Sweden)
Ellina V. Grigorieva
2010-09-01
Full Text Available In this work, a model of a waste water treatment plant is investigated. The model is described by a nonlinear system of two differential equations with one bounded control. An optimal control problem of minimizing concentration of the polluted water at the terminal time T is stated and solved analytically with the use of the Pontryagin Maximum Principle. Dependence of the optimal solution on the initial conditions is established. Computer simulations of a model of an industrial waste water treatment plant show the advantage of using our optimal strategy. Possible applications are discussed.
Directory of Open Access Journals (Sweden)
Moneta Diana
2014-01-01
Full Text Available The diffusion of Distributed Generation (DG based on Renewable Energy Sources (RES requires new strategies to ensure reliable and economic operation of the distribution networks and to support the diffusion of DG itself. An advanced algorithm (DISCoVER – DIStribution Company VoltagE Regulator is being developed to optimize the operation of active network by means of an advanced voltage control based on several regulations. Starting from forecasted load and generation, real on-field measurements, technical constraints and costs for each resource, the algorithm generates for each time period a set of commands for controllable resources that guarantees achievement of technical goals minimizing the overall cost. Before integrating the controller into the telecontrol system of the real networks, and in order to validate the proper behaviour of the algorithm and to identify possible critical conditions, a complete simulation phase has started. The first step is concerning the definition of a wide range of “case studies”, that are the combination of network topology, technical constraints and targets, load and generation profiles and “costs” of resources that define a valid context to test the algorithm, with particular focus on battery and RES management. First results achieved from simulation activity on test networks (based on real MV grids and actual battery characteristics are given, together with prospective performance on real case applications.
Moneta, Diana; Mora, Paolo; Viganò, Giacomo; Alimonti, Gianluca
2014-12-01
The diffusion of Distributed Generation (DG) based on Renewable Energy Sources (RES) requires new strategies to ensure reliable and economic operation of the distribution networks and to support the diffusion of DG itself. An advanced algorithm (DISCoVER - DIStribution Company VoltagE Regulator) is being developed to optimize the operation of active network by means of an advanced voltage control based on several regulations. Starting from forecasted load and generation, real on-field measurements, technical constraints and costs for each resource, the algorithm generates for each time period a set of commands for controllable resources that guarantees achievement of technical goals minimizing the overall cost. Before integrating the controller into the telecontrol system of the real networks, and in order to validate the proper behaviour of the algorithm and to identify possible critical conditions, a complete simulation phase has started. The first step is concerning the definition of a wide range of "case studies", that are the combination of network topology, technical constraints and targets, load and generation profiles and "costs" of resources that define a valid context to test the algorithm, with particular focus on battery and RES management. First results achieved from simulation activity on test networks (based on real MV grids) and actual battery characteristics are given, together with prospective performance on real case applications.
Optimal control of anthracnose using mixed strategies.
Fotsa Mbogne, David Jaures; Thron, Christopher
2015-11-01
In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. Copyright © 2015 Elsevier Inc. All rights reserved.
Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.
Directory of Open Access Journals (Sweden)
Arne J Nagengast
2010-07-01
Full Text Available Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller or as an added value (risk-seeking controller to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models.