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Sample records for adaptive control

  1. Decentralized adaptive control

    Oh, B. J.; Jamshidi, M.; Seraji, H.

    1988-01-01

    A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.

  2. Adaptive shared control system

    Sanders, David

    2009-01-01

    A control system to aid mobility is presented that is intended to assist living independently and that provides physical guidance. The system has two levels: a human machine interface and an adaptive shared controller.

  3. Robust Adaptive Control

    Narendra, K. S.; Annaswamy, A. M.

    1985-01-01

    Several concepts and results in robust adaptive control are are discussed and is organized in three parts. The first part surveys existing algorithms. Different formulations of the problem and theoretical solutions that have been suggested are reviewed here. The second part contains new results related to the role of persistent excitation in robust adaptive systems and the use of hybrid control to improve robustness. In the third part promising new areas for future research are suggested which combine different approaches currently known.

  4. Robust Adaptive Structural Control

    Yang, Chi-Ming; Beck, James L.

    1995-01-01

    A new robust adaptive structural control design methodology is developed and presented which treats modeling uncertainties and limitations of control devices. Furthermore, no restriction is imposed on the structural models and the nature of the control devices so that the proposed method is very general. A simple linear single degree-of-freedom numerical example is presented to illustrate this approach.

  5. Adaptive Inflow Control System

    Volkov, Vasily Y; Zhuravlev, Oleg N; Nukhaev, Marat T; Shchelushkin, Roman V

    2014-01-01

    This article presents the idea and realization for the unique Adaptive Inflow Control System being a part of well completion, able to adjust to the changing in time production conditions. This system allows to limit the flow rate from each interval at a certain level, which solves the problem of water and gas breakthroughs. We present the results of laboratory tests and numerical calculations obtaining the characteristics of the experimental setup with dual-in-position valves as parts of adaptive inflow control system, depending on the operating conditions. The flow distribution in the system was also studied with the help of three-dimensional computer model. The control ranges dependences are determined, an influence of the individual elements on the entire system is revealed.

  6. Adaptive Structural Mode Control Project

    National Aeronautics and Space Administration — M4 Engineering proposes the development of an adaptive structural mode control system. The adaptive control system will begin from a "baseline" dynamic model of the...

  7. Stored waveform adaptive motor control

    Beall, Jeffery C.

    1986-01-01

    This study investigates an adaptive control scheme designed to maintain accurate motor speed control in spite of high-frequency periodic variations in load torque, load inertia, and motor parameters. The controller adapts, stores and replays a schedule of torques to be delivered at discrete points throughout the periodic load cycle. The controller also adapts to non-periodic changes in load conditions which occur over several load cycles and contains inherent integrator control action to ...

  8. Adaptive filtering prediction and control

    Goodwin, Graham C

    2009-01-01

    Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

  9. Maritime adaptive optics beam control

    Corley, Melissa S.

    2010-01-01

    The Navy is interested in developing systems for horizontal, near ocean surface, high-energy laser propagation through the atmosphere. Laser propagation in the maritime environment requires adaptive optics control of aberrations caused by atmospheric distortion. In this research, a multichannel transverse adaptive filter is formulated in Matlab's Simulink environment and compared to a complex lattice filter that has previously been implemented in large system simulations. The adaptive fil...

  10. INDIRECT ACCELERATED ADAPTIVE FUZZY CONTROLLER

    ZHU Liye; FANG Yuan; ZHANG Weidong

    2008-01-01

    According to a type of normal nonlinear system, an indirect adaptive fuzzy (IAF) controller has been applied to those systems where no accurate mathematical models of the systems under control are available. To satisfy with system performance, an indirect accelerated adaptive fuzzy (IAAF) controller is proposed, and its general form is presented. The general form IAAF controller ensures necessary control criteria and system's global stability using Lyapunov Theorem. It has been proved that the close-loop system error converges to a small neighborhood of equilibrium point. The optimal IAAF controller is derived to guarantee the process's shortest settling time. Simulation results indicate the IAAF controller make the system more stable, accurate, and fast.

  11. Communication for adaptive control

    Malik, Abdul Mubeen

    2010-01-01

    Ericsson developed the signal processing methods to be used in the digital power to increase the performance and the functionality of the converter. In the continuation of that the method of identifying the load of the DC/DC converter was developed in this project. The aim was to develop the algorithm that controls and communicate with the DC/DC converter “BMR450”. A current sensing circuit was been made for the voltage measurement in the DC/DC converter across the “inductor” in one part of t...

  12. 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.

  13. Adaptive controlling of power boiler

    Wojcik, W.; Kalita, M; Smolarz, A.

    2004-01-01

    This paper presents research on adaptive control (AC) of combastion process in in¬dustry. Results were obtained from research conducted in laboratory combustion chamber with usage of Fiber Optical Measurement System (FOMS) with electronic block. Simulation proved that implementing AC and FOMS to burning process improves flue gasses parameters -direct measure of power boiler ecologic and economical quality of work.

  14. Adaptive Control of Parabolic PDEs

    Smyshlyaev, Andrey

    2010-01-01

    This book introduces a comprehensive methodology for adaptive control design of parabolic partial differential equations with unknown functional parameters, including reaction-convection-diffusion systems ubiquitous in chemical, thermal, biomedical, aerospace, and energy systems. Andrey Smyshlyaev and Miroslav Krstic develop explicit feedback laws that do not require real-time solution of Riccati or other algebraic operator-valued equations. The book emphasizes stabilization by boundary control and using boundary sensing for unstable PDE systems with an infinite relative degree. The book also

  15. Multiple Regressive Model Adaptive Control

    Garipov, Emil; Stoilkov, Teodor; Kalaykov, Ivan

    2008-01-01

    The essence of the ideas applied to this text consists in the development of the strategy for control of the arbitrary in complexity continuous plant by means of a set of discrete timeinvariant linear controllers. Their number and tuned parameters correspond to the number and parameters of the linear time-invariant regressive models in the model bank, which approximate the complex plant dynamics in different operating points. Described strategy is known as Multiple Regressive Model Adaptive C...

  16. Adaptive Controller Effects on Pilot Behavior

    Trujillo, Anna C.; Gregory, Irene M.; Hempley, Lucas E.

    2014-01-01

    Adaptive control provides robustness and resilience for highly uncertain, and potentially unpredictable, flight dynamics characteristic. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the software adaptive control system and the pilot. An experiment was conducted to categorize these interactions on the pilot with an adaptive controller during control surface failures. One of the objectives of this experiment was to determine how the adaptation time of the controller affects pilots. The pitch and roll errors, and stick input increased for increasing adaptation time and during the segment when the adaptive controller was adapting. Not surprisingly, altitude, cross track and angle deviations, and vertical velocity also increase during the failure and then slowly return to pre-failure levels. Subjects may change their behavior even as an adaptive controller is adapting with additional stick inputs. Therefore, the adaptive controller should adapt as fast as possible to minimize flight track errors. This will minimize undesirable interactions between the pilot and the adaptive controller and maintain maneuvering precision.

  17. Adaptive feedback active noise control

    Kuo, Sen M.; Vijayan, Dipa

    Feedforward active noise control (ANC) systems use a reference sensor that senses a reference input to the controller. This signal is assumed to be unaffected by the secondary source and is a good measure of the undesired noise to be cancelled by the system. The reference sensor may be acoustic (e.g., microphone) or non-acoustic (e.g., tachometer, optical transducer). An obvious problem when using acoustic sensors is that the reference signal may be corrupted by the canceling signal generated by the secondary source. This problem is known as acoustic feedback. One way of avoiding this is by using a feedback active noise control (FANC) system which dispenses with the reference sensor. The FANC technique originally proposed by Olson and May employs a high gain negative feedback amplifier. This system suffered from the drawback that the error microphone had to be placed very close to the loudspeaker. The operation of the system was restricted to low frequency range and suffered from instability due to the possibility of positive feedback. Feedback systems employing adaptive filtering techniques for active noise control were developed. This paper presents the FANC system modeled as an adaptive prediction scheme.

  18. Adaptive Extremum Control and Wind Turbine Control

    Ma, Xin

    1997-01-01

    . Firstly, it is assumed that the nonlinear processes can be divided into a dynamic linear part and static nonlinear part. Consequently the processes with input nonlinearity and output nonlinearity are treated separately. With the nonlinearity at the input it is easy to set up a model which is linear in...... parameters, and thus directly lends itself to parameter estimation and adaptive control. The extremum control law is derived based on static optimization of a performance function. For a process with nonlinearity at output the intermediate signal between the linear part and nonlinear part plays an important...... measuring device. The investigation of control design is divided into below rated operation and above rated operation. Below ratedpower, the aim of control is to extract maximumenergy from the wind. The pitch angle of the rotor blades is xed at its optimal value and turbine speed is adjusted to follow...

  19. Adaptive Fuzzy Control for CVT Vehicle

    2005-01-01

    On the simple continuously variable transmission (CVT) driveline model, the design of adaptive fuzzy control system for CVT vehicle is presented. The adaptive fuzzy control system consists of a scaling factor self-tuning fuzzy-PI throttle controller, and a hybrid fuzzy-PID CVT ratio and brake controller. The presented adaptive fuzzy control strategy is vehicle model independent, which depends only on the instantaneous vehicle states, but does not depend on vehicle parameters. So it has good robustness against uncertain vehicle parameters and exogenous load disturbance. Simulation results show that the proposed adaptive fuzzy strategy has good adaptability and practicality value.

  20. Adaptive fuzzy controllers based on variable universe

    李洪兴

    1999-01-01

    Adaptive fuzzy controllers by means of variable universe are proposed based on interpolation forms of fuzzy control. First, monotonicity of control rules is defined, and it is proved that the monotonicity of interpolation functions of fuzzy control is equivalent to the monotonicity of control rules. This means that there is not any contradiction among the control rules under the condition for the control rules being monotonic. Then structure of the contraction-expansion factor is discussed. At last, three models of adaptive fuzzy control based on variable universe are given which are adaptive fuzzy control model with potential heredity, adaptive fuzzy control model with obvious heredity and adaptive fuzzy control model with successively obvious heredity.

  1. Flight Test Approach to Adaptive Control Research

    Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

    2011-01-01

    The National Aeronautics and Space Administration s Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The validation of adaptive controls has the potential to enhance safety in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

  2. Adaptive, predictive controller for optimal process control

    Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.

    1995-12-01

    One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.

  3. Robust adaptive control design for generator excitation

    Ni, Y.; Lan, Z.; Gan, D

    2006-01-01

    In this paper a new nonlinear robust adaptive excitation control strategy for multi-machine power systems is presented. The designed controller is adaptive to unknown generator parameters, and robust to model errors or disturbances. It is locally implemented and independent of network topology or load conditions. In the paper the power system model is presented and the control law and adaptive law are derived. The close-loop system stability is proven. Computer test results show clearly that ...

  4. Adaptive Vector Control of Induction Motor

    O. F. Opeiko

    2012-01-01

    Full Text Available A synthesis of adaptive PID controller has been executed for flux linkage and speed channels of a vector control system for an induction short-circuited motor. While using an imitation simulation method results of a synthesized system analysis show that the adaptive PID controller has some advantages under conditions of parametric disturbances affecting the object.

  5. On Adaptation of Loss Functions in Decentralized Adaptive Control

    Šmídl, Václav

    Villeneuve d'Ascq: IFAC, 2010, s. 1-6. [12th LSS symposium, Large Scale Systems: Theory and Applications. Villeneuve d'Ascq (FR), 12.07.2010-14.07.2010] R&D Projects: GA MŠk 1M0572; GA ČR GP102/08/P250 Institutional research plan: CEZ:AV0Z10750506 Keywords : decentralized control * LQG control * fully probabilistic design Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2010/AS/smidl-on adaptation of loss functions in decentralized adaptive control .pdf

  6. Operational reliability assessment of adaptive control strategies

    Adaptive control strategies carry a promise for on-line design of control actions in automation of nuclear power plants and components. Operational reliability analysis of a typical adaptive control algorithm is performed using failure modes and effects analysis. The adaptive controller is susceptible to failure characteristic of the process of model identification involved in the on-line design of the control. Means of failure detection and enhancement of the controller fault tolerance are sought as well as means of placing the controlled process and the plant into a safe state, or termination of the process in case of encountering control failure. Those means are incorporated in a supervisory system to monitor the control system performance, mitigate some of the failure consequences and alert the operator of the state of the plant. Recommendations are given of design improvement to upgrade the adaptive control system performance in nuclear environments. (author)

  7. Adaptive gain control during human perceptual choice

    Cheadle, Samuel; WYART, Valentin; Tsetsos, Konstantinos; Myers, Nicholas; de Gardelle, Vincent; Herce Castañón, Santiago; Summerfield, Christopher

    2014-01-01

    Neural systems adapt to background levels of stimulation. Adaptive gain control has been extensively studied in sensory systems, but overlooked in decision-theoretic models. Here, we describe evidence for adaptive gain control during the serial integration of decision-relevant information. Human observers judged the average information provided by a rapid stream of visual events (samples). The impact that each sample wielded over choices depended on its consistency with the previous sample, w...

  8. An adaptive model-free fuzzy controller

    In this paper, we present an adaptive, stable fuzzy controller whose parameters are optimized via a genetic algorithm. The controller model is capable of building itself on the basis of measured plant data and then of adapting to new dynamics. The stability of the overall system, made up of the plant and the controller, is guaranteed by Lyapunov's theory. As a case study, the stable adaptive fuzzy controller is employed to drive the narrow water level of a simulated Steam Generator (SG) to a desired reference trajectory. The numerical results confirm that the controller bears good performances in terms of small oscillations and fast settling time even in presence of external disturbances. (authors)

  9. Adaptive Method Using Controlled Grid Deformation

    Florin FRUNZULICA

    2011-09-01

    Full Text Available The paper presents an adaptive method using the controlled grid deformation over an elastic, isotropic and continuous domain. The adaptive process is controlled with the principal strains and principal strain directions and uses the finite elements method. Numerical results are presented for several test cases.

  10. Adaptive Control Based On Neural Network

    Wei, Sun; Lujin, Zhang; Jinhai, Zou; Siyi, Miao

    2009-01-01

    In this paper, the adaptive control based on neural network is studied. Firstly, a neural network based adaptive robust tracking control design is proposed for robotic systems under the existence of uncertainties. In this proposed control strategy, the NN is used to identify the modeling uncertainties, and then the disadvantageous effects caused by neural network approximating error and external disturbances in robotic system are counteracted by robust controller. Especially the proposed cont...

  11. Adaptive muffler based on controlled flow valves.

    Šteblaj, Peter; Čudina, Mirko; Lipar, Primož; Prezelj, Jurij

    2015-06-01

    An adaptive muffler with a flexible internal structure is considered. Flexibility is achieved using controlled flow valves. The proposed adaptive muffler is able to adapt to changes in engine operating conditions. It consists of a Helmholtz resonator, expansion chamber, and quarter wavelength resonator. Different combinations of the control valves' states at different operating conditions define the main working principle. To control the valve's position, an active noise control approach was used. With the proposed muffler, the transmission loss can be increased by more than 10 dB in the selected frequency range. PMID:26093462

  12. Flight Approach to Adaptive Control Research

    Pavlock, Kate Maureen; Less, James L.; Larson, David Nils

    2011-01-01

    The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on a full-scale F-18 testbed. The testbed served as a full-scale vehicle to test and validate adaptive flight control research addressing technical challenges involved with reducing risk to enable safe flight in the presence of adverse conditions such as structural damage or control surface failures. This paper describes the research interface architecture, risk mitigations, flight test approach and lessons learned of adaptive controls research.

  13. Adaptive control of sulphur recovery units

    Efficient removal of sulfur is important in the operation of a gas processing plant. Control of the sulfur recovery unit (SRU) is difficult using conventional controllers due to variations in gas composition and time delays within the recovery process itself. Adaptive controllers are well-suited to the problem of handling lengthy and varying process time delays. Adaptive controllers use a mathematical model of the process, including time delay, to forecast a process response. A new approach to adaptive control is presented which uses orthogonal functions to model the process. The transfer function required for implementing the controller can then be identified using a minimum of historical process information. The controller can do this while it controls the process, automatically adapting to changes in gain, time constants, or time delay in order to maintain optimal control. The sulfur recovery process is explained and test results are presented showing the performance of the new adaptive controller compared to the performance of a conventional controller in recovering sulfur and reducing SO2 emissions. The adaptive controller had a 38% lower standard deviation and the improved tail gas ratio control alone is estimated to have resulted in a 0.4% increase in sulfur recovery efficiency. Using the adaptive controller on other stages of the plant could raise the total improvement to 0.6-0.7%. Additional benefits of using the new controller include increased production, avoidance of major capital and operating expense to achieve increases in recovery efficiency, avoidance of penalties for exceeding sulfur emission limits, and extension of catalyst bed life. 3 refs., 8 figs., 2 tabs

  14. ADAPTIVE GENERALIZED PREDICTIVE CONTROL OF SWITCHED SYSTEMS

    WANG Yi-jing; WANG Long

    2005-01-01

    The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied. The switching law is determined by the output predictive errors of a finite number of subsystems. For the single subsystem and multiple subsystems cases, it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system. This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.

  15. Decentralized Adaptive Control For Robots

    Seraji, Homayoun

    1989-01-01

    Precise knowledge of dynamics not required. Proposed scheme for control of multijointed robotic manipulator calls for independent control subsystem for each joint, consisting of proportional/integral/derivative feedback controller and position/velocity/acceleration feedforward controller, both with adjustable gains. Independent joint controller compensates for unpredictable effects, gravitation, and dynamic coupling between motions of joints, while forcing joints to track reference trajectories. Scheme amenable to parallel processing in distributed computing system wherein each joint controlled by relatively simple algorithm on dedicated microprocessor.

  16. Digital adaptive control laws for VTOL aircraft

    Hartmann, G. L.; Stein, G.

    1979-01-01

    Honeywell has designed a digital self-adaptive flight control system for flight test in the VALT Research Aircraft (a modified CH-47). The final design resulted from a comparison of two different adaptive concepts: one based on explicit parameter estimates from a real-time maximum likelihood estimation algorithm and the other based on an implicit model reference adaptive system. The two designs are compared on the basis of performance and complexity.

  17. Adaptive LQ control: Conflict between identification and control

    Polderman, J.W.

    1989-01-01

    We consider one of the fundamental limitations of indirect adaptive control based on the minimization of a quadratic cost criterion and the certainty equivalence principle. We show that the interaction between (closed-loop) identification and optimal control is conflictive in the sense that almost all possible limits of the sequence of parameter estimates induce suboptimal behavior of the adaptively controlled system.

  18. Decentralized digital adaptive control of robot motion

    Tarokh, M.

    1990-01-01

    A decentralized model reference adaptive scheme is developed for digital control of robot manipulators. The adaptation laws are derived using hyperstability theory, which guarantees asymptotic trajectory tracking despite gross robot parameter variations. The control scheme has a decentralized structure in the sense that each local controller receives only its joint angle measurement to produce its joint torque. The independent joint controllers have simple structures and can be programmed using a very simple and computationally fast algorithm. As a result, the scheme is suitable for real-time motion control.

  19. Adaptive Feedfoward Feedback Control Framework Project

    National Aeronautics and Space Administration — An Adaptive Feedforward and Feedback Control (AFFC) Framework is proposed to suppress the aircraft's structural vibrations and to increase the resilience of the...

  20. Adaptive Control Applied to Financial Market Data

    Šindelář, Jan; Kárný, Miroslav

    Strasbourg cedex: European Science Foundation, 2007, s. 1-6. [Advanced Mathematical Methods for Finance. Vídeň (AT), 17.09.2007-22.09.2007] R&D Projects: GA MŠk(CZ) 2C06001 Institutional research plan: CEZ:AV0Z10750506 Keywords : bayesian statistics * portfolio optimization * finance * adaptive control Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2007/si/sindelar-adaptive control applied to financial market data.pdf

  1. Adaptive Control Algorithms, Analysis and Applications

    Landau, Ioan; Lozano, Rogelio; M'Saad, Mohammed; Karimi, Alireza

    2011-01-01

    Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the ...

  2. Simple adaptive tracking control for mobile robots

    Bobtsov, Alexey; Faronov, Maxim; Kolyubin, Sergey; Pyrkin, Anton

    2014-12-01

    The problem of simple adaptive and robust control is studied for the case of parametric and dynamic dimension uncertainties: only the maximum possible relative degree of the plant model is known. The control approach "consecutive compensator" is investigated. To illustrate the efficiency of proposed approach an example with the mobile robot motion control using computer vision system is considered.

  3. Switching Control for Adaptive Disturbance Attenuation

    Battistelli, Giorgio; Mari, Daniele; Selvi, Daniela; Tesi, Alberto; Tesi, Pietro

    2014-01-01

    The problem of adaptive disturbance attenuation is addressed in this paper using a switching control approach. A finite family of stabilizing controllers is pre-designed, with the assumption that, for any possible operating condition, at least one controller is able to achieve a prescribed level of

  4. Adaptive Sliding Mode Control for Hydraulic Drives

    Schmidt, Lasse; Andersen, Torben Ole; Pedersen, Henrik C.;

    2013-01-01

    This paper presents a new adaptive sliding mode controller generally applicable for position tracking control of electro-hydraulic valve-cylinder drives (VCD’s). The proposed control scheme requires limited knowledge on system parameters, and employs only piston- and valve spool position feedback...

  5. Multiple models adaptive feedforward decoupling controller

    Wang Xin; Li Shaoyuan; Wang Zhongjie

    2005-01-01

    When the parameters of the system change abruptly, a new multivariable adaptive feedforward decoupling controller using multiple models is presented to improve the transient response. The system models are composed of multiple fixed models, one free-running adaptive model and one re-initialized adaptive model. The fixed models are used to provide initial control to the process. The re-initialized adaptive model can be reinitialized as the selected model to improve the adaptation speed. The free-running adaptive controller is added to guarantee the overall system stability. At each instant, the best system model is selected according to the switching index and the corresponding controller is designed. During the controller design, the interaction is viewed as the measurable disturbance and eliminated by the choice of the weighting polynomial matrix. It not only eliminates the steady-state error but also decouples the system dynamically. The global convergence is obtained and several simulation examples are presented to illustrate the effectiveness of the proposed controller.

  6. Genetic algorithms in adaptive fuzzy control

    Karr, C. Lucas; Harper, Tony R.

    1992-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

  7. An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

    Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

    2008-01-01

    This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

  8. Adaptive Control Strategies for Flexible Robotic Arm

    Bialasiewicz, Jan T.

    1996-01-01

    The control problem of a flexible robotic arm has been investigated. The control strategies that have been developed have a wide application in approaching the general control problem of flexible space structures. The following control strategies have been developed and evaluated: neural self-tuning control algorithm, neural-network-based fuzzy logic control algorithm, and adaptive pole assignment algorithm. All of the above algorithms have been tested through computer simulation. In addition, the hardware implementation of a computer control system that controls the tip position of a flexible arm clamped on a rigid hub mounted directly on the vertical shaft of a dc motor, has been developed. An adaptive pole assignment algorithm has been applied to suppress vibrations of the described physical model of flexible robotic arm and has been successfully tested using this testbed.

  9. Adaptive Cruise Control and Driver Modeling

    Bengtsson, Johan

    2001-01-01

    Many vehicle manufacturers have lately introduced advance driver support in some of their automobiles. One of those new features is Adaptive Cruise Control DACCE, which extends the conventional cruise control system to control of relative speed and distance to other vehicles. In order to design an ACC controller it is suitable to have a model of driver behavior. The approach in the thesis is to use system identification methodology to obtain dynamic models of driver behavior useful for ACC ap...

  10. Reference model decomposition in direct adaptive control

    Butler, H.; Honderd, G.; Amerongen, van, W.E.

    1991-01-01

    This paper introduces the method of reference model decomposition as a way to improve the robustness of model reference adaptive control systems (MRACs) with respect to unmodelled dynamics with a known structure. Such unmodelled dynamics occur when some of the nominal plant dynamics are purposely neglected in the controller design with the aim of keeping the controller order low. One of the effects of such undermodelling of the controller is a violation of the perfect model-matching condition...

  11. Adaptive gain control during human perceptual choice

    Cheadle, Samuel; Wyart, Valentin; Tsetsos, Konstantinos; Myers, Nicholas; de Gardelle, Vincent; Castañón, Santiago Herce; Summerfield, Christopher

    2015-01-01

    Neural systems adapt to background levels of stimulation. Adaptive gain control has been extensively studied in sensory systems, but overlooked in decision-theoretic models. Here, we describe evidence for adaptive gain control during the serial integration of decision-relevant information. Human observers judged the average information provided by a rapid stream of visual events (samples). The impact that each sample wielded over choices depended on its consistency with the previous sample, with more consistent or expected samples wielding the greatest influence over choice. This bias was also visible in the encoding of decision information in pupillometric signals, and in cortical responses measured with functional neuroimaging. These data can be accounted for with a new serial sampling model in which the gain of information processing adapts rapidly to reflect the average of the available evidence. PMID:24656259

  12. Modelling and (adaptive) control of greenhouse climates

    Udink ten Cate, A.J.

    1983-01-01

    The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.System conceptsIn Chapters 1 and 2 an overview of the problem formulation is presented. It is suggested that there

  13. Robust adaptive neural network control with supervisory controller

    张天平; 梅建东

    2004-01-01

    The problem of direct adaptive neural network control for a class of uncertain nonlinear systems with unknown constant control gain is studied in this paper. Based on the supervisory control strategy and the approximation capability of multilayer neural networks (MNNs), a novel design scheme of direct adaptive neural network controller is proposed.The adaptive law of the adjustable parameter vector and the matrix of weights in the neural networks and the gain of sliding mode control term to adaptively compensate for the residual and the approximation error of MNNs is determined by using a Lyapunov method. The approach does not require the optimal approximation error to be square-integrable or the supremum of the optimal approximation error to be known. By theoretical analysis, the closed-loop control system is proven to be globally stable in the sense that all signals involved are bounded, with tracking error converging to zero.Simulation results demonstrate the effectiveness of the approach.

  14. Dynamics and Control of Adaptive Shells with Curvature Transformations

    Tzou, H.S.; Bao, Y.

    1995-01-01

    Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencie...

  15. Adaptive position controller for double armature brushless dc linear motor

    Demirci, R. [Abant Izzet Baysal Univ., Technical Education Faculty, Electrical Dept., Dunez (Turkey); Dursun, M. [Gazi University, Technical Education Faculty, Electrical Dept., Ankara (Turkey)

    2000-08-01

    An adaptive position controller has been proposed for double armature brushless DC linear motor. The proposed position control system comprises an inner model reference adaptive velocity control loop and an outer position control loop. The parameters of the adaptive controller have been adjusted by using modified gradient type parameter adaptation algorithm. (orig.)

  16. Logic reliability analysis of adaptive control strategies

    An approach is developed for the evaluation of the reliability of logic of adaptive control strategies, taking into account logic structural complexity and potential failure of programming modules. Flaws in the control system algorithm may not be discovered during debugging or initial testing and may only affect the performance under abnormal situations although the system may appear reliable in normal operations. Considering an adaptive control system designed for use in control of equipment employed in nuclear power stations, logic reliability evaluation is demonstrated. The approach given is applicable to any other designs and may be used to compare different control system logic structures from the reliability viewpoint. Evaluation of the reliability of control systems is essential to automated operation of equipment used in nuclear power plants. (author)

  17. Hybrid adaptive control of a dragonfly model

    Couceiro, Micael S.; Ferreira, Nuno M. F.; Machado, J. A. Tenreiro

    2012-02-01

    Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.

  18. Adaptive Piezoelectric Absorber for Active Vibration Control

    Sven Herold

    2016-02-01

    Full Text Available Passive vibration control solutions are often limited to working reliably at one design point. Especially applied to lightweight structures, which tend to have unwanted vibration, active vibration control approaches can outperform passive solutions. To generate dynamic forces in a narrow frequency band, passive single-degree-of-freedom oscillators are frequently used as vibration absorbers and neutralizers. In order to respond to changes in system properties and/or the frequency of excitation forces, in this work, adaptive vibration compensation by a tunable piezoelectric vibration absorber is investigated. A special design containing piezoelectric stack actuators is used to cover a large tuning range for the natural frequency of the adaptive vibration absorber, while also the utilization as an active dynamic inertial mass actuator for active control concepts is possible, which can help to implement a broadband vibration control system. An analytical model is set up to derive general design rules for the system. An absorber prototype is set up and validated experimentally for both use cases of an adaptive vibration absorber and inertial mass actuator. Finally, the adaptive vibration control system is installed and tested with a basic truss structure in the laboratory, using both the possibility to adjust the properties of the absorber and active control.

  19. Framework of Combined Adaptive and Non-adaptive Attitude Control System for a Helicopter Experimental System

    Akira Inoue; Ming-Cong Deng

    2006-01-01

    This paper presents a framework of a combined adaptive and non-adaptive attitude control system for a helicopter experimental system. The design method is based on a combination of adaptive nonlinear control and non-adaptive nonlinear control. With regard to detailed attitude control system design, two schemes are shown for different application cases.

  20. Adaptive control of solar energy collector systems

    Lemos, João M; Igreja, José M

    2014-01-01

    This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts

  1. Adaptive Control with Approximated Policy Search Approach

    Agus Naba

    2010-05-01

    Full Text Available Most of existing adaptive control schemes are designed to minimize error between plant state and goal state despite the fact that executing actions that are predicted to result in smaller errors only can mislead to non-goal states. We develop an adaptive control scheme that involves manipulating a controller of a general type to improve its performance as measured by an evaluation function. The developed method is closely related to a theory of Reinforcement Learning (RL but imposes a practical assumption made for faster learning. We assume that a value function of RL can be approximated by a function of Euclidean distance from a goal state and an action executed at the state. And, we propose to use it for the gradient search as an evaluation function. Simulation results provided through application of the proposed scheme to a pole-balancing problem using a linear state feedback controller and fuzzy controller verify the scheme’s efficacy.

  2. Adaptive control of nonlinear underwater robotic systems

    Thor I. Fossen

    1991-04-01

    Full Text Available The problem of controlling underwater mobile robots in 6 degrees of freedom (DOF is addressed. Uncertainties in the input matrix due to partly known nonlinear thruster characteristics are modeled as multiplicative input uncertainty. This paper proposes two methods to compensate for the model uncertainties: (1 an adaptive passivity-based control scheme and (2 deriving a hybrid (adaptive and sliding controller. The hybrid controller consists of a switching term which compensates for uncertainties in the input matrix and an on-line parameter estimation algorithm. Global stability is ensured by applying Barbalat's Lyapunovlike lemma. The hybrid controller is simulated for the horizontal motion of the Norwegian Experimental Remotely Operated Vehicle (NEROV.

  3. Evolving Systems and Adaptive Key Component Control

    Frost, Susan A.; Balas, Mark J.

    2009-01-01

    We propose a new framework called Evolving Systems to describe the self-assembly, or autonomous assembly, of actively controlled dynamical subsystems into an Evolved System with a higher purpose. An introduction to Evolving Systems and exploration of the essential topics of the control and stability properties of Evolving Systems is provided. This chapter defines a framework for Evolving Systems, develops theory and control solutions for fundamental characteristics of Evolving Systems, and provides illustrative examples of Evolving Systems and their control with adaptive key component controllers.

  4. Adaptive, Nonlinear Model Predictive Control for Accelerator Feedback Control Systems

    Variations in systems dynamics and modeling uncertainty(due to unmodeled systems behavior and/or presence of disturbances),have posed significant challenges to the effective luminosity and orbit control in accelerators.Problems of similar nature occur in a wide variety of other applications from chemical processes to power plants to financial systems.Adaptive control has long been pursued as a possible solution,but difficulties with online model identification and robust implementation of the adaptive control algorithms has prevented their widespread application.In general developing and maintaining appropriate models is the key to the success of any deployed control solution.Meanwhile the performance of the control system is contingent on the responsiveness of the control algorithm to the inevitable deviations of the model from the actual system.This project uses neural networks to detect significant changes in system behavior,and develops an optimal model-predictive-based adaptive control algorithm that enables the robust implementation of an effective control strategy that is applicable in a wide range of applications.Simulation studies were conducted to clearly demonstrate the feasibility and benefits of implementing model predictive control technology in accelerator control problems.The requirements for an effective commercial product that can meet the challenge of optimal model-predictive-based adaptive control technology were developed.A prototype for the optimal model-predictive-based adaptive control algorithm was developed for a well-known nonlinear temperature control problem for gas-phase reactors that proved the feasibility of the proposed approach.This research enables a commercial party to leverage the knowledge gained through collaboration with a national laboratory to develop new system identification and optimal model-predictive-based adaptive control software to address current and future challenges in process industries,power systems

  5. An asymptotically optimal nonparametric adaptive controller

    郭雷; 谢亮亮

    2000-01-01

    For discrete-time nonlinear stochastic systems with unknown nonparametric structure, a kernel estimation-based nonparametric adaptive controller is constructed based on truncated certainty equivalence principle. Global stability and asymptotic optimality of the closed-loop systems are established without resorting to any external excitations.

  6. Adaptive control system for gas producing wells

    Optimal adaptive automatic control system for gas producing wells cluster is proposed intended for solving the problem of stabilization of the output gas pressure in the cluster at conditions of changing gas flow rate and changing parameters of the wells themselves, providing the maximum high resource of hardware elements of automation

  7. Nonlinear and Adaptive Dynamic Control Allocation

    Tjønnås, Johannes

    2008-01-01

    This work addresses the control allocation problem for a nonlinear over-actuated time-varying system where parameters a¢ ne in the actuator dynamics and actuator force model may be assumed unknown. Instead of optimizing the control allocation at each time instant, a dynamic approach is considered by constructing update-laws that represent asymptotically optimal allocation search and adaptation. A previous result on uniform global asymptotic stability (UGAS) of the equilibrium of cascaded time...

  8. Robust and Adaptive Control With Aerospace Applications

    Lavretsky, Eugene

    2013-01-01

    Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems.  The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: ·         case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; ·         detailed background material for each chapter to motivate theoretical developments; ·         realistic examples and simulation data illustrating key features ...

  9. Humanoid Robot Arm Adaptive Control: Experimental Implementation

    Said G. Khan

    2014-01-01

    Full Text Available In this study, a partially model based adaptive control of humanoid robot arm is presented. The aim of the adaptive control scheme is to deal with the uncertain parameters in its own dynamic model such as link masses or actuators inertias as well as to cope with changing dynamics in the tasks like passing objects between a human and a robot. The main idea here is to derive a dynamic model of the robot’s arm via a software package and parameterized it. Then, employ the adaptive control scheme to identify uncertain parameters such as link masses and actuator inertias online. This scheme will also be suitable for the tasks where robot is lifting weight and or passing an object to a human or vice versa (which is the ultimate goal of this work. The adaptive scheme is simulated and experimentally tested on the Bristol Robotics Laboratory humanoid Bristol- Elumotion-Robot-Torso (BERT Arm. Humanoid BERT robot is developed as a collaboration between Bristol Robotics Laboratory and Elumotion (a Bristol based robotic company.

  10. On adaptive control of mobile slotted aloha networks

    Lim J.-T.

    1995-01-01

    Full Text Available An adaptive control scheme for mobile slotted ALOHA is presented and the effect of capture on the adaptive control scheme is investigated. It is shown that with the proper choice of adaptation parameters the adaptive control scheme can be made independent of the effect of capture.

  11. Improvement of Adaptive Cruise Control Performance

    Nakagami Takashi

    2010-01-01

    Full Text Available This paper describes the Adaptive Cruise Control system (ACC, a system which reduces the driving burden on the driver. The ACC system primarily supports four driving modes on the road and controls the acceleration and deceleration of the vehicle in order to maintain a set speed or to avoid a crash. This paper proposes more accurate methods of detecting the preceding vehicle by radar while cornering, with consideration for the vehicle sideslip angle, and also of controlling the distance between vehicles. By making full use of the proposed identification logic for preceding vehicles and path estimation logic, an improvement in driving stability was achieved.

  12. Safe and Optimal Adaptive Cruise Control

    Larsen, Kim Guldstrand; Mikučionis, Marius; Taankvist, Jakob Haahr

    2015-01-01

    In a series of contributions Olderog et al. have formulated and verified safety controllers for a number of lane-maneuvers on multilane roads. Their work is characterized by great clarity and elegance partly due to the introduction of a special-purpose Multi-Lane Spatial Logic. In this paper, we...... want to illustrate the potential of current modelchecking technology for automatic synthesis of optimal yet safe (collision-free) controllers. We demonstrate this potential on an Adaptive Cruise Control problem, being a small part of the overall safety problem considered by Olderog....

  13. Parallel computations and control of adaptive structures

    Park, K. C.; Alvin, Kenneth F.; Belvin, W. Keith; Chong, K. P. (Editor); Liu, S. C. (Editor); Li, J. C. (Editor)

    1991-01-01

    The equations of motion for structures with adaptive elements for vibration control are presented for parallel computations to be used as a software package for real-time control of flexible space structures. A brief introduction of the state-of-the-art parallel computational capability is also presented. Time marching strategies are developed for an effective use of massive parallel mapping, partitioning, and the necessary arithmetic operations. An example is offered for the simulation of control-structure interaction on a parallel computer and the impact of the approach presented for applications in other disciplines than aerospace industry is assessed.

  14. L1 adaptive control with sliding-mode based adaptive law

    Jie LUO; Chengyu CAO

    2015-01-01

    This paper presents an adaptive control scheme with an integration of sliding mode control into the L1 adaptive control architecture, which provides good tracking performance as well as robustness against matched uncertainties. Sliding mode control is used as an adaptive law in the L1 adaptive control architecture, which is considered as a virtual control of error dynamics between estimated states and real states. Low-pass filtering mechanism in the control law design prevents a discontinuous signal in the adaptive law from appearing in actual control signal while maintaining control accuracy. By using sliding mode control as a virtual control of error dynamics and introducing the low-pass filtered control signal, the chattering effect is eliminated. The performance bounds between the close-loop adaptive system and the closed-loop reference system are characterized in this paper. Numerical simulation is provided to demonstrate the performance of the presented adaptive control scheme.

  15. Adaptive control based on retrospective cost optimization

    Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)

    2012-01-01

    A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.

  16. Adaptive control of active filter using DSP

    In order to reduce output-voltage ripple of power supply, an active filter is necessary. In this paper, the active filter with DSP is proposed. The waveform from active filter can be flexibly improved by DSP programming. The output-voltage ripple can be enough reduced by mixing frequency components of the input-voltage ripple. The result of adaptive control using LMS algorism is presented. The improvement by using filtered-X method is discussed. (author)

  17. Adaptive Fuzzy Backstepping Control against Actuator Faults

    Fujiang Jin

    2011-01-01

    Full Text Available In this study, the problem of Fault-Tolerant Control (FTC for a class of uncertain nonlinear systems is studied. A novel FTC scheme is proposed to deal with both lock-in-place and loss of effectiveness faults of actuators. By employing fuzzy approximation and on-line adaptive updating, the proposed control scheme can tolerate the faults without detection and diagnosis mechanism. It is proved in theory that the FTC scheme can guarantee the closed-loop stability and desired output tracking performance in spite of all kinds of the faults and external disturbances. A simulation example is also included to show the effectiveness of the scheme.

  18. ADAPTIVE SUBOPTIMAL CONTROL OF INPUT CONSTRAINED PLANTS

    Valerii Azarskov

    2011-03-01

    Full Text Available Abstract. This paper deals with adaptive regulation of a discrete-time linear time-invariant plant witharbitrary bounded disturbances whose control input is constrained to lie within certain limits. The adaptivecontrol algorithm exploits the one-step-ahead control strategy and the gradient projection type estimationprocedure using the modified dead zone. The convergence property of the estimation algorithm is shown tobe ensured. The sufficient conditions guaranteeing the global asymptotical stability and simultaneously thesuboptimality of the closed-loop systems are derived. Numerical examples and simulations are presented tosupport the theoretical results.

  19. Adaptive Control Applied to Financial Market Data

    Šindelář, Jan; Kárný, Miroslav

    Vol. I. Praha : Matfyz press, 2007, s. 1-6. ISBN 978-80-7378-023-4. [Week of Doctoral Students 2007. Praha (CZ), 05.06.2007-08.06.2007] R&D Projects: GA MŠk(CZ) 2C06001 Institutional research plan: CEZ:AV0Z10750506 Keywords : baysian statistics * finance * financial engineering * stochastic control Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2007/si/sindelar-adaptive control applied to financial market data.pdf

  20. Adaptive Fuzzy Knowledge Based Controller for Autonomous Robot Motion Control

    Mbaitiga Zacharie

    2010-01-01

    Full Text Available Problem statement: Research into robot motion control offers research opportunities that will change scientists and engineers for year to come. Autonomous robots are increasingly evident in many aspects of industry and everyday life and a robust robot motion control can be used for homeland security and many consumer applications. This study discussed the adaptive fuzzy knowledge based controller for robot motion control in indoor and outdoor environment. Approach: The proposed method consisted of two components: the process monitor that detects changes in the process characteristics and the adaptation mechanism that used information passed to it by the process monitor to update the controller parameters. Results: Experimental evaluation had been done in both indoor and outdoor environment where the robot communicates with the base station through its Wireless fidelity antenna and the performance monitor used a set of five performance criteria to access the fuzzy knowledge based controller. Conclusion: The proposed method had been found to be robust.

  1. Direct adaptive control for nonlinear uncertain dynamical systems

    Hayakawa, Tomohisa

    In light of the complex and highly uncertain nature of dynamical systems requiring controls, it is not surprising that reliable system models for many high performance engineering and life science applications are unavailable. In the face of such high levels of system uncertainty, robust controllers may unnecessarily sacrifice system performance whereas adaptive controllers are clearly appropriate since they can tolerate far greater system uncertainty levels to improve system performance. In this dissertation, we develop a Lyapunov-based direct adaptive and neural adaptive control framework that addresses parametric uncertainty, unstructured uncertainty, disturbance rejection, amplitude and rate saturation constraints, and digital implementation issues. Specifically, we consider the following research topics; direct adaptive control for nonlinear uncertain systems with exogenous disturbances; robust adaptive control for nonlinear uncertain systems; adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints; adaptive reduced-order dynamic compensation for nonlinear uncertain systems; direct adaptive control for nonlinear matrix second-order dynamical systems with state-dependent uncertainty; adaptive control for nonnegative and compartmental dynamical systems with applications to general anesthesia; direct adaptive control of nonnegative and compartmental dynamical systems with time delay; adaptive control for nonlinear nonnegative and compartmental dynamical systems with applications to clinical pharmacology; neural network adaptive control for nonlinear nonnegative dynamical systems; passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems; neural network adaptive dynamic output feedback control for nonlinear nonnegative systems using tapped delay memory units; Lyapunov-based adaptive control framework for discrete-time nonlinear systems with exogenous disturbances

  2. Comments on 'Hamiltonian adaptive control of spacecraft'

    Fossen, Thor I.

    1993-04-01

    In the adaptive scheme presented by Slotine and Benedetto (1990) for attitude tracking control of rigid spacecraft, the spacecraft is parameterized in terms of the inertial frame. This note shows how a parameterization in body coordinates considerably simplifies the representation of the adaptation scheme. The new symbolic expression for the regressor matrix is easy to find even for 6-degrees of freedom (DOF) Hamiltonian systems with a large number of unknown parameters. If the symbolic expression for the regressor matrix is known in advance, the computational complexity is approximately equal for both representations. In the scheme presented by Slotine and Benedetto this is not trivial because the transformation matrix between the inertial frame and the body coordinates is included in the expression for the regressor matrix. Hence, implementation for higher DOF systems is strongly complicated. An example illustrates the advantage of the new representation when modeling a simple three-DOF model of the lateral motion of a space shuttle.

  3. Robust adaptive control for Unmanned Aerial Vehicles

    Kahveci, Nazli E.

    The objective of meeting higher endurance requirements remains a challenging task for any type and size of Unmanned Aerial Vehicles (UAVs). According to recent research studies significant energy savings can be realized through utilization of thermal currents. The navigation strategies followed across thermal regions, however, are based on rather intuitive assessments of remote pilots and lack any systematic path planning approaches. Various methods to enhance the autonomy of UAVs in soaring applications are investigated while seeking guarantees for flight performance improvements. The dynamics of the aircraft, small UAVs in particular, are affected by the environmental conditions, whereas unmodeled dynamics possibly become significant during aggressive flight maneuvers. Besides, the demanded control inputs might have a magnitude range beyond the limits dictated by the control surface actuators. The consequences of ignoring these issues can be catastrophic. Supporting this claim NASA Dryden Flight Research Center reports considerable performance degradation and even loss of stability in autonomous soaring flight tests with the subsequent risk of an aircraft crash. The existing control schemes are concluded to suffer from limited performance. Considering the aircraft dynamics and the thermal characteristics we define a vehicle-specific trajectory optimization problem to achieve increased cross-country speed and extended range of flight. In an environment with geographically dispersed set of thermals of possibly limited lifespan, we identify the similarities to the Vehicle Routing Problem (VRP) and provide both exact and approximate guidance algorithms for the navigation of automated UAVs. An additional stochastic approach is used to quantify the performance losses due to incorrect thermal data while dealing with random gust disturbances and onboard sensor measurement inaccuracies. One of the main contributions of this research is a novel adaptive control design with

  4. Blowdown wind tunnel control using an adaptive fuzzy PI controller

    Corneliu Andrei NAE

    2013-09-01

    Full Text Available The paper presents an approach towards the control of a supersonic blowdown wind tunnel plant (as evidenced by experimental data collected from “INCAS Supersonic Blowdown Wind Tunnel” using a PI type controller. The key to maintain the imposed experimental conditions is the control of the air flow using the control valve of the plant. A proposed mathematical model based on the control valve will be analyzed using the PI controller. This control scheme will be validated using experimental data collected from real test cases. In order to improve the control performances an adaptive fuzzy PI controller will be implemented in SIMULINK in the present paper. The major objective is to reduce the transient regimes and the global reduction of the start-up loads on the models during this phase.

  5. Control adaptable utilizando Redes Neuronales Artificiales Polinomiales

    Gómez, E.; A. S. Poznyak; Lozano, R, R.

    2000-01-01

    Existen en la literatura de Control Adaptable, diferentes procedimientos en los que es posible identificar un sistema lineal. El problema fundamental es que una cantidad importante de fenómenos de la vida real son de tipo no lineal y no es tan sencillo el modelar este tipo de dinámicas. En este trabajo se presenta una forma de identificar sistemas no lineales utilizando las propiedades de las Redes Neuronales Artificiales y las técnicas de Algoritmo Genético en la optimización de ...

  6. Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

    Frost, Susan A.; Balas, Mark J.

    2011-01-01

    Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

  7. Myoelectric Control for Adaptable Biomechanical Energy Harvesting.

    Selinger, Jessica C; Donelan, J Maxwell

    2016-03-01

    We have designed and tested a myoelectric controller that automatically adapts energy harvesting from the motion of leg joints to match the power available in different walking conditions. To assist muscles in performing negative mechanical work, the controller engages power generation only when estimated joint mechanical power is negative. When engaged, the controller scales its resistive torque in proportion to estimated joint torque, thereby automatically scaling electrical power generation in proportion to the available mechanical power. To produce real-time estimates of joint torque and mechanical power, the controller leverages a simple model that predicts these variables from measured muscle activity and joint angular velocity. We first tested the model using available literature data for a range of walking speeds and found that estimates of knee joint torque and power well match the corresponding literature profiles (torque R(2): 0.73-0.92; power R(2): 0.60-0.94). We then used human subject experiments to test the performance of the entire controller. Over a range of steady state walking speeds and inclines, as well as a number of non-steady state walking conditions, the myoelectric controller accurately identified when the knee generated negative mechanical power, and automatically adjusted the magnitude of electrical power generation. PMID:26841402

  8. Adaptive Control of Flexible Structures Using Residual Mode Filters

    Balas, Mark J.; Frost, Susan

    2010-01-01

    Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.

  9. Adaptive quality control for multimedia communications

    Santichai Chuaywong

    2008-01-01

    Full Text Available Multimedia communications are communications with several types of media, such as audio, video and data. The current Internet has some levels of capability to support multimedia communications, unfortunately, the QoS (Quality of Service is still challenging. A large number of QoS mechanisms has been proposed; however, the main concern is for low levels, e.g. layer 2 (Data Link or 3 (Transport. In this paper, mechanisms for control the quality of audio and video are proposed. G.723.1 and MPEG-4 are used as the audio and video codec respectively. The proposed algorithm for adaptive quality control of audio communication is based on forward error correction (FEC. In the case of video communication, the proposed algorithm adapts the value of key frame interval, which is an encoding parameter of MPEG-4. We evaluated our proposed algorithms by computer simulation. We have shown that, in most cases, the proposed scheme gained a higher throughput compared to other schemes.

  10. Adaptive collaborative control of highly redundant robots

    Handelman, David A.

    2008-04-01

    The agility and adaptability of biological systems are worthwhile goals for next-generation unmanned ground vehicles. Management of the requisite number of degrees of freedom, however, remains a challenge, as does the ability of an operator to transfer behavioral intent from human to robot. This paper reviews American Android research funded by NASA, DARPA, and the U.S. Army that attempts to address these issues. Limb coordination technology, an iterative form of inverse kinematics, provides a fundamental ability to control balance and posture independently in highly redundant systems. Goal positions and orientations of distal points of the robot skeleton, such as the hands and feet of a humanoid robot, become variable constraints, as does center-of-gravity position. Behaviors utilize these goals to synthesize full-body motion. Biped walking, crawling and grasping are illustrated, and behavior parameterization, layering and portability are discussed. Robotic skill acquisition enables a show-and-tell approach to behavior modification. Declarative rules built verbally by an operator in the field define nominal task plans, and neural networks trained with verbal, manual and visual signals provide additional behavior shaping. Anticipated benefits of the resultant adaptive collaborative controller for unmanned ground vehicles include increased robot autonomy, reduced operator workload and reduced operator training and skill requirements.

  11. Adaptive Torque Control of Variable Speed Wind Turbines

    Johnson, K. E.

    2004-08-01

    The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry for variable speed wind turbines below rated power. This adaptive controller uses a simple, highly intuitive gain adaptation law designed to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds.

  12. Synthesis of Adaptive Gain Robust Controllers for Polytopic Uncertain Systems

    Hidetoshi Oya; Daisuke Yamasaki; Shunya Nagai; Kojiro Hagino

    2015-01-01

    We present a new adaptive gain robust controller for polytopic uncertain systems. The proposed adaptive gain robust controller consists of a state feedback law with a fixed gain and a compensation input with adaptive gains which are tuned by updating laws. In this paper, we show that sufficient conditions for the existence of the proposed adaptive gain robust controller are given in terms of LMIs. Finally, illustrative examples are presented to show the effectiv...

  13. An adaptive control system for wing TE shape control

    Dimino, I.; Concilio, A.; Schueller, M.; Gratias, A.

    2013-03-01

    A key technology to enable morphing aircraft for enhanced aerodynamic performance is the design of an adaptive control system able to emulate target structural shapes. This paper presents an approach to control the shape of a morphing wing by employing internal, integrated actuators acting on the trailing edge. The adaptive-wing concept employs active ribs, driven by servo actuators, controlled in turn by a dedicated algorithm aimed at shaping the wing cross section, according to a pre-defined geometry. The morphing control platform is presented and a suitable control algorithm is implemented in a dedicated routine for real-time simulations. The work is organized as follows. A finite element model of the uncontrolled, non-actuated structure is used to obtain the plant model for actuator torque and displacement control. After having characterized and simulated pure rotary actuator behavior over the structure, selected target wing shapes corresponding to rigid trailing edge rotations are achieved through both open-loop and closed-loop control logics.

  14. Model reference adaptive control and adaptive stability augmentation

    Henningsen, Arne; Ravn, Ole

    1993-01-01

    A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...

  15. Model reference adaptive control and adaptive stability augmentation

    Henningsen, Arne; Ravn, Ole

    A comparison of the standard concepts in MRAC design suggests that a combination of the implicit and the explicit design techniques may lead to an improvement of the overall system performance in the presence of unmodelled dynamics. Using the ideas of adaptive stability augmentation a combined...

  16. Adaptive nonlinear control for a research reactor

    Linearization by feedback of states is based on the idea of transform the nonlinear dynamic equation of a system in a linear form. This linear behavior can be achieve well in a complete way (input state) or in partial way (input output). This can be applied to systems of single or multiple inputs, and can be used to solve problems of stabilization and tracking of references trajectories. Comparing this method with conventional ones, linearization by feedback of states is exact in certain region of the space of state, instead of linear approximations of the equations in a certain point of the operation. In the presence of parametric uncertainties in the model of the system, the introduction of adaptive schemes provide a type toughness to the control system by nonlinear feedback, which gives as result the eventual cancellation of the nonlinear terms in the dynamic relationship between the output and the input of the auxiliary control. In the same way, it has been presented the design of a nonlinearizing control for the non lineal model of a TRIGA Mark III type reactor, with the aim of tracking a predetermined power profile. The asymptotic tracking of such profile is, at the present moment, in the stage of verification by computerized simulation the relative easiness in the design of auxiliary variable of control, as well as the decoupling action of the output variable, make very attractive the utilization of the method herein presented. (Author)

  17. A new adaptive scheme for the adaptive linearizing control of bioprocesses

    Ferreira, E. C.; Azevedo, S. Feyo de

    1996-01-01

    This work deals with the development of model-based adaptive control algorithms for bioprocess operation. Non-linear adaptive control laws are proposed for single input single output regulation. Parameters are continuously adapted following a new adaptive scheme which ensures second-order dynamics of the parameter error system. A computational study is presented of the application of this theory to baker’s yeast fermentation. Results put in evidence the efficient performance both of ...

  18. Adaptive Dynamic Surface Control for Generator Excitation Control System

    Zhang Xiu-yu

    2014-01-01

    Full Text Available For the generator excitation control system which is equipped with static var compensator (SVC and unknown parameters, a novel adaptive dynamic surface control scheme is proposed based on neural network and tracking error transformed function with the following features: (1 the transformation of the excitation generator model to the linear systems is omitted; (2 the prespecified performance of the tracking error can be guaranteed by combining with the tracking error transformed function; (3 the computational burden is greatly reduced by estimating the norm of the weighted vector of neural network instead of the weighted vector itself; therefore, it is more suitable for the real time control; and (4 the explosion of complicity problem inherent in the backstepping control can be eliminated. It is proved that the new scheme can make the system semiglobally uniformly ultimately bounded. Simulation results show the effectiveness of this control scheme.

  19. A hybrid adaptive control strategy for a smart prosthetic hand

    Chen, Cheng-Hung; Naidu, D. Subbaram; Perez-Gracia, Alba; Schoen, Marco P.

    2009-01-01

    This paper presents a hybrid of a soft computing technique of adaptive neuro-fuzzy inference system (ANFIS) and a hard computing technique of adaptive control for a two- dimensional movement of a prosthetic hand with a thumb and index finger. In particular, ANFIS is used for inverse kinematics, and the adaptive control is used for linearized dynamics to minimize tracking error. The simulations of this hybrid controller, when compared with the proportional-integral-derivative (PID) controller s...

  20. Adaptive Controller Design for Continuous Stirred Tank Reactor

    Prabhu, K; V. Murali Bhaskaran

    2014-01-01

    Continues Stirred Tank Reactor (CSTR) is an important issue in chemical process and a wide range of research in the area of chemical engineering. Temperature Control of CSTR has been an issue in the chemical control engineering since it has highly non-linear complex equations. This study presents problem of temperature control of CSTR with the adaptive Controller. The Simulation is done in MATLAB and result shows that adaptive controller is an efficient controller for temperature control of C...

  1. Modular and Adaptive Control of Sound Processing

    van Nort, Douglas

    parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.

  2. Adaptive Inverse Optimal Control of a Magnetic Levitation System

    SATOH, YASUYUKI; Nakamura, Hisakazu; Katayama, Hitoshi; Nishitani, Hirokazu

    2009-01-01

    In this article, we proposed an adaptive inverse optimal controller for the magnetic levitation system. First, we designed an inverse optimal controller with a pre-feedback gravity compensator and applied it to the magnetic levitation system. However, this controller cannot guarantee any stability margin. We demonstrated that the controller did not work well (offset error remained) in the experiment. Hence, we proposed an improved controller via an adaptive control technique to guarantee the ...

  3. Adaptive Landing Gear: Optimum Control Strategy and Potential for Improvement

    Grzegorz Mikułowski; Łukasz Jankowski

    2009-01-01

    An adaptive landing gear is a landing gear (LG) capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~va...

  4. System Dynamics and Adaptive Control for MEMS Gyroscope Sensor

    Juntao Fei; Hongfei Ding

    2010-01-01

    This paper presents an adaptive control approach for Micro-Electro-Mechanical Systems (MEMS) z-axis gyroscope sensor. The dynamical model of MEMS gyroscope sensor is derived and adaptive state tracking control for MEMS gyroscope is developed. The proposed adaptive control approaches can estimate the angular velocity and the damping and stiffness coefficients including the coupling terms due to the fabrication imperfection. The stability of the closed-loop systems is established with the propo...

  5. Adaptive tracking control of nonholonomic systems : an example

    Lefeber, AAJ Erjen; Nijmeijer, H Henk

    1999-01-01

    We study an example of an adaptive (state) tracking control problem for a four-wheel mobile robot, as it is an illustrative example of the general adaptive state-feedback tracking control problem. It turns out that formulating the adaptive state-feedback tracking control problem is not straightforward, since specifying the reference state-trajectory can be in conflict with not knowing certain parameters. Our example illustrates this difficulty and we propose a problem formulation for the adap...

  6. Robust adaptive control of continuous system with unknown deadzone

    2000-01-01

    Presents an adaptive controller for continuous systems with unknown deadzones and known linear part which consists of an adaptive deadzone inverse to cancel the effects of deadzone and a linear-like control law to track the system output. It concludes from simulation results that this control possesses good robustness and improves the tracking performance of the system.

  7. Adaptation in the fuzzy self-organising controller

    Jantzen, Jan; Poulsen, Niels Kjølstad

    2003-01-01

    This simulation study provides an analysis of the adaptation mechanism in the self-organising fuzzy controller, SOC. The approach is to apply a traditional adaptive control viewpoint. A simplified performance measure in the SOC controller is used in a loss function, and thus the MIT rule implies an...

  8. Adaptive Linear Parameter Varying Control for Aeroservoelastic Suppression Project

    National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill present and future aircraft safety objectives though automated vehicle recovery while maintaining performance and...

  9. Nonlinear Direct Robust Adaptive Control Using Lyapunov Method

    Chunbo Xiu

    2013-07-01

    Full Text Available    The problem of robust adaptive stabilization of a class of multi-input nonlinear systems with arbitrary unknown parameters and unknown structure of bounded variation have been considered. By employing the direct adaptive and control Lyapunov function method, a robust adaptive controller is designed to complete the globally adaptive stability of the system states. By employing our result, a kind of nonlinear system is analyzed, the concrete form of the control law is given and the meaningful quadratic control Lyapunov function for the system is constructed. Simulation of parallel manipulator is provided to illustrate the effectiveness of the proposed method.

  10. Adaptive Clutch Engaging Process Control for Automatic Mechanical Transmission

    LIU Hai-ou; CHEN Hui-yan; DING Hua-rong; HE Zhong-bo

    2005-01-01

    Based on detail analysis of clutch engaging process control targets and adaptive demands, a control strategy which is based on speed signal, different from that of based on main clutch displacement signal, is put forward. It considers both jerk and slipping work which are the most commonly used quality evaluating indexes of vehicle starting phase. The adaptive control system and its reference model are discussed profoundly.Taking the adaptability to different starting gears and different road conditions as examples, some proving field test records are shown to illustrate the main clutch adaptive control strategy at starting phase. Proving field test gives acceptable results.

  11. Adaptive Linear Parameter Varying Control for Aeroservoelastic Suppression Project

    National Aeronautics and Space Administration — Adaptive control offers an opportunity to fulfill aircraft safety objectives though automated vehicle recovery while maintaining performance and stability...

  12. Dynamics and Control of Adaptive Shells with Curvature Transformations

    H.S. Tzou

    1995-01-01

    Full Text Available Adaptive structures with controllable geometries and shapes are rather useful in many engineering applications, such as adaptive wings, variable focus mirrors, adaptive machines, micro-electromechanical systems, etc. Dynamics and feedback control effectiveness of adaptive shells whose curvatures are actively controlled and continuously changed are evaluated. An adaptive piezoelectric laminated cylindrical shell composite with continuous curvature changes is studied, and its natural frequencies and controlled damping ratios are evaluated. The curvature change of the adaptive shell starts from an open shallow shell (30° and ends with a deep cylindrical shell (360°. Dynamic characteristics and control effectiveness (via the proportional velocity feedback of this series of shells are investigated and compared at every 30° curvature change. Analytical solutions suggest that the lower modes are sensitive to curvature changes and the higher modes are relatively insensitive.

  13. Simulation and Rapid Prototyping of Adaptive Control Systems using the Adaptive Blockset for Simulink

    Ravn, Ole

    1998-01-01

    The paper describes the design considerations and implementational aspects of the Adaptive Blockset for Simulink which has been developed in a prototype implementation. The concept behind the Adaptive Blockset for Simulink is to bridge the gap between simulation and prototype controller...... implementation. This is done using the code generation capabilities of Real Time Workshop in combination with C s-function blocks for adaptive control in Simulink. In the paper the design of each group of blocks normally found in adaptive controllers is outlined. The block types are, identification, controller...... design, controller and state variable filter.The use of the Adaptive Blockset is demonstrated using a simple laboratory setup. Both the use of the blockset for simulation and for rapid prototyping of a real-time controller are shown....

  14. Neural Control of Chronic Stress Adaptation

    James Herman

    2013-08-01

    Full Text Available Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced stress reactivity and eventually become maladaptive. The long-term impact of stress is kept in check by the process of habituation, which reduces HPA axis responses upon repeated exposure to homotypic stressors and likely limits deleterious actions of prolonged glucocorticoid secretion. Habituation is regulated by limbic stress-regulatory sites, and is at least in part glucocorticoid feedback-dependent. Chronic stress also sensitizes reactivity to new stimuli. While sensitization may be important in maintaining response flexibility in response to new threats, it may also add to the cumulative impact of glucocorticoids on the brain and body. Finally, unpredictable or severe stress exposure may cause long-term and lasting dysregulation of the HPA axis, likely due to altered limbic control of stress effector pathways. Stress-related disorders, such as depression and PTSD, are accompanied by glucocorticoid imbalances and structural/ functional alterations in limbic circuits that resemble those seen following chronic stress, suggesting that inappropriate processing of stressful information may be part of the pathological process.

  15. Synthetic consciousness: the distributed adaptive control perspective.

    Verschure, Paul F M J

    2016-08-19

    Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'. PMID

  16. Experimental investigation of adaptive control of a parallel manipulator

    Nguyen, Charles C.; Antrazi, Sami S.

    1992-01-01

    The implementation of a joint-space adaptive control scheme used to control non-compliant motion of a Stewart Platform-based Manipulator (SPBM) is presented. The SPBM is used in a facility called the Hardware Real-Time Emulator (HRTE) developed at Goddard Space Flight Center to emulate space operations. The SPBM is comprised of two platforms and six linear actuators driven by DC motors, and possesses six degrees of freedom. The report briefly reviews the development of the adaptive control scheme which is composed of proportional-derivative (PD) controllers whose gains are adjusted by an adaptation law driven by the errors between the desired and actual trajectories of the SPBM actuator lengths. The derivation of the adaptation law is based on the concept of model reference adaptive control (MRAC) and Lyapunov direct method under the assumption that SPBM motion is slow as compared to the controller adaptation rate. An experimental study is conducted to evaluate the performance of the adaptive control scheme implemented to control the SPBM to track a vertical and circular paths under step changes in payload. Experimental results show that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.

  17. Neuro-Genetic Adaptive Optimal Controller for DC Motor

    Mahmoud Mohamed Elkholy; Mohammed Abd Elhameed Abd Elnaiem

    2014-01-01

    Conventional speed controllers of DC motors suffer from being not adaptive, this is because of the nonlinearity in the motor model due to saturation. Structure of DC motor speed controller should vary according to its operating conditions, so that the transient performance is acceptable. In this paper an adaptive and optimal Neuro-Genetic controller is used to control a DC motor speed. GA will be used first to obtain the optimal controller parameter for each load torque and motor refer...

  18. STOCHASTIC ADAPTIVE SWITCHING CONTROL BASED ON MULTIPLE MODELS

    ZHANG Yanxia; GUO Lei

    2002-01-01

    It is well known that the transient behaviors of the traditional adaptive control may be very poor in general, and that the adaptive control designed based on switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances. In this paper, we shall prove that for a typical class of linear systems disturbed by random noises, the multiple model based least-squares (LS)adaptive switching control is stable and convergent, and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators. Moreover,the mixed case combining adaptive models with fixed models is also considered.

  19. Pulse front control with adaptive optics

    Sun, B.; Salter, P. S.; Booth, M. J.

    2016-03-01

    The focusing of ultrashort laser pulses is extremely important for processes including microscopy, laser fabrication and fundamental science. Adaptive optic elements, such as liquid crystal spatial light modulators or membrane deformable mirrors, are routinely used for the correction of aberrations in these systems, leading to improved resolution and efficiency. Here, we demonstrate that adaptive elements used with ultrashort pulses should not be considered simply in terms of wavefront modification, but that changes to the incident pulse front can also occur. We experimentally show how adaptive elements may be used to engineer pulse fronts with spatial resolution.

  20. Adaptive Intelligent Ventilation Noise Control Project

    National Aeronautics and Space Administration — To address the NASA need for quiet on-orbit crew quarters (CQ), Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...

  1. Adaptive Intelligent Ventilation Noise Control Project

    National Aeronautics and Space Administration — To address NASA needs for quiet crew volumes in a space habitat, Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...

  2. SOFC temperature evaluation based on an adaptive fuzzy controller

    Xiao-juan WU; Xin-jian ZHU; Guang-yi CAO; Heng-yong TU

    2008-01-01

    The operating temperature of a solid oxide fuel cell (SOFC) stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative (PID) control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.

  3. Adaptive sliding mode control for a class of chaotic systems

    Farid, R.; Ibrahim, A.; Zalam, B., E-mail: ramy5475@yahoo.com [Menofia University, Faculty of Electronic Engineering, Department of Industrial Electronics and Control, Menuf, Menofia (Egypt)

    2015-03-30

    Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller.

  4. Adaptive learning fuzzy control of a mobile robot

    In this report a problem is studied to construct a fuzzy controller for a mobile robot to move autonomously along a given reference direction curve, for which control rules are generated and acquired through an adaptive learning process. An adaptive learning fuzzy controller has been developed for a mobile robot. Good properties of the controller are shown through the travelling experiments of the mobile robot. (author)

  5. Discrete Model Reference Adaptive Control System for Automatic Profiling Machine

    Peng Song; Guo-kai Xu; Xiu-chun Zhao

    2012-01-01

    Automatic profiling machine is a movement system that has a high degree of parameter variation and high frequency of transient process, and it requires an accurate control in time. In this paper, the discrete model reference adaptive control system of automatic profiling machine is discussed. Firstly, the model of automatic profiling machine is presented according to the parameters of DC motor. Then the design of the discrete model reference adaptive control is proposed, and the control rules...

  6. Adaptive sliding mode control for a class of chaotic systems

    Chaos control here means to design a controller that is able to mitigating or eliminating the chaos behavior of nonlinear systems that experiencing such phenomenon. In this paper, an Adaptive Sliding Mode Controller (ASMC) is presented based on Lyapunov stability theory. The well known Chua's circuit is chosen to be our case study in this paper. The study shows the effectiveness of the proposed adaptive sliding mode controller

  7. Systems and Methods for Derivative-Free Adaptive Control

    Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor); Calise, Anthony J. (Inventor)

    2015-01-01

    An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

  8. An adaptive active control for the modified Chua's circuit

    In this Letter, it is shown that a couple of the modified Chua's systems with different parameters and initial conditions can be synchronized using active control when the values of parameters both in drive system and response system are known aforehand. Furthermore, an adaptive active control approach is proposed based on Lyapunov stability theory to make the states of two identical Chua's systems with unknown constant parameters be asymptotically synchronized. In addition, the proposed adaptive active control method guarantees that the designed controller is independent to those uncertain parameters. Simulation results by using both active control and adaptive active control are provided, and the feasibility and effectiveness of the proposed adaptive active control are demonstrated

  9. Flexible Satellite Attitude Control via Adaptive Fuzzy Linearization

    GUAN Ping; LIU Xiang-dong; CHEN Jia-bin; LIU Xiao-he

    2005-01-01

    The adaptive fuzzy control is combined with input-output linearization control to constitute the hybrid controller. The control method is then applied to the attitude maneuver control of the flexible satellite.The basic control structure is given. The rules of the controller parameter selection, which guarantee the attitude stabilization of the satellite with parameter uncertainties, have been analyzed. Simulation results show that the precise attitude control is accomplished in spite of the uncertainty in the system.

  10. The Reduced-order Design of Robust Adaptive Backstepping Controller

    WUZhao-Jing; XIEXue-Jun; ZHANGSi-Ying

    2005-01-01

    For a class of systems with unmodeled dynamics, robust adaptive stabilization problem is considered in this paper. Firstly, by a series of coordinate changes, the original system is reparameterized. Then, by introducing a reduced-order observer, an error system is obtained. Based on the system, a reduced-order adaptive backstepping controller design scheme is given. It is proved that all the signals in the adaptive control system are globally uniformly bounded, and the regulation error converges to zero asymptotically. Due to the order deduction of the controller, the design scheme in this paper has more practical values. A simulation example further demonstrates the efficiency of the control scheme.

  11. Linear Perturbation Adaptive Control of Hydraulically Driven Manipulators

    Andersen, T.O.; Hansen, M.R.; Conrad, Finn

    2004-01-01

    A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation...... control.Using the Lyapunov approach, under slowly time-varying assumptions, it is shown that the tracking error and the parameter error remain bounded. This bound is a function of the ideal parameters and a bounded disturbance. The control algorithm decouples and linearizes the manipulator so that each...... joint behaves as an independent second-order system with fixed dynamics....

  12. Linear Perturbation Adaptive Control of Hydraulically Driven Manipulators

    Andersen, T.O.; Hansen, M.R.; Conrad, Finn

    control.Using the Lyapunov approach, under slowly time-varying assumptions, it is shown that the tracking error and the parameter error remain bounded. This bound is a function of the ideal parameters and a bounded disturbance. The control algorithm decouples and linearizes the manipulator so that each......A method for synthesis of a robust adaptive scheme for a hydraulically driven manipulator, that takes full advantage of any known system dynamics to simplify the adaptive control problem for the unknown portion of the dynamics is presented. The control method is based on adaptive perturbation...

  13. Adaptive control strategies for cooperative dual-arm manipulators

    Seraji, H.

    1987-01-01

    Three strategies for adaptive control of cooperative dual-arm robots are discussed. Implementation of these adaptive controllers does not require the use of complex mathematical models of the arm dynamics or knowledge of the arm dynamic parameters or load parameters. These strategies have simple structures, and are computationally fast for on-line implementation with high sampling rates. In all three cases, the coupling effects between the arms through the load are treated as disturbances which are rejected by the adaptive controllers while following desired commands in a common frame of reference. Simulation results demonstrate the usefulness of the controllers.

  14. Adaptive P300 based control system

    Jin J; Allison B.Z.; Sellers E.W.; Brunner & C.; Horki P.; Wang X; Neuper C.

    2011-01-01

    An adaptive P300 brain-computer interface (BCI) using a 12 × 7 matrix explored new paradigms to improve bit rate and accuracy. During online use, the system adaptively selects the number of flashes to average. Five different flash patterns were tested. The 19-flash paradigm represents the typical row/column presentation (i.e., 12 columns and 7 rows). The 9- and 14-flash A & B paradigms present all items of the 12 × 7 matrix three times using either nine or 14 flashes (instead of 19), decreasi...

  15. Adaptive torque control of variable speed wind turbines

    Johnson, Kathryn E.

    Wind is a clean, renewable resource that has become more popular in recent years due to numerous advances in technology and public awareness. Wind energy is quickly becoming cost competitive with fossil fuels, but further reductions in the cost of wind energy are necessary before it can grow into a fully mature technology. One reason for higher-than-necessary cost of the wind energy is uncertainty in the aerodynamic parameters, which leads to inefficient controllers. This thesis explores an adaptive control technique designed to reduce the negative effects of this uncertainty. The primary focus of this work is a new adaptive controller that is designed to resemble the standard non-adaptive controller used by the wind industry. The standard controller was developed for variable speed wind turbines operating below rated power. The new adaptive controller uses a simple, highly intuitive gain adaptation law intended to seek out the optimal gain for maximizing the turbine's energy capture. It is designed to work even in real, time-varying winds. The adaptive controller has been tested both in simulation and on a real turbine, with numerous experimental results provided in this work. Simulations have considered the effects of erroneous wind measurements and time-varying turbine parameters, both of which are concerns on the real turbine. The adaptive controller has been found to operate as desired under realistic operating conditions, and energy capture has increased on the real turbine as a result. Theoretical analyses of the standard and adaptive controllers were performed, as well, providing additional insight into the system. Finally, a few extensions were made with the intent of making the adaptive control idea even more appealing in the commercial wind turbine market.

  16. Hormesis and adaptive cellular control systems

    Hormetic dose response occurs for many endpoints associated with exposures of biological organisms to environmental stressors. Cell-based U- or inverted U-shaped responses may derive from common processes involved in activation of adaptive responses required to protect cells from...

  17. Parameter Identification and Adaptive Control Applied to the Inverted Pendulum

    Carlos A. Saldarriaga-Cortés; Víctor D. Correa-Ramírez; Didier Giraldo-Buitrago

    2012-01-01

    This paper presents a methodology to implement an adaptive control of the inverted pendulum system; which uses the recursive square minimum method for the identification of a dynamic digital model of the plant and then, with its estimated parameters, tune in real time a pole placement control. The plant to be used is an unstable and nonlinear system. This fact, combined with the adaptive controller characteristics, allows the obtained results to be extended to a great variety of systems. The ...

  18. Revisionist integral deferred correction with adaptive step-size control

    Christlieb, Andrew

    2015-03-27

    © 2015 Mathematical Sciences Publishers. Adaptive step-size control is a critical feature for the robust and efficient numerical solution of initial-value problems in ordinary differential equations. In this paper, we show that adaptive step-size control can be incorporated within a family of parallel time integrators known as revisionist integral deferred correction (RIDC) methods. The RIDC framework allows for various strategies to implement stepsize control, and we report results from exploring a few of them.

  19. Fully probabilistic control design in an adaptive critic framework

    Herzallah, R.; Kárný, Miroslav

    2011-01-01

    Roč. 24, č. 10 (2011), s. 1128-1135. ISSN 0893-6080 R&D Projects: GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : Stochastic control design * Fully probabilistic design * Adaptive control * Adaptive critic Subject RIV: BC - Control Systems Theory Impact factor: 2.182, year: 2011 http://library.utia.cas.cz/separaty/2011/AS/karny-0364820.pdf

  20. Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

    Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

    2010-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as 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 the 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 robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

  1. Dual-thread parallel control strategy for ophthalmic adaptive optics

    Yu, Yongxin; Zhang, Yuhua

    2014-01-01

    To improve ophthalmic adaptive optics speed and compensate for ocular wavefront aberration of high temporal frequency, the adaptive optics wavefront correction has been implemented with a control scheme including 2 parallel threads; one is dedicated to wavefront detection and the other conducts wavefront reconstruction and compensation. With a custom Shack-Hartmann wavefront sensor that measures the ocular wave aberration with 193 subapertures across the pupil, adaptive optics has achieved a ...

  2. Design of Low Complexity Model Reference Adaptive Controllers

    Hanson, Curt; Schaefer, Jacob; Johnson, Marcus; Nguyen, Nhan

    2012-01-01

    Flight research experiments have demonstrated that adaptive flight controls can be an effective technology for improving aircraft safety in the event of failures or damage. However, the nonlinear, timevarying nature of adaptive algorithms continues to challenge traditional methods for the verification and validation testing of safety-critical flight control systems. Increasingly complex adaptive control theories and designs are emerging, but only make testing challenges more difficult. A potential first step toward the acceptance of adaptive flight controllers by aircraft manufacturers, operators, and certification authorities is a very simple design that operates as an augmentation to a non-adaptive baseline controller. Three such controllers were developed as part of a National Aeronautics and Space Administration flight research experiment to determine the appropriate level of complexity required to restore acceptable handling qualities to an aircraft that has suffered failures or damage. The controllers consist of the same basic design, but incorporate incrementally-increasing levels of complexity. Derivations of the controllers and their adaptive parameter update laws are presented along with details of the controllers implementations.

  3. Disturbance Accommodating Adaptive Control with Application to Wind Turbines

    Frost, Susan

    2012-01-01

    Adaptive control techniques are well suited to applications that have unknown modeling parameters and poorly known operating conditions. Many physical systems experience external disturbances that are persistent or continually recurring. Flexible structures and systems with compliance between components often form a class of systems that fail to meet standard requirements for adaptive control. For these classes of systems, a residual mode filter can restore the ability of the adaptive controller to perform in a stable manner. New theory will be presented that enables adaptive control with accommodation of persistent disturbances using residual mode filters. After a short introduction to some of the control challenges of large utility-scale wind turbines, this theory will be applied to a high-fidelity simulation of a wind turbine.

  4. Neural control of chronic stress adaptation

    James eHerman

    2013-01-01

    Stress initiates adaptive processes that allow the organism to physiologically cope with prolonged or intermittent exposure to real or perceived threats. A major component of this response is repeated activation of glucocorticoid secretion by the hypothalamo-pituitary-adrenocortical (HPA) axis, which promotes redistribution of energy in a wide range of organ systems, including the brain. Prolonged or cumulative increases in glucocorticoid secretion can reduce benefits afforded by enhanced s...

  5. Adaptive optimization and control using neural networks

    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.

  6. Adaptive Human Control Gains During Precision Grip

    Erik D. Engeberg

    2013-03-01

    Full Text Available Eight human test subjects attempted to track a desired position trajectory with an instrumented manipulandum (MN. The test subjects used the MN with three different levels of stiffness. A transfer function was developed to represent the human application of a precision grip from the data when the test subjects initially displaced the MN so as to learn the position mapping from the MN onto the display. Another transfer function was formed from the data of the remainder of the experiments, after significant displacement of the MN occurred. Both of these transfer functions accurately modelled the system dynamics for a portion of the experiments, but neither was accurate for the duration of the experiments because the human grip dynamics changed while learning the position mapping. Thus, an adaptive system model was developed to describe the learning process of the human test subjects as they displaced the MN in order to gain knowledge of the position mapping. The adaptive system model was subsequently validated following comparison with the human test subject data. An examination of the average absolute error between the position predicted by the adaptive model and the actual experimental data yielded an overall average error of 0.34mm for all three levels of stiffness.

  7. Adaptive tracking control for a class of uncertain chaotic systems

    Chen Feng-Xiang; Wang Wei; Zhang Wei-Dong

    2007-01-01

    The paper is concerned with adaptive tracking problem for a class of chaotic system with time-varying uncertainty,but bounded by norm polynomial. Based on adaptive technique, it proposes a novel controller to asymptotically track the arbitrary desired bounded trajectory. Simulation on the Rossler chaotic system is performed and the result verifies the effectiveness of the proposed method.

  8. Stability and Performance Metrics for Adaptive Flight Control

    Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens

    2009-01-01

    This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.

  9. L1 adaptive output-feedback control architectures

    Kharisov, Evgeny

    This research focuses on development of L 1 adaptive output-feedback control. The objective is to extend the L1 adaptive control framework to a wider class of systems, as well as obtain architectures that afford more straightforward tuning. We start by considering an existing L1 adaptive output-feedback controller for non-strictly positive real systems based on piecewise constant adaptation law. It is shown that L 1 adaptive control architectures achieve decoupling of adaptation from control, which leads to bounded away from zero time-delay and gain margins in the presence of arbitrarily fast adaptation. Computed performance bounds provide quantifiable performance guarantees both for system output and control signal in transient and steady state. A noticeable feature of the L1 adaptive controller is that its output behavior can be made close to the behavior of a linear time-invariant system. In particular, proper design of the lowpass filter can achieve output response, which almost scales for different step reference commands. This property is relevant to applications with human operator in the loop (for example: control augmentation systems of piloted aircraft), since predictability of the system response is necessary for adequate performance of the operator. Next we present applications of the L1 adaptive output-feedback controller in two different fields of engineering: feedback control of human anesthesia, and ascent control of a NASA crew launch vehicle (CLV). The purpose of the feedback controller for anesthesia is to ensure that the patient's level of sedation during surgery follows a prespecified profile. The L1 controller is enabled by anesthesiologist after he/she achieves sufficient patient sedation level by introducing sedatives manually. This problem formulation requires safe switching mechanism, which avoids controller initialization transients. For this purpose, we used an L1 adaptive controller with special output predictor initialization routine

  10. Adaptive control in series load PWM induction heating inverters

    Szelitzky, Tibor; Henrietta Dulf, Eva

    2013-12-01

    Permanent variations of the electric properties of the load in induction heating equipment make difficult to control the plant. To overcome these disadvantages, the authors propose a new approach based on adaptive control methods. For real plants it is enough to present desired performances or start-up variables for the controller, from which the algorithms tune the controllers by itself. To present the advantages of the proposed controllers, comparisons are made to a PI controller tuned through Ziegler-Nichols method.

  11. Missile guidance law design using adaptive cerebellar model articulation controller.

    Lin, Chih-Min; Peng, Ya-Fu

    2005-05-01

    An adaptive cerebellar model articulation controller (CMAC) is proposed for command to line-of-sight (CLOS) missile guidance law design. In this design, the three-dimensional (3-D) CLOS guidance problem is formulated as a tracking problem of a time-varying nonlinear system. The adaptive CMAC control system is comprised of a CMAC and a compensation controller. The CMAC control is used to imitate a feedback linearization control law and the compensation controller is utilized to compensate the difference between the feedback linearization control law and the CMAC control. The online adaptive law is derived based on the Lyapunov stability theorem to learn the weights of receptive-field basis functions in CMAC control. In addition, in order to relax the requirement of approximation error bound, an estimation law is derived to estimate the error bound. Then the adaptive CMAC control system is designed to achieve satisfactory tracking performance. Simulation results for different engagement scenarios illustrate the validity of the proposed adaptive CMAC-based guidance law. PMID:15940993

  12. Discrete Time Optimal Adaptive Control for Linear Stochastic Systems

    JIANG Rui; LUO Guiming

    2007-01-01

    The least-squares(LS)algorithm has been used for system modeling for a long time. Without any excitation conditions, only the convergence rate of the common LS algorithm can be obtained. This paper analyzed the weighted least-squares(WLS)algorithm and described the good properties of the WLS algorithm. The WLS algorithm was then used for daptive control of linear stochastic systems to show that the linear closed-loop system was globally stable and that the system identification was consistent. Compared to the past optimal adaptive controller,this controller does not impose restricted conditions on the coefficients of the system, such as knowing the first coefficient before the controller. Without any persistent excitation conditions, the analysis shows that, with the regulation of the adaptive control, the closed-loop system was globally stable and the adaptive controller converged to the one-step-ahead optimal controller in some sense.

  13. Adaptive slope compensation for high bandwidth digital current mode controller

    Taeed, Fazel; Nymand, Morten

    converter duty cycle. The adaptive slope compensation provides optimum controller operation in term of bandwidth over wide range of operating points. In this paper operation principle of the controller is discussed. The proposed controller is implemented in an FPGA to control a 100 W buck converter. The......An adaptive slope compensation method for digital current mode control of dc-dc converters is proposed in this paper. The compensation slope is used for stabilizing the inner current loop in peak current mode control. In this method, the compensation slope is adapted with the variations in...... experimental results of measured loop-gain at different operating points are presented to validate the theoretical performance of the controller....

  14. Novel hybrid adaptive controller for manipulation in complex perturbation environments.

    Alex M C Smith

    Full Text Available In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.

  15. Adaptive Importance Sampling for Control and Inference

    Kappen, H. J.; Ruiz, H. C.

    2016-03-01

    Path integral (PI) control problems are a restricted class of non-linear control problems that can be solved formally as a Feynman-Kac PI and can be estimated using Monte Carlo sampling. In this contribution we review PI control theory in the finite horizon case. We subsequently focus on the problem how to compute and represent control solutions. We review the most commonly used methods in robotics and control. Within the PI theory, the question of how to compute becomes the question of importance sampling. Efficient importance samplers are state feedback controllers and the use of these requires an efficient representation. Learning and representing effective state-feedback controllers for non-linear stochastic control problems is a very challenging, and largely unsolved, problem. We show how to learn and represent such controllers using ideas from the cross entropy method. We derive a gradient descent method that allows to learn feed-back controllers using an arbitrary parametrisation. We refer to this method as the path integral cross entropy method or PICE. We illustrate this method for some simple examples. The PI control methods can be used to estimate the posterior distribution in latent state models. In neuroscience these problems arise when estimating connectivity from neural recording data using EM. We demonstrate the PI control method as an accurate alternative to particle filtering.

  16. Adult Development, Control, and Adaptive Functioning.

    Schulz, Richard; And Others

    1991-01-01

    Research suggests that primary control increases as humans develop from infancy through middle age and then decreases in old age. To minimize losses, individuals rely on cognitively based secondary control processes in middle and old age. Literature on adult control processes is reviewed. (SLD)

  17. High Efficiency Lighting with Integrated Adaptive Control (HELIAC) Project

    National Aeronautics and Space Administration — The innovation of the proposed project is the development of High Efficiency Lighting with Integrated Adaptive Control (HELIAC) systems to drive plant growth. Solar...

  18. Integrated Damage-Adaptive Control System (IDACS) Project

    National Aeronautics and Space Administration — SSCI, in collaboration with Boeing Phantom Works, proposes to develop and test an efficient Integrated Damage Adaptive Control System (IDACS). The proposed system...

  19. $l^p$ Gain Bounds for Switched Adaptive Controllers

    French, Mark; Trenn, Stephan

    2005-01-01

    A class of discrete plants controlled by a switching adaptive strategy is considered, and $l^p$ bounds, $1 \\le p \\le \\infty$, are obtained for the closed loop gain relating input and output disturbances to internal signals.

  20. High Efficiency Lighting with Integrated Adaptive Control (HELIAC) Project

    National Aeronautics and Space Administration — The proposed project is the continued development of the High Efficiency Lighting with Integrated Adaptive Control (HELIAC) system. Solar radiation is not a viable...

  1. Fault Adaptive Control of Overactuated Systems Using Prognostic Estimation

    National Aeronautics and Space Administration — Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper...

  2. Integrated Damage-Adaptive Control System (IDACS) Project

    National Aeronautics and Space Administration — SSCI proposes to further develop, implement and test the damage-adaptive control algorithms developed in Phase I within the framework of an Integrated Damage...

  3. 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.

  4. Controling contagious processes on temporal networks via adaptive rewiring

    Belik, Vitaly; Hövel, Philipp

    2015-01-01

    We consider recurrent contagious processes on a time-varying network. As a control procedure to mitigate the epidemic, we propose an adaptive rewiring mechanism for temporary isolation of infected nodes upon their detection. As a case study, we investigate the network of pig trade in Germany. Based on extensive numerical simulations for a wide range of parameters, we demonstrate that the adaptation mechanism leads to a significant extension of the parameter range, for which most of the index nodes (origins of the epidemic) lead to vanishing epidemics. We find that diseases with detection times around a week and infectious periods up to 3 months can be effectively controlled. Furthermore the performance of adaptation is very heterogeneous with respect to the index node. We identify index nodes that are most responsive to the adaptation strategy and quantify the success of the proposed adaptation scheme in dependence on the infectious period and detection times.

  5. Adaptive Non-linear Control of Hydraulic Actuator Systems

    Hansen, Poul Erik; Conrad, Finn

    Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....

  6. Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

    Alejandro Carrasco Elizalde; Peter Goldsmith

    2008-01-01

    The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the cont...

  7. Adaptive Non-linear Control of Hydraulic Actuator Systems

    Hansen, Poul Erik; Conrad, Finn

    1998-01-01

    Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF).......Presentation of two new developed adaptive non-liner controllers for hydraulic actuator systems to give stable operation and improved performance.Results from the IMCIA project supported by the Danish Technical Research Council (STVF)....

  8. Scalable Harmonization of Complex Networks With Local Adaptive Controllers

    Kárný, Miroslav; Herzallah, R.

    -, - (2016). ISSN 2168-2216 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Adaptive control * Adaptive estimation * Bayes methods * Complex networks * Decentralized control * Feedback * Feedforward systems * Recursive estimation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.699, year: 2014 http://library.utia.cas.cz/separaty/2016/AS/karny-0457337.pdf

  9. Adaptive control with an expert system based supervisory level. Thesis

    Sullivan, Gerald A.

    1991-01-01

    Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up

  10. Adaptive Attitude Control of the Crew Launch Vehicle

    Muse, Jonathan

    2010-01-01

    An H(sub infinity)-NMA architecture for the Crew Launch Vehicle was developed in a state feedback setting. The minimal complexity adaptive law was shown to improve base line performance relative to a performance metric based on Crew Launch Vehicle design requirements for all most all of the Worst-on-Worst dispersion cases. The adaptive law was able to maintain stability for some dispersions that are unstable with the nominal control law. Due to the nature of the H(sub infinity)-NMA architecture, the augmented adaptive control signal has low bandwidth which is a great benefit for a manned launch vehicle.

  11. Synchronization of general complex networks via adaptive control schemes

    Ping He; Chun-Guo Jing; Chang-Zhong Chen; Tao Fan; Hassan Saberi Nik

    2014-03-01

    In this paper, the synchronization problem of general complex networks is investigated by using adaptive control schemes. Time-delay coupling, derivative coupling, nonlinear coupling etc. exist universally in real-world complex networks. The adaptive synchronization scheme is designed for the complex network with multiple class of coupling terms. A criterion guaranteeing synchronization of such complex networks is established by employing the Lyapunov stability theorem and adaptive control schemes. Finally, an illustrative example with numerical simulation is given to show the feasibility and efficiency of theoretical results.

  12. Adaptive Generalized Predictive Control for Mechatronic Systems

    Belda, Květoslav; Böhm, Josef

    2006-01-01

    Roč. 5, č. 8 (2006), s. 1830-1837. ISSN 1109-2777 R&D Projects: GA ČR GP102/06/P275; GA ČR GA102/05/0271 Institutional research plan: CEZ:AV0Z10750506 Keywords : on-line identification * predictive control * input/output equations of predictions * real-time control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0040149.pdf

  13. Adaptive fuzzy logic control for solar buildings

    El-Deen, M. M. G. Naser

    2002-01-01

    Significant progress has been made on maximising passive solar heating loads through the careful selection of glazing, orientation and internal mass within building spaces. Control of space heating in buildings of this type has become a complex problem. Additionally, and in common with most building control applications, there is a need to develop control solutions that permit simple and transparent set up and commissioning procedures. This work concerns the development and testing of an adap...

  14. Human Adaptation to the Control of Fire

    Wrangham, Richard W.; Carmody, Rachel Naomi

    2010-01-01

    Charles Darwin attributed human evolutionary success to three traits. Our social habits and anatomy were important, he said, but the critical feature was our intelligence, because it led to so much else, including such traits as language, weapons, tools, boats, and the control of fire. Among these, he opined, the control of fire was “probably the greatest ever [discovery] made by man, excepting language.” Despite this early suggestion that the control of fire was even more important than tool...

  15. Robust adaptive fuzzy control scheme for nonlinear system with uncertainty

    Mingjun ZHANG; Huaguang ZHANG

    2006-01-01

    In this paper, a robust adaptive fuzzy control scheme for a class of nonlinear system with uncertainty is proposed. First, using prior knowledge about the plant we obtain a fuzzy model, which is called the generalized fuzzy hyperbolic model (GFHM). Secondly, for the case that the states of the system are not available an observer is designed and a robust adaptive fuzzy output feedback control scheme is developed. The overall control system guarantees that the tracking error converges to a small neighborhood of origin and that all signals involved are uniformly bounded. The main advantages of the proposed control scheme are that the human knowledge about the plant under control can be used to design the controller and only one parameter in the adaptive mechanism needs to be on-line adjusted.

  16. Adaptive process control using fuzzy logic and genetic algorithms

    Karr, C. L.

    1993-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

  17. Adaptive Process Control with Fuzzy Logic and Genetic Algorithms

    Karr, C. L.

    1993-01-01

    Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision-making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific laboratory acid-base pH system is used to demonstrate the ideas presented.

  18. An adaptive learning control system for aircraft

    Mekel, R.; Nachmias, S.

    1978-01-01

    A learning control system and its utilization as a flight control system for F-8 Digital Fly-By-Wire (DFBW) research aircraft is studied. The system has the ability to adjust a gain schedule to account for changing plant characteristics and to improve its performance and the plant's performance in the course of its own operation. Three subsystems are detailed: (1) the information acquisition subsystem which identifies the plant's parameters at a given operating condition; (2) the learning algorithm subsystem which relates the identified parameters to predetermined analytical expressions describing the behavior of the parameters over a range of operating conditions; and (3) the memory and control process subsystem which consists of the collection of updated coefficients (memory) and the derived control laws. Simulation experiments indicate that the learning control system is effective in compensating for parameter variations caused by changes in flight conditions.

  19. Backstepping design of missile guidance and control based on adaptive fuzzy sliding mode control

    Ran Maopeng; Wang Qing; Hou Delong; Dong Chaoyang

    2014-01-01

    This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of...

  20. Robust adaptive control for interval time-delay systems

    Yizhong WANG; Huaguang ZHANG; Jun YANG

    2006-01-01

    This paper focuses on the robust adaptive control problems for a class of interval time-delay systems and a class of large-scale interconnected systems. The nonlinear uncertainties of the systems under study are bounded by high-order polynomial functions with unknown gains. Firstly, the adaptive feedback controller which can guarantee the stability of the closed-loop system in the sense of uniform ultimate boundedness is proposed. Then the proposed adaptive idea is extended to robust stabilizing designing method for a class of large-scale interconnected systems. Here, another problem we address is to design a decentralized feedback adaptive controller such that the closed-loop system is stable in the sense of uniform ultimate boundedness for all admissible uncertainties and time-delay. Finally, an illustrative example is given to show the validity of the proposed approach.

  1. Merging of Multistep Predictors for Decentralized Adaptive Control

    Šmídl, Václav; Andrýsek, Josef

    Seattle : IEEE, 2008, s. 3414-3415. ISBN 978-1-4244-2078-0. [American Control Conference. Seattle (US), 11.06.2008-13.06.2008] R&D Projects: GA MŠk 1M0572; GA ČR GP102/08/P250 Institutional research plan: CEZ:AV0Z10750506 Keywords : adaptive control * decentralised control * probability Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2008/AS/smidl-merging of multistep predictors for decentralized adaptive.pdf

  2. Frequency Response Adaptive Control of a Refrigeration Cycle

    Jens G. Balchen

    1989-01-01

    Full Text Available A technique for the adaptation of controller parameters in a single control loop based upon the estimation of frequency response parameters has been presented in an earlier paper. This paper contains an extension and a generalization of the first method and results in a more versatile solution which is applicable to a wider range of process characteristics. The application of this adaptive control technique is illustrated by a laboratory refrigeration cycle in which the evaporator pressure controls the speed of the compressor.

  3. Adaptive control strategies for a class of nonlinear propagation bioprocesses

    This paper presents the control problem of a class of propagation bio-processes that are carried out in fixed bed reactors. Since the dynamics of these processes are described by partial differential equations, in order to obtain useful models for control purposes, a possible method consists of approximation of their infinitely order associated models by finite order models. A class of nonlinear adaptive controllers are then designed based on these finite order models, which consist of a set of ordinary differential equations obtained here by orthogonal collocation method. Computer simulations conducted in the case of a fixed bed reactor are included to illustrate the performances of the proposed adaptive controllers. (authors)

  4. Adaptive Backstepping Control of Lightweight Tower Wind Turbine

    Galeazzi, Roberto; Borup, Kasper Trolle; Niemann, Hans Henrik;

    2015-01-01

    This paper investigates the feasibility of operating a wind turbine with lightweight tower in the full load region exploiting an adaptive nonlinear controller that allows the turbine to dynamically lean against the wind while maintaining nominal power output. The use of lightweight structures for...... towers and foundations would greatly reduce the construction cost of the wind turbine, however extra features ought be included in the control system architecture to avoid tower collapse. An adaptive backstepping collective pitch controller is proposed for tower point tracking control, i.e. to modify the...

  5. Dynamic multimedia stream adaptation and rate control for heterogeneous networks

    SZWABE Andrzej; SCHORR Andreas; HAUCK Franz J.; KASSLER Andreas J.

    2006-01-01

    Dynamic adaptation of multimedia content is seen as an important feature of next generation networks and pervasive systems enabling terminals and applications to adapt to changes in e.g. context, access network, and available Quality-of-Service(QoS) due to mobility of users, devices or sessions. We present the architecture of a multimedia stream adaptation service which enables communication between terminals having heterogeneous hardware and software capabilities and served by heterogeneous networks. The service runs on special content adaptation nodes which can be placed at any location within the network. The flexible structure of our architecture allows using a variety of different adaptation engines. A generic transcoding engine is used to change the codec of streams. An MPEG-21 Digital Item Adaptation (DIA) based transformation engine allows adjusting the data rate of scalable media streams. An intelligent decision-taking engine implements adaptive flow control which takes into account current network QoS parameters and congestion information. Measurements demonstrate the quality gains achieved through adaptive congestion control mechanisms under conditions typical for a heterogeneous network.

  6. Decentralized adaptive control of manipulators - Theory, simulation, and experimentation

    Seraji, Homayoun

    1989-01-01

    The author presents a simple decentralized adaptive-control scheme for multijoint robot manipulators based on the independent joint control concept. The control objective is to achieve accurate tracking of desired joint trajectories. The proposed control scheme does not use the complex manipulator dynamic model, and each joint is controlled simply by a PID (proportional-integral-derivative) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. Simulation results are given for a two-link direct-drive manipulator under adaptive independent joint control. The results illustrate trajectory tracking under coupled dynamics and varying payload. The proposed scheme is implemented on a MicroVAX II computer for motion control of the three major joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite coupled nonlinear joint dynamics.

  7. Adaptive predictive control for simple mechatronic systems

    Belda, Květoslav; Böhm, Josef

    Athens: WSEAS, 2006 - (Bardis, N.; Mladenov, V.), s. 307-312 ISBN 960-8457-47-5. [WSEAS International Conference on System. Athens (GR), 10.07.2006-12.07.2006] R&D Projects: GA ČR GP102/06/P275; GA ČR GA102/05/0271 Institutional research plan: CEZ:AV0Z10750506 Keywords : on-line identification * predictive control * input/output equations of predictions * real time control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0040145.pdf

  8. Robust adaptive control of nonlinearly parameterized systems with unmodeled dynamics

    LIU Yu-sheng; CHEN Jiang; LI Xing-yuan

    2006-01-01

    Many physical systems such as biochemical processes and machines with friction are of nonlinearly parameterized systems with uncertainties.How to control such systems effectively is one of the most challenging problems.This paper presents a robust adaptive controller for a significant class of nonlinearly parameterized systems.The controller can be used in cases where there exist parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The design of the controller is based on the control Lyapunov function method.A dynamic signal is introduced and adaptive nonlinear damping terms are used to restrain the effects of unmodeled dynamics,nonlinear uncertainties and unknown bounded disturbances.The backstepping procedure is employed to overcome the complexity in the design.With the proposed method,the estimation of the unknown parameters of the system is not required and there is only one adaptive parameter no matter how high the order of the system is and how many unknown parameters.there are.It is proved theoretically that the proposed robust adaptive control scheme guarantees the stability of nonlinearly parameterized system.Furthermore,all the states approach the equilibrium in arbitrary precision by choosing some design constants appropriately.Simulation results illustrate the effectiveness of the proposed robust adaptive controller.

  9. Adaptive Feedfoward Feedback Control Framework Project

    National Aeronautics and Space Administration — A novel approach is proposed for the suppression of the aircraft's structural vibration to increase the resilience of the flight control law in the presence of the...

  10. Identification and dual adaptive control of a turbojet engine

    Merrill, W.; Leininger, G.

    1979-01-01

    The objective of this paper is to utilize the design methods of modern control theory to realize a 'dual-adaptive' feedback control unit for a highly non-linear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the non-linear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a 'dual-adpative' control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.

  11. An integrated approach to modeling and adaptive control

    HAN Zhi-gang

    2006-01-01

    In the book (Adaptive Identification,Prediction and Control-Multi Level Recursive Approach), the concept of dynamical linearization of nonlinear systems has been presented.This dynamical linearization is formal only,not a real linearization.From the linearization procedure,we can find a new approach of system identification,which is on-line real-time modeling and real-time feedback control correction.The modeling and real-time feedback control have been integrated in the identification approach,with the parameter adaptation model being abandoned.The structure adaptation of control systems has been achieved,which avoids the complex modeling steps.The objective of this paper is to introduce the approach of integrated modeling and control.

  12. Adaptive neuro-fuzzy controller of switched reluctance motor

    Tahour Ahmed

    2007-01-01

    Full Text Available This paper presents an application of adaptive neuro-fuzzy (ANFIS control for switched reluctance motor (SRM speed. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. An adaptive neuro-fuzzy controller of the motor speed is then designed and simulated. Digital simulation results show that the designed ANFIS speed controller realizes a good dynamic behaviour of the motor, a perfect speed tracking with no overshoot and a good rejection of impact loads disturbance. The results of applying the adaptive neuro-fuzzy controller to a SRM give better performance and high robustness than those obtained by the application of a conventional controller (PI.

  13. Control Reallocation Strategies for Damage Adaptation in Transport Class Aircraft

    Gundy-Burlet, Karen; Krishnakumar, K.; Limes, Greg; Bryant, Don

    2003-01-01

    This paper examines the feasibility, potential benefits and implementation issues associated with retrofitting a neural-adaptive flight control system (NFCS) to existing transport aircraft, including both cable/hydraulic and fly-by-wire configurations. NFCS uses a neural network based direct adaptive control approach for applying alternate sources of control authority in the presence of damage or failures in order to achieve desired flight control performance. Neural networks are used to provide consistent handling qualities across flight conditions, adapt to changes in aircraft dynamics and to make the controller easy to apply when implemented on different aircraft. Full-motion piloted simulation studies were performed on two different transport models: the Boeing 747-400 and the Boeing C-17. Subjects included NASA, Air Force and commercial airline pilots. Results demonstrate the potential for improving handing qualities and significantly increased survivability rates under various simulated failure conditions.

  14. Nonlinear Adaptive Robust Force Control of Hydraulic Load Simulator

    YAO Jianyong; JIAO Zongxia; YAO Bin; SHANG Yaoxing; DONG Wenbin

    2012-01-01

    This paper deals with the high performance force control of hydraulic load samulator.Many prevtous works for hydraultc force control are based on their linearization equations,but hydraulic inherent nonlinear properties and uncertainties make the conventional feedback proportional-integral-derivative control not yield to high-performance requirements.In this paper,a nonlinear system model is derived and linear parameterization is made for adaptive control.Then a discontinuous projection-based nonlinear adaptive robust force controller is developed for hydraulic load simulator.The proposed controller constructs an asymptotically stable adaptive controller and adaptation laws,which can compensate for the system nonlinearities and uncertain parameters.Meanwhile a well-designed robust controller is also developed to cope with the hydraulic system uncertain nonlinearities.The controller achieves a guaranteed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities; in the absence of uncertain nonlinearities,the scheme also achieves asymptotic tracking performance.Simulation and experiment comparative results are obtained to verify the high-performance nature of the proposed control strategy and the tracking accuracy is greatly improved.

  15. Design of an adaptable nonlinear controller

    The study of the behavior of a nuclear reactor is of great importance as it allows to know a priori the conditions at which a reactor is submitted. In the sareactor are the design and simulation of control algorithms based on the theories of modern control with the objective of improving improving the performance criterions as well as to guarantee the the stability of the retrofitting system. (author)

  16. Mixture-based adaptive probabilistic control

    Kárný, Miroslav; Böhm, Josef; Guy, Tatiana Valentine; Nedoma, Petr

    2003-01-01

    Roč. 17, č. 2 (2003), s. 119-132. ISSN 0890-6327 R&D Projects: GA ČR GA102/02/0204; GA ČR GA102/00/P045 Grant ostatní: ProDaCTool(XE) IST-1999-12058 Institutional research plan: CEZ:AV0Z1075907 Keywords : Bayesian identification * fully probabilistic control * finite mixtures Subject RIV: BC - Control Systems Theory Impact factor: 0.602, year: 2003 http://library.utia.cas.cz/prace/20030048.ps

  17. Neural and Fuzzy Adaptive Control of Induction Motor Drives

    This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller

  18. Adaptive controller design for feedrate maximization of machining process

    F. Cus

    2006-04-01

    Full Text Available Purpose: An adaptive control system is built which controlling the cutting force and maintaining constant roughness of the surface being milled by digital adaptation of cutting parameters.Design/methodology/approach: The paper discusses the use of combining the methods of neural networks, fuzzy logic and PSO evolutionary strategy (Particle Swarm Optimization in modeling and adaptively controlling the process of end milling. An overall approach of hybrid modeling of cutting process (ANfis-system, used for working out the CNC milling simulator has been prepared. The basic control design is based on the control scheme (UNKS consisting of two neural identificators of the process dynamics and primary regulator.Findings: The experimental results show that not only does the milling system with the design controller have high robustness, and global stability but also the machining efficiency of the milling system with the adaptive controller is much higher than for traditional CNC milling system. Experiments have confirmed efficiency of the adaptive control system, which is reflected in improved surface quality and decreased tool wear.Research limitations/implications: The proposed architecture for on-line determining of optimal cutting conditions is applied to ball-end milling in this paper, but it is obvious that the system can be extended to other machines to improve cutting efficiency.Practical implications: The results of experiments demonstrate the ability of the proposed system to effectively regulate peak cutting forces for cutting conditions commonly encountered in end milling operations. The high accuracy of results within a wide range of machining parameters indicates that the system can be practically applied in industry.Originality/value: By the hybrid process modeling and feed-forward neural control scheme (UNKS the combined system for off-line optimization and adaptive adjustment of cutting parameters is built.

  19. An Adaptive Multivariable Control System for Hydroelectric Generating Units

    Gunne J. Hegglid

    1983-04-01

    Full Text Available This paper describes an adaptive multivariable control system for hydroelectric generating units. The system is based on a detailed mathematical model of the synchronous generator, the water turbine, the exiter system and turbine control servo. The models of the water penstock and the connected power system are static. These assumptions are not considered crucial. The system uses a Kalman filter for optimal estimation of the state variables and the parameters of the electric grid equivalent. The multivariable control law is computed from a Riccatti equation and is made adaptive to the generators running condition by means of a least square technique.

  20. A Decentralized Adaptive Approach to Fault Tolerant Flight Control

    Wu, N. Eva; Nikulin, Vladimir; Heimes, Felix; Shormin, Victor

    2000-01-01

    This paper briefly reports some results of our study on the application of a decentralized adaptive control approach to a 6 DOF nonlinear aircraft model. The simulation results showed the potential of using this approach to achieve fault tolerant control. Based on this observation and some analysis, the paper proposes a multiple channel adaptive control scheme that makes use of the functionally redundant actuating and sensing capabilities in the model, and explains how to implement the scheme to tolerate actuator and sensor failures. The conditions, under which the scheme is applicable, are stated in the paper.

  1. Dynamical singularities in adaptive delayed-feedback control.

    Saito, Asaki; Konishi, Keiji

    2011-09-01

    We demonstrate the dynamical characteristics of adaptive delayed-feedback control systems, exploiting a discrete-time adaptive control method derived for carrying out detailed analysis. In particular, the systems exhibit singularities such as power-law decay of the distribution of transient times and almost zero finite-time Lyapunov exponents. We can explain these results by characterizing such systems as having (1) a Jacobian matrix with unity eigenvalue in the whole phase space, and (2) parameters approaching a stability boundary proven to be identical with that of (nonadaptive) delayed-feedback control. PMID:22060398

  2. Adaptive Control of Truss Structures for Gossamer Spacecraft

    Yang, Bong-Jun; Calise, Anthony J.; Craig, James I.; Whorton, Mark S.

    2007-01-01

    Neural network-based adaptive control is considered for active control of a highly flexible truss structure which may be used to support solar sail membranes. The objective is to suppress unwanted vibrations in SAFE (Solar Array Flight Experiment) boom, a test-bed located at NASA. Compared to previous tests that restrained truss structures in planar motion, full three dimensional motions are tested. Experimental results illustrate the potential of adaptive control in compensating for nonlinear actuation and modeling error, and in rejecting external disturbances.

  3. Adaptive Landing Gear: Optimum Control Strategy and Potential for Improvement

    Grzegorz Mikułowski

    2009-01-01

    Full Text Available An adaptive landing gear is a landing gear (LG capable of active adaptation to particular landing conditions by means of controlled hydraulic force. The objective of the adaptive control is to mitigate the peak force transferred to the aircraft structure during touch-down, and thus to limit the structural fatigue factor. This paper investigates the ultimate limits for improvement due to various strategies of active control. Five strategies are proposed and investigated numerically using a~validated model of a real, passive landing gear as a reference. Potential for improvement is estimated statistically in terms of the mean and median (significant peak strut forces as well as in terms of the extended safe sinking velocity range. Three control strategies are verified experimentally using a laboratory test stand.

  4. Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

    Alejandro Carrasco Elizalde

    2008-01-01

    Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.

  5. Parameter Identification and Adaptive Control Applied to the Inverted Pendulum

    Carlos A. Saldarriaga-Cortés

    2012-06-01

    Full Text Available This paper presents a methodology to implement an adaptive control of the inverted pendulum system; which uses the recursive square minimum method for the identification of a dynamic digital model of the plant and then, with its estimated parameters, tune in real time a pole placement control. The plant to be used is an unstable and nonlinear system. This fact, combined with the adaptive controller characteristics, allows the obtained results to be extended to a great variety of systems. The results show that the above methodology was implemented satisfactorily in terms of estimation, stability and control of such a system. It was established that adaptive techniques have a proper performance even in systems with complex features such as nonlinearity and instability.

  6. Adaptive Contingency Control: Wind Turbine Operation Integrated with Blade Condition Monitoring

    National Aeronautics and Space Administration — We report here on first steps towards integrating systems health monitoring with adaptive contingency controls. In the scenario considered, the adaptive controller...

  7. On flexible CAD of adaptive control and identification algorithms

    Christensen, Anders; Ravn, Ole

    SLLAB is a MATLAB-family software package for solving control and identification problems. This paper concerns the planning of a general-purpose subroutine structure for solving identification and adaptive control problems. A general-purpose identification algorithm is suggested, which allows a t...

  8. Adaptive control of a manipulator with a flexible link

    Yang, Y. P.; Gibson, J. S.

    1988-01-01

    An adaptive controller for a manipulator with one rigid link and one flexible link is presented. The performance and robustness of the controller are demonstrated by numerical simulation results. In the simulations, the manipulator moves in a gravitational field and a finite element model represents the flexible link.

  9. Study on rule-based adaptive fuzzy excitation control technology

    Zhao, Hui; Wang, Hong-jun; Liu, Lu-yuan; Yue, You-jun

    2008-10-01

    Power system is a kind of typical non-linear system, it is hard to achieve excellent control performance with conventional PID controller under different operating conditions. Fuzzy parameter adaptive PID exciting controller is very efficient to overcome the influence of tiny disturbances, but the performance of the control system will be worsened when operating conditions of the system change greatly or larger disturbances occur. To solve this problem, this article presents a rule adaptive fuzzy control scheme for synchronous generator exciting system. In this scheme the control rule adaptation is implemented by regulating the value of parameter di under the given proportional divisors K1, K2 and K3 of fuzzy sets Ai and Bi. This rule adaptive mechanism is constituted by two groups of original rules about the self-generation and self-correction of the control rule. Using two groups of rules, the control rule activated by status 1 and 2 in figure 2 system can be regulated automatically and simultaneously at the time instant k. The results from both theoretical analysis and simulation show that the presented scheme is effective and feasible and possesses good performance.

  10. Direct adaptive control for nonlinear uncertain system based on control Lyapunov function method

    Chen Yimei; Han Zhengzhi; Tang Houjun

    2006-01-01

    The problem of adaptive stabilization of a class of multi-input nonlinear systems with unknown parameters both in the state vector-field and the input vector-field has been considered. By employing the control Lyapunov function method, a direct adaptive controller is designed to complete the global adaptive stability of the uncertain system. At the same time, the controller is also verified to possess the optimality. Example and simulations are provided to illustrate the effectiveness of the proposed method.

  11. Postural control adaptation during galvanic vestibular and vibratory proprioceptive stimulation.

    Fransson, Per-Anders; Hafström, Anna; Karlberg, Mikael; Magnusson, Måns; Tjäder, Annika; Johansson, Rolf

    2003-01-01

    he objective for this study was to investigate whether the adaptation of postural control was similar during galvanic vestibular stimulation and during vibratory proprioceptivestimulation of the calf muscles. Healthy subjects were tested during erect stance with eyes open or closed. An analysis method designed to consider the adaptive adjustments was used to evaluate the motion dynamics and the evoked changes of posture and stimulation response.Galvanic vestibular stimulation induced primaril...

  12. Adaptive active vibration isolation – A control perspective

    Landau Ioan Doré

    2015-01-01

    The paper will review a number of recent developments for adaptive feedback compensation of multiple unknown and time-varying narrow band disturbances and for adaptive feedforward compensation of broad band disturbances in the presence of the inherent internal positive feedback caused by the coupling between the compensator system and the measurement of the image of the disturbance. Some experimental results obtained on a relevant active vibration control system will illustrate the performance of the various algorithms presented.

  13. Adaptation of Sonix+ to control the D3 diffractometer

    The work is devoted to the adaptation of the Sonix+ software tool kit to control the powder diffractometer D3 at one of the beams of the IVV-2M reactor at the Neutron Complex for Materials Research in the Institute of Metal Physics (Zarechny). Sonix+ was designed for instruments at the IBR-2 reactor using the time-of-flight mode of spectra accumulation. However, the underlying solutions simplified the software adaptation for use at stationary reactors.

  14. Adaptive model based control for wastewater treatment plants

    Niet, de, A.; Vrugt, van de, Noëlle Maria; Korving, Hans; Boucherie, Richard J.; Savic, D.A.; Kapelan, Z.; Butler, D.

    2011-01-01

    In biological wastewater treatment, nitrogen and phosphorous are removed by activated sludge. The process requires oxygen input via aeration of the activated sludge tank. Aeration is responsible for about 60% of the energy consumption of a treatment plant. Hence optimization of aeration can contribute considerably to the increase of energy-efficiency in wastewater treatment. To this end, we introduce an adaptive model based control strategy for aeration called adaptive WOMBAT. The strategy is...

  15. Adaptive Media Access Control for Energy Harvesting - Wireless Sensor Networks

    Fafoutis, Xenofon; Dragoni, Nicola

    2012-01-01

    ODMAC (On-Demand Media Access Control) is a recently proposed MAC protocol designed to support individual duty cycles for Energy Harvesting — Wireless Sensor Networks (EH-WSNs). Individual duty cycles are vital for EH-WSNs, because they allow nodes to adapt their energy consumption to the ever...... three key properties of EH-WSNs: adaptability of energy consumption, distributed energy-aware load balancing and support for different application-specific requirements....

  16. Adaptive significance of avian beak morphology for ectoparasite control

    Clayton, Dale H.; Moyer, Brett R; Bush, Sarah E.; Jones, Tony G; Gardiner, David W; Rhodes, Barry B; Goller, Franz

    2005-01-01

    The beaks of Darwin's finches and other birds are among the best known examples of adaptive evolution. Beak morphology is usually interpreted in relation to its critical role in feeding. However, the beak also plays an important role in preening, which is the first line of defence against harmful ectoparasites such as feather lice, fleas, bugs, flies, ticks and feather mites. Here, we show a feature of the beak specifically adapted for ectoparasite control. Experimental trimming of the tiny (...

  17. Adaptive quality control for multimedia communications

    Santichai Chuaywong; Sinchai Kamolphiwong; Thossaporn Kamolphiwong; Kevin Robert Elz; Suthon Sae-Wong

    2008-01-01

    Multimedia communications are communications with several types of media, such as audio, video and data. The current Internet has some levels of capability to support multimedia communications, unfortunately, the QoS (Quality of Service) is still challenging. A large number of QoS mechanisms has been proposed; however, the main concern is for low levels, e.g. layer 2 (Data Link) or 3 (Transport). In this paper, mechanisms for control the quality of audio and video are proposed. G.723.1 and MP...

  18. Adaptive independent joint control of manipulators - Theory and experiment

    Seraji, H.

    1988-01-01

    The author presents a simple decentralized adaptive control scheme for multijoint robot manipulators based on the independent joint control concept. The proposed control scheme for each joint consists of a PID (proportional integral and differential) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. The static and dynamic couplings that exist between the joint motions are compensated by the adaptive independent joint controllers while ensuring trajectory tracking. The proposed scheme is implemented on a MicroVAX II computer for motion control of the first three joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite strongly coupled, highly nonlinear joint dynamics. The results confirm that the proposed decentralized adaptive control of manipulators is feasible, in spite of strong interactions between joint motions. The control scheme presented is computationally very fast and is amenable to parallel processing implementation within a distributed computing architecture, where each joint is controlled independently by a simple algorithm on a dedicated microprocessor.

  19. Adaptive control system having hedge unit and related apparatus and methods

    Johnson, Eric Norman (Inventor); Calise, Anthony J. (Inventor)

    2007-01-01

    The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

  20. Adaptive Control of Flexible Redundant Manipulators Using Neural Networks

    SONG Yimin; LI Jianxin; WANG Shiyu; LIU Jianping

    2006-01-01

    An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted.The smart links of the manipulator were synthesized with the flexible links to which were attached piezoceramic actuators and strain gauge sensors.A nonlinear adaptive control strategy named neural networks based indirect adaptive control (NNIAC) was employed to improve the dynamic performance of the manipulator.The mathematical model of the 4-layered dynamic recurrent neural networks (DRNN) was introduced.The neuro-identifier and the neurocontroller featuring the DRNN topology were designed off line so as to enhance the initial robustness of the NNIAC.By adjusting the neuro-identifier and the neuro-controller alternatively,the manipulator was controlled on line for achieving the desired dynamic performance.Finally,a planar 3R redundant manipulator with one smart link was utilized as an illustrative example.The simulation results proved the validity of the control strategy.

  1. Control of multi-machine using adaptive fuzzy

    Bouchiba Bousmaha

    2011-01-01

    Full Text Available An indirect Adaptive fuzzy excitation control (IAFLC of power systems based on multi-input-multi-output linearization technique is developed in this paper. The power system considered in this paper consists of two generators and infinite bus connected through a network of transformers and transmission lines. The fuzzy controller is constructed from fuzzy feedback linearization controller whose parameters are adjusted indirectly from the estimates of plant parameters. The adaptation law adjusts the controller parameters on-line so that the plant output tracks the reference model output. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition linearization technique can enhance the transient stability of the power system.

  2. Adaptive Dynamic Programming for Control Algorithms and Stability

    Zhang, Huaguang; Luo, Yanhong; Wang, Ding

    2013-01-01

    There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of  adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and  proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...

  3. Adaptive control of large space structures using recursive lattice filters

    Sundararajan, N.; Goglia, G. L.

    1985-01-01

    The use of recursive lattice filters for identification and adaptive control of large space structures is studied. Lattice filters were used to identify the structural dynamics model of the flexible structures. This identification model is then used for adaptive control. Before the identified model and control laws are integrated, the identified model is passed through a series of validation procedures and only when the model passes these validation procedures is control engaged. This type of validation scheme prevents instability when the overall loop is closed. Another important area of research, namely that of robust controller synthesis, was investigated using frequency domain multivariable controller synthesis methods. The method uses the Linear Quadratic Guassian/Loop Transfer Recovery (LQG/LTR) approach to ensure stability against unmodeled higher frequency modes and achieves the desired performance.

  4. STOCHASTIC ADAPTIVE SWITCHING CONTROL BASED ON MULTIPLE MODELS

    ZHANGYanxia; GUOLei

    2002-01-01

    It is well known that the transient behaviors of the traditional adaptive control may be very poor in general,and that the adaptive control designed based in switching between multiple models is an intuitively appealing and practically feasible approach to improve the transient performances.In this paper,we shall prove that for a typical class of linear systems disturbed by random noises,the multiple model based least-equares(LS)adaptive switching control is statble and convergent and has the same convergence rate as that established for the standard least-squares-based self-tunning regulators.Moreover,the mixed case combining adative models with fixed models is also considered.

  5. Adaptive nonlinear control using input normalized neural networks

    An adaptive feedback linearization technique combined with the neural network is addressed to control uncertain nonlinear systems. The neural network-based adaptive control theory has been widely studied. However, the stability analysis of the closed-loop system with the neural network is rather complicated and difficult to understand, and sometimes unnecessary assumptions are involved. As a result, unnecessary assumptions for stability analysis are avoided by using the neural network with input normalization technique. The ultimate boundedness of the tracking error is simply proved by the Lyapunov stability theory. A new simple update law as an adaptive nonlinear control is derived by the simplification of the input normalized neural network assuming the variation of the uncertain term is sufficiently small

  6. Robust adaptive output feedback control of nonlinearly parameterized systems

    LIU Yusheng; LI Xingyuan

    2007-01-01

    The ideas of adaptive nonlinear damping and changing supply functions were used to counteract the effects of parameter and nonlinear uncertainties,unmodeled dynamics and unknown bounded disturbances.The high-gain observer was used to estimate the state of the system.A robust adaptive output feedback control scheme was proposed for nonlinearly parameterized systems represented by inputoutput models.The scheme does not need to estimate the unknown parameters nor add a dynamical signal to dominate the effects of unmodeled dynamics.It is proven that the proposed control scheme guarantees that all the variables in the closed-loop system are bounded and the mean-square tracking error can be made arbitrarily small by choosing some design parameters appropriately.Simulation results have illustrated the effectiveness of the proposed robust adaptive control scheme.

  7. Parallel computation of geometry control in adaptive truss structures

    Ramesh, A. V.; Utku, S.; Wada, B. K.

    1992-01-01

    The fast computation of geometry control in adaptive truss structures involves two distinct parts: the efficient integration of the inverse kinematic differential equations that govern the geometry control and the fast computation of the Jacobian, which appears on the right-hand-side of the inverse kinematic equations. This paper present an efficient parallel implementation of the Jacobian computation on an MIMD machine. Large speedup from the parallel implementation is obtained, which reduces the Jacobian computation to an O(M-squared/n) procedure on an n-processor machine, where M is the number of members in the adaptive truss. The parallel algorithm given here is a good candidate for on-line geometry control of adaptive structures using attached processors.

  8. Decoding information by following parameter modulation with parameter adaptive control

    Zhou, Changsong; Lai, C.-H.

    1999-06-01

    It has been proposed to realize secure communication using chaotic synchronization via transmission of a binary message encoded by parameter modulation in the chaotic system. This paper considers the use of parameter adaptive control techniques to extract the message, based on the assumptions that we know the equation form of the chaotic system in the transmitter but do not have access to the precise values of the parameters which are kept secret as a secure set. In the case in which a synchronizing system can be constructed using parameter adaptive control by the transmitted signal and the synchronization is robust to parameter mismatches, the parameter modulation can be revealed and the message decoded without resorting to exact parameter values in the secure set. A practical local Lyapunov function method for designing parameter adaptive control rules based on originally synchronized systems is presented.

  9. A Comprehensive Robust Adaptive Controller for Gust Load Alleviation

    Elisa Capello; Giorgio Guglieri; Fulvia Quagliotti

    2014-01-01

    The objective of this paper is the implementation and validation of an adaptive controller for aircraft gust load alleviation. The contribution of this paper is the design of a robust controller that guarantees the reduction of the gust loads, even when the nominal conditions change. Some preliminary results are presented, considering the symmetric aileron deflection as control device. The proposed approach is validated on subsonic transport aircraft for different mass and flight conditions. ...

  10. Mechanisms of motor adaptation in reactive balance control.

    Torrence D J Welch

    Full Text Available Balance control must be rapidly modified to provide stability in the face of environmental challenges. Although changes in reactive balance over repeated perturbations have been observed previously, only anticipatory postural adjustments preceding voluntary movements have been studied in the framework of motor adaptation and learning theory. Here, we hypothesized that adaptation occurs in task-level balance control during responses to perturbations due to central changes in the control of both anticipatory and reactive components of balance. Our adaptation paradigm consisted of a Training set of forward support-surface perturbations, a Reversal set of novel countermanding perturbations that reversed direction, and a Washout set identical to the Training set. Adaptation was characterized by a change in a motor variable from the beginning to the end of each set, the presence of aftereffects at the beginning of the Washout set when the novel perturbations were removed, and a return of the variable at the end of the Washout to a level comparable to the end of the Training set. Task-level balance performance was characterized by peak center of mass (CoM excursion and velocity, which showed adaptive changes with repetitive trials. Only small changes in anticipatory postural control, characterized by body lean and background muscle activity were observed. Adaptation was found in the evoked long-latency muscular response, and also in the sensorimotor transformation mediating that response. Finally, in each set, temporal patterns of muscle activity converged towards an optimum predicted by a trade-off between maximizing motor performance and minimizing muscle activity. Our results suggest that adaptation in balance, as well as other motor tasks, is mediated by altering central sensitivity to perturbations and may be driven by energetic considerations.

  11. Multiple Estimation Architecture in Discrete-Time Adaptive Mixing Control

    Simone Baldi

    2013-05-01

    Full Text Available Adaptive mixing control (AMC is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Even if the stability of the control scheme, also in the presence of modeling errors and disturbances, has been shown analytically, its transient performance might be sensitive to the initial conditions of the parameter estimator. In particular, for some initial conditions, transient oscillations may not be acceptable in practical applications. In order to account for such a possible phenomenon and to improve the learning capability of the adaptive scheme, in this paper a new mixing architecture is developed, involving the use of parallel parameter estimators, or multi-estimators, each one working on a small subset of the uncertainty set. A supervisory logic, using performance signals based on the past and present estimation error, selects the parameter estimate to determine the mixing of the controllers. The stability and robustness properties of the resulting approach, referred to as multi-estimator adaptive mixing control (Multi-AMC, are analytically established. Besides, extensive simulations demonstrate that the scheme improves the transient performance of the original AMC with a single estimator. The control scheme and the analysis are carried out in a discrete-time framework, for easier implementation of the method in digital control.

  12. Adaptive control of uncertain time-delay chaotic systems

    Zhuhong ZHANG

    2005-01-01

    This work investigates adaptive control of a large class of uncertain me-delay chaotic systems (UTCSs) with unknown general perturbation terms bounded by a polynomial ( unknown gains). Associated with the different cases of known and unknown system matrices, two corresponding adaptive controllers are proposed to stabilize unstable fixed points of the systems by means of Lyapunov stability theory and linear matrix inequalities (LMI) which can be solved easily by convex optimization algorithms. Two examples are used for examining the effectiveness of the proposed methods.

  13. Decentralized model reference adaptive control of large flexible structures

    Lee, Fu-Ming; Fong, I-Kong; Lin, Yu-Hwan

    1988-01-01

    A decentralized model reference adaptive control (DMRAC) method is developed for large flexible structures (LFS). The development follows that of a centralized model reference adaptive control for LFS that have been shown to be feasible. The proposed method is illustrated using a simply supported beam with collocated actuators and sensors. Results show that the DMRAC can achieve either output regulation or output tracking with adequate convergence, provided the reference model inputs and their time derivatives are integrable, bounded, and approach zero as t approaches infinity.

  14. The Adaptive Control of FES-assisted Indoor Rowing Exercise

    Hussain, Zakaria; Bin Zaidan, Martha Arbayani; M.O. Tokhi; Jailani, Rozita

    2009-01-01

    This paper describes the development of an adaptive control mechanism for FES-assisted indoor rowing exercise (FES-rowing). The FES-rowing is intro-duced as a total body exercise for rehabilitation of function of lower body through the application of functional elec-trical stimulation (FES). A model of the rowing ergometer with humanoid is developed using the visual Nastran soft-ware environment (vN4D). A fuzzy logic control (FLC) scheme is designed in Matlab/Simulink and adapted online by pr...

  15. Rotor Field Oriented Control with adaptive Iron Loss Compensation

    Rasmussen, Henrik; Vadstrup, P.; Børsting, H.

    1999-01-01

    It is well known from the literature that iron loses in an induction motor implies field angle estimation errors and hence detuning problems. In this paper a new method for estimating the iron loss resistor in an induction motor is presented. The method is based on a traditional dynamic model of ...... current controlled in a Field Oriented Control scheme. This deviation is used to force a MIT-rule based adaptive estimator. An adaptive compensator containing the developed estimator is introduced and verified by simulations and tested by real time experiments....

  16. Adaptive optimization of agile organization of command and control resource

    Yang Chunhui; Liu Junxian; Chen Honghui; Luo Xueshan

    2009-01-01

    Adaptive optimization is one of the means that agile organization of command and control resource (AOC2R) adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put forward by analyzing the interrelating concept and research. The model takes the adaptive process as a multi-stage decision making problem. The 2-phases method is presented to calculate the model, which obtains the related parameters by running the colored Petri net (CPN) model of AOC2R and then searches for the result by ant colony optimization (ACO) algorithm integrated with genetic optimization techniques. The simulation results demonstrate that the proposed algorithm greatly improves the performance of AOC2R.

  17. Backstepping design of missile guidance and control based on adaptive fuzzy sliding mode control

    Ran Maopeng

    2014-06-01

    Full Text Available This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of the system, and for the uncertainties, we utilize an online-adaptive control law to estimate the unknown parameters. The stability analysis of the closed-loop system is also conducted. Simulation results show that, with the application of the adaptive fuzzy sliding mode control, small miss distances and smooth missile trajectories are achieved, and the system is robust against system uncertainties and external disturbances.

  18. Backstepping design of missile guidance and control based on adaptive fuzzy sliding mode control

    Ran Maopeng; Wang Qing; Hou Delong; Dong Chaoyang

    2014-01-01

    This paper presents an integrated missile guidance and control law based on adaptive fuzzy sliding mode control. The integrated model is formulated as a block-strict-feedback nonlinear system, in which modeling errors, unmodeled nonlinearities, target maneuvers, etc. are viewed as unknown uncertainties. The adaptive nonlinear control law is designed based on backstepping and sliding mode control techniques. An adaptive fuzzy system is adopted to approximate the coupling nonlinear functions of the system, and for the uncertainties, we utilize an online-adaptive control law to estimate the unknown parameters. The stability analysis of the closed-loop system is also conducted. Simulation results show that, with the application of the adaptive fuzzy sliding mode control, small miss distances and smooth missile trajectories are achieved, and the system is robust against system uncertainties and external disturbances.

  19. Laser vision based adaptive fill control system for TIG welding

    2008-01-01

    The variation of joint groove size during tungsten inert gas (TIG) welding will result in the non-uniform fill of deposited metal. To solve this problem, an adaptive fill control system was developed based on laser vision sensing. The system hardware consists of a modular development kit (MDK) as the real-time image capturing system, a computer as the controller, a D/A conversion card as the interface of controlled variable output, and a DC TIG welding system as the controlled device. The system software is developed and the developed feature extraction algorithm and control strategy are of good accuracy and robustness. Experimental results show that the system can implement adaptive fill of melting metal with high stability, reliability and accuracy. The groove is filled well and the quality of the weld formation satisfies the relevant industry criteria.

  20. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    Jorgensen, Charles C.

    1997-01-01

    A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

  1. Study on Adaptive Control with Neural Network Compensation

    单剑锋; 黄忠华; 崔占忠

    2004-01-01

    A scheme of adaptive control based on a recurrent neural network with a neural network compensation is presented for a class of nonlinear systems with a nonlinear prefix. The recurrent neural network is used to identify the unknown nonlinear part and compensate the difference between the real output and the identified model output. The identified model of the controlled object consists of a linear model and the neural network. The generalized minimum variance control method is used to identify pareters, which can deal with the problem of adaptive control of systems with unknown nonlinear part, which can not be controlled by traditional methods. Simulation results show that this algorithm has higher precision, faster convergent speed.

  2. Dynamic Performance of Grid Converters using Adaptive DC Voltage Control

    Trintis, Ionut; Sun, Bo; Guerrero, Josep M.; Munk-Nielsen, Stig; Abrahamsen, Flemming; Thøgersen, Paul Bach

    2014-01-01

    This paper investigates a controller that ensures minimum operating dc-link voltage of a back-to-back converter system. The dc-link voltage adapts its reference based on the system state, reference given by an outer loop to the dc-link voltage controller. The operating dc-link voltage should be k...... kept as low as possible to increase the power conversion efficiency and increase the reliability of converters. The dynamic performance of the proposed controller is investigated by simulations and experiments.......This paper investigates a controller that ensures minimum operating dc-link voltage of a back-to-back converter system. The dc-link voltage adapts its reference based on the system state, reference given by an outer loop to the dc-link voltage controller. The operating dc-link voltage should be...

  3. Model-free adaptive control of advanced power plants

    Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

    2015-08-18

    A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  4. Applications of active adaptive noise control to jet engines

    Shoureshi, Rahmat; Brackney, Larry

    1993-01-01

    During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.

  5. An adaptive robust controller for time delay maglev transportation systems

    Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza

    2012-12-01

    For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.

  6. ROBUST ADAPTIVE CONTROL OF NONHOLONOMIC SYSTEMS WITH UNCERTAINTIES

    慕小武; 虞继敏; 毕卫萍; 程代展

    2004-01-01

    Robust adaptive control of nonholonomic systems in chained form with linearly parameterized and strongly nonlinear disturbance and drift terms is dicussed.The novelty of the proposed method is a combined use of the state-scaling and the back-stepping procedure.

  7. Adaptive Superheat Control of a Refrigeration Plant using Backstepping

    Rasmussen, Henrik

    2008-01-01

    . A new low order nonlinear model of the evaporator is developed and used in a backstepping design of an adaptive nonlinear controller.  The stability of the proposed method is validated theoretically by Lyapunov analysis and experimental results shows the performance of the system for a wide range of...

  8. Adaptive feed forward in the LANL RF control system

    This paper describes an adaptive feed forward system that corrects repetitive errors in the amplitude and phase of the RF field of a pulsed accelerator. High-frequency disturbances that are beyond the effective bandwidth of the RF-field feedback control system can be eliminated with a feed forward system. Many RF-field disturbances for a pulsed accelerator are repetitive, occurring at the same relative time in every pulse. This design employs digital signal processing hardware to adaptively determine and track the control signals required to eliminate the repetitive errors in the feedback control system. In order to provide the necessary high-frequency response, the adaptive feed forward hardware provides the calculated control signal prior to the repetitive disturbance that it corrects. This system has been demonstrated to reduce the transient disturbances caused by beam pulses. Furthermore, it has been shown to negate high-frequency phase and amplitude oscillations in a high-power klystron amplifier caused by PFN ripple on the high-voltage. The design and results of the adaptive feed forward system are presented. (Author) 3 figs., 2 refs

  9. Evaluating adaptive cruise control strategies in worst-case scenarios

    Willigen, W.H. van; Schut, M.C.; Kester, L.J.H.M.

    2011-01-01

    This paper is concerned with safety in (cooperative) adaptive cruise control systems. In these systems, the speed of the cars is maintained automatically, based on the preferred speed of the driver and the speed of the preceding car. Technologies that are used in these systems, such as radar and rad

  10. Adaptive Insecure Attachment and Resource Control Strategies during Middle Childhood

    Chen, Bin-Bin; Chang, Lei

    2012-01-01

    By integrating the life history theory of attachment with resource control theory, the current study examines the hypothesis that insecure attachment styles reorganized in middle childhood are alternative adaptive strategies used to prepare for upcoming competition with the peer group. A sample of 654 children in the second through seventh grades…

  11. A proposal for an Adaptive Information Filtering and Control Concept

    Maas, H.L.M.M.; Meiler, P.P.

    1998-01-01

    This paper describes a concept to manage the information exchange between the operators and their consoles (the interface to the computer system) within a Command and Control (C2) centre. Application of his concept will result in a more effective and efficient information exchange, using adaptive in

  12. Adaptive feedforward in the LANL rf control system

    This paper describes an adaptive feedforward system that corrects repetitive errors in the amplitude and phase of the RF field of a pulsed accelerator. High-frequency disturbances that are beyond the effective bandwidth of the RF field feedback control system can be eliminated with a feedforward system. Many RF field disturbances for a pulsed accelerator are repetitive, occurring at the same relative time in every pulse. This design employs digital signal processing hardware to adaptively determine and track the control signals required to eliminate the repetitive errors in the feedback control system. In order to provide the necessary high-frequency response, the adaptive feedforward hardware provides the calculated control signal prior to the repetitive disturbance that it corrects. This system has been demonstrated to reduce the transient disturbances caused by beam pulses. Furthermore, it has been shown to negate high-frequency phase and amplitude oscillations in a high-power klystron amplifier caused by PFN ripple on the high-voltage. The design and results of the adaptive feedforward system are presented

  13. Adaptive Current Control with PI-Fuzzy Compound Controller for Shunt Active Power Filter

    Juntao Fei

    2013-01-01

    Full Text Available An adaptive control technology and PI-fuzzy compound control technology are proposed to control an active power filter (APF. AC side current compensation and DC capacitor voltage tracking control strategy are discussed and analyzed. Model reference adaptive controller for the AC side current compensation is derived and established based on Lyapunov stability theory; proportional and integral (PI fuzzy compound controller is designed for the DC side capacitor voltage control. The adaptive current controller based on PI-fuzzy compound system is compared with the conventional PI controller for active power filter. Simulation results demonstrate the feasibility and satisfactory performance of the proposed control strategies. It is shown that the proposed control method has an excellent dynamic performance such as small current tracking error, reduced total harmonic distortion (THD, and strong robustness in the presence of parameters variation and nonlinear load.

  14. Variable Neural Adaptive Robust Control: A Switched System Approach

    Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

    2015-05-01

    Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewise quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.

  15. Microgrid Stability Controller Based on Adaptive Robust Total SMC

    Xiaoling Su; Minxiao Han; Josep M. Guerrero; Hai Sun

    2015-01-01

    This paper presents a microgrid stability controller (MSC) in order to provide existing distributed generation units (DGs) the additional functionality of working in islanding mode without changing their control strategies in grid-connected mode and to enhance the stability of the microgrid. Microgrid operating characteristics and mathematical models of the MSC indicate that the system is inherently nonlinear and time-variable. Therefore, this paper proposes an adaptive robust total sliding...

  16. Hybrid adaptive feedforward control of structures to seismic inputs

    Matevosian, Armond

    1996-01-01

    The key conclusions of this research are: 1. The EFXLMS algorithm demonstrated superior performance than the FXLMS algorithm during fast adaptive processes, in particular for non-stationary inputs. 2. Good attenuation of the peak. and root-mean-square (rms) values of the structural responses using the hybrid control system were observed for most of the real accelerograms. It was also observed that the hybrid control system always improved the performance of the passive contr...

  17. Robust Adaptive Dynamic Programming for Optimal Nonlinear Control Design

    Jiang, Yu; Jiang, Zhong-Ping

    2013-01-01

    This paper studies the robust optimal control design for uncertain nonlinear systems from a perspective of robust adaptive dynamic programming (robust-ADP). The objective is to fill up a gap in the past literature of ADP where dynamic uncertainties or unmodeled dynamics are not addressed. A key strategy is to integrate tools from modern nonlinear control theory, such as the robust redesign and the backstepping techniques as well as the nonlinear small-gain theorem, with the theory of ADP. The...

  18. Adaptive Control of the Chaotic System via Singular System Approach

    Yudong Li; Tianyu Zhang; Yujun Zhang

    2014-01-01

    This paper deals with the control problem of the chaotic system subject to disturbance. The sliding mode surface is designed by singular system approach, and sufficient condition for convergence is given. Then, the adaptive sliding mode controller is designed to make the state arrive at the sliding mode surface in finite time. Finally, Lorenz system is considered as an example to show the effectiveness of the proposed method.

  19. Adaptive Proactive Inhibitory Control for Embedded Real-Time Applications

    Yang, Shufan; McGinnity, T. Martin; Wong-Lin, KongFatt

    2012-01-01

    Psychologists have studied the inhibitory control of voluntary movement for many years. In particular, the countermanding of an impending action has been extensively studied. In this work, we propose a neural mechanism for adaptive inhibitory control in a firing-rate type model based on current findings in animal electrophysiological and human psychophysical experiments. We then implement this model on a field-programmable gate array (FPGA) prototyping system, using dedicated real-time hardwa...

  20. Adaptive Proactive Inhibitory Control for Embedded Real-time Applications

    Shufan Yang

    2012-01-01

    Psychologists have studied the inhibitory control of voluntary movement for many years. In particular, the countermanding of an impending action has been extensively studied. In this work, we propose a neural mechanism for adaptive inhibitory control in a firing-rate type model based on current findings in animal electrophysiological and human psychophysical experiments. We then implement this model on a field-programmable gate array (FPGA) prototyping system, using dedicated real-time hardwa...

  1. Flexible parylene actuator for micro adaptive flow control

    Pornsin-Sirirak, T. N.; Tai, Y. C.; Nassef, H.; Ho, C M

    2001-01-01

    This paper describes the first flexible parylene electrostatic actuator valves intended for micro adaptive flow control for the future use on the wings of micro-air-vehicle (MAV). The actuator diaphragm is made of two layers of parylene membranes with offset vent holes. Without electrostatic actuation, air can move freely from one side of the skin to the other side through the vent holes. With actuation, these vent holes are sealed and the airflow is controlled. The membrane behaves as a comp...

  2. Adaptive Control of the Chaotic System via Singular System Approach

    Yudong Li

    2014-01-01

    Full Text Available This paper deals with the control problem of the chaotic system subject to disturbance. The sliding mode surface is designed by singular system approach, and sufficient condition for convergence is given. Then, the adaptive sliding mode controller is designed to make the state arrive at the sliding mode surface in finite time. Finally, Lorenz system is considered as an example to show the effectiveness of the proposed method.

  3. Adaptive Medium Access Control Protocol for Wireless Body Area Networks

    Javaid, N.; Ahmad, A.; A. Rahim; Z.A. Khan; M. Ishfaq; Qasim, U.

    2014-01-01

    Wireless Body Area Networks (WBANs) are widely used for applications such as modern health-care systems, where wireless sensors (nodes) monitor the parameter(s) of interest. Nodes are provided with limited battery power and battery power is dependent on radio activity. MAC protocols play a key role in controlling the radio activity. Therefore, we present Adaptive Medium Access Control (A-MAC) protocol for WBANs supported by linear programming models for the minimization of energy consumption ...

  4. Active Inference, homeostatic regulation and adaptive behavioural control

    Pezzulo, G; Rigoli, F.; Friston, K.

    2015-01-01

    We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a...

  5. ADAPTIVE CONTROLLER AND ITS APPLICATION IN FORCE SYSTEM OF ASYMMETRIC CYLINDER CONTROLLED BY SYMMETRIC VALVE

    2007-01-01

    Partial pressure, system vibration and asymmetric system dynamic performance exit in asymmetric cylinder controller by symmetric valve hydraulic system. To solve this problem in the force control system, model reference adaptive controller is designed using equilibrium point stability theory and output error equation polynomial. The reference model is selected in such a way that it meets the system dynamic performance. Hardware configuration of asymmetric cylinder controlled by asymmetric valve hydraulic system is replaced by intelligent control algorithm, thus the cost is lowered and easy to application. Simulation results demonstrate that the proposed adaptive control sheme has good adaptive ability and well solves asymmetric dynamic performance problem. The designed adaptive controller is fairly robust to load disturbance and system parameter variation.

  6. A Comprehensive Robust Adaptive Controller for Gust Load Alleviation

    Elisa Capello

    2014-01-01

    Full Text Available The objective of this paper is the implementation and validation of an adaptive controller for aircraft gust load alleviation. The contribution of this paper is the design of a robust controller that guarantees the reduction of the gust loads, even when the nominal conditions change. Some preliminary results are presented, considering the symmetric aileron deflection as control device. The proposed approach is validated on subsonic transport aircraft for different mass and flight conditions. Moreover, if the controller parameters are tuned for a specific gust model, even if the gust frequency changes, no parameter retuning is required.

  7. Decentralized adaptive generalized predictive control for structural vibration

    LU Minyue; GU Zhongquan

    2005-01-01

    A decentralized generalized predictive control (GPC) algorithm is developed for strongly coupled multi-input multi-output systems with parallel computation. The algorithm is applied to adaptive control of structural vibration. The key steps in this algorithm are to group the actuators and the sensors and then to pair these groups into subsystems. It is important that the on-line identification and the control law design can be a parallel process for all these subsystems. It avoids the high computation cost in ordinary predictive control,and is of great advantage especially for large-scale systems.

  8. A novel adaptive force control method for IPMC manipulation

    Hao, Lina; Sun, Zhiyong; Li, Zhi; Su, Yunquan; Gao, Jianchao

    2012-07-01

    IPMC is a type of electro-active polymer material, also called artificial muscle, which can generate a relatively large deformation under a relatively low input voltage (generally speaking, less than 5 V), and can be implemented in a water environment. Due to these advantages, IPMC can be used in many fields such as biomimetics, service robots, bio-manipulation, etc. Until now, most existing methods for IPMC manipulation are displacement control not directly force control, however, under most conditions, the success rate of manipulations for tiny fragile objects is limited by the contact force, such as using an IPMC gripper to fix cells. Like most EAPs, a creep phenomenon exists in IPMC, of which the generated force will change with time and the creep model will be influenced by the change of the water content or other environmental factors, so a proper force control method is urgently needed. This paper presents a novel adaptive force control method (AIPOF control—adaptive integral periodic output feedback control), based on employing a creep model of which parameters are obtained by using the FRLS on-line identification method. The AIPOF control method can achieve an arbitrary pole configuration as long as the plant is controllable and observable. This paper also designs the POF and IPOF controller to compare their test results. Simulation and experiments of micro-force-tracking tests are carried out, with results confirming that the proposed control method is viable.

  9. Robust observer-based adaptive fuzzy sliding mode controller

    Oveisi, Atta; Nestorović, Tamara

    2016-08-01

    In this paper, a new observer-based adaptive fuzzy integral sliding mode controller is proposed based on the Lyapunov stability theorem. The plant is subjected to a square-integrable disturbance and is assumed to have mismatch uncertainties both in state- and input-matrices. Based on the classical sliding mode controller, the equivalent control effort is obtained to satisfy the sufficient requirement of sliding mode controller and then the control law is modified to guarantee the reachability of the system trajectory to the sliding manifold. In order to relax the norm-bounded constrains on the control law and solve the chattering problem of sliding mode controller, a fuzzy logic inference mechanism is combined with the controller. An adaptive law is then introduced to tune the parameters of the fuzzy system on-line. Finally, for evaluating the controller and the robust performance of the closed-loop system, the proposed regulator is implemented on a real-time mechanical vibrating system.

  10. Dynamic data-driven sensor network adaptation for border control

    Bein, Doina; Madan, Bharat B.; Phoha, Shashi; Rajtmajer, Sarah; Rish, Anna

    2013-06-01

    Given a specific scenario for the border control problem, we propose a dynamic data-driven adaptation of the associated sensor network via embedded software agents which make sensor network control, adaptation and collaboration decisions based on the contextual information value of competing data provided by different multi-modal sensors. We further propose the use of influence diagrams to guide data-driven decision making in selecting the appropriate action or course of actions which maximize a given utility function by designing a sensor embedded software agent that uses an influence diagram to make decisions about whether to engage or not engage higher level sensors for accurately detecting human presence in the region. The overarching goal of the sensor system is to increase the probability of target detection and classification and reduce the rate of false alarms. The proposed decision support software agent is validated experimentally on a laboratory testbed for multiple border control scenarios.

  11. A Robot Manipulator with Adaptive Fuzzy Controller in Obstacle Avoidance

    Sreekumar, Muthuswamy

    2016-03-01

    Building robots and machines to act within a fuzzy environment is a problem featuring complexity and ambiguity. In order to avoid obstacles, or move away from it, the robot has to perform functions such as obstacle identification, finding the location of the obstacle, its velocity, direction of movement, size, shape, and so on. This paper presents about the design, and implementation of an adaptive fuzzy controller designed for a 3 degree of freedom spherical coordinate robotic manipulator interfaced with a microcontroller and an ultrasonic sensor. Distance between the obstacle and the sensor and its time rate are considered as inputs to the controller and how the manipulator to take diversion from its planned trajectory, in order to avoid collision with the obstacle, is treated as output from the controller. The obstacles are identified as stationary or moving objects and accordingly adaptive self tuning is accomplished with three set of linguistic rules. The prototype of the manipulator has been fabricated and tested for collision avoidance by placing stationary and moving obstacles in its planned trajectory. The performance of the adaptive control algorithm is analyzed in MATLAB by generating 3D fuzzy control surfaces.

  12. Adaptation with disturbance attenuation in nonlinear control systems

    Basar, T. [Univ. of Illinois, Urbana, IL (United States)

    1997-12-31

    We present an optimization-based adaptive controller design for nonlinear systems exhibiting parametric as well as functional uncertainty. The approach involves the formulation of an appropriate cost functional that places positive weight on deviations from the achievement of desired objectives (such as tracking of a reference trajectory while the system exhibits good transient performance) and negative weight on the energy of the uncertainty. This cost functional also translates into a disturbance attenuation inequality which quantifies the effect of the presence of uncertainty on the desired objective, which in turn yields an interpretation for the optimizing control as one that optimally attenuates the disturbance, viewed as the collection of unknown parameters and unknown signals entering the system dynamics. In addition to this disturbance attenuation property, the controllers obtained also feature adaptation in the sense that they help with identification of the unknown parameters, even though this has not been set as the primary goal of the design. In spite of this adaptation/identification role, the controllers obtained are not of certainty-equivalent type, which means that the identification and the control phases of the design are not decoupled.

  13. Adaptive Vibration Control System for MR Damper Faults

    Juan C. Tudón-Martínez

    2015-01-01

    Full Text Available Several methods have been proposed to estimate the force of a semiactive damper, particularly of a magnetorheological damper because of its importance in automotive and civil engineering. Usually, all models have been proposed assuming experimental data in nominal operating conditions and some of them are estimated for control purposes. Because dampers are prone to fail, fault estimation is useful to design adaptive vibration controllers to accommodate the malfunction in the suspension system. This paper deals with the diagnosis and estimation of faults in an automotive magnetorheological damper. A robust LPV observer is proposed to estimate the lack of force caused by a damper leakage in a vehicle corner. Once the faulty damper is isolated in the vehicle and the fault is estimated, an Adaptive Vibration Control System is proposed to reduce the fault effect using compensation forces from the remaining healthy dampers. To fulfill the semiactive damper constraints in the fault adaptation, an LPV controller is designed for vehicle comfort and road holding. Simulation results show that the fault observer has good performance with robustness to noise and road disturbances and the proposed AVCS improves the comfort up to 24% with respect to a controlled suspension without fault tolerance features.

  14. A Robot Manipulator with Adaptive Fuzzy Controller in Obstacle Avoidance

    Sreekumar, Muthuswamy

    2016-07-01

    Building robots and machines to act within a fuzzy environment is a problem featuring complexity and ambiguity. In order to avoid obstacles, or move away from it, the robot has to perform functions such as obstacle identification, finding the location of the obstacle, its velocity, direction of movement, size, shape, and so on. This paper presents about the design, and implementation of an adaptive fuzzy controller designed for a 3 degree of freedom spherical coordinate robotic manipulator interfaced with a microcontroller and an ultrasonic sensor. Distance between the obstacle and the sensor and its time rate are considered as inputs to the controller and how the manipulator to take diversion from its planned trajectory, in order to avoid collision with the obstacle, is treated as output from the controller. The obstacles are identified as stationary or moving objects and accordingly adaptive self tuning is accomplished with three set of linguistic rules. The prototype of the manipulator has been fabricated and tested for collision avoidance by placing stationary and moving obstacles in its planned trajectory. The performance of the adaptive control algorithm is analyzed in MATLAB by generating 3D fuzzy control surfaces.

  15. Beaconless adaptive-optics technique for HEL beam control

    Khizhnyak, Anatoliy; Markov, Vladimir

    2016-05-01

    Effective performance of forthcoming laser systems capable of power delivery on a distant target requires an adaptive optics system to correct atmospheric perturbations on the laser beam. The turbulence-induced effects are responsible for beam wobbling, wandering, and intensity scintillation, resulting in degradation of the beam quality and power density on the target. Adaptive optics methods are used to compensate for these negative effects. In its turn, operation of the AOS system requires a reference wave that can be generated by the beacon on the target. This report discusses a beaconless approach for wavefront correction with its performance based on the detection of the target-scattered light. Postprocessing of the beacon-generated light field enables retrieval and detailed characterization of the turbulence-perturbed wavefront -data that is essential to control the adaptive optics module of a high-power laser system.

  16. Flexible Joints Robotic Manipulator Control By Adaptive Gain Smooth Sliding Observer-Controller

    A. FILIPESCU

    2003-12-01

    Full Text Available An adaptive gain sliding observer for uncertain parameter nonlinear systems together with an adaptive gain sliding controller is proposed in this paper. It considered nonlinear, SISO affine systems, with uncertainties in steady-state functions and parameters. A further parameter term, adaptively updated, has been introduced in steady state space model of the controlled system, in order to obtain useful information despite fault detection and isolation. By using of the sliding observer with adaptive gain, the robustness to uncertainties is increased and the parameters adaptively updated can provide useful information in fault detection. Also, the state estimation error is bounded accordingly with bound limits of the uncertainties. The both of them, the sliding adaptive observer and sliding controller are designed to fulfill the attractiveness condition of its corresponding switching surface. An application to a single arm with flexible joint robot is presented. In order to alleviate chattering, a parameterized tangent hyperbolic has been used as switching function, instead of pure relay one, to the observer and the controller. Also, the gains of the switching functions, to the sliding observer and sliding controller are adaptively updated depending of estimation error and tracking error, respectively. By the using adaptive gains, the transient and tracking response can be improved.

  17. Direct model reference adaptive control of a flexible robotic manipulator

    Meldrum, D. R.

    1985-01-01

    Quick, precise control of a flexible manipulator in a space environment is essential for future Space Station repair and satellite servicing. Numerous control algorithms have proven successful in controlling rigid manipulators wih colocated sensors and actuators; however, few have been tested on a flexible manipulator with noncolocated sensors and actuators. In this thesis, a model reference adaptive control (MRAC) scheme based on command generator tracker theory is designed for a flexible manipulator. Quicker, more precise tracking results are expected over nonadaptive control laws for this MRAC approach. Equations of motion in modal coordinates are derived for a single-link, flexible manipulator with an actuator at the pinned-end and a sensor at the free end. An MRAC is designed with the objective of controlling the torquing actuator so that the tip position follows a trajectory that is prescribed by the reference model. An appealing feature of this direct MRAC law is that it allows the reference model to have fewer states than the plant itself. Direct adaptive control also adjusts the controller parameters directly with knowledge of only the plant output and input signals.

  18. VFI-based Robotic Arm Control for Natural Adaptive Motion

    Woosung Yang

    2014-03-01

    Full Text Available Since neural oscillator based control methods can generate rhythmic motion without information on system dynamics, they can be a promising alternative to traditional motion planning based control approaches. However, for field application, they still need to be robust against unexpected forces or changes in environments so as to be able to generate “natural motion” like most biological systems. In this study a biologically inspired control algorithm that combines neural oscillators and virtual force is proposed. This work gives the condition with respect to parameters tuning to stably activate the neural oscillators. This is helpful to achieve motion adaptability to environmental changes keeping the motion repeatability. He efficacy and efficiency of the proposed methods are tested in the control of a planar three-linkage robotic arm. It is shown that the proposed controller generates a given circular path stably and repeatedly, even with unexpected contact with a wall. The adaptivity of motion control is also tested in control of a robotic arm with redundant degrees of freedom. The proposed control algorithm works throughout the simulations and experiments.

  19. Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems

    Jinxiang Dong

    2008-07-01

    Full Text Available There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting crosslayer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An eventdriven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN.

  20. Microgrid Stability Controller Based on Adaptive Robust Total SMC

    Su, Xiaoling; Han, Minxiao; Guerrero, Josep M.; Sun, Hai

    2015-01-01

    This paper presents a microgrid stability controller (MSC) in order to provide existing DGs the additional functionality of working in islanding mode without changing their control strategies in grid-connected mode and to enhance the stability of the microgrid. Microgrid operating characteristics...... and mathematical models of the MSC indicate that the system is inherently nonlinear and time-variable. Therefore, this paper proposes an adaptive robust total sliding-mode control (ARTSMC) system for the MSC. It is proved that the ARTSMC system is insensitive to parametric uncertainties and external...

  1. Energy-saving technology of vector controlled induction motor based on the adaptive neuro-controller

    Engel, E.; Kovalev, I. V.; Karandeev, D.

    2015-10-01

    The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.

  2. Geometry adaptive control of a composite reflector using PZT actuator

    Lan, Lan; Jiang, Shuidong; Zhou, Yang; Fang, Houfei; Tan, Shujun; Wu, Zhigang

    2015-04-01

    Maintaining geometrical high precision for a graphite fiber reinforced composite (GFRC) reflector is a challenging task. Although great efforts have been placed to improve the fabrication precision, geometry adaptive control for a reflector is becoming more and more necessary. This paper studied geometry adaptive control for a GFRC reflector with piezoelectric ceramic transducer (PZT) actuators assembled on the ribs. In order to model the piezoelectric effect in finite element analysis (FEA), a thermal analogy was used in which the temperature was applied to simulate the actuation voltage, and the piezoelectric constant was mimicked by a Coefficient of Thermal Expansion (CTE). PZT actuator's equivalent model was validated by an experiment. The deformations of a triangular GFRC specimen with three PZT actuators were also measured experimentally and compared with that of simulation. This study developed a multidisciplinary analytical model, which includes the composite structure, thermal, thermal deformation and control system, to perform an optimization analysis and design for the adaptive GFRC reflector by considering the free vibration, gravity deformation and geometry controllability.

  3. Adaptive and predictive control of a simulated robot arm.

    Tolu, Silvia; Vanegas, Mauricio; Garrido, Jesús A; Luque, Niceto R; Ros, Eduardo

    2013-06-01

    In this work, a basic cerebellar neural layer and a machine learning engine are embedded in a recurrent loop which avoids dealing with the motor error or distal error problem. The presented approach learns the motor control based on available sensor error estimates (position, velocity, and acceleration) without explicitly knowing the motor errors. The paper focuses on how to decompose the input into different components in order to facilitate the learning process using an automatic incremental learning model (locally weighted projection regression (LWPR) algorithm). LWPR incrementally learns the forward model of the robot arm and provides the cerebellar module with optimal pre-processed signals. We present a recurrent adaptive control architecture in which an adaptive feedback (AF) controller guarantees a precise, compliant, and stable control during the manipulation of objects. Therefore, this approach efficiently integrates a bio-inspired module (cerebellar circuitry) with a machine learning component (LWPR). The cerebellar-LWPR synergy makes the robot adaptable to changing conditions. We evaluate how this scheme scales for robot-arms of a high number of degrees of freedom (DOFs) using a simulated model of a robot arm of the new generation of light weight robots (LWRs). PMID:23627657

  4. A Proposal of Adaptive PID Controller Based on Reinforcement Learning

    WANG Xue-song; CHENG Yu-hu; SUN Wei

    2007-01-01

    Aimed at the lack of self-tuning PID parameters in conventional PID controllers, the structure and learning algorithm of an adaptive PID controller based on reinforcement learning were proposed. Actor-Critic learning was used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency,a single RBF neural network was used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for complex nonlinear systems and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

  5. Model reference adaptive force and surface roughness control in milling

    F. Cus

    2008-02-01

    Full Text Available Purpose: of this paper. The paper presents the model based mechanism of control assuring constant quality of surface finish by controlling the cutting forces in the end milling process. By dynamic adaptation of feeding and speed the system controls the surface roughness and the cutting forces on the milling cutter. The purpose of developing such a mechanism is to find the limitations of such control which maintains constant cutting force by adapting the cutting parameters.Design/methodology/approach: The model based system of control has been developed by the evolutionary method of genetic programming (GP. A drawing of experiments has been made in order to determine the empirical correlations between the quality of surface finish and the cutting force. Genetic programming method has been applied to derive empirical relationship of the surface finish and cutting force values for steel material. These relationships have been applied to develop the proposed evolution simulation model in which the cutting force is adjusted to improve the required surface quality.Findings: The system eliminates the problems related to assurance of quality of machining, efficiency of machining and prevention of tool damages.Research limitations/implications: While force control approach performed satisfactorily in a laboratory environment, it can be generally concluded that their implementation should be dictated by the economics of the production environment.Practical implications: The results provide a means of greater efficiency by improving the surface quality, minimizing the effect of the process variability and reducing the error cost in finishing operations.Originality/value: An adaptive system of control which controls the cutting force and maintains constant roughness of the machined surface during milling by continuous dynamic adjustment of the cutting parameters is devolped.

  6. Dissipative-based adaptive neural control for nonlinear systems

    Yugang NIU; Xingyu WANG; Junwei LU

    2004-01-01

    A dissipative-based adaptive neural control scheme was developed for a class of nonlinear uncertain systems with unknown nonlinearities that might not be linearly parameterized. The major advantage of the present work was to relax the requirement of matching condition, I.e., the unknown nonlinearities appear on the same equation as the control input in a state-space representation, which was required in most of the available neural network controllers. By synthesizing a state-feedback neural controller to nake the closed-loop system dissipative with respect to a quadratic supply rate, the developed control scheme guarantees that the L2-gain of controlled system was less than or equal to a prescribed level. And then, it is shown that the output tracking error is uniformly ultimate bounded. The design scheme is illustrated using a numerical simulation.

  7. Adaptive model predictive process control using neural networks

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

  8. Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

    Volyanskyy, Kostyantyn Y.

    Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance

  9. Discrete-time minimal control synthesis adaptive algorithm

    di Bernardo, M.; di Gennaro, F.; Olm, J. M.; Santini, S.

    2010-12-01

    This article proposes a discrete-time Minimal Control Synthesis (MCS) algorithm for a class of single-input single-output discrete-time systems written in controllable canonical form. As it happens with the continuous-time MCS strategy, the algorithm arises from the family of hyperstability-based discrete-time model reference adaptive controllers introduced in (Landau, Y. (1979), Adaptive Control: The Model Reference Approach, New York: Marcel Dekker, Inc.) and is able to ensure tracking of the states of a given reference model with minimal knowledge about the plant. The control design shows robustness to parameter uncertainties, slow parameter variation and matched disturbances. Furthermore, it is proved that the proposed discrete-time MCS algorithm can be used to control discretised continuous-time plants with the same performance features. Contrary to previous discrete-time implementations of the continuous-time MCS algorithm, here a formal proof of asymptotic stability is given for generic n-dimensional plants in controllable canonical form. The theoretical approach is validated by means of simulation results.

  10. A modified Adaptive Wavelet PID Control Based on Reinforcement Learning for Wind Energy Conversion System Control

    REZAZADEH, A.

    2010-05-01

    Full Text Available Nonlinear characteristics of wind turbines and electric generators necessitate complicated and nonlinear control of grid connected Wind Energy Conversion Systems (WECS. This paper proposes a modified self-tuning PID control strategy, using reinforcement learning for WECS control. The controller employs Actor-Critic learning in order to tune PID parameters adaptively. These Actor-Critic learning is a special kind of reinforcement learning that uses a single wavelet neural network to approximate the policy function of the Actor and the value function of the Critic simultaneously. These controllers are used to control a typical WECS in noiseless and noisy condition and results are compared with an adaptive Radial Basis Function (RBF PID control based on reinforcement learning and conventional PID control. Practical emulated results prove the capability and the robustness of the suggested controller versus the other PID controllers to control of the WECS. The ability of presented controller is tested by experimental setup.

  11. Adaptive Traffic Signalization Model using Neuro-Fuzzy Controllers

    Devesh Batra*

    2014-07-01

    Full Text Available Current traffic lights are pre-programmed and use daily signal timing schedules, which contribute to traffic congestion and delay. Thus, with the increase in the number of vehicles on road, need for adaptive signal technology arises which has the potential to adjust the timing of red, yellow and green lights in order to accommodate changing traffic patterns and ease traffic congestion. In this paper, we present a model for adaptive traffic signalization, which uses fuzzy neural network for designing traffic signal controller. The controllers use vehicle detectors in order to detect the number of incoming vehicles. Based on the number of approaching vehicles, the current signal phase is either extended or terminated. The traffic volume at one particular region in an intersection is compared with that in the competing regions of the same intersection. The decision made is thus robust and results in less congestion and delays.

  12. Cell cycle control after DNA damage: arrest, recovery and adaptation

    DNA damage triggers surveillance mechanisms, the DNA checkpoints, that control the genome integrity. The DNA checkpoints induce several responses, either cellular or transcriptional, that favor DNA repair. In particular, activation of the DNA checkpoints inhibits cell cycle progression in all phases, depending on the stage when lesions occur. These arrests are generally transient and cells ultimately reenter the cell division cycle whether lesions have been repaired (this process is termed 'recovery') or have proved un-repairable (this option is called 'adaptation'). The mechanisms controlling cell cycle arrests, recovery and adaptation are largely conserved among eukaryotes, and much information is now available for the yeast Saccharomyces cerevisiae, that is used as a model organism in these studies. (author)

  13. Adaptive control of ROVs with actuator dynamics and saturation

    Ola-Erik Fjellstad

    1992-07-01

    Full Text Available A direct model reference adaptive controller (MRAC is derived for an underwater vehicle with significant thruster dynamics and limited thruster power. The reference model decomposition (RMD technique is used to compensate for the thruster dynamics. A reference model adjustment (RMA technique modifying the reference model acceleration is used to avoid thruster saturation. The design methods are simulated for the yawing motion of an underwater vehicle.

  14. Thermotropic and Thermochromic Polymer Based Materials for Adaptive Solar Control

    Olaf Mühling; Ralf Ruhmann; Arno Seeboth

    2010-01-01

    The aim of this review is to present the actual status of development in adaptive solar control by use of thermotropic and organic thermochromic materials. Such materials are suitable for application in smart windows. In detail polymer blends, hydrogels, resins, and thermoplastic films with a reversible temperature-dependent switching behavior are described. A comparative evaluation of the concepts for these energy efficient materials is given as well. Furthermore, the change of strategy from...

  15. Reinforcement Learning Adaptive Control and Explicit Criterion Maximization

    Landelius, Tomas; Knutsson, Hans

    1996-01-01

    This paper reviews an existing algorithm for adaptive control based on explicit criterion maximization (ECM) and presents an extended version suited for reinforcement learning tasks. Furthermore, assumptions under which the algorithm convergences to a local maxima of a long term utility function are given. Such convergence theorems are very rare for reinforcement learning algorithms working with continuous state and action spaces. A number of similar algorithms, previously suggested to the re...

  16. Decoding Information by Following Parameter Modulation With Parameter Adaptive Control

    Zhou, Changsong; Lai, C.-H.

    2000-01-01

    It has been proposed to realize secure communication using chaotic synchronization via transmission of binary message encoded by parameter modulation in the chaotic system. This paper considers the use of parameter adaptive control techniques to extract the message, based on the assumptions that we know the equation form of the chaotic system in the transmitter but do not have access to the precise values of the parameters which are kept secret as a secure set. In the case that a synchronizin...

  17. Comparison of Adaptive Antenna Arrays Controlled by Gradient Algorithms

    Z. Raida

    1994-09-01

    Full Text Available The paper presents the Simple Kalman filter (SKF that has been designed for the control of digital adaptive antenna arrays. The SKF has been applied to the pilot signal system and the steering vector one. The above systems based on the SKF are compared with adaptive antenna arrays controlled by the classical LMS and the Variable Step Size (VSS LMS algorithms and by the pure Kalman filter. It is shown that the pure Kalman filter is the most convenient for the control of the adaptive arrays because it does not require any a priori information about noise statistics and excels in high rate of convergence and low misadjustment. Extremely high computational requirements are drawback of this filter. Hence, if low computational power of signal processors is at the disposal, the SKF is recommended to be used. Computational requirements of the SKF are of the same order as the classical LMS algorithm exhibits. On the other hand, all the important features of the pure Kalman filter are inherited by the SKF. The paper shows that presented Kalman filters can be regarded as special gradient algorithms. That is why they can be compared with the LMS family.

  18. Adaptive power-controllable orbital angular momentum (OAM) multicasting

    Li, Shuhui; Wang, Jian

    2015-01-01

    We report feedback-assisted adaptive multicasting from a single Gaussian mode to multiple orbital angular momentum (OAM) modes using a single phase-only spatial light modulator loaded with a complex phase pattern. By designing and optimizing the complex phase pattern through the adaptive correction of feedback coefficients, the power of each multicast OAM channel can be arbitrarily controlled. We experimentally demonstrate power-controllable multicasting from a single Gaussian mode to two and six OAM modes with different target power distributions. Equalized power multicasting, “up-down” power multicasting and “ladder” power multicasting are realized in the experiment. The difference between measured power distributions and target power distributions is assessed to be less than 1 dB. Moreover, we demonstrate data-carrying OAM multicasting by employing orthogonal frequency-division multiplexing 64-ary quadrature amplitude modulation (OFDM 64-QAM) signal. The measured bit-error rate curves and observed optical signal-to-noise ratio penalties show favorable operation performance of the proposed adaptive power-controllable OAM multicasting. PMID:25989251

  19. Adaptive power-controllable orbital angular momentum (OAM) multicasting.

    Li, Shuhui; Wang, Jian

    2015-01-01

    We report feedback-assisted adaptive multicasting from a single Gaussian mode to multiple orbital angular momentum (OAM) modes using a single phase-only spatial light modulator loaded with a complex phase pattern. By designing and optimizing the complex phase pattern through the adaptive correction of feedback coefficients, the power of each multicast OAM channel can be arbitrarily controlled. We experimentally demonstrate power-controllable multicasting from a single Gaussian mode to two and six OAM modes with different target power distributions. Equalized power multicasting, "up-down" power multicasting and "ladder" power multicasting are realized in the experiment. The difference between measured power distributions and target power distributions is assessed to be less than 1 dB. Moreover, we demonstrate data-carrying OAM multicasting by employing orthogonal frequency-division multiplexing 64-ary quadrature amplitude modulation (OFDM 64-QAM) signal. The measured bit-error rate curves and observed optical signal-to-noise ratio penalties show favorable operation performance of the proposed adaptive power-controllable OAM multicasting. PMID:25989251

  20. Robust adaptive control of underwater vehicles: A comparative study

    Thor I. Fossen

    1996-01-01

    Full Text Available Robust adaptive control of underwater vehicles in 6 DOF is analysed in the context of measurement noise. The performance of the adaptive control laws of Sadegh and Harowitz (1990 and Slotine and Benedetto (1990 are compared. Both these schemes require that all states are measured, that is the velocities and positions in surge, sway, heave, roll, pitch and yaw. However, for underwater vehicles it is difficult to measure the linear velocities whereas angular velocity measurements can be obtained by using a 3 axes angular rate sensor. This problem is addressed by designing a nonlinear observer for linear velocity state estimation. The proposed observer requires that the position and the attitude are measured, e.g. by using a hydroacoustic positioning system for linear positions, two gyros for roll and pitch and a compass for yaw. In addition angular rate measurements will be assumed available from a 3-axes rate sensor or a state estimator. It is also assumed that the measurement rate is limited to 2 Hz for all the sensors. Simulation studies with a 3 DOF AUV model are used to demonstrate the convergence and robustness of the adaptive control laws and the velocity state observer.

  1. Adaptive Proactive Inhibitory Control for Embedded Real-time Applications

    Shufan Yang

    2012-06-01

    Full Text Available Psychologists have studied the inhibitory control of voluntary movement for many years. In particular, the countermanding of an impending action has been extensively studied. In this work, we propose a neural mechanism for adaptive inhibitory control in a firing-rate type model based on current findings in animal electrophysiological and human psychophysical experiments. We then implement this model on a field-programmable gate array (FPGA prototyping system, using dedicated real-time hardware circuitry. Our results show that the FPGA-based implementation can run in real time while achieving behavioural performance qualitatively suggestive of the animal experiments. Implementing such biological inhibitory control in an embedded device can lead to the development of control systems that may be used in more realistic cognitive robotics or in neural prosthetic systems aiding human movement control.

  2. Robust Adaptive Reactive Power Control for Doubly Fed Induction Generator

    Huabin Wen

    2014-01-01

    Full Text Available The problem of reactive power control for mains-side inverter (MSI in doubly fed induction generator (DFIG is studied in this paper. To accommodate the modelling nonlinearities and inherent uncertainties, a novel robust adaptive control algorithm for MSI is proposed by utilizing Lyapunov theory that ensures asymptotic stability of the system under unpredictable external disturbances and significant parametric uncertainties. The distinguishing benefit of the aforementioned scheme consists in its capabilities to maintain satisfactory performance under varying operation conditions without the need for manually redesigning or reprogramming the control gains in contrast to the commonly used PI/PID control. Simulations are also built to confirm the correctness and benefits of the control scheme.

  3. Speed Sensorless Vector Control of Unbalanced Three-Phase Induction Motor with Adaptive Sliding Mode Control

    Mohammad Jannati

    2014-05-01

    Full Text Available This paper presents a technique for speed sensorless Rotor Flux Oriented Control (RFOC of 3-phase Induction Motor (IM under open-phase fault (unbalanced or faulty IM. The presented RFOC strategy is based on rotational transformation. An adaptive sliding mode control system with an adaptive switching gain is proposed instead of the speed PI controller. Using an adaptive sliding mode control causes the proposed speed sensorless RFOC drive system to become insensitive to uncertainties such as load disturbances and parameter variations. Moreover, with adaptation of the sliding switching gain, calculation of the system uncertainties upper bound is not needed. Finally, simulation results have been presented to confirm the good performance of the proposed method.

  4. Are integral controllers adapted to the new era of ELT adaptive optics?

    Conan, J.-M.; Raynaud, H.-F.; Kulcsár, C.; Meimon, S.

    2011-09-01

    With ELTs we are now entering a new era in adaptive optics developments. Meeting unprecedented level of performance with incredibly complex systems implies reconsidering AO concepts at all levels, including controller design. Concentrating mainly on temporal aspects, one may wonder if integral controllers remain an adequate solution. This question is all the more important that, with ever larger degrees of freedom, one may be tempted to discard more sophisticated approaches because they are deemed too complex to implement. The respective performance of integrator versus LQG control should therefore be carefully evaluated in the ELT context. We recall for instance the impressive correction improvement brought by such controllers for the rejection of windshake and vibration components. LQG controller significantly outperforms the integrator because its disturbance rejection transfer function closely matches the energy concentration, respectively at low temporal frequencies for windshake, and around localized resonant peaks for vibrations. The application to turbulent modes should also be investigated, especially for very low spatial frequencies now explored on the huge ELT pupil. The questions addressed here are: 1/ How do integral and LQG controllers compare in terms of performance for a given sampling frequency and noise level?; 2/ Could we relax sampling frequency with LQG control?; 3/ Does a mode to mode adaptation of temporal rejection bring significant performance improvement?; 4/ Which modes particularly benefit from this fine tuning of the rejection transfer function? Based on a simplified ELT AO configuration, and through a simple analytical formulation, performance is evaluated for several control approaches. Various assumptions concerning the perturbation parameters (seeing and outer-scale value, windshake amplitude) are considered. Bode's integral theorem allows intuitive understanding of the results. Practical implementation and computation complexity

  5. Adaptive Fractional Fuzzy Sliding Mode Control for Multivariable Nonlinear Systems

    Junhai Luo

    2014-01-01

    Full Text Available This paper presents a robust adaptive fuzzy sliding mode control method for a class of uncertain nonlinear systems. The fractional order calculus is employed in the parameter updating stage. The underlying stability analysis as well as parameter update law design is carried out by Lyapunov based technique. In the simulation, two examples including a comparison with the traditional integer order counterpart are given to show the effectiveness of the proposed method. The main contribution of this paper consists in the control performance is better for the fractional order updating law than that of traditional integer order.

  6. Model-Free Adaptive Control Algorithm with Data Dropout Compensation

    Xuhui Bu

    2012-01-01

    Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.

  7. Optimization of adaptive feedback control for ultrafast semiconductor spectroscopy

    We present an experimental study of the control of ultrafast semiconductor nonlinearities by adaptive feedback optical pulse shaping. In the feedback loop, an evolutionary algorithm directs the modulation of the spectral phase of 20-fs laser pulses. In this way, control is achieved over the broadband semiconductor continuum nonlinearity as measured in differential transmission experiments. Design guidelines are given for the implementation of the evolutionary algorithm. Our results demonstrate that a feedback loop with a carefully designed algorithm can serve as a new, sensitive tool in ultrafast semiconductor spectroscopy. Moreover, an optimized feedback loop allows for the substantial enhancement of ultrafast semiconductor nonlinearities. [copyright] 2001 Optical Society of America

  8. Mechanisms in Adaptive Feedback Control: Photoisomerization in a Liquid

    Hoki, K; Hoki, Kunihito; Brumer, Paul

    2005-01-01

    The underlying mechanism for Adaptive Feedback Control in the experimental photoisomerization of NK88 in methanol is exposed theoretically. With given laboratory limitations on laser output, the complicated electric fields are shown to achieve their targets in qualitatively simple ways. Further, control over the cis population without laser limitations reveals an incoherent pump-dump scenario as the optimal isomerization strategy. In neither case are there substantial contributions from quantum multiple-path interference or from nuclear wavepacket coherence. Environmentally induced decoherence is shown to justify the use of a simplified theoretical model.

  9. Non-linear and adaptive control of a refrigeration system

    Rasmussen, Henrik; Larsen, Lars F. S.

    2011-01-01

    capacities ensures a high energy efficiency. The level of liquid filling is indirectly measured by the superheat. Introduction of variable speed compressors and electronic expansion valves enables the use of more sophisticated control algorithms, giving a higher degree of performance and just as important...... and used in a backstepping design of a nonlinear adaptive controller. The stability of the proposed method is validated theoretically by Lyapunov analysis and experimental results show the performance of the system for a wide range of operating points. The method is compared to a conventional method based...

  10. Generalized projective synchronization of chaotic systems via adaptive learning control

    In this paper, a learning control approach is applied to the generalized projective synchronisation (GPS) of different chaotic systems with unknown periodically time-varying parameters. Using the Lyapunov–Krasovskii functional stability theory, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to make the states of two different chaotic systems asymptotically synchronised. The scheme is successfully applied to the generalized projective synchronisation between the Lorenz system and Chen system. Moreover, numerical simulations results are used to verify the effectiveness of the proposed scheme. (general)

  11. Application of Adaptive Filters to Active Noise Control

    PEI Bingnan; LI Chuanguang

    2001-01-01

    A modified LMS algorithm for noise-control is suggested after a mathematical model ofsound-cancellation is established, on the basis of thesound wave interference principle and the physicalmodel of progressive waves in a duct. Its applicationin controlling noise with the frequency range from 100to 800 Hz can be implemented by using the adaptivedigital signal processing technique. The experimentson a pink noise, a broadband noise and a noise takenfrom a tank were made, which show that there existsan attenuation of 11 dB at the frequency of 500 Hzor so, and that the proposed adaptive noise controltechnique is very effective and valid.

  12. A Bayesian Rule for Adaptive Control based on Causal Interventions

    Ortega, Pedro A

    2009-01-01

    Explaining adaptive behavior is a central problem in artificial intelligence research. Here we formalize adaptive agents as mixture distributions over sequences of inputs and outputs (I/O). Each distribution of the mixture constitutes a 'possible world', but the agent does not know which of the possible worlds it is actually facing. The problem is to adapt the I/O stream in a way that is compatible with the true world. A natural measure of adaptation can be obtained by the Kullback-Leibler (KL) divergence between the I/O distribution of the true world and the I/O distribution expected by the agent that is uncertain about possible worlds. In the case of pure input streams, the Bayesian mixture provides a well-known solution for this problem. We show, however, that in the case of I/O streams this solution breaks down, because outputs are issued by the agent itself and require a different probabilistic syntax as provided by intervention calculus. Based on this calculus, we obtain a Bayesian control rule that all...

  13. Adaptive myoelectric pattern recognition toward improved multifunctional prosthesis control.

    Liu, Jie

    2015-04-01

    The non-stationary property of electromyography (EMG) signals in real life settings usually hinders the clinical application of the myoelectric pattern recognition for prosthesis control. The classical EMG pattern recognition approach consists of two separate steps: training and testing, without considering the changes between training and testing data induced by electrode shift, fatigue, impedance changes and psychological factors, and often results in performance degradation. The aim of this study was to develop an adaptive myoelectric pattern recognition system, aiming to retrain the classifier online with the testing data without supervision, providing a self-correction mechanism for suppressing misclassifications. This paper presents an adaptive unsupervised classifier based on support vector machine (SVM) to improve the classification performance. Experimental data from 15 healthy subjects were used to evaluate performance. Preliminary study on intra-session and inter-session EMG data was conducted to verify the performance of the unsupervised adaptive SVM classifier. The unsupervised adaptive SVM classifier outperformed the conventional SVM by 3.3% and 8.0% for the combination of time-domain and autoregressive features in the intra-session and inter-session tests, respectively. The proposed approach is capable of incorporating the useful information in testing data to the classification model by taking into account the overtime changes in the testing data with respect to the training data to retrain the original classifier, therefore providing a self-correction mechanism for suppressing misclassifications. PMID:25749182

  14. New synchronization criteria for memristor-based networks: adaptive control and feedback control schemes.

    Li, Ning; Cao, Jinde

    2015-01-01

    In this paper, we investigate synchronization for memristor-based neural networks with time-varying delay via an adaptive and feedback controller. Under the framework of Filippov's solution and differential inclusion theory, and by using the adaptive control technique and structuring a novel Lyapunov functional, an adaptive updated law was designed, and two synchronization criteria were derived for memristor-based neural networks with time-varying delay. By removing some of the basic literature assumptions, the derived synchronization criteria were found to be more general than those in existing literature. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results. PMID:25299765

  15. Closed Loop Speed Control of a BLDC Motor Drive Using Adaptive Fuzzy Tuned PI Controller

    Sri Latha Eti

    2014-11-01

    Full Text Available Brushless DC Motors are widely used for many industrial applications because of their high efficiency, high torque and low volume. This paper proposed an improved Adaptive Fuzzy PI controller to control the speed of BLDC motor. This paper provides an overview of different tuning methods of PID Controller applied to control the speed of the transfer function model of the BLDC motor drive and then to the mathematical model of the BLDC motor drive. It is difficult to tune the parameters and get satisfied control characteristics by using normal conventional PI controller. The experimental results verify that Adaptive Fuzzy PI controller has better control performance than the conventional PI controller. The modeling, control and simulation of the BLDC motor have been done using the MATLAB/SIMULINK software. Also, the dynamic characteristics of the BLDC motor (i.e. speed and torque as well as currents and voltages of the inverter components are observed by using the developed model.

  16. Strategy missile control system design using adaptive fuzzy control based on Popov stability criterion

    Zhang, Jianling; An, Jinwen; Wang, Mina

    2005-11-01

    This paper describes the application and simulation of an adaptive fuzzy controller for a missile model. The fuzzy control system is tested using different values of fuzzy controller correctional factor on a nonlinear missile model. It is shown that the self-tuning fuzzy controller is well suited for controlling the pitch loop of the missile control system with air turbulence and parameter variety. The research shows that the Popov stability criterion could successfully guarantee the stability of the fuzzy system. It provides a good method for the design of missile control system. Simulation results suggest significant benefits from fuzzy logic in control task for missile pitch loop control.

  17. Adaptive nonlinear hierarchical control of a quad tilt-wing UAV

    Yıldız, Yıldıray; Yildiz, Yildiray; Ünel, Mustafa; Unel, Mustafa; Demirel, Ahmet Eren

    2015-01-01

    Position control of a quad tilt-wing UAV via a nonlinear hierarchical adaptive control approach is presented. The hierarchy consists of two levels. In the upper level, a model reference adaptive controller creates virtual control commands so as to make the UAV follow a given desired trajectory. The virtual control inputs are then converted to desired attitude angle references which are fed to the lower level attitude controller. Lower level controller is a nonlinear adaptive controller. The o...

  18. The coordinated control of SVC and excitation of generators Using Adaptive Fuzzy Control

    Berbaoui Brahim; Bousmaha Bouchiba,; Youssef Mouloudi,; Abdellah Laoufi

    2011-01-01

    Based on the feedback linearized technique and control of differential and algebraic systems, the Indirect Adaptive fuzzy excitation control is presented in this paper for SVC (static var compensator) and generator excitation controllers in power systems with nonlinear loads. It can improve both the power angle stability ofgenerators and the voltage behavior at the SVC location. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition lineariz...

  19. Application of Adaptive Predictive Control to a Newborn Incubator

    Med A. Zermani

    2011-01-01

    Full Text Available Problem statement: This study presents an application of Indirect Adaptive Generalized Predictive Control (IAGPC of an incubator for newborn, in order to improve the performance of temperature control. Approach: Analysis of physical phenomena of incubator was involved together knowledge of the dynamic behavior. Incubator was identified by means of Recursive Least Square (RLS technique associated with a projection of the model parameters for robust system identification. Results: Results showed that mathematical model of neonatal incubator predicted coincide with the measured data. A comparative study was made between ON-OFF, PID and IAGPC control in order to provide the performance of each strategy. Conclusion: Results had proved effectiveness of the IAGPC as a control of incubator system.

  20. Fuzzy Adaptive PI Controller for DTFC in Electric Vehicle

    Medjdoub khessam

    2014-12-01

    Full Text Available This paper presents a technique to control the electric vehicle (EV speed and torque at any curve. Our propulsion model consist of two permanent magnet synchronous (PMSM motors. The fuzzy adaptive PI controller is used to adjust the different static error constants, as per the speed error. The suggested based on the direct torque fuzzy control (DTFC. A Mamdani type fuzzy direct torque controller is first developed and then rules are modified using stator current membership functions. The computations are ensured by the electronic differential, this driving process permit to steer each driving wheels at any curve separately.Modeling and simulation are carried out using the Matlab/Simulink tool to investigate the performance of the proposed system.

  1. Adaptive neural network error control for generalized perturbation theory

    This paper addresses the issue of adaptive error control within generalized perturbation theory (GPT). The strategy herein assessed considers an artificial neural network (ANN) error estimator. The underlying tool facilitating this research is the FORMOSA-P code, a pressurized water reactor (PWR) nuclear fuel management optimization package, which combines simulated annealing and nodal GPT. A number of applications exist where traditional GPT may be limited by the magnitude of perturbations, which it can accurately handle. In fact, other alternative such as supervariational techniques (i.e., n'th-order GPT) and/or multireference strategies (i.e., rodded adjoints) are being sought for boiling water reactor and rodded applications. A perhaps not-so-obvious alternative could be to employ a neural network for adaptive error control within GPT. This study presents the results of two ANN models. The first model constitutes an intensively well-trained ANN used to contrast its global core parameter (i.e., keff) prediction capability versus that of a GPT model. The second model is a similar ANN intended for adaptive GPT error correction. In other words, the latter ANN is trained on-the-fly within the scope of a standard FORMOSA-P calculation

  2. Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

    Nguyen, Nhan T.

    2010-01-01

    This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.

  3. Damping Force Tracking Control of MR Damper System Using a New Direct Adaptive Fuzzy Controller

    Xuan Phu Do

    2015-01-01

    Full Text Available This paper presents a new direct adaptive fuzzy controller and its effectiveness is verified by investigating the damping force tracking control of magnetorheological (MR fluid based damper (MR damper in short system. In the formulation of the proposed controller, a model of interval type 2 fuzzy controller is combined with the direct adaptive control to achieve high performance in vibration control. In addition, H∞ (H infinity tracking technique is used in building a model of the direct adaptive fuzzy controller in which an enhanced iterative algorithm is combined with the fuzzy model. After establishing a closed-loop control structure to achieve high control performance, a cylindrical MR damper is adopted and damping force tracking results are obtained and discussed. In addition, in order to demonstrate the effectiveness of the proposed control strategy, two existing controllers are modified and tested for comparative work. It has been demonstrated from simulation and experiment that the proposed control scheme provides much better control performance in terms of damping force tracking error. This leads to excellent vibration control performance of the semiactive MR damper system associated with the proposed controller.

  4. An improved Direct Adaptive Fuzzy controller for an uncertain DC Motor Speed Control System

    Chunjie Zhou; Shuang Huang; Quan Yin; Duc Cuong Quach

    2013-01-01

    In this paper, we present an improved Direct Adaptive Fuzzy (IDAF) controller applied to general control DC motor speed system. In particular, an IDAF algorithm is designed to control an uncertain DC motor speed to track a given reference signal. In fact, the quality of the control system depends significantly on the amount of fuzzy rules-fuzzy sets and the updating coefficient of the adaptive rule. This can be observed clearly by the system error when the reference input is constant and out ...

  5. Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification

    Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)

    2016-01-01

    Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.

  6. Controls on Extreme Droughts and Adaptation Strategies in Semiarid Regions

    Scanlon, B. R.; Cook, C.; Fernando, D. N.; LeBlanc, M.

    2012-12-01

    Increasing vulnerability to droughts with reduced per capita water storage, particularly in semiarid regions, underscores the need for predictive understanding of drought controls and development of adaptation strategies for water resources management. In this study we evaluate causes of major droughts in southwest and southcentral US (California and Texas) and southeast Australia (Murray Darling Basin). Impacts of climate cycles (ENSO, PDO, AMO, NAO, IOD) and atmospheric circulation on drought initiation and persistence are examined. Effects of drought on surface water reservoir storage, groundwater storage, irrigation, and crop production are compared. Adaptation strategies being evaluated include water transfers among sectors, particularly from irrigated agriculture to other groups, increasing storage using managed aquifer recharge, water reuse, and development of new water sources (e.g. seawater desalination). It is critical to develop a broad portfolio of water sources to increase resilience to future droughts.

  7. Fibradapt trademark: Adaptive Wind Turbine Control System; Fibradapt trademark: Adaptive Wind Turbine Control System

    Wernicke, J.-Th. [Wind Force Engineering and Consulting GmbH, Bremerhaven (Germany)

    2004-07-01

    The technology of Time Division Multiplexing (TDM) is compared with conventional strain gauge technologies in practical operation in a wind power system. Load cycles in the rotor blade were measured during plant life, and the data were used in plant control. The system is a tool in technical project management and financial management of a wind park. (orig.)

  8. Adaptive Congestion Control Protocol (ACCP for Wireless Sensor Networks

    James DzisiGadze

    2013-10-01

    Full Text Available In Wireless Sensor Networks (WSN when an event is detected there is an increase in data traffic that mightlead to packets being transmitted through the network close to the packet handling capacity of the WSN.The WSN experiences a decrease in network performance due to packet loss, long delays, and reduction inthroughput. In this paper we developed an adaptive congestion control algorithm that monitors networkutilization and adjust traffic levels and/or increases network resources to improve throughput and conserveenergy. The traffic congestion control protocol DelStatic is developed by introducing backpressuremechanism into NOAH. We analyzed various routing protocols and established that DSR has a higherresource congestion control capability. The proposed protocol, ACCP uses a sink switching algorithm totrigger DelStatic or DSR feedback to a congested node based on its Node Rank. From the simulationresults, ACCP protocol does not only improve throughput but also conserves energy which is critical tosensor application survivability on the field. Our Adaptive Congestion control achieved reliability, highthroughput and energy efficiency.

  9. Space Launch System Implementation of Adaptive Augmenting Control

    Wall, John H.; Orr, Jeb S.; VanZwieten, Tannen S.

    2014-01-01

    Given the complex structural dynamics, challenging ascent performance requirements, and rigorous flight certification constraints owing to its manned capability, the NASA Space Launch System (SLS) launch vehicle requires a proven thrust vector control algorithm design with highly optimized parameters to provide stable and high-performance flight. On its development path to Preliminary Design Review (PDR), the SLS flight control system has been challenged by significant vehicle flexibility, aerodynamics, and sloshing propellant. While the design has been able to meet all robust stability criteria, it has done so with little excess margin. Through significant development work, an Adaptive Augmenting Control (AAC) algorithm has been shown to extend the envelope of failures and flight anomalies the SLS control system can accommodate while maintaining a direct link to flight control stability criteria such as classical gain and phase margin. In this paper, the work performed to mature the AAC algorithm as a baseline component of the SLS flight control system is presented. The progress to date has brought the algorithm design to the PDR level of maturity. The algorithm has been extended to augment the full SLS digital 3-axis autopilot, including existing load-relief elements, and the necessary steps for integration with the production flight software prototype have been implemented. Several updates which have been made to the adaptive algorithm to increase its performance, decrease its sensitivity to expected external commands, and safeguard against limitations in the digital implementation are discussed with illustrating results. Monte Carlo simulations and selected stressing case results are also shown to demonstrate the algorithm's ability to increase the robustness of the integrated SLS flight control system.

  10. ADEX optimized adaptive controllers and systems from research to industrial practice

    Martín-Sánchez, Juan M

    2015-01-01

    This book is a didactic explanation of the developments of predictive, adaptive predictive and optimized adaptive control, including the latest methodology of adaptive predictive expert (ADEX) control, and their practical applications. It is focused on the stability perspective, used in the introduction of these methodologies, and is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. ADEX Optimized Adaptive Controllers and Systems begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guarantee achievement of desired control performance. The second and third parts are centered on the design of the driver block and adaptive mechanism, which verify these stability conditions. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control m...

  11. Application of adaptive fuzzy control technology to pressure control of a pressurizer

    YANG Ben-kun; BIAN Xin-qian; GUO Wei-lai

    2005-01-01

    A pressurizer is one of important equipment in a pressurized water reactor plant. It is used to maintain the pressure of primary coolant within allowed range because the sharp change of coolant pressure affects the security of reactor,therefor,the study of pressurizer's pressure control methods is very important. In this paper, an adaptive fuzzy controller is presented for pressure control of a pressurizer in a nuclear power plant. The controller can on-line tune fuzzy control rules and parameters by self-learning in the actual control process, which possesses the way of thinking like human to make a decision. The simulation results for a pressurized water reactor plant show that the adaptive fuzzy controller has optimum and intelligent characteristics, which prove the controller is effective.

  12. Towards Adaptive Virtual Camera Control In Computer Games

    Burelli, Paolo; Yannakakis, Georgios N.

    2011-01-01

    Automatic camera control aims to define a framework to control virtual camera movements in dynamic and unpredictable virtual environments while ensuring a set of desired visual properties. We inves- tigate the relationship between camera placement and playing behaviour in games and build a user...... model of the camera behaviour that can be used to control camera movements based on player preferences. For this purpose, we collect eye gaze, camera and game-play data from subjects playing a 3D platform game, we cluster gaze and camera information to identify camera behaviour profiles and we employ...... machine learning to build predictive models of the virtual camera behaviour. The perfor- mance of the models on unseen data reveals accuracies above 70% for all the player behaviour types identified. The characteristics of the gener- ated models, their limits and their use for creating adaptive automatic...

  13. Fully probabilistic control design in an adaptive critic framework.

    Herzallah, Randa; Kárný, Miroslav

    2011-12-01

    Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem; in particular, very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic control algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this paper. PMID:21752597

  14. Fuzzy Adaptive Control for Trajectory Tracking of Autonomous Underwater Vehicle

    Saeed Nakhkoob

    2014-01-01

    Full Text Available In this paper, the problem of the position and attitude tracking of an autonomous underwater vehicle (AUV in the horizontal plane, under the presence of ocean current disturbances is discussed. The effect of the gradual variation of the parameters is taken into account. The effectiveness of the adaptive controller is compared with a feedback linearization method and fuzzy gain control approach. The proposed strategy has been tested through simulations. Also, the performance of the propos-ed method is compared with other strategies given in some other studies. The boundedness and asymptotic converge-nce properties of the control algorithm and its semi-global stability are analytically proven using Lyapunov stability theory and Barbalat’s lemma.

  15. Active Inference, homeostatic regulation and adaptive behavioural control.

    Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl

    2015-11-01

    We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. PMID:26365173

  16. Electro-magnetically controlled acoustic metamaterials with adaptive properties.

    Malinovsky, Vladimir S; Donskoy, Dimitri M

    2012-10-01

    A design of actively controlled metamaterial is proposed and discussed. The metamaterial consists of layers of electrically charged nano or micro particles exposed to external magnetic field. The particles are also attached to compliant layers in a way that the designed structure exhibits two resonances: mechanical spring-mass resonance and electro-magnetic cyclotron resonance. It is shown that if the cyclotron frequency is greater than the mechanical resonance frequency, the designed structure could be highly attenuative (40-60 dB) for vibration and sound waves in very broad frequency range even for wavelength much greater than the thickness of the metamaterial. The approach opens up wide range of opportunities for design of adaptively controlled acoustic metamaterials by controlling magnetic field and/or electrical charges. PMID:23039553

  17. Adaptive integral dynamic surface control of a hypersonic flight vehicle

    Aslam Butt, Waseem; Yan, Lin; Amezquita S., Kendrick

    2015-07-01

    In this article, non-linear adaptive dynamic surface air speed and flight path angle control designs are presented for the longitudinal dynamics of a flexible hypersonic flight vehicle. The tracking performance of the control design is enhanced by introducing a novel integral term that caters to avoiding a large initial control signal. To ensure feasibility, the design scheme incorporates magnitude and rate constraints on the actuator commands. The uncertain non-linear functions are approximated by an efficient use of the neural networks to reduce the computational load. A detailed stability analysis shows that all closed-loop signals are uniformly ultimately bounded and the ? tracking performance is guaranteed. The robustness of the design scheme is verified through numerical simulations of the flexible flight vehicle model.

  18. Nonlinear vibration with control for flexible and adaptive structures

    Wagg, David

    2015-01-01

    This book provides a comprehensive discussion of nonlinear multi-modal structural vibration problems, and shows how vibration suppression can be applied to such systems by considering a sample set of relevant control techniques. It covers the basic principles of nonlinear vibrations that occur in flexible and/or adaptive structures, with an emphasis on engineering analysis and relevant control techniques. Understanding nonlinear vibrations is becoming increasingly important in a range of engineering applications, particularly in the design of flexible structures such as aircraft, satellites, bridges, and sports stadia. There is an increasing trend towards lighter structures, with increased slenderness, often made of new composite materials and requiring some form of deployment and/or active vibration control. There are also applications in the areas of robotics, mechatronics, micro electrical mechanical systems, non-destructive testing and related disciplines such as structural health monitoring. Two broader ...

  19. Adaptive-passive vibration control systems for industrial applications

    Mayer, D.; Pfeiffer, T.; Vrbata, J.; Melz, T.

    2015-04-01

    Tuned vibration absorbers have become common for passive vibration reduction in many industrial applications. Lightly damped absorbers (also called neutralizers) can be used to suppress narrowband disturbances by tuning them to the excitation frequency. If the resonance is adapted in-operation, the performance of those devices can be significantly enhanced, or inertial mass can be decreased. However, the integration of actuators, sensors and control electronics into the system raises new design challenges. In this work, the development of adaptive-passive systems for vibration reduction at an industrial scale is presented. As an example, vibration reduction of a ship engine was studied in a full scale test. Simulations were used to study the feasibility and evaluate the system concept at an early stage. Several ways to adjust the resonance of the neutralizer were evaluated, including piezoelectric actuation and common mechatronic drives. Prototypes were implemented and tested. Since vibration absorbers suffer from high dynamic loads, reliability tests were used to assess the long-term behavior under operational conditions and to improve the components. It was proved that the adaptive systems are capable to withstand the mechanical loads in an industrial application. Also a control strategy had to be implemented in order to track the excitation frequency. The most mature concepts were integrated into the full scale test. An imbalance exciter was used to simulate the engine vibrations at a realistic level experimentally. The neutralizers were tested at varying excitation frequencies to evaluate the tracking capabilities of the control system. It was proved that a significant vibration reduction is possible.

  20. A modified Adaptive Wavelet PID Control Based on Reinforcement Learning for Wind Energy Conversion System Control

    REZAZADEH, A.; SEDIGHIZADEH, M.

    2010-01-01

    Nonlinear characteristics of wind turbines and electric generators necessitate complicated and nonlinear control of grid connected Wind Energy Conversion Systems (WECS). This paper proposes a modified self-tuning PID control strategy, using reinforcement learning for WECS control. The controller employs Actor-Critic learning in order to tune PID parameters adaptively. These Actor-Critic learning is a special kind of reinforcement learning that uses a single wavelet neural network to appro...

  1. Robust time and frequency domain estimation methods in adaptive control

    Lamaire, Richard Orville

    1987-01-01

    A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.

  2. Nonlinear time-series-based adaptive control applications

    Mohler, R. R.; Rajkumar, V.; Zakrzewski, R. R.

    1991-01-01

    A control design methodology based on a nonlinear time-series reference model is presented. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible AC transmission system with series capacitor power feedback control is studied. A bilinear autoregressive moving average reference model is identified from system data, and the feedback control is manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index. A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack.

  3. Models Adaptation of Complex Objects Structure Dynamics Control

    Sokolov, B. V.; Zelentsov, V. A.; Brovkina, Olga; Mochalov, V. F.; Potryasaev, S. A.

    Cham: Springer, 2015 - (Šilhavý, R.; Šenkeřík, R.; Komínková-Oplatková, Z.; Prokopová, Z.; Šilhavý, P.), s. 21-33. (Intelligent Systems in Cybernetics and Automation Theory . 348). ISBN 978-3-319-18502-6. ISSN 2194-5357. [Computer Science On-line Conference /4./. Zlín (CZ), 27.04.2015-30.04.2015] Institutional support: RVO:67179843 Keywords : complex technical * organizational system * structure dynamic control * planning and scheduling * parametric and structure adaptation of models Subject RIV: EH - Ecology, Behaviour

  4. Optimal Control Modification for Robust Adaptation of Singularly Perturbed Systems with Slow Actuators

    Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan

    2009-01-01

    Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.

  5. Fuzzy Adaptive Model Following Speed Control for Vector Controlled Permanent Magnet Synchronous Motor

    Baghdad BELABES

    2008-12-01

    Full Text Available In this paper a hybrid controller combining a linear model following controller (LMFC and fuzzy logic control (FLC for speed vector controlled permanent magnet synchronous motor (PMSM is described on this study. The FLC is introduced at the adaptive mechanism level. First, an LMFC system is designed to allow the plant states to be controlled to follow the states produced by a reference model. In the nominal conditions, the model following is perfect and the adaptive mechanism based on the fuzzy logic is idle. Secondly, when parameter variations or external disturbances occur, an augmented signal will be generated by FLC mechanism to preserve the desired model following control performance. The effectiveness and robustness of the proposed controller is demonstrated by some simulation results.

  6. Efficient community-based control strategies in adaptive networks

    Most studies on adaptive networks concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structure in the transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing the modularity, we investigate the evolution of community structure during the transient process, and find that a strong community structure is induced by the rewiring mechanism in the early stage of epidemic dynamics, which, remarkably, delays the outbreak of disease. We then study the effects of control strategies started at different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not ‘the earlier, the better’ for the implementation of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of a strong community structure. For the immunization strategy, immunizing the susceptible nodes on susceptible–infected links and immunizing susceptible nodes randomly have similar control effects. However, for the quarantine strategy, quarantining the infected nodes on susceptible–infected links can yield a far better result than quarantining infected nodes randomly. More significantly, the community-based quarantine strategy performs better than the community-based immunization strategy. This study may shed new light on the forecast and the prevention of epidemics among humans. (paper)

  7. Traffic Signals Control with Adaptive Fuzzy Controller in Urban Road Network

    LI Yan; FAN Xiao-ping

    2008-01-01

    An adaptive fuzzy logic controller (AFC) is presented for the signal control of the urban traffic network.The AFC is composed of the signal control system-oriented control level and the signal controller-oriented fuzzy rules regulation level.The control level decides the signal tunings in an intersection with a fuzzy logic controller.The regulation level optimizes the fuzzy rules by the Adaptive Rule Module in AFC according to both the system performance index in current control period and the traffic flows in the last one.Consequently the system performances are improved.A weight coefficient controller (WCC) is also developed to describe the interactions of traffic flow among the adjacent intersections.So the AFC combined with the WCC can be applied in a road network for signal timings.Simulations of the AFC on a real traffic scenario have been conducted.Simulation results indicate that the adaptive controller for traffic control shows better performance than the actuated one.

  8. Adaptive Automatic Gauge Control of a Cold Strip Rolling Process

    ROMAN, N.

    2010-02-01

    Full Text Available The paper tackles with thickness control structure of the cold rolled strips. This structure is based on the rolls position control of a reversible quarto rolling mill. The main feature of the system proposed in the paper consists in the compensation of the errors introduced by the deficient dynamics of the hydraulic servo-system used for the rolls positioning, by means of a dynamic compensator that approximates the inverse system of the servo-system. Because the servo-system is considered variant over time, an on-line identification of the servo-system and parameter adapting of the compensator are achieved. The results obtained by numerical simulation are presented together with the data taken from real process. These results illustrate the efficiency of the proposed solutions.

  9. Kalman filtering to suppress spurious signals in Adaptive Optics control

    Poyneer, L; Veran, J P

    2010-03-29

    In many scenarios, an Adaptive Optics (AO) control system operates in the presence of temporally non-white noise. We use a Kalman filter with a state space formulation that allows suppression of this colored noise, hence improving residual error over the case where the noise is assumed to be white. We demonstrate the effectiveness of this new filter in the case of the estimated Gemini Planet Imager tip-tilt environment, where there are both common-path and non-common path vibrations. We discuss how this same framework can also be used to suppress spatial aliasing during predictive wavefront control assuming frozen flow in a low-order AO system without a spatially filtered wavefront sensor, and present experimental measurements from Altair that clearly reveal these aliased components.

  10. Development of Power Controller System based on Model Reference Adaptive Control for a Nuclear Reactor

    The Reactor TRIGA PUSPATI (RTP)-type TRIGA Mark II was installed in the year 1982. The Power Controller System (PCS) or Automated Power Controller System (APCS) is very important for reactor operation and safety reasons. It is a function of controlled reactivity and reactor power. The existing power controller system is under development and due to slow response, low accuracy and low stability on reactor power control affecting the reactor safety. The nuclear reactor is a nonlinear system in nature, and it is power increases continuously with time. The reactor parameters vary as a function of power, fuel burnup and control rod worth. The output power value given by the power control system is not exactly as real value of reactor power. Therefore, controller system design is very important, an adaptive controller seems to be inevitable. The method chooses is a linear controller by using feedback linearization, for example Model Reference Adaptive Control. The developed APCS for RTP will be design by using Model Reference Adaptive Control (MRAC). The structured of RTP model to produce the dynamic behaviour of RTP on entire operating power range from 0 to 1MWatt. The dynamic behavior of RTP model is produced by coupling of neutronic and thermal-hydraulics. It will be developed by using software MATLAB/Simulink and hardware module card to handle analog input signal. A new algorithm for APCS is developed to control the movement of control rods with uniformity and orderly for RTP. Before APCS test to real plant, simulation results shall be obtained from RTP model on reactor power, reactivity, period, control rod positions, fuel and coolant temperatures. Those data are comparable with the real data for validation. After completing the RTP model, APCS will be tested to real plant on power control system performance by using real signal from RTP including fail-safe operation, system reliable, fast response, stability and accuracy. The new algorithm shall be a satisfied

  11. Model adaptation in a central controller for a sewer system

    van Nooijen, Ronald; Kolechkina, Alla; Mol, Bart

    2013-04-01

    For small sewer systems that combine foul water and storm water sewer functions in flat terrain, central control of the sewer system may have problems during dry weather. These systems are a combination of local gravity flow networks connected by pumps. Under those conditions the level in the wet well (local storage at the pumping station) should be kept below the entrance pipe but above the top of the intake of the pump. The pumps are dimensioned to cope with the combined flow of foul water and precipitation run off so their capacity is relatively large when compared wityh the volume available in the wet well. Under local control this is not a major problem because the effective controller time step is very short. For central control the control time step can become a problem. Especially when there is uncertainty about the relation between level and volume in the wet well. In this paper we describe a way to dynamically adapt the level to volume relation based on dry weather behaviour. This is important because a better estimate of this volume will reduce the number of on/off cycles for the pumps. It will also allow detection and correction for changes in pump performance due to aging.

  12. Adaptive finite-time control for hyperchaotic Lorenz–Stenflo systems

    This paper investigates the issue of adaptive finite-time control for hyperchaotic Lorenz–Stenflo systems with parameter uncertainties. Based on finite-time Lyapunov theory, a class of non-smooth adaptive finite time controllers is given to guarantee the adaptive finite-time stability and make the states of the systems converge to the origins within a finite-time. Finally, illustrative examples are presented to verify the effectiveness of the proposed adaptive finite-time controller. (paper)

  13. Synchronization of hyperchaotic Chen systems: a class of the adaptive control approach

    The synchronization of hyperchaotic Chen systems is considered. An adaptive synchronization approach and a cascade adaptive synchronization approach are presented to synchronize a drive system and a response system. By utilizing an adaptive controller based on the dynamic compensation mechanism, exact knowledge of the systems is not necessarily required, and the synchronous speed is controllable by tuning the controller parameters. Sufficient conditions for the asymptotic stability of the two synchronization schemes are derived. Numerical simulation results demonstrate that the adaptive synchronization scheme with four control inputs and the cascade adaptive synchronization scheme with only one control signal are effective and feasible in chaos synchronization of hyperchaotic systems. (general)

  14. An insula-frontostriatal network mediates flexible cognitive control by adaptively predicting changing control demands

    Jiang, Jiefeng; Beck, Jeffrey; Heller, Katherine; Egner, Tobias

    2015-01-01

    The anterior cingulate and lateral prefrontal cortices have been implicated in implementing context-appropriate attentional control, but the learning mechanisms underlying our ability to flexibly adapt the control settings to changing environments remain poorly understood. Here we show that human adjustments to varying control demands are captured by a reinforcement learner with a flexible, volatility-driven learning rate. Using model-based functional magnetic resonance imaging, we demonstrat...

  15. Systems and Methods for Parameter Dependent Riccati Equation Approaches to Adaptive Control

    Kim, Kilsoo (Inventor); Yucelen, Tansel (Inventor); Calise, Anthony J. (Inventor)

    2015-01-01

    Systems and methods for adaptive control are disclosed. The systems and methods can control uncertain dynamic systems. The control system can comprise a controller that employs a parameter dependent Riccati equation. The controller can produce a response that causes the state of the system to remain bounded. The control system can control both minimum phase and non-minimum phase systems. The control system can augment an existing, non-adaptive control design without modifying the gains employed in that design. The control system can also avoid the use of high gains in both the observer design and the adaptive control law.

  16. L(sub 1) Adaptive Flight Control System: Flight Evaluation and Technology Transition

    Xargay, Enric; Hovakimyan, Naira; Dobrokhodov, Vladimir; Kaminer, Isaac; Gregory, Irene M.; Cao, Chengyu

    2010-01-01

    Certification of adaptive control technologies for both manned and unmanned aircraft represent a major challenge for current Verification and Validation techniques. A (missing) key step towards flight certification of adaptive flight control systems is the definition and development of analysis tools and methods to support Verification and Validation for nonlinear systems, similar to the procedures currently used for linear systems. In this paper, we describe and demonstrate the advantages of L(sub l) adaptive control architectures for closing some of the gaps in certification of adaptive flight control systems, which may facilitate the transition of adaptive control into military and commercial aerospace applications. As illustrative examples, we present the results of a piloted simulation evaluation on the NASA AirSTAR flight test vehicle, and results of an extensive flight test program conducted by the Naval Postgraduate School to demonstrate the advantages of L(sub l) adaptive control as a verifiable robust adaptive flight control system.

  17. Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

    Nguyen, Nhan T.

    2010-01-01

    Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

  18. Adaptive source rate control for wireless video conferencing

    Liu, Hang; El Zarki, Magda

    1997-12-01

    Hybrid ARQ schemes can yield much better throughput and reliability than static FEC schemes for the transmission of data over time-varying wireless channels. However these schemes result in higher delay. They adapt to the varying channel conditions by retransmitting erroneous packets, this results in variable effective data rates for current PCS networks because the channel bandwidth is constant. Hybrid ARQ schemes are currently being proposed as the error control schemes for real-time video transmission. The standardization process is on-going in ITU, MPEG-4 and wireless ATM forum. The important issue is how to ensure low delay while taking advantage of the high throughput and reliability that these schemes provide for. In this paper we propose an adaptive source rate control (ASRC) protocol which can work together with the hybrid ARQ error control schemes to achieve efficient transmission of real-time video with low delay and high reliability. The ASRC scheme adjusts the source rate based on the channel conditions, the transport buffer occupancy and the delay constraints. It optimizes the video quality by dynamically changing both the number of the forced update (intracoded) macroblocks and the quantization scale used in a frame. The number of the forced update macroblocks used in a frame is first adjusted according to the allocated source rate. This reduces the fluctuation of the quantization scale with the change in the channel conditions during encoding so that the uniformity of the video quality is improved. The simulation results show that the proposed ASRC protocol performs very well for both slow fading and fast fading channels.

  19. A self-adaptive feedforward rf control system for linacs

    The design and performance of a self-adaptive feedforward rf control system are reported. The system was built for the linac of the Accelerator Test Facility (ATF) at Brookhaven National Laboratory. Variables of time along the linac macropulse, such as field or phase are discretized and represented as vectors. Upon turn-on or after a large change in the operating-point, the control system acquires the response of the system to test signal vectors and generates a linearized system response matrix. During operation an error vector is generated by comparing the linac variable vectors and a target vector. The error vector is multiplied by the inverse of the system's matrix to generate a correction vector is added to an operating point vector. This control system can be used to control a klystron to produce flat rf amplitude and phase pulses, to control a rf cavity to reduce the rf field fluctuation, and to compensate the energy spread among bunches in a rf linac. Beam loading effects can be corrected and a programmed ramp can be produced. The performance of the control system has been evaluated on the control of a klystron's output as well as an rf cavity. Both amplitude and phase have been regulated simultaneously. In initial tests, the rf output from a klystron has been regulated to an amplitude fluctuation of less than ±0.3% and phase variation of less than ±0.6deg. The rf field of the ATF's photo-cathode microwave gun cavity has been regulated to ±5% in amplitude and simultaneously to ±1deg in phase. Regulating just the rf field amplitude in the rf gun cavity, we have achieved amplitude fluctuation of less than ±2%. (orig.)

  20. Adaptive Neural Network Control with Control Allocation for A Manned Submersible in Deep Sea

    YU Jian-cheng; ZHANG Ai-qun; WANG Xiao-hui; WU Bao-ju

    2007-01-01

    This paper thoroughly studies a control system with control allocation for a manned submersible in deep sea being developed in China. The proposed control system consists of a neural-network-based direct adaptive controller and a dynamic control allocation module. A control energy cost function is used as the optimization criteria of the control allocation module, and weighted pseudo-inverse is used to find the solution of the control allocation problem. In the presence of bounded unknown disturbance and neural networks approximation error, stability of the closed-loop control system of manned submersible is proved with Lyaponov theory. The feasibility and validity of the proposed control system is further verified through experiments conducted on a semi-physical simulation platform for the manned submersible in deep sea.

  1. The coordinated control of SVC and excitation of generators Using Adaptive Fuzzy Control

    Berbaoui Brahim

    2011-01-01

    Full Text Available Based on the feedback linearized technique and control of differential and algebraic systems, the Indirect Adaptive fuzzy excitation control is presented in this paper for SVC (static var compensator and generator excitation controllers in power systems with nonlinear loads. It can improve both the power angle stability ofgenerators and the voltage behavior at the SVC location. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition linearization technique can enhance the transient stability of the power system. In addition, this system is used through the Algerian South-Western power system (SONELGAZ "Algerian electrical society" NAAMA city and BECHAR city.

  2. Adaptive Control of Scalar Plants in the Presence of Unmodeled Dynamics

    Hussain, Heather S.; Matsutani, Megumi M.; Annaswamy, Anuradha M.; Lavretsky, Eugene

    2013-01-01

    Robust adaptive control of scalar plants in the presence of unmodeled dynamics is established in this paper. It is shown that implementation of a projection algorithm with standard adaptive control of a scalar plant ensures global boundedness of the overall adaptive system for a class of unmodeled dynamics.

  3. Method and apparatus for adaptive force and position control of manipulators

    Seraji, Homayoun (Inventor)

    1995-01-01

    The described and improved multi-arm invention of this application presents three strategies for adaptive control of cooperative multi-arm robots which coordinate control over a common load. In the position-position control strategy, the adaptive controllers ensure that the end-effector positions of both arms track desired trajectories in Cartesian space despite unknown time-varying interaction forces exerted through a load. In the position-hybrid control strategy, the adaptive controller of one arm controls end-effector motions in the free directions and applied forces in the constraint directions; while the adaptive controller of the other arm ensures that the end-effector tracks desired position trajectories. In the hybrid-hybrid control strategy, the adaptive controllers ensure that both end-effectors track reference position trajectories while simultaneously applying desired forces on the load. In all three control strategies, the cross-coupling effects between the arms are treated as disturbances which are compensated for by the adaptive controllers while following desired commands in a common frame of reference. The adaptive controllers do not require the complex mathematical model of the arm dynamics or any knowledge of the arm dynamic parameters or the load parameters such as mass and stiffness. Circuits in the adaptive feedback and feedforward controllers are varied by novel adaptation laws.

  4. Thermotropic and Thermochromic Polymer Based Materials for Adaptive Solar Control

    Olaf Mühling

    2010-12-01

    Full Text Available The aim of this review is to present the actual status of development in adaptive solar control by use of thermotropic and organic thermochromic materials. Such materials are suitable for application in smart windows. In detail polymer blends, hydrogels, resins, and thermoplastic films with a reversible temperature-dependent switching behavior are described. A comparative evaluation of the concepts for these energy efficient materials is given as well. Furthermore, the change of strategy from ordinary shadow systems to intrinsic solar energy reflection materials based on phase transition components and a first remark about their realization is reported. Own current results concerning extruded films and high thermally stable casting resins with thermotropic properties make a significant contribution to this field.

  5. Design of Attitude Control System for UAV Based on Feedback Linearization and Adaptive Control

    Wenya Zhou

    2014-01-01

    Full Text Available Attitude dynamic model of unmanned aerial vehicles (UAVs is multi-input multioutput (MIMO, strong coupling, and nonlinear. Model uncertainties and external gust disturbances should be considered during designing the attitude control system for UAVs. In this paper, feedback linearization and model reference adaptive control (MRAC are integrated to design the attitude control system for a fixed wing UAV. First of all, the complicated attitude dynamic model is decoupled into three single-input single-output (SISO channels by input-output feedback linearization. Secondly, the reference models are determined, respectively, according to the performance indexes of each channel. Subsequently, the adaptive control law is obtained using MRAC theory. In order to demonstrate the performance of attitude control system, the adaptive control law and the proportional-integral-derivative (PID control law are, respectively, used in the coupling nonlinear simulation model. Simulation results indicate that the system performance indexes including maximum overshoot, settling time (2% error range, and rise time obtained by MRAC are better than those by PID. Moreover, MRAC system has stronger robustness with respect to the model uncertainties and gust disturbance.

  6. Multiple-model-and-neural-network-based nonlinear multivariable adaptive control

    Yue FU; Tianyou CHAI

    2007-01-01

    A multivariable adaptive controller feasible for implementation on distributed computer systems (DCS) is presented for a class of uncertain nonlinear multivariable discrete time systems. The adaptive controller is composed of a linear adaptive controller, a neural network nonlinear adaptive controller and a switching mechanism. The linear controller can provide boundedness of the input and output signals, and the nonlinear controller can improve the performance of the system. The purpose of using the switching mechanism is to obtain the improved system performance and stability simultaneously. Theory analysis and simulation results are presented to show the effectiveness of the proposed method.

  7. Considering Variable Road Geometry in Adaptive Vehicle Speed Control

    Xinping Yan

    2013-01-01

    Full Text Available Adaptive vehicle speed control is critical for developing Advanced Driver Assistance Systems (ADAS. Vehicle speed control considering variable road geometry has become a hotspot in ADAS research. In this paper, first, an exploration of intrinsic relationship between vehicle operation and road geometry is made. Secondly, a collaborative vehicle coupling model, a road geometry model, and an AVSC, which can respond to variable road geometry in advance, are developed. Then, based on H∞ control method and the minimum energy principle, a performance index is specified by a cost function for the proposed AVSC, which can explicitly consider variable road geometry in its optimization process. The proposed AVSC is designed by the Hamilton-Jacobi Inequality (HJI. Finally, simulations are carried out by combining the vehicle model with the road geometry model, in an aim of minimizing the performance index of the AVSC. Analyses of the simulation results indicate that the proposed AVSC can automatically and effectively regulate speed according to variable road geometry. It is believed that the proposed AVSC can be used to improve the economy, comfort, and safety effects of current ADAS.

  8. On Optimization Control Parameters in an Adaptive Error-Control Scheme in Satellite Networks

    Ranko Vojinović

    2011-09-01

    Full Text Available This paper presents a method for optimization of control parameters of an adaptive GBN scheme in error-prone satellite channel. Method is based on the channel model with three state, where channel have the variable noise level.

  9. Stabilization Controller Design for a class of Inverted Pendulums via Adaptive Fuzzy Sliding Mode Control

    Heng Liu

    2013-07-01

    Full Text Available X–Z inverted pendulum is a new kind of inverted pendulum and it can move with the combination of the vertical and horizontal forces. This paper addresses  the control problem of X-Z inverted pendulum in the presents of system uncertainties and external disturbances, and an adaptive fuzzy sliding mode control approach is proposed. The fuzzy  system is used to approximate the system uncertainties and the complicated intermediate control functions in the backstepping control design. To update the parameters of the fuzzy system, a proper proportional-integral adaptation law is introduced.  Finally, simulation studies are done to show the stabilization of the X-Z inverted pendulum under the proposed method.

  10. A Feed-forward Geometrical Compensation and Adaptive Feedback Control Algorithm for Hydraulic Robot Manipulators

    Conrad, Finn; Zhou, Jianjun; Gabacik, Andrzej; Stecki, Jacek

    1998-01-01

    Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control.......Invited paper presents a new control algorithm based on feed-forward geometrical compensation strategy combined with adaptive feedback control....

  11. Adaptive Neural Control Design For a Class of Nonlinear Time-delay Systems

    FENG Ling-ling; ZHANG Wei

    2014-01-01

    This paper proposes an indirect adaptive neural control scheme for a class of nonlinear systems with time delays. Based on the backstepping technique and Lyapunov–Krasovskii functional method are combined to construct the indirect adaptive neural controller. The proposed indirect adaptive neural controller guarantees that the state variables converge to a small neighborhood of the origin and all the signals of the closed-loop system are bounded. Finally, an example is used to show the effectiveness of the proposed control strategy.

  12. L1 Adaptive Control of Parallel Kinematic Manipulators: Design and Real-Time Experiments

    Bennehar, Moussab; Chemori, Ahmed; Pierrot, François

    2015-01-01

    — In this paper, the recently developed L1 adaptive control strategy is experimentally validated for the first time on a parallel kinematic manipulator. The L1 adaptive controller is known for its decoupled estimation and control loops which enables fast adaptation while guaranteeing robustness of the closed-loop system. The control scheme is experimentally implemented on a 4-DOFs parallel kinematic manipulator. Based on the obtained experimental results, a comparative study shows that the pr...

  13. Stabilization Controller Design for a class of Inverted Pendulums via Adaptive Fuzzy Sliding Mode Control

    Heng Liu; Jin Xu; Yeguo Sun

    2013-01-01

    X–Z inverted pendulum is a new kind of inverted pendulum and it can move with the combination of the vertical and horizontal forces. This paper addresses  the control problem of X-Z inverted pendulum in the presents of system uncertainties and external disturbances, and an adaptive fuzzy sliding mode control approach is proposed. The fuzzy  system is used to approximate the system uncertainties and the complicated intermediate control functions in the backstepping control design. To update th...

  14. Adaptive Backstepping Controller Design for Leveling Control of an Underwater Platform Based on Joint Space

    Zhi-Lin Zeng

    2014-01-01

    Full Text Available This paper focuses on high precision leveling control of an underwater heavy load platform, which is viewed as an underwater parallel robot on the basis of its work pattern. The kinematic of platform with deformation is analyzed and the dynamics model of joint space is established. An adaptive backstepping controller according to Lyapunov's function is proposed for leveling control of platform based on joint space. Furthermore, the “lowest point fixed angle error” leveling scheme called “chase” is chosen for leveling control of platform. The digital simulation and practical experiment of single joint space actuator are carried out, and the results show high precision servo control of joint space. On the basis of this, the platform leveling control simulation relies on the hardware-in-loop system. The results indicate that the proposed controller can effectively restrain the influence from system parameter uncertainties and external disturbance to realize high precision leveling control of the underwater platform.

  15. MTPA control of mechanical sensorless IPMSM based on adaptive nonlinear control.

    Najjar-Khodabakhsh, Abbas; Soltani, Jafar

    2016-03-01

    In this paper, an adaptive nonlinear control scheme has been proposed for implementing maximum torque per ampere (MTPA) control strategy corresponding to interior permanent magnet synchronous motor (IPMSM) drive. This control scheme is developed in the rotor d-q axis reference frame using adaptive input-output state feedback linearization (AIOFL) method. The drive system control stability is supported by Lyapunov theory. The motor inductances are online estimated by an estimation law obtained by AIOFL. The estimation errors of these parameters are proved to be asymptotically converged to zero. Based on minimizing the motor current amplitude, the MTPA control strategy is performed by using the nonlinear optimization technique while considering the online reference torque. The motor reference torque is generated by a conventional rotor speed PI controller. By performing MTPA control strategy, the generated online motor d-q reference currents were used in AIOFL controller to obtain the SV-PWM reference voltages and the online estimation of the motor d-q inductances. In addition, the stator resistance is online estimated using a conventional PI controller. Moreover, the rotor position is detected using the online estimation of the stator flux and online estimation of the motor q-axis inductance. Simulation and experimental results obtained prove the effectiveness and the capability of the proposed control method. PMID:26830002

  16. Nutrient-dependent/pheromone-controlled adaptive evolution: a model

    James Vaughn Kohl

    2013-06-01

    Full Text Available Background: The prenatal migration of gonadotropin-releasing hormone (GnRH neurosecretory neurons allows nutrients and human pheromones to alter GnRH pulsatility, which modulates the concurrent maturation of the neuroendocrine, reproductive, and central nervous systems, thus influencing the development of ingestive behavior, reproductive sexual behavior, and other behaviors. Methods: This model details how chemical ecology drives adaptive evolution via: (1 ecological niche construction, (2 social niche construction, (3 neurogenic niche construction, and (4 socio-cognitive niche construction. This model exemplifies the epigenetic effects of olfactory/pheromonal conditioning, which alters genetically predisposed, nutrient-dependent, hormone-driven mammalian behavior and choices for pheromones that control reproduction via their effects on luteinizing hormone (LH and systems biology. Results: Nutrients are metabolized to pheromones that condition behavior in the same way that food odors condition behavior associated with food preferences. The epigenetic effects of olfactory/pheromonal input calibrate and standardize molecular mechanisms for genetically predisposed receptor-mediated changes in intracellular signaling and stochastic gene expression in GnRH neurosecretory neurons of brain tissue. For example, glucose and pheromones alter the hypothalamic secretion of GnRH and LH. A form of GnRH associated with sexual orientation in yeasts links control of the feedback loops and developmental processes required for nutrient acquisition, movement, reproduction, and the diversification of species from microbes to man. Conclusion: An environmental drive evolved from that of nutrient ingestion in unicellular organisms to that of pheromone-controlled socialization in insects. In mammals, food odors and pheromones cause changes in hormones such as LH, which has developmental affects on pheromone-controlled sexual behavior in nutrient-dependent reproductively

  17. Adaptive robotic control driven by a versatile spiking cerebellar network.

    Casellato, Claudia; Antonietti, Alberto; Garrido, Jesus A; Carrillo, Richard R; Luque, Niceto R; Ros, Eduardo; Pedrocchi, Alessandra; D'Angelo, Egidio

    2014-01-01

    The cerebellum is involved in a large number of different neural processes, especially in associative learning and in fine motor control. To develop a comprehensive theory of sensorimotor learning and control, it is crucial to determine the neural basis of coding and plasticity embedded into the cerebellar neural circuit and how they are translated into behavioral outcomes in learning paradigms. Learning has to be inferred from the interaction of an embodied system with its real environment, and the same cerebellar principles derived from cell physiology have to be able to drive a variety of tasks of different nature, calling for complex timing and movement patterns. We have coupled a realistic cerebellar spiking neural network (SNN) with a real robot and challenged it in multiple diverse sensorimotor tasks. Encoding and decoding strategies based on neuronal firing rates were applied. Adaptive motor control protocols with acquisition and extinction phases have been designed and tested, including an associative Pavlovian task (Eye blinking classical conditioning), a vestibulo-ocular task and a perturbed arm reaching task operating in closed-loop. The SNN processed in real-time mossy fiber inputs as arbitrary contextual signals, irrespective of whether they conveyed a tone, a vestibular stimulus or the position of a limb. A bidirectional long-term plasticity rule implemented at parallel fibers-Purkinje cell synapses modulated the output activity in the deep cerebellar nuclei. In all tasks, the neurorobot learned to adjust timing and gain of the motor responses by tuning its output discharge. It succeeded in reproducing how human biological systems acquire, extinguish and express knowledge of a noisy and changing world. By varying stimuli and perturbations patterns, real-time control robustness and generalizability were validated. The implicit spiking dynamics of the cerebellar model fulfill timing, prediction and learning functions. PMID:25390365

  18. The Adaptive Control of Nonlinear Systems Using the T-S-K Fuzzy Logic

    Martin Kratmüller

    2009-07-01

    Full Text Available Fuzzy adaptive tracking controllers for a class of uncertain nonlinear dynamicalsystems are proposed and analyzed. The controller consists of adaptive and robustifyingcomponents whose role is to nullify the effect of uncertainties and achieve a desiredtracking performance. The interactions between the two components have beeninvestigated. We use the Takagi-Sugeno-Kang type of the fuzzy logic system to approximatethe controller. It is proved that the closed-loop system using this adaptive fuzzy controlleris globally stable in the sense that all signals involved are bounded. Finally, we apply themethod of direct adaptive fuzzy controllers to control an inverted pendulum and thesimulation results are included.

  19. ADAPTIVE NONLINEAR FEEDBACK CONTROL OF CHAOTIC SYSTEMSBASED ON REDUCED PARAMETER QUADRATIC PREDICTORS

    张家树; 肖先赐; 万继宏

    2001-01-01

    An adaptive nonlinear feedback-control method is proposed to control continuous-time chaotic dynamical systems,where the adaptive nonlinear controller acts on only one-dimensional error signals between the desired state and the observed chaotic state of a system. The reduced parameter adaptive quadratic predictor used in adaptive feedback cancellation of the nonlinear terms can control the system at any desired state. Computer simulation results on the Lorenz system are shown to demonstrate the effectiveness of this feedback-control method.

  20. Intelligent control of non-linear dynamical system based on the adaptive neurocontroller

    Engel, E.; Kovalev, I. V.; Kobezhicov, V.

    2015-10-01

    This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.

  1. Adaptive control of an active seat for occupant vibration reduction

    Gan, Zengkang; Hillis, Andrew J.; Darling, Jocelyn

    2015-08-01

    The harmful effects on human performance and health caused by unwanted vibration from vehicle seats are of increasing concern. This paper presents an active seat system to reduce the vibration level transmitted to the seat pan and the occupants' body under low frequency periodic excitation. Firstly, the detail of the mechanical structure is given and the active seat dynamics without external load are characterized by vibration transmissibility and frequency responses under different excitation forces. Owing the nonlinear and time-varying behaviour of the proposed system, a Filtered-x least-mean-square (FXLMS) adaptive control algorithm with on-line Fast-block LMS (FBLMS) identification process is employed to manage the system operation for high vibration cancellation performance. The effectiveness of the active seat system is assessed through real-time experimental tests using different excitation profiles. The system identification results show that an accurate estimation of the secondary path is achieved by using the FBLMS on-line technique. Substantial reduction is found for cancelling periodic vibration containing single and multiple frequencies. Additionally, the robustness and stability of the control system are validated through transient switching frequency tests.

  2. A Study on Mode Confusions in Adaptive Cruise Control Systems

    Ahn, Dae Ryong; Yang, Ji Hyun; Lee, Sang Hun [Kookmin University, Seoul (Korea, Republic of)

    2015-05-15

    Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions.

  3. A Study on Mode Confusions in Adaptive Cruise Control Systems

    Recent development in science and technology has enabled vehicles to be equipped with advanced autonomous functions. ADAS (Advanced Driver Assistance Systems) are examples of such advanced autonomous systems added. Advanced systems have several operational modes and it has been observed that drivers could be unaware of the mode they are in during vehicle operation, which can be a contributing factor of traffic accidents. In this study, possible mode confusions in a simulated environment when vehicles are equipped with an adaptive cruise control system were investigated. The mental model of the system was designed and verified using the formal analysis method. Then, the user interface was designed on the basis of those of the current cruise control systems. A set of human-in-loop experiments was conducted to observe possible mode confusions and redesign the user interface to reduce them. In conclusion, the clarity and transparency of the user interface was proved to be as important as the correctness and compactness of the mental model when reducing mode confusions

  4. Reaction jet and aerodynamics compound control missile autopilot design based on adaptive fuzzy sliding mode control

    Wu, Zhenhui; Dong, Chaoyang

    2006-11-01

    Because of nonlinearity and strong coupling of reaction-jet and aerodynamics compound control missile, a missile autopilot design method based on adaptive fuzzy sliding mode control (AFSMC) is proposed in this paper. The universal approximation ability of adaptive fuzzy system is used to approximate the nonlinear function in missile dynamics equation during the flight of high angle of attack. And because the sliding mode control is robustness to external disturbance strongly, the sliding mode surface of the error system is constructed to overcome the influence of approximation error and external disturbance so that the actual overload can track the maneuvering command with high precision. Simulation results show that the missile autopilot designed in this paper not only can track large overload command with higher precision than traditional method, but also is robust to model uncertainty and external disturbance strongly.

  5. Adaptive Control for Linear Uncertain Systems with Unmodeled Dynamics Revisited via Optimal Control Modification

    Nguyen, Nhan

    2013-01-01

    This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.

  6. Adaptive Controllers for Permanent Magnet Brushless DC Motor Drive System using Adaptive-Network-based Fuzzy Interference System

    V. M. Varatharaju; Badrilal Mathur; Udhayakumar

    2011-01-01

    Problem statement: The tuning methodology for the parameters of adaptive speed controller causes a transient deviation of the response from the set reference following variation in load torque in a permanent-magnet brushless DC (BLDC) motor drive system. Approach: This study develops a mathematical model of the BLDC drive system, firstly. Secondly, discusses a design of the closed loop drive system employing the Adaptive-Network-based Fuzzy Interference System (ANFIS). The nonlinear simulatio...

  7. Design of an Adaptive Controller for Dive-plane Control of a Torpedo-shaped AUV

    Jian Cao; Yumin Su; Jinxin Zhao

    2011-01-01

    Underwater vehicles operating in complex ocean conditions present difficulties in determining accurate dynamic models.To guarantee robustness against parameter uncertainty,an adaptive controller for dive-plane control,based on Lyapunov theory and back-stepping techniques,was proposed.In the closed-loop system,asymptotic tracking of the reference depth and pitch angle trajectories was accomplished.Simulation results were presented which show effective dive-plane control in spite of the uncertainties in the system parameters.

  8. An adaptive controller for Wolsong NGS bulk liquid zone control of RRS

    The evaluation and inspection of linear stability of Liquid Zone Controller (LZC) has been being performed with design data and actual program parameters installed in plant Digital Control Computers (DCC) during licensing stage of Wolsong Units 2,3 and 4. The study was done to identify the candidates -the vulnerable devices or control parameters on stability when plant is undergone with improper tuning or control components' aging. The time constant of LZC valve was analyzed as the critical parameter among the candidates. However, the surveillance requirements could not be applied to the process control system such as control devices of RRS. The response time of RRS controllers have not been measured since commissioned. The fine tuning parameters and gains should have been justified with an analysis, but is tuned with experiences learned from previous CANDU plants. With limited simulation results, we have confirmed that no fundamental barriers of RRS bulk control for Wolsong 2/3/4 exist. The dynamic calibration in DCC program could correct continuously a wrong input-sensing signal of log neutron power such like an adaptive system. The first order lag term of the actuator, LZC valve, is the most critical among other sensing and actuating devices. It is, however, a quite large degradation from design value when it disturbs the plant. With a help of MRAS (model reference adaptive system) regulator in this study, the adaptive controller with an aged actuator has a possibility to cope with the worst situation with which the DCC program could not deal. It will give guidance for plant engineer when the tuning is necessary or preventive maintenance is planned against aging. If a fault tolerant control scheme is applied, an unstable operation of RRS will be relieved from such an unexpected malfunction. We recommend that the precautions and limitations for dynamic response of LZC be considered to apply the vulnerable parameters identified in this study. In this study we

  9. Adaptive switching control of discrete time nonlinear systems based on multiple models

    Rui KAN

    2004-01-01

    We use the approach of "optimal" switching to design the adaptive control because the design among multiple models is intuitively more practically feasible than the traditional adaptive control in improving the performances. We prove that for a typical class of nonlinear systems disturbed by random noise, the multiple model adaptive switching control based on WLS(Weighted Least Squares) or projected-LS (Least Squares) is stable and convergent.

  10. Adaptive chaos control and synchronization for uncertain new chaotic dynamical system

    This Letter presents the adaptive control and synchronization problems for uncertain new chaotic dynamical system (Liu system). Based on Lyapunov stability theory, adaptive control law is derived such that the trajectory of Liu system with unknown parameters is globally stabilized to each unstable equilibrium point of the uncontrolled system. In addition, an adaptive control approach is proposed to make the states of two identical Liu systems with unknown parameters asymptotically synchronized. Numerical simulations are shown to verify the results

  11. Function projective synchronization of two-cell quantum-CNN chaotic oscillators by nonlinear adaptive controller

    In this Letter, we investigate function projective synchronization of two-cell quantum-CNN chaotic oscillators using nonlinear adaptive controller. Based on Lyapunov stability theory, the nonlinear adaptive control law is derived to make the state of two chaotic systems function projective synchronized. Two numerical simulations are presented to illustrate the effectiveness of the proposed nonlinear adaptive control scheme, which is more effective than that in previous literature.

  12. TCSC Nonlinear Adaptive Damping Controller Design Based on RBF Neural Network to Enhance Power System Stability

    Yao, Wei; Fang, Jiakun; Zhao, Ping;

    2013-01-01

    In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have the...

  13. Controlling Strong Chaos by Adaptive Coupling Method in the Perturbed Cat Map

    许海波; 王光瑞; 陈式刚

    2001-01-01

    The method for controlling Hamiltonian chaos by adaptive integrable mode coupling is extended to controlling strong chaos by adaptive integrable and near-integrable mode coupling. We illustrate this method with a highly chaotic system, the perturbed cat map. All orbits can be effectively controlled to the periodic or quasiperiodic orbits. The method is robust against the presence of weak external noise.

  14. Model Reference Adaptive Speed Control of 2-Phase Travelling Wave Ultrasonic Motor

    Zhang Wen Yu; Shi Jing Zhuo

    2013-01-01

    Adopting relatively simple motion control algorithm, helps reduce the cost of ultrasonic motor system including the drive control circuit, so as to promote its industrialization. For this purpose, this paper presents a simple model reference adaptive control strategy. The small amount of calculation of the policy, and with a certain degree of adaptive capacity, improves the system cost-effective.

  15. A new adaptive PI controller and its application in HVAC systems

    The paper concerns the development of a new adaptive PI controller for use in HVAC systems. The process of HVAC control can be described as a first order plus dead time model. A kind of arithmetic of recursive least squares (RLS) with exponential forgetting combined with model matching of a zero frequency method is adopted to estimate the model's parameters while the system remained in closed loop. Then, a simple tuning formula for a PI controller with robustness based on the estimated parameters was used to adjust the controller's parameters automatically while under closed loop. To evaluate the effectiveness of the adaptive PI controller, the proposed method was compared with a H ∞ adaptive PI controller. The simulation results show that the new adaptive PI controller has superior performance to that of the H ∞ adaptive PI controller

  16. Adaptive Sliding Mode Control of Chaos in Permanent Magnet Synchronous Motor via Fuzzy Neural Networks

    Tat-Bao-Thien Nguyen

    2014-01-01

    Full Text Available In this paper, based on fuzzy neural networks, we develop an adaptive sliding mode controller for chaos suppression and tracking control in a chaotic permanent magnet synchronous motor (PMSM drive system. The proposed controller consists of two parts. The first is an adaptive sliding mode controller which employs a fuzzy neural network to estimate the unknown nonlinear models for constructing the sliding mode controller. The second is a compensational controller which adaptively compensates estimation errors. For stability analysis, the Lyapunov synthesis approach is used to ensure the stability of controlled systems. Finally, simulation results are provided to verify the validity and superiority of the proposed method.

  17. Adaptive evolution of a generalist parasitoid: implications for the effectiveness of biological control agents

    Zepeda-Paulo, Francisca A; Ortiz-Martínez, Sebastián A; Figueroa, Christian C.; Lavandero, Blas

    2013-01-01

    The use of alternative hosts imposes divergent selection pressures on parasitoid populations. In response to selective pressures, these populations may follow different evolutionary trajectories. Divergent natural selection could promote local host adaptation in populations, translating into direct benefits for biological control, thereby increasing their effectiveness on the target host. Alternatively, adaptive phenotypic plasticity could be favored over local adaptation in temporal and spat...

  18. Convergence of a simple adaptive finite element method for optimal control

    Becker, Roland; Karim, Hafida; Mao, Shipeng

    2008-01-01

    We prove convergence and optimal complexity of an adaptive finite element algorithm for a model problem of optimal control. Following previous work, our algorithm is based on an adaptive marking strategy which compares a simple edge estimator with an oscillation term in each step of the algorithm in order to adapt the marking of cells.

  19. Novel Robot Manipulator Adaptive Artificial Control: Design a Novel SISO Adaptive Fuzzy Sliding Algorithm Inverse Dynamic Like Method

    Farzin Piltan

    2011-12-01

    Full Text Available Refer to the research, design a novel SISO adaptive fuzzy sliding algorithm inverse dynamic like method (NAIDLC and application to robot manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in inverse dynamic controller, fuzzy logic controller and self tuning fuzzy sliding method, the output has improved. The main objective in this research is analyses and design of the adaptive robust controller based on artificial intelligence and nonlinear control. Robot manipulator is nonlinear, time variant and a number of parameters are uncertain, so design the best controller for this plant is the main target. Although inverse dynamic controller have acceptable performance with known dynamic parameters but regarding to uncertainty, this controller\\'s output has fairly fluctuations. In order to solve this problem this research is focoused on two methodology the first one is design a fuzzy inference system as a estimate nonlinear part of main controller but this method caused to high computation load in fuzzy rule base and the second method is focused on design novel adaptive method to reduce the computation in fuzzy algorithm.

  20. PFC design via FRIT Approach for Adaptive Output Feedback Control of Discrete-time Systems

    Mizumoto, Ikuro; Takagi, Taro; Fukui, Sota; Shah, Sirish L.

    This paper deals with a design problem of an adaptive output feedback control for discrete-time systems with a parallel feedforward compensator (PFC) which is designed for making the augmented controlled system ASPR. A PFC design scheme by a FRIT approach with only using an input/output experimental data set will be proposed for discrete-time systems in order to design an adaptive output feedback control system. Furthermore, the effectiveness of the proposed PFC design method will be confirmed through numerical simulations by designing adaptive control system with adaptive NN (Neural Network) for an uncertain discrete-time system.

  1. Adaptive efficient video transmission over the Internet based on congestion control and RS coding

    黄伟红; 张福炎; 孙正兴

    2002-01-01

    An approach based on adaptive congestion control and adaptive error recovery with RS (Reed-Solomon) coding method is presented for efficient video transmission over the Internet.Featured by weighted moving average rate control and TCP-fdendliness,AVSP,a novel adaptive video streaming protocol,is designed with adjustable rate control parameters so as to respond quickly to the QoS status fluctuation during video transmission over the Internet.Combined with congestion control policy,an adaptive RS coding error recovery scheme with variable parameters is presented to enhance the robustness of MPEG video transmission over the Intemet with restriction to the total system bandwidth.``

  2. An Adaptive Supervisory Sliding Fuzzy Cerebellar Model Articulation Controller for Sensorless Vector-Controlled Induction Motor Drive Systems

    Shun-Yuan Wang

    2015-03-01

    Full Text Available This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC in the speed sensorless vector control of an induction motor (IM drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.

  3. Adaptive, Distributed Control of Constrained Multi-Agent Systems

    Bieniawski, Stefan; Wolpert, David H.

    2004-01-01

    Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.

  4. Control of the adaptive immune response by tumor vasculature

    Laetitia eMauge

    2014-03-01

    Full Text Available The endothelium is nowadays described as an entire organ that regulates various processes: vascular tone, coagulation, inflammation, and immune cell trafficking, depending on the vascular site and its specific microenvironment as well as on endothelial cell-intrinsic mechanisms like epigenetic changes. In this review, we will focus on the control of the adaptive immune response by the tumor vasculature. In physiological conditions, the endothelium acts as a barrier regulating cell trafficking by specific expression of adhesion molecules enabling adhesion of immune cells on the vessel, and subsequent extravasation. This process is also dependent on chemokine and integrin expression, and on the type of junctions defining the permeability of the endothelium. Endothelial cells can also regulate immune cell activation. In fact, the endothelial layer can constitute immunological synapses due to its close interactions with immune cells, and the delivery of co-stimulatory or co-inhibitory signals. In tumor conditions, the vasculature is characterized by abnormal vessel structure and permeability, and by specific phenotype of endothelial cells. All these abnormalities lead to a modulation of intratumoral immune responses and contribute to the development of intratumoral immunosuppression, which is a major mechanism for promoting the development, progression and treatment resistance of tumors. The in-depth analysis of these various abnormalities will help defining novel targets for the development of antitumoral treatments. Furthermore, eventual changes of the endothelial cell phenotype identified by plasma biomarkers could secondarily be selected to monitor treatment efficacy.

  5. Electrowetting-Controlled Dual Liquid Prism for Adaptive Beam Steering

    Cheng, Jiangtao

    2015-03-01

    The use of concentrating photovoltaic (CPV) technology has been the most promising method of harvesting solar radiation. These CPV systems often require motor-driven tracking devices to steer the sun's beams onto solar cells. The cost of maintaining these tracking systems is the primary inhibitor for widespread application. We aim to overcome the need for mechanical trackers through the use of an electrowetting-driven solar tracking (EWST) system. The electrowetting-driven solar tracking system consists of an array of novel electrowetting-controlled dual liquid prisms, which are filled with immiscible fluids that have large differences in refractive indices. The naturally formed meniscus between the fluids can function as a dynamic optical prism. Via the full-range modulation of the liquid prisms, incident sunlight can be adaptively tracked, steered, and focused onto CPV cells through a fixed optical condenser. Furthermore, unlike the conventional and cumbersome motor-driven tracking systems used today, the liquid prism system would be suitable for rooftop applications. The results of this project reveal that the EWST system has the potential to generate ~ 70% more green energy at 50% of the conventional capital cost.

  6. Adaptive Feed-Forward Control of Low Frequency Interior Noise

    Kletschkowski, Thomas

    2012-01-01

    This book presents a mechatronic approach to Active Noise Control (ANC). It describes the required elements of system theory, engineering acoustics, electroacoustics and adaptive signal processing in a comprehensive, consistent and systematic manner using a unified notation. Furthermore, it includes a design methodology for ANC-systems, explains its application and describes tools to be used for ANC-system design. From the research point of view, the book presents new approaches to sound source localization in weakly damped interiors. One is based on the inverse finite element method, the other is based on a sound intensity probe with an active free field. Furthermore, a prototype of an ANC-system able to reach the physical limits of local (feed-forward) ANC is described. This is one example for applied research in ANC-system design. Other examples are given for (i) local ANC in a semi-enclosed subspace of an aircraft cargo hold and (ii) for the combination of audio entertainment with ANC.

  7. Flexible Microgrid Power Quality Enhancement Using Adaptive Hybrid Voltage and Current Controller

    He, Jinwei; Li, Yun Wei; Blaabjerg, Frede

    2014-01-01

    To accomplish superior harmonic compensation performance using distributed generation (DG) unit power electronics interfaces, an adaptive hybrid voltage and current controlled method (HCM) is proposed in this paper. It shows that the proposed adaptive HCM can reduce the numbers of low-pass/bandpa......To accomplish superior harmonic compensation performance using distributed generation (DG) unit power electronics interfaces, an adaptive hybrid voltage and current controlled method (HCM) is proposed in this paper. It shows that the proposed adaptive HCM can reduce the numbers of low...... harmonic compensation performance. Comprehensive simulated and experimental results from a single-phase microgrid are provided to verify the feasibility of the proposed adaptive HCM approach....

  8. Adaptive environmental control for optimal results during plant microgravity experiments

    Kostov, P.; Ivanova, T.; Dandolov, I.; Sapunova, S.; Ilieva, I.

    2002-07-01

    The SVET Space Greenhouse (SG) - the first and the only automated plant growth facility onboard the MIR Space Station in the period 1990-2000 was developed on a Russian-Bulgarian Project in the 80s. The aim was to study plant growth under microgravity in order to include plants as a link of future Biological Life Support Systems for the long-term manned space missions. An American developed Gas Exchange Measurement System (GEMS) was added to the existing SVET SG equipment in 1995 to monitor more environmental and physiological parameters. A lot of long-duration plant flight experiments were carried out in the SVET+GEMS. They led to significant results in the Fundamental Gravitational Biology field - second-generation wheat seeds were produced in the conditions of microgravity. The new International Space Station (ISS) will provide a perfect opportunity for conducting full life cycle plant experiments in microgravity, including measurement of more vital plant parameters, during the next 15-20 years. Nowadays plant growth facilities for scientific research based on the SVET SG functional principles are developed for the ISS by different countries (Russia, USA, Italy, Japan, etc.). A new Concept for an advanced SVET-3 Space Greenhouse for the ISS, based on the Bulgarian experience and "know-how" is described. The absolute and differential plant chamber air parameters and some plant physiological parameters are measured and processed in real time. Using the transpiration and photosynthesis measurement data the Control Unit evaluates the plant status and performs adaptive environmental control in order to provide the most favorable conditions for plant growth at every stage of plant development in experiments. A conceptual block-diagram of the SVET-3 SG is presented.

  9. Adaptive Output Tracking Control for Nonlinear Systems with Failed Actuators and Aircraft Flight System Applications

    Chuanjing Hou; Lisheng Hu; Yingwei Zhang

    2015-01-01

    An adaptive failure compensation scheme using output feedback is proposed for a class of nonlinear systems with nonlinearities depending on the unmeasured states of systems. Adaptive high-gain K-filters are presented to suppress the nonlinearities while the proposed backstepping adaptive high-gain controller guarantees the stability of the closed-loop system and small tracking errors. Simulation results verify that the adaptive failure compensation scheme is effective.

  10. A new class of energy based control laws for revolute robot arms - Tracking control, robustness enhancement and adaptive control

    Wen, John T.; Kreutz, Kenneth; Bayard, David S.

    1988-01-01

    A class of joint-level control laws for all-revolute robot arms is introduced. The analysis is similar to the recently proposed energy Liapunov function approach except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. By using energy Liapunov functions with the modified potential energy, a much simpler analysis can be used to show closed-loop global asymptotic stability and local exponential stability. When Coulomb and viscous friction and model parameter errors are present, a sliding-mode-like modification of the control law is proposed to add a robustness-enhancing outer loop. Adaptive control is also addressed within the same framework. A linear-in-the-parameters formulation is adopted, and globally asymptotically stable adaptive control laws are derived by replacing the model parameters in the nonadaptive control laws by their estimates.

  11. Adaptive neural network controller for the molten steel level control of strip casting processes

    The twin-roll strip casting process is a steel-strip production method which combines continuous casting and hot rolling processes. The production line from molten liquid steel to the final steel-strip is shortened and the production cost is reduced significantly as compared to conventional continuous casting. The quality of strip casting process depends on many process parameters, such as molten steel level in the pool, solidification position, and roll gap. Their relationships are complex and the strip casting process has the properties of nonlinear uncertainty and time-varying characteristics. It is difficult to establish an accurate process model for designing a model-based controller to monitor the strip quality. In this paper, a model-free adaptive neural network controller is developed to overcome this problem. The proposed control strategy is based on a neural network structure combined with a sliding-mode control scheme. An adaptive rule is employed to on-line adjust the weights of radial basis functions by using the reaching condition of a specified sliding surface. This surface has the on-line learning ability to respond to the system's nonlinear and time-varying behaviors. Since this model-free controller has a simple control structure and small number of control parameters, it is easy to implement. Simulation results, based on a semi experimental system dynamic model and parameters, are executed to show the control performance of the proposed intelligent controller. In addition, the control performance is compared with that of a traditional Pid controller

  12. Control of Chaos in Rate-Dependent Friction-Induced Vibration Using Adaptive Sliding Mode Control and Impulse Damper

    Ehsan Maani Miandoab

    2013-01-01

    Full Text Available Two different control methods, namely, adaptive sliding mode control and impulse damper, are used to control the chaotic vibration of a block on a belt system due to the rate-dependent friction. In the first method, using the sliding mode control technique and based on the Lyapunov stability theory, a sliding surface is determined, and an adaptive control law is established which stabilizes the chaotic response of the system. In the second control method, the vibration of this system is controlled by an impulse damper. In this method, an impulsive force is applied to the system by expanding and contracting the PZT stack according to efficient control law. Numerical simulations demonstrate the effectiveness of both methods in controlling the chaotic vibration of the system. It is shown that the settling time of the controlled system using impulse damper is less than that one controlled by adaptive sliding mode control; however, it needs more control effort.

  13. A distributed system adaptive control strategy. [for attitude control of large spacecraft

    Johnson, C. R., Jr.; Montgomery, R. C.

    1979-01-01

    One attitude control device being studied for large spacecraft consists of two counter-rotating rings, each designated as an annular momentum control device (AMCD), that are attached to a spacecraft using several magnetic bearings distributed along the circumference of the rings. For large spacecraft large rings are desirable. Unfortunately, for large rings flexibility is appreciable and it becomes necessary to account for the distributed nature of the rings in the design of the magnetic bearing controllers. Also ring behavior is unpredictably sensitive to ring temperature, spin rate, manufacturing imperfections, and other variables. For that reason a distributed adaptive microcomputer-based control system is being sought for ring stabilization and maneuvering. An original adaptive-control methodology for distributed-parameter systems is detailed and application to spinning ring, i.e., AMCD, stabilization is used as an illustration. The proposed methodology, presented as a step-by-step procedure, combines a lumped-parameter expansion description of distributed parameter systems with a fundamental simultaneous identification and control strategy. Simulations are presented providing preliminary evidence of the capabilities of the proposed procedure.

  14. Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems

    A robust adaptive PID controller design motivated from the sliding mode control is proposed for a class of uncertain chaotic systems in this paper. Three PID control gains, K p, K i, and K d, are adjustable parameters and will be updated online with an adequate adaptation mechanism to minimize a previously designed sliding condition. By introducing a supervisory controller, the stability of the closed-loop PID control system under with the plant uncertainty and external disturbance can be guaranteed. Finally, a well-known Duffing-Holmes chaotic system is used as an illustrative to show the effectiveness of the proposed robust adaptive PID controller

  15. Adaptive Backstepping Control of Nonlinear Hydraulic-Mechanical System Including Valve Dynamics

    M. Choux

    2010-01-01

    Full Text Available The main contribution of the paper is the development of an adaptive backstepping controller for a nonlinear hydraulic-mechanical system considering valve dynamics. The paper also compares the performance of two variants of an adaptive backstepping tracking controller with a simple PI controller. The results show that the backstepping controller considering valve dynamics achieves significantly better tracking performance than the PI controller, while handling uncertain parameters related to internal leakage, friction, the orifice equation and oil characteristics.

  16. Adaptive control of bifurcation and chaos in a time-delayed system

    Li Ning; Yuan Hui-Qun; Sun Hai-Yi; Zhang Qing-Ling

    2013-01-01

    In this paper,the stabilization of a continuous time-delayed system is considered.To control the bifurcation and chaos in a time-delayed system,a parameter perturbation control and a hybrid control are proposed.Then,to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes,the adaptive control idea is introduced,i.e.,the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws,respectively.The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem.The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods.They have the advantages of increased stability,adaptability to the changes of the system parameters,control cost saving,and simplicity.Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods.A comparison of the two adaptive control methods is also made in an experimental study.

  17. Adaptive control of bifurcation and chaos in a time-delayed system

    In this paper, the stabilization of a continuous time-delayed system is considered. To control the bifurcation and chaos in a time-delayed system, a parameter perturbation control and a hybrid control are proposed. Then, to ensure the asymptotic stability of the system in the presence of unexpected system parameter changes, the adaptive control idea is introduced, i.e., the perturbation control parameter and the hybrid control parameter are automatically tuned according to the adaptation laws, respectively. The adaptation algorithms are constructed based on the Lyapunov-Krasovskii stability theorem. The adaptive parameter perturbation control and the adaptive hybrid control methods improve the corresponding constant control methods. They have the advantages of increased stability, adaptability to the changes of the system parameters, control cost saving, and simplicity. Numerical simulations for a well-known chaotic time-delayed system are performed to demonstrate the feasibility and superiority of the proposed control methods. A comparison of the two adaptive control methods is also made in an experimental study

  18. Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources

    Sun, Yiming

    2016-01-01

    In this work, an innovative real-time microwave control approach is proposed, to improve the temperature homogeneity under microwave heating. Multiple adaptive or intelligent control structures have been developed, including the model predictive control, neural network control and reinforcement learning control methods. Experimental results prove that these advanced control methods can effectively reduce the final temperature derivations and improve the temperature homogeneity.

  19. Neural Control and Adaptive Neural Forward Models for Insect-like, Energy-Efficient, and Adaptable Locomotion of Walking Machines

    Poramate Manoonpong

    2013-02-01

    Full Text Available Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs and sensory feedback (afferent-based control but also on internal forward models (efference copies. They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.

  20. Adapt

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  1. Applications of Fuzzy adaptive PID control in the thermal power plant denitration liquid ammonia evaporation

    Li Jing

    2016-01-01

    Full Text Available For the control of the liquid level of liquid ammonia in thermal power plant’s ammonia vaporization room, traditional PID controller parameter tuning is difficult to adapt to complex control systems, the setting of the traditional PID controller parameters is difficult to adapt to the complex control system. For the disadvantage of bad parameter setting, poor performance and so on the fuzzy adaptive PID control is proposed. Fuzzy adaptive PID control combines the advantages of traditional PID technology and fuzzy control. By using the fuzzy controller to intelligent control the object, the performance of the PID controller is further improved, and the control precision of the system is improved[1]. The simulation results show that the fuzzy adaptive PID controller not only has the advantages of high accuracy of PID controller, but also has the characteristics of fast and strong adaptability of fuzzy controller. It realizes the optimization of PID parameters which are in the optimal state, and the maximum increase production efficiency, so that are more suitable for nonlinear dynamic system.

  2. Adaptive Impedance Control to Enhance Human Skill on a Haptic Interface System

    Satoshi Suzuki

    2012-01-01

    Full Text Available Adaptive assistive control for a haptic interface system is proposed in the present paper. The assistive control system consists of three subsystems: a servo controller to match the response of the controlled machine to the virtual model, an online identifier of the operator’s control characteristics, and a variable dynamics control using adaptive mechanism. The adaptive mechanism tunes an impedance of the virtual model for the haptic device according to the identified operator’s characteristics so as to enhance the operator’s control performance. The adaptive law is derived by utilizing a Lyapunov candidate function. Using a haptic interface device composed by a xy-stage, an effectiveness of the proposed control method was evaluated experimentally. As a result, it was confirmed that the operator’s characteristics can be estimated sufficiently and that performance of the operation was enhanced by the variable dynamics assistive control.

  3. Backstepping Adaptive Controller of Electro-Hydraulic Servo System of Continuous Rotary Motor

    XiaoJing Wang; ChangFu Xian; CaoLei Wan; JinBao Zhao; LiWei Xiu; AnCai Yu

    2014-01-01

    In order to consider the influence of the continuous rotary motor electro-hydraulic servo system parameters change on its performance, the design method of backstepping adaptive controller is put forward. The mathematical model of electro-hydraulic servo system of continuous rotary motor is established, and the whole system is decomposed into several lower order subsystems, and the virtual control signal is designed for each subsystem from the final subsystem with motor angular displacement to the subsystem with system control input voltage. Based on Lyapunov method and the backstepping theory, an adaptive backstepping controller is designed with the changed parameters adaptive law. It is proved that the system reaches the global asymptotic stability, and the system tracking error asymptotically tends to zero. The simulation results show that the backstepping adaptive controller based on the adaptive law of the changed parameters can improve the performance of continuous rotary motor, and the proposed control strategy is feasible.

  4. Improved adaptive fuzzy control for MIMO nonlinear time-delay systems

    2011-01-01

    This paper presents an improved observer-based indirect adaptive fuzzy control scheme for multiinput-multioutput (MIMO) nonlinear time-delay systems.The control scheme synthesizes adaptive fuzzy control with adaptive fuzzy identification.An observer is designed to observe the system state,and an identifier is developed to identify the unknown parts of the system.The update laws for parameters utilize two types of errors in the adaptive time-delay fuzzy logic systems,the observation error and the identificat...

  5. Indirect Adaptive Attitude Control for a Ducted Fan Vertical Takeoff and Landing Microaerial Vehicle

    Shouzhao Sheng

    2015-01-01

    Full Text Available The present paper addresses an attitude tracking control problem of a ducted fan microaerial vehicle. The proposed indirect adaptive controller can greatly reduce tracking error in the initial stage of the adaptive learning process by using an error compensation strategy and can achieve good capability to eliminate the adverse effect of measurement noises on the convergence of adjustable parameters. Moreover, the learning rate adaptation strategy is proposed to further minimize the adverse effect of large learning rates on the convergence of adjustable parameters. The experimental tests have illustrated the effectiveness of the proposed adaptive controller.

  6. Decentralized Adaptive Control of Systems with Uncertain Interconnections, Plant-Model Mismatch and Actuator Failures

    Patre, Parag; Joshi, Suresh M.

    2011-01-01

    Decentralized adaptive control is considered for systems consisting of multiple interconnected subsystems. It is assumed that each subsystem s parameters are uncertain and the interconnection parameters are not known. In addition, mismatch can exist between each subsystem and its reference model. A strictly decentralized adaptive control scheme is developed, wherein each subsystem has access only to its own state but has the knowledge of all reference model states. The mismatch is estimated online for each subsystem and the mismatch estimates are used to adaptively modify the corresponding reference models. The adaptive control scheme is extended to the case with actuator failures in addition to mismatch.

  7. Adaptive tuning of feedback gain in time-delayed feedback control

    Lehnert, J.; Hövel, P.; Flunkert, V.; Guzenko, P. Yu.; Fradkov, A. L.; Schöll, E.

    2011-12-01

    We demonstrate that time-delayed feedback control can be improved by adaptively tuning the feedback gain. This adaptive controller is applied to the stabilization of an unstable fixed point and an unstable periodic orbit embedded in a chaotic attractor. The adaptation algorithm is constructed using the speed-gradient method of control theory. Our computer simulations show that the adaptation algorithm can find an appropriate value of the feedback gain for single and multiple delays. Furthermore, we show that our method is robust to noise and different initial conditions.

  8. Adaptive synchronization of a class of chaotic systems via variable structure control

    Li Huiguang; Zhang Xinying; Guan Xinping

    2005-01-01

    The synchronization problem under two cases is considered. One is that the bound on the uncertainty existing in the controller is known, the other is that the bound is unknown. In the latter case, the simple adaptation laws for upper bound on the norm of the uncertainty is proposed. Using this adaptive upper bound, a variable structure control is designed. The proposed method does not guarantee the convergence of the adaptive upper bound to the real one but makes the system asymptotically stable.

  9. Optimal Adaptive Control of a Class of Stochastic Systems Using Game Theory

    2002-01-01

    This paper attempts to study a optimal adaptive con tr ol problem using game theory, and proposes an important practical result that an adaptive processes is a set of sufficient conditions under which pure strategy is essentially complete, and thus the fact that yield a very useful desirable pu re optimal control rule.Optimal Adaptive Control of a Class of Stochastic Systems Using Game Theory

  10. Adaptive Control for Uncertain Nonlinear Multi-Input Multi-Output Systems

    Cao, Chengyu (Inventor); Hovakimyan, Naira (Inventor); Xargay, Enric (Inventor)

    2014-01-01

    Systems and methods of adaptive control for uncertain nonlinear multi-input multi-output systems in the presence of significant unmatched uncertainty with assured performance are provided. The need for gain-scheduling is eliminated through the use of bandwidth-limited (low-pass) filtering in the control channel, which appropriately attenuates the high frequencies typically appearing in fast adaptation situations and preserves the robustness margins in the presence of fast adaptation.

  11. An Adaptive Observer for Dynamical Ship Position Control Using Vectorial Observer Backstepping

    Calugi, Francesco; Robertsson, Anders; Johansson, Rolf

    2003-01-01

    In this paper, we propose an adaptive observer for dynamically positioned ships, that can be used together with the controller shown by Fossen and Grovlen, to design an observer-based adaptive control scheme. The resulting closed-loop system is globally asymptotically stable with respect to the ship positions and velocities, and globally stable with respect to adaptation to unknown parameters. A discrete-time approximation scheme is presented.

  12. Robust Adaptive Fault-Tolerant Tracking Control of Three-Phase Induction Motor

    Hossein Tohidi; Koksal Erenturk

    2014-01-01

    This paper deals with the problem of induction motor tracking control against actuator faults and external disturbances using the linear matrix inequalities (LMIs) method and the adaptive method. A direct adaptive fault-tolerant tracking controller design method is developed based on Lyapunov stability theory and a constructive algorithm based on linear matrix inequalities for online tuning of adaptive and state feedback gains to stabilize the closed-loop system in order to reduce the fault e...

  13. A UPFC damping control scheme using Lead-Lag and ANN based Adaptive controllers

    D. Ramesh

    2012-09-01

    Full Text Available Low Frequency Oscillations (LFO occur inpower systems because of lack of the damping torque inorder to dominance to power system disturbances aschange in mechanical input power. In the recent pastPower System Stabilizer (PSS was used to damp LFO.FACTs devices, such as Unified Power Flow Controller(UPFC, can control power flow and increase transientstability. So UPFC may be used to damp LFO instead ofPSS. UPFC damps LFO through direct control of voltageand power. In this research the linearized model ofsynchronous machine (Heffron-Philips connected toinfinite bus (Single Machine-Infinite Bus: SMIB withUPFC is used and also in order to damp LFO, adaptiveANN damping controller for UPFC is designed andsimulated. Simulation is performed for various types ofloads and for different disturbances. Simulation resultsdemonstrate that the developed ANN damping controllerwould be more effective in damping electromechanicaloscillations in comparison with the conventional lead-lagcontroller.

  14. Adaptive observer for speed sensorless PM motor control

    Rasmussen, Henrik; Vadstrup, P.; Børsting, H.

    2003-01-01

    This paper presents an adaptive observer for extimating the rotor position and speed of a permanent magnet synchronous motors (PMSM). The observer compensates for voltage offsets and permanent magnet strength variations. The adaptation structure for estimating the strength of the permanent magnet...... is determined from a Lyapunov stability proof. The observer estimates the stator flux by integration of the measured BEMF signal. In order to verify the applicability of the method the observer has been implemented and tested on a 800 W motor....

  15. Adaptive Traffic Signalization Model using Neuro-Fuzzy Controllers

    Devesh Batra; Pragya Verma

    2014-01-01

    Current traffic lights are pre-programmed and use daily signal timing schedules, which contribute to traffic congestion and delay. Thus, with the increase in the number of vehicles on road, need for adaptive signal technology arises which has the potential to adjust the timing of red, yellow and green lights in order to accommodate changing traffic patterns and ease traffic congestion. In this paper, we present a model for adaptive traffic signalization, which uses fuzzy neura...

  16. The ADAPT design model: towards instructional control of transfer

    Jelsma, Otto; Merrienboer, van, Jeroen J.G.; Bijlstra, Jim P.

    1990-01-01

    This paper presents a detailed description of the ADAPT (Apply Delayed Automatization for Positive Transfer) design model. ADAPT is based upon production system models of learning and provides guidelines for developing instructional systems that offer transfer of leamed skills. The model suggests that transfer of training can be attributed to procedure overlap between the original training task and the transfer task, as well as to analogy between new problem solving situations and acquired co...

  17. Adaptive Epidemic Dynamics in Networks: Thresholds and Control

    Xu, Shouhuai; Lu, Wenlian; Xu, Li; Zhan, Zhenxin

    2013-01-01

    Theoretical modeling of computer virus/worm epidemic dynamics is an important problem that has attracted many studies. However, most existing models are adapted from biological epidemic ones. Although biological epidemic models can certainly be adapted to capture some computer virus spreading scenarios (especially when the so-called homogeneity assumption holds), the problem of computer virus spreading is not well understood because it has many important perspectives that are not necessarily ...

  18. Analyzing the effect of slowly variable parameters on the adaptive active control strategy

    This paper reveals that the adaptive active control strategy used to completely synchronize two chaotic systems with unknown parameters is not suitable to those systems with slowly variable parameters, such as electronic neuron systems. Simulation results show that two electronic neuron systems can be phase synchronized only by using adaptive active control strategy

  19. Adaptive Controllers for Permanent Magnet Brushless DC Motor Drive System using Adaptive-Network-based Fuzzy Interference System

    V. M. Varatharaju

    2011-01-01

    Full Text Available Problem statement: The tuning methodology for the parameters of adaptive speed controller causes a transient deviation of the response from the set reference following variation in load torque in a permanent-magnet brushless DC (BLDC motor drive system. Approach: This study develops a mathematical model of the BLDC drive system, firstly. Secondly, discusses a design of the closed loop drive system employing the Adaptive-Network-based Fuzzy Interference System (ANFIS. The nonlinear simulation model of the BLDC motors drive system with ANFIS control based is simulated in the MATLAB/SIMULINK platform. Results: The necessitated data for training the ANFIS control is generated by simulation of the system with conventional PI controller. Conclusion: The simulated electromagnetic torque and rotor speed signify the superiority of the proposed technique over the classical method.

  20. Mood states influence cognitive control: the case of conflict adaptation.

    Schuch, Stefanie; Koch, Iring

    2015-09-01

    Conflict adaptation can be measured by the "congruency sequence effect", denoting the reduction of congruency effects after incongruent trials (where response conflict occurs) relative to congruent trials (without response conflict). Recently, it has been reported that conflict adaptation is larger in negative mood than in positive mood (van Steenbergen et al., Psychological Science 21:1629-1634, 2010). We conducted two experiments further investigating this important finding. Two different interference paradigms were applied to measure conflict adaptation: Experiment 1 was a Flanker task, Experiment 2 was a Stroop-like task. To get as pure a measure of conflict adaptation as possible, we minimized the influence of trial-to-trial priming effects by excluding all kinds of stimulus repetitions. Mood states were induced by presenting film clips with emotional content prior to the interference task. Three mood states were manipulated between subjects: amused, anxious, and sad. Across both interference paradigms, we consistently found conflict adaptation in negative, but not in positive mood. Taken together with van Steenbergen et al. (Psychological Science 21:1629-1634, 2010) findings, the results suggest that the negative-mood-triggered increase in conflict adaptation is a general phenomenon that occurs independently of the particular mood-induction procedure and interference paradigm involved. PMID:25100233

  1. Aero-Effected Distributed Adaptive Control of Flexible Aircraft Using Active Bleed Project

    National Aeronautics and Space Administration — The proposed research focuses on the development of a new adaptive control methodology for active control of wing aerodynamic shape to effect distributed...

  2. Pressure regulation for earth pressure balance control on shield tunneling machine by using adaptive robust control

    Xie, Haibo; Liu, Zhibin; Yang, Huayong

    2016-05-01

    Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control (ARC) are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve's dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.

  3. Pressure regulation for earth pressure balance control on shield tunneling machine by using adaptive robust control

    Xie, Haibo; Liu, Zhibin; Yang, Huayong

    2016-04-01

    Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control (ARC) are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve's dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.

  4. Adaptive control of call acceptance in WCDMA network

    Milan Manojle Šunjevarić

    2013-10-01

    Full Text Available In this paper, an overview of the algorithms for access control in mobile wireless networks is presented. A review of adaptive control methods of accepting a call in WCDMA networks is discussed, based on the overview of the algorithms used for this purpose, and their comparison. Appropriate comments and conculsions in comparison with the basic characteristics of these algorithms are given. The OVSF codes are explained as well as how the allocation method influences the capacity and probability of blocking.. Introduction We are witnessing a steady increase in the number of demands placed upon modern wireless networks. New applications and an increasing number of users as well as user activities growth in recent years reinforce the need for an efficient use of the spectrum and its proper distribution among different applications and classes of services. Besides humans, the last few years saw different computers, machines, applications, and, in the future, many other devices, RFID applications, and finally networked objects, as a new kind of wireless networks "users". Because of the exceptional rise in the number of users, the demands placed upon modern wireless networks are becoming larger, and spectrum management plays an important role. For these reasons, choosing an appropriate call admission control algorithm is of great importance. Multiple access and resource management in wireless networks Radio resource management of mobile networks is a set of algorithms to manage the use of radio resources with the aim is to maximize the total capacity of wireless systems with equal distribution of resources to users. Management of radio resources in cellular networks is usually located in the base station controller, the base station and the mobile terminal, and is based on decisions made on appropriate measurement and feedback. It is often defined as the maximum volume of traffic load that the system can provide for some of the requirements for the

  5. On application of constrained receding horizon control in astronomical adaptive optics

    Konnik, Mikhail V.; De Doná, José; Welsh, James Stuart

    2012-07-01

    Control system design for adaptive optics is becoming more complex and sophisticated with increasing demands on the compensation of atmospheric turbulence. Contemporary controllers used in adaptive optics systems are optimised in the sense of a cost function (linear quadratic regulators) or to a worst case scenario (robust H∞ controllers). Prediction, to some extent, can be incorporated into the controllers using the Kalman filter and a model of the atmospheric turbulence. Despite the growing number of publications on adaptive optics control systems, only the unconstrained case is usually considered. Accounting for the physical constraints of the adaptive optics system components, such as limited actuator stroke, still represents a problem. As a possible solution, one can consider constrained receding horizon control (RHC), also known as Model Predictive Control (MPC). The ability of RHC to handle constraints and make predictions of the future control signals makes it attractive for application in astronomical adaptive optics. The main potential difficulty with the application of RHC is its heavy computational load. This paper presents preliminary results on numerical simulations of an adaptive optics system controlled by constrained RHC. In particular, the case of output disturbance rejection is considered. The results of numerical simulations are provided. Finally, methods for improving the computational performance of constrained receding horizon controllers in adaptive optics are also discussed.

  6. Robust synchronization of drive-response chaotic systems via adaptive sliding mode control

    A robust adaptive sliding control scheme is developed in this study to achieve synchronization for two identical chaotic systems in the presence of uncertain system parameters, external disturbances and nonlinear control inputs. An adaptation algorithm is given based on the Lyapunov stability theory. Using this adaptation technique to estimate the upper-bounds of parameter variation and external disturbance uncertainties, an adaptive sliding mode controller is then constructed without requiring the bounds of parameter and disturbance uncertainties to be known in advance. It is proven that the proposed adaptive sliding mode controller can maintain the existence of sliding mode in finite time in uncertain chaotic systems. Finally, numerical simulations are presented to show the effectiveness of the proposed control scheme.

  7. Neural-network adaptive controller for nonlinear systems and its application in pneumatic servo systems

    Lu LU; Fagui LIU; Weixiang SHI

    2008-01-01

    In this paper, a novel control law is presented, which uses neural-network techniques to approximate the affine class nonlinear system having unknown or uncertain dynamics and noise disturbances. It adopts an adaptive control law to adjust the network parameters online and adds another control component according to H-infinity control theory to attenuate the disturbance. This control law is applied to the position tracking control of pneumatic servo systems. Simulation and experimental results show that the tracking precision and convergence speed is obviously superior to the results by using the basic BP-network controller and self-tuning adaptive controller.

  8. Adaptive Control of Linear Modal Systems Using Residual Mode Filters and a Simple Disturbance Estimator

    Balas, Mark; Frost, Susan

    2012-01-01

    Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter.

  9. Estimation, filtering and adaptative control of a waste water processing process; Estimation, filtrage et commande adaptive d`un procede de traitement des eaux usees

    Ben Youssef, C.; Dahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Rols, J.L. [Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)

    1995-12-31

    Controlling the process of a fixed bed bioreactor imply solving filtering and adaptative control problems. Estimation processes have been developed for unmeasurable parameters. An adaptative non linear control has been built, instead of conventional approaches trying to linearize the system and apply a linear control system. (D.L.) 10 refs.

  10. The beauty of simple adaptive control and new developments in nonlinear systems stability analysis

    Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits

  11. The beauty of simple adaptive control and new developments in nonlinear systems stability analysis

    Barkana, Itzhak, E-mail: ibarkana@gmail.com [BARKANA Consulting, Ramat Hasharon (Israel)

    2014-12-10

    Although various adaptive control techniques have been around for a long time and in spite of successful proofs of stability and even successful demonstrations of performance, the eventual use of adaptive control methodologies in practical real world systems has met a rather strong resistance from practitioners and has remained limited. Apparently, it is difficult to guarantee or even understand the conditions that can guarantee stable operations of adaptive control systems under realistic operational environments. Besides, it is difficult to measure the robustness of adaptive control system stability and allow it to be compared with the common and widely used measure of phase margin and gain margin that is utilized by present, mainly LTI, controllers. Furthermore, customary stability analysis methods seem to imply that the mere stability of adaptive systems may be adversely affected by any tiny deviation from the pretty idealistic and assumably required stability conditions. This paper first revisits the fundamental qualities of customary direct adaptive control methodologies, in particular the classical Model Reference Adaptive Control, and shows that some of their basic drawbacks have been addressed and eliminated within the so-called Simple Adaptive Control methodology. Moreover, recent developments in the stability analysis methods of nonlinear systems show that prior conditions that were customarily assumed to be needed for stability are only apparent and can be eliminated. As a result, sufficient conditions that guarantee stability are clearly stated and lead to similarly clear proofs of stability. As many real-world applications show, once robust stability of the adaptive systems can be guaranteed, the added value of using Add-On Adaptive Control along with classical Control design techniques is pushing the desired performance beyond any previous limits.

  12. Chaos control using an adaptive fuzzy sliding mode controller with application to a nonlinear pendulum

    Chaos control may be understood as the use of tiny perturbations for the stabilization of unstable periodic orbits embedded in a chaotic attractor. The idea that chaotic behavior may be controlled by small perturbations of physical parameters allows this kind of behavior to be desirable in different applications. In this work, chaos control is performed employing a variable structure controller. The approach is based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm to cope with modeling inaccuracies. The convergence properties of the closed-loop system are analytically proven using Lyapunov's direct method and Barbalat's lemma. As an application of the control procedure, a nonlinear pendulum dynamics is investigated. Numerical results are presented in order to demonstrate the control system performance. A comparison between the stabilization of general orbits and unstable periodic orbits embedded in chaotic attractor is carried out showing that the chaos control can confer flexibility to the system by changing the response with low power consumption.

  13. Design of a new adaptive fuzzy controller and its implementation for the damping force control of a magnetorheological damper

    This paper presents a new adaptive fuzzy controller and its implementation for the damping force control of a magnetorheological (MR) fluid damper in order to validate the effectiveness of the control performance. An interval type 2 fuzzy model is built, and then combined with modified adaptive control to achieve the desired damping force. In the formulation of the new adaptive controller, an enhanced iterative algorithm is integrated with the fuzzy model to decrease the time of calculation (D Wu 2013 IEEE Trans. Fuzzy Syst. 21 80–99) and the control algorithm is synthesized based on the H∞ tracking technique. In addition, for the verification of good control performance of the proposed controller, a cylindrical MR damper which can be applied to the vibration control of a washing machine is designed and manufactured. For the operating fluid, a recently developed plate-like particle-based MR fluid is used instead of a conventional MR fluid featuring spherical particles. To highlight the control performance of the proposed controller, two existing adaptive fuzzy control algorithms proposed by other researchers are adopted and altered for a comparative study. It is demonstrated from both simulation and experiment that the proposed new adaptive controller shows better performance of damping force control in terms of response time and tracking accuracy than the existing approaches. (papers)

  14. Chattering-free fuzzy adaptive robust sliding-mode vibration control of a smart flexible beam

    Chattering is an undesired phenomenon associated with classical sliding-mode control. The discontinuous bang–bang robust controller causes chattering near the equilibrium. To attenuate the chattering, in this paper, a fuzzy logic smooth switch system is integrated with the adaptive robust sliding-mode control to form a fuzzy adaptive robust sliding-mode control for the active vibration control of a smart flexible beam integrated with piezoceramic actuators and sensors. The asymptotical stability proof of the proposed fuzzy adaptive robust sliding-mode controller is provided by Lyapunov's direct method. The experimental results show that the proposed fuzzy adaptive robust sliding-mode controller quickly suppresses the vibration. Additionally, with the fuzzy switch system, the chattering is successfully attenuated

  15. Synchronization of a modified Chua's circuit system via adaptive sliding mode control

    This study addresses the adaptive synchronization of a modified Chua's circuit system with both unknown system parameters and the nonlinearity in the control input. An adaptive switching surface is newly adopted such that it becomes easy to ensure the stability of the error dynamics in the sliding mode. Based on this adaptive switching surface, an adaptive sliding mode controller (ASMC) is derived to guarantee the occurrence of the sliding motion, even when the system is undergoing input nonlinearity. This method can also be easily extended to a general class of Chua's circuits. An illustrative example is given to show the applicability of the proposed ASMC design

  16. Two fiber optics communication adapters apply to the control system of HIRFL-CSR

    The authors introduced two kinds of fiber adapters that apply to the engineering HIRFL-CSR. Including design of two adapters, operational principle, and hardware construction, field of application. How to control equipment which have the standard RS232 or RS485 interface at long distance by two adapters. Replace the RS485 bus with the fiber and the 485-Fiber Adapter, solved the problem of communication disturb. The requirements of control in the national great science engineering HIRFL-CSR are fulfilled. (authors)

  17. Real-Time Discrete Adaptive Control of Robot Arm Based on Digital Signal Processing

    2008-01-01

    A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control (MRAC) and digital signal processing (DSP) computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.

  18. Temporal adaptation enhances efficient contrast gain control on natural images.

    Fabian Sinz

    Full Text Available Divisive normalization in primary visual cortex has been linked to adaptation to natural image statistics in accordance to Barlow's redundancy reduction hypothesis. Using recent advances in natural image modeling, we show that the previously studied static model of divisive normalization is rather inefficient in reducing local contrast correlations, but that a simple temporal contrast adaptation mechanism of the half-saturation constant can substantially increase its efficiency. Our findings reveal the experimentally observed temporal dynamics of divisive normalization to be critical for redundancy reduction.

  19. Reinforcement Learning Adaptive PID Controller for an Under-actuated Robot Arm

    Adel Akbarimajd

    2015-10-01

    Full Text Available Abstract: An adaptive PID controller is used to control of a two degrees of freedom under actuated manipulator. An actor-critic based reinforcement learning is employed for tuning of parameters of the adaptive PID controller. Reinforcement learning is an unsupervised scheme wherein no reference exists to which convergence of algorithm is anticipated. Thus, it is appropriate for real time applications. Controller structure and learning equations as well as update rules are provided. Simulations are performed in SIMULINK and performance of the controller is compared with NARMA-L2 controller. The results verified good performance of the controller in tracking and disturbance rejection tests.

  20. Distributed Consensus-Based Robust Adaptive Formation Control for Nonholonomic Mobile Robots with Partial Known Dynamics

    Zhaoxia Peng

    2014-01-01

    Full Text Available This paper investigates the distributed consensus-based robust adaptive formation control for nonholonomic mobile robots with partially known dynamics. Firstly, multirobot formation control problem has been converted into a state consensus problem. Secondly, the practical control strategies, which incorporate the distributed kinematic controllers and the robust adaptive torque controllers, are designed for solving the formation control problem. Thirdly, the specified reference trajectory for the geometric centroid of the formation is assumed as the trajectory of a virtual leader, whose information is available to only a subset of the followers. Finally, numerical results are provided to illustrate the effectiveness of the proposed control approaches.

  1. Adaptive trajectory tracking control of two-wheeled self-balance robot

    Qin Yong; Zang Xizhe; Wang Xiaoyu; Li Tian; Zhao Jie

    2009-01-01

    Wheeled mobile robot is one of the well-known nonholonomic systems. A two-wheeled self-balance robot is taken as the research objective. This paper carried out a detailed force analysis of the robot and established a non-linear dynamics model. An adaptive tracking controller for the kinematic model of a nonholonomic mobile robot with unknown parameters is also proposed. Using control Lyapunov function (CLF), the controller's global asymptotic stability has been proven. The adaptive trajectory tracking controller decreases the disturbance in the course of tracking control and enhances the real-time control characteristics. The simulation result indicated that the wheeled mobile robot tracking can be effectively controlled.

  2. Adaptive Control of a Utility-Scale Wind Turbine Operating in Region 3

    Frost, Susan A.; Balas, Mark J.; Wright, Alan D.

    2009-01-01

    Adaptive control techniques are well suited to nonlinear applications, such as wind turbines, which are difficult to accurately model and which have effects from poorly known operating environments. The turbulent and unpredictable conditions in which wind turbines operate create many challenges for their operation. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility scale, variable-speed horizontal axis wind turbine. The objective of the adaptive pitch controller in Region 3 is to regulate generator speed and reject step disturbances. The control objective is accomplished by collectively pitching the turbine blades. We use an extension of the Direct Model Reference Adaptive Control (DMRAC) approach to track a reference point and to reject persistent disturbances. The turbine simulation models the Controls Advanced Research Turbine (CART) of the National Renewable Energy Laboratory in Golden, Colorado. The CART is a utility-scale wind turbine which has a well-developed and extensively verified simulator. The adaptive collective pitch controller for Region 3 was compared in simulations with a bas celliansesical Proportional Integrator (PI) collective pitch controller. In the simulations, the adaptive pitch controller showed improved speed regulation in Region 3 when compared with the baseline PI pitch controller and it demonstrated robustness to modeling errors.

  3. Design of smart composite platforms for adaptive trust vector control and adaptive laser telescope for satellite applications

    Ghasemi-Nejhad, Mehrdad N.

    2013-04-01

    This paper presents design of smart composite platforms for adaptive trust vector control (TVC) and adaptive laser telescope for satellite applications. To eliminate disturbances, the proposed adaptive TVC and telescope systems will be mounted on two analogous smart composite platform with simultaneous precision positioning (pointing) and vibration suppression (stabilizing), SPPVS, with micro-radian pointing resolution, and then mounted on a satellite in two different locations. The adaptive TVC system provides SPPVS with large tip-tilt to potentially eliminate the gimbals systems. The smart composite telescope will be mounted on a smart composite platform with SPPVS and then mounted on a satellite. The laser communication is intended for the Geosynchronous orbit. The high degree of directionality increases the security of the laser communication signal (as opposed to a diffused RF signal), but also requires sophisticated subsystems for transmission and acquisition. The shorter wavelength of the optical spectrum increases the data transmission rates, but laser systems require large amounts of power, which increases the mass and complexity of the supporting systems. In addition, the laser communication on the Geosynchronous orbit requires an accurate platform with SPPVS capabilities. Therefore, this work also addresses the design of an active composite platform to be used to simultaneously point and stabilize an intersatellite laser communication telescope with micro-radian pointing resolution. The telescope is a Cassegrain receiver that employs two mirrors, one convex (primary) and the other concave (secondary). The distance, as well as the horizontal and axial alignment of the mirrors, must be precisely maintained or else the optical properties of the system will be severely degraded. The alignment will also have to be maintained during thruster firings, which will require vibration suppression capabilities of the system as well. The innovative platform has been

  4. Data-Driven Optimal Control for Adaptive Optics

    Hinnen, K.J.G.

    2007-01-01

    Adaptive optics (AO) is a technique to actively correct the wavefront distortions introduced in a light beam as it propagates through a turbulent medium. Nowadays, it is commonly applied in ground-based telescopes to counteract the devastating effect of atmospheric turbulence. This thesis focuses on

  5. Robot Swarms in an Uncertain World: Controllable Adaptability

    Alexandr Shillerov

    2008-11-01

    Full Text Available There is a belief that complexity and chaos are essential for adaptability. But life deals with complexity every moment, without the chaos that engineers fear so, by invoking goal-directed behaviour. Goals can be programmed. That is why living organisms give us hope to achieve adaptability in robots. In this paper a method for the description of a goal-directed, or programmed, behaviour, interacting with uncertainty of environment, is described. We suggest reducing the structural (goals, intentions and stochastic components (probability to realise the goal of individual behaviour to random variables with nominal values to apply probabilistic approach. This allowed us to use a Normalized Entropy Index to detect the system state by estimating the contribution of each agent to the group behaviour. The number of possible group states is 27. We argue that adaptation has a limited number of possible paths between these 27 states. Paths and states can be programmed so that after adjustment to any particular case of task and conditions, adaptability will never involve chaos. We suggest the application of the model to operation of robots or other devices in remote and/or dangerous places.

  6. Controlling the local false discovery rate in the adaptive Lasso

    Sampson, J. N.

    2013-04-09

    The Lasso shrinkage procedure achieved its popularity, in part, by its tendency to shrink estimated coefficients to zero, and its ability to serve as a variable selection procedure. Using data-adaptive weights, the adaptive Lasso modified the original procedure to increase the penalty terms for those variables estimated to be less important by ordinary least squares. Although this modified procedure attained the oracle properties, the resulting models tend to include a large number of "false positives" in practice. Here, we adapt the concept of local false discovery rates (lFDRs) so that it applies to the sequence, λn, of smoothing parameters for the adaptive Lasso. We define the lFDR for a given λn to be the probability that the variable added to the model by decreasing λn to λn-δ is not associated with the outcome, where δ is a small value. We derive the relationship between the lFDR and λn, show lFDR =1 for traditional smoothing parameters, and show how to select λn so as to achieve a desired lFDR. We compare the smoothing parameters chosen to achieve a specified lFDR and those chosen to achieve the oracle properties, as well as their resulting estimates for model coefficients, with both simulation and an example from a genetic study of prostate specific antigen.

  7. Adaptive synchronization control of coupled chaotic neurons in an external electrical stimulation

    In this paper we present a combined algorithm for the synchronization control of two gap junction coupled chaotic FitzHugh—Nagumo (FHN) neurons in an external electrical stimulation. The controller consists of a combination of dynamical sliding mode control and adaptive backstepping control. The combined algorithm yields an adaptive dynamical sliding mode control law which has the advantage over static sliding mode-based controllers of being chattering-free, i.e., a sufficiently smooth control input signal is generated. It is shown that the proposed control scheme can not only compensate for the system uncertainty, but also guarantee the stability of the synchronized error system. In addition, numerical simulations are also performed to demonstrate the effectiveness of the proposed adaptive controller. (interdisciplinary physics and related areas of science and technology)

  8. Direct adaptive control of wind energy conversion systems using Gaussian networks.

    Mayosky, M A; Cancelo, I E

    1999-01-01

    Grid connected wind energy conversion systems (WECS) present interesting control demands, due to the intrinsic nonlinear characteristics of windmills and electric generators. In this paper a direct adaptive control strategy for WECS control is proposed. It is based on the combination of two control actions: a radial basis zfunction network-based adaptive controller, which drives the tracking error to zero with user specified dynamics, and a supervisory controller, based on crude bounds of the system's nonlinearities. The supervisory controller fires when the finite neural-network approximation properties cannot be guaranteed. The form of the supervisor control and the adaptation law for the neural controller are derived from a Lyapunov analysis of stability. The results are applied to a typical turbine/generator pair, showing the feasibility of the proposed solution. PMID:18252585

  9. Adaptive synchronization control of coupled chaotic neurons in an external electrical stimulation

    Yu Hai-Tao; Wang Jiang; Deng Bin; Wei Xi-Le; Chen Ying-Yuan

    2013-01-01

    In this paper we present a combined algorithm for the synchronization control of two gap junction coupled chaotic FitzHugh-Nagumo (FHN) neurons in an external electrical stimulation.The controller consists of a combination of dynamical sliding mode control and adaptive backstepping control.The combined algorithm yields an adaptive dynamical sliding mode control law which has the advantage over static sliding mode-based controllers of being chattering-free,i.e.,a sufficiently smooth control input signal is generated.It is shown that the proposed control scheme can not only compensate for the system uncertainty,but also guarantee the stability of the synchronized error system.In addition,numerical simulations are also performed to demonstrate the effectiveness of the proposed adaptive controller.

  10. Parametric adaptive estimation and backstepping control of electro-hydraulic actuator with decayed memory filter.

    Guo, Qing; Sun, Ping; Yin, Jing-Min; Yu, Tian; Jiang, Dan

    2016-05-01

    Some unknown parameter estimation of electro-hydraulic system (EHS) should be considered in hydraulic controller design due to many parameter uncertainties in practice. In this study, a parametric adaptive backstepping control method is proposed to improve the dynamic behavior of EHS under parametric uncertainties and unknown disturbance (i.e., hydraulic parameters and external load). The unknown parameters of EHS model are estimated by the parametric adaptive estimation law. Then the recursive backstepping controller is designed by Lyapunov technique to realize the displacement control of EHS. To avoid explosion of virtual control in traditional backstepping, a decayed memory filter is presented to re-estimate the virtual control and the dynamic external load. The effectiveness of the proposed controller has been demonstrated by comparison with the controller without adaptive and filter estimation. The comparative experimental results in critical working conditions indicate the proposed approach can achieve better dynamic performance on the motion control of Two-DOF robotic arm. PMID:26920086

  11. Adaptive Global Sliding Mode Control for MEMS Gyroscope Using RBF Neural Network

    Yundi Chu

    2015-01-01

    Full Text Available An adaptive global sliding mode control (AGSMC using RBF neural network (RBFNN is proposed for the system identification and tracking control of micro-electro-mechanical system (MEMS gyroscope. Firstly, a new kind of adaptive identification method based on the global sliding mode controller is designed to update and estimate angular velocity and other system parameters of MEMS gyroscope online. Moreover, the output of adaptive neural network control is used to adjust the switch gain of sliding mode control dynamically to approach the upper bound of unknown disturbances. In this way, the switch item of sliding mode control can be converted to the output of continuous neural network which can weaken the chattering in the sliding mode control in contrast to the conventional fixed gain sliding mode control. Simulation results show that the designed control system can get satisfactory tracking performance and effective estimation of unknown parameters of MEMS gyroscope.

  12. On the Adaptive Tracking Control of 3-D Overhead Crane Systems

    Yang, Jung Hua

    2009-01-01

    In this chapter, a nonlinear adaptive control law has been presented for the motion control of overhead crane. By utilizing a Lyapunov-based stability analysis, we can achieve asymptotic tracking of the crane position and stabilization of payload sway angle for an overhead crane system which is subject to both underactuation and parametric uncertainties. Comparative simulation studies have been performed to validate the proposed control algorithm. To practically validate the proposed adaptive...

  13. Chattering-Free Adaptive Sliding Mode Control for Attitude Tracking of Spacecraft with External Disturbance

    Xuxi Zhang

    2014-01-01

    Full Text Available The attitude tracking problem of spacecraft in the presence of unknown disturbance is investigated. By using the adaptive control technique and the Lyapunov stability theory, a chattering-free adaptive sliding mode control law is proposed for the attitude tracking problem of spacecraft with unknown disturbance. Simulation results are employed to demonstrate the effectiveness of the proposed control design technique in this paper.

  14. Cross-layer combining of power control and adaptive modulation with truncated ARQ for cognitive radios

    CHENG Shi-lun; YANG Zhen

    2008-01-01

    To maximize throughput and to satisfy users' requirements in cognitive radios, a cross-layer optimization problem combining adaptive modulation and power control at the physical layer and truncated automatic repeat request at the medium access control layer is proposed. Simulation results show the combination of power control, adaptive modulation, and truncated automatic repeat request can regulate transmitter powers and increase the total throughput effectively.

  15. Adaptive control of an active magnetic bearing flywheel system using neural networks / Angelique Combrinck

    Combrinck, Angelique

    2010-01-01

    The School of Electrical, Electronic and Computer Engineering at the North-West University in Potchefstroom has established an active magnetic bearing (AMB) research group called McTronX. This group provides extensive knowledge and experience in the theory and application of AMBs. By making use of the expertise contained within McTronX and the rest of the control engineering community, an adaptive controller for an AMB flywheel system is implemented. The adaptive controller is ...

  16. Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

    Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

    2010-09-01

    This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach. PMID:20729168

  17. System identification of a mechanical system with impacts using model reference adaptive control

    Virden, D.; Wagg, D.J.

    2005-01-01

    A single degree of freedom mechanical spring-mass system was considered where the motion of the mass is constrained by an adjustable rigid impact stop. A model reference adaptive control algorithm combined with interspike interval techniques was used to consider the viability of identifying system parameters when impacts are present. The unmodified adaptive control algorithm destabilizes during vibro-impact motion, so three modified control algorithms were tested experimentally. The first, th...

  18. Adaptive Backstepping controller design and implementation for a matrix-converter-based IM drive system

    R.R. Joshi; R.A. Gupta; A.K. Wadhwani

    2007-01-01

    A systematic controller design and implementation for a matrix-converter-based induction motor drive system is proposed. A nonlinear adaptive backstepping controller is proposed to improve the speed and position responses of the induction motor system. By using the proposed adaptive backstepping controller, the system can track a time-varying speed command and a time-varying position command well. Moreover, the system has a good load disturbance rejection capability. The realization of the co...

  19. Exoskeleton control for lower-extremity assistance based on adaptive frequency oscillators: adaptation of muscle activation and movement frequency.

    Aguirre-Ollinger, Gabriel

    2015-01-01

    In this article, we analyze a novel strategy for assisting the lower extremities based on adaptive frequency oscillators. Our aim is to use the control algorithm presented here as a building block for the control of powered lower-limb exoskeletons. The algorithm assists cyclic movements of the human extremities by synchronizing actuator torques with the estimated net torque exerted by the muscles. Synchronization is produced by a nonlinear dynamical system combining an adaptive frequency oscillator with a form of adaptive Fourier analysis. The system extracts, in real time, the fundamental frequency component of the net muscle torque acting on a specific joint. Said component, nearly sinusoidal in shape, is the basis for the assistive torque waveform delivered by the exoskeleton. The action of the exoskeleton can be interpreted as a virtual reduction in the mechanical impedance of the leg. We studied the ability of human subjects to adapt their muscle activation to the assistive torque. Ten subjects swung their extended leg while coupled to a stationary hip joint exoskeleton. The experiment yielded a significant decrease, with respect to unassisted movement, of the activation levels of an agonist/antagonist pair of muscles controlling the hip joint's motion, which suggests the exoskeleton control has potential for assisting human gait. A moderate increase in swing frequency was observed as well. We theorize that the increase in frequency can be explained by the impedance model of the assisted leg. Per this model, subjects adjust their swing frequency in order to control the amount of reduction in net muscle torque. PMID:25655955

  20. Adaptive RBF Neural Network Control for Three-Phase Active Power Filter

    Juntao Fei; Zhe Wang

    2013-01-01

    An adaptive radial basis function (RBF) neural network control system for three‐phase active power filter (APF) is proposed to eliminate harmonics. Compensation current is generated to track command current so as to eliminate the harmonic current of non‐linear load and improve the quality of the power system. The asymptotical stability of the APF system can be guaranteed with the proposed adaptive neural network strategy. The parameters of the neural network can be adaptively updated to achie...

  1. L1 Adaptive Manoeuvring Control of Unmanned High-speed Water Craft

    Svendsen, Casper H.; Holck, Niels Ole; Galeazzi, Roberto; Blanke, Mogens

    This work addresses the issue of designing an adaptive robust control system to govern the steering of a high speed unmanned personal watercraft (PWC) maintaining equal performance across the craft’s envelope of operation. The maneuvering dynamics of a high speed PWC is presented and a strong......-of-freedom surge-sway-yaw-roll model. An L1 adaptive autopilot is then designed, which allows to achieve fast adaption to system parameters’ changes and robustness of the closed loop system....

  2. Multivariable direct adaptive decoupling controller using multiple models and a case study

    WANG Xin; YANG Hui; ZHENG YiHui

    2009-01-01

    In this paper, a multivariable direct adaptive controller using multiple models without minimum phase assumption is presented to improve the transient response when the parameters of the system jump abruptly. The controller is composed of multiple fixed controller models, a free-running adaptive controller model and a re-initialized adaptive controller model. The fixed controller models are derived from the corresponding fixed system models directly. The adaptive controller models adopt the direct adaptive algorithm to reduce the design calculation. At every instant, the optimal controller is chosen out according to the switching index. The interaction of the system is viewed as the measured disturbance which is eliminated by the choice of the weighing polynomial matrix. The global convergence is obtained. Finally, several simulation examples in a wind tunnel experiment are given to show both effectiveness and practicality of the proposed method. The significance of the proposed method is that it is applicable to a non-minimum phase system, adopting direct adaptive algorithm to overcome the singularity problem during the matrix calculation and realizing decoupling control for a multivariable system.

  3. Adaptive model predictive control of the hybrid dynamics of a fuel cell system

    Fiacchini, Mirko; Alamo, Teodoro; Albea-Sanchez, Carolina; Fernandez Camacho, Eduardo

    2007-01-01

    International audience In this paper, an adaptive control scheme for the safe operation of a fuel cell system is presented. The aim of the control design is to guarantee that the oxygen ratio do not reach dangerous values. A first level of control is given by a feedforward control. An improved behavior is obtained using an adaptive predictive controller to determine the voltage to be applied to the air compressor. An admissible robust control invariant set for the PWA model of the system i...

  4. Sliding mode control of wind-induced vibrations using fuzzy sliding surface and gain adaptation

    Thenozhi, Suresh; Yu, Wen

    2016-04-01

    Although fuzzy/adaptive sliding mode control can reduce the chattering problem in structural vibration control applications, they require the equivalent control and the upper bounds of the system uncertainties. In this paper, we used fuzzy logic to approximate the standard sliding surface and designed a dead-zone adaptive law for tuning the switching gain of the sliding mode control. The stability of the proposed controller is established using Lyapunov stability theory. A six-storey building prototype equipped with an active mass damper has been used to demonstrate the effectiveness of the proposed controller towards the wind-induced vibrations.

  5. Adaptive fault-tolerant control of linear systems with actuator saturation and L2-disturbances

    Wei GUAN; Guanghong YANG

    2009-01-01

    This paper studies the problem of designing adaptive fault-tolerant H-infinity controllers for linear timeinvariant systems with actuator saturation. The disturbance tolerance ability of the closed-loop system is measured by an optimal index. The notion of an adaptive H-infinity performance index is proposed to describe the disturbance attenuation performances of closed-loop systems. New methods for designing indirect adaptive fault-tolerant controllers via state feedback are presented for actuator fault compensations. Based on the on-line estimation of eventual faults, the adaptive fault-tolerant controller parameters are updated automatically to compensate for the fault effects on systems. The designs are developed in the framework of the linear matrix inequality (LMI) approach, which can guarantee the disturbance tolerance ability and adaptive H-infinity performances of closed-loop systems in the cases of actuator saturation and actuator failures. An example is given to illustrate the efficiency of the design method.

  6. Adaptive H∞ synchronization of chaotic systems via linear and nonlinear feedback control

    Adaptive H∞ synchronization of chaotic systems via linear and nonlinear feedback control is investigated. The chaotic systems are redesigned by using the generalized Hamiltonian systems and observer approach. Based on Lyapunov's stability theory, linear and nonlinear feedback control of adaptive H∞ synchronization is established in order to not only guarantee stable synchronization of both master and slave systems but also reduce the effect of external disturbance on an H∞-norm constraint. Adaptive H∞ synchronization of chaotic systems via three kinds of control is investigated with applications to Lorenz and Chen systems. Numerical simulations are also given to identify the effectiveness of the theoretical analysis. (general)

  7. Adaptive control and synchronization of an uncertain new hyperchaotic Lorenz system

    This paper is involved with the adaptive control and synchronization problems for an uncertain new hyperchaotic Lorenz system. Based on the Lyapunov stability theory, the adaptive control law is derived such that the trajectory of hyperchaotic Lorenz system with unknown parameters can be globally stabilized to an unstable equilibrium point of the uncontrolled system. Furthermore, an adaptive control approach is presented to the synchronizations between two identical hyperchaotic systems, particularly between two different uncertain hyperchaotic systems. Numerical simulations show the effectiveness of the presented method. (general)

  8. Adaptive control and synchronization of an uncertain new hyperchaotic Lorenz system

    Cai Guo-Liang; Zheng Song; Tian Li-Xin

    2008-01-01

    This paper is involved with the adaptive control and synchronization problems for an uncertain new hyperchaotic Lorenz system. Based on the Lyapunov stability theory, the adaptive control law is derived such that the trajectory of hyperchaotic Lorenz system with unknown parameters can be globally stabilized to an unstable equilibrium point of the uncontrolled system. Furthermore, an adaptive control approach is presented to the synchronizations between two identical hyperchaotic systems, particularly between two different uncertain hyperchaotic systems. Numerical simulations show the effectiveness of the presented method.

  9. Adaptive control for a class of chaotic systems with unknown bounded uncertainties

    In this paper, a new adaptive control scheme is developed for a class of chaotic systems with unknown bounded uncertainties. Based on Lyapunov stability theory, an adaptive feedback controller is designed for tracking a smooth orbit that can be a limit cycle or a chaotic orbit of another system. Furthermore, it is worthy of note that the proposed adaptive control scheme does not involve any information about the bounds of uncertainties. A numerical example of the Duffing system is included to verify the validity of the proposed scheme. (author)

  10. ADAPTIVE CONTROL OF FLEXIBLE BEAM WITH UNKNOWN DEAD-ZONE IN THE DRIVING MOTOR

    Wang Xingsong; Hong Henry; Su Chunyi

    2004-01-01

    Adaptive control of a flexible beam system preceded by an unknown dead-zone in the driving motor is investigated in state space form. By introducing an important lemma for simplifying error equation between the flexible beam model and the matching reference model, a robust adaptive control scheme is developed by involving the dead-zone inverse terms. The new adaptive control law ensures global stability of the entire system and achieves desired tracking precision even when the slopes of the dead-zone are not equal. Simulations performed on a typical flexible beam system illustrate and clarify the validity of this approach.

  11. A practical scheme for adaptive aircraft flight control systems

    Athans, M.; Willner, D.

    1974-01-01

    A flight control system design is presented, that can be implemented by analog hardware, to be used to control an aircraft with uncertain parameters. The design is based upon the use of modern control theory. The ideas are illustrated by considering control of STOL longitudinal dynamics.

  12. Decentralized direct adaptive neural network control for a class of interconnected systems

    Zhang Tianping; Mei Jiandong

    2006-01-01

    The problem of direct adaptive neural network control for a class of large-scale systems with unknown function control gains and the high-order interconnections is studied in this paper. Based on the principle of sliding mode control and the approximation capability of multilayer neural networks, a design scheme of decentralized direct adaptive sliding mode controller is proposed. The plant dynamic uncertainty and modeling errors are adaptively compensated by adjusted the weights and sliding mode gains on-line for each subsystem using only local information. According to the Lyapunov method, the closed-loop adaptive control system is proven to be globally stable, with tracking errors converging to a neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed approach.

  13. Improved adaptive input voltage control of a solar array interfacing current mode controlled boost power stage

    Highlights: • Photovoltaic generator dynamic resistance online estimation method is proposed. • Control method allowing to achieve nominal performance at all time is presented. • The method is suitable for any type of photovoltaic system. - Abstract: Nonlinear characteristics of photovoltaic generators were recently shown to significantly influence the dynamics of interfacing power stages. Moreover, since the dynamic resistance of photovoltaic generators is both operating point and environmental variables dependent, the combined dynamics exhibits these dependencies as well, burdening control challenge. Typically, linear time invariant input voltage loop controllers (e.g. Proportional-Integrative-Derivative) are utilized in photovoltaic applications, designed according to nominal operating conditions. Nevertheless, since actual dynamics is seldom nominal, closed loop performance of such systems varies as well. In this paper, adaptive control method is proposed, allowing to estimate photovoltaic generator resistance online and utilize it to modify the controller parameters such that closed loop performance remains nominal throughout the whole operation range. Unlike previously proposed method, utilizing double-grid-frequency component for estimation purposes and suffering from various drawbacks such as operation point dependence and applicability to single-phase grid connected systems only, the proposed method is based on harmonic current injection and is independent on operating point and system topology

  14. Adaptive Motor Control: Neuronal Mechanisms Underlying (Targeted) Searching Movements

    Berg, Eva

    2014-01-01

    Animals move through a complex environment and therefore constantly need to adapt their behavior to the surroundings. For this purpose, they use sensory information of various kind. As one strategy to gain tactile cues, animals perform leg searching movements when loosing foothold. The kinematics of these searching movements have been well investigated in the stick insect. In this thesis, the modification of stick insect searching movements following a tactile cue are explored as an example o...

  15. 3D Printing device adaptable to Computer Numerical Control (CNC)

    Gardan, Julien; DANESI, Frédéric; Roucoules, Lionel; Schneider, A

    2014-01-01

    This article presents the development of a 3D printing device for the additive manufacturing adapted to a CNC machining. The application involves the integration of a specific printing head. Additive manufacturing technology is most commonly used for modeling, prototyping, tooling through an exclusive machine or 3D printer. A global review and analysis of technologies show the additive manufacturing presents little independent solutions [6][9]. The problem studied especially the additive manu...

  16. Uncovering the transcriptional control of "Bartonella henselae" host adaptation factors

    Québatte, Maxime

    2014-01-01

    A recurrent theme in bacterial pathogenicity is the understanding of the regulatory events necessary for a given pathogen to progress through its infection cycle while resisting the host defense mechanisms. This progression typically requires the coordinated expression of defined sub-portions of the virulence repertoire at the same time as others need to be tightly repressed or degraded. This so-called adaptive response is ultimately linked to the ability of the pathogen to sense its direct e...

  17. Process- and controller-adaptations determine the physiological effects of cold acclimation.

    Werner, Jürgen

    2008-09-01

    Experimental results on physiological effects of cold adaptation seem confusing and apparently incompatible with one another. This paper will explain that a substantial part of such a variety of results may be deduced from a common functional concept. A core/shell treatment ("model") of the thermoregulatory system is used with mean body temperature as the controlled variable. Adaptation, as a higher control level, is introduced into the system. Due to persistent stressors, either the (heat transfer) process or the controller properties (parameters) are adjusted (or both). It is convenient to call the one "process adaptation" and the other "controller adaptation". The most commonly demonstrated effect of autonomic cold acclimation is a change in the controller threshold. The analysis shows that this necessarily means a lowering of body temperature because of a lowered metabolic rate. This explains experimental results on both Europeans in the climatic chamber and Australian Aborigines in a natural environment. Exclusive autonomic process adaptation occurs in the form of a better insulation. The analysis explains why the post-adaptive steady-state can only be achieved, if the controller system reduces metabolism and why in spite of this the new state is inevitably characterized by a rise in body temperature. If both process and controller adaptations are simultaneously present, there may be not any change of body temperature at all, e.g., as demonstrated in animal experiments. Whether this kind of adaptation delivers a decrease, an increase or no change of mean body temperature, depends on the proportion of process and controller adaptation. PMID:18026979

  18. Suppressing Halo-chaos for Intense Ion Beamby Neural Network Adaptation Control Strategy

    FANGJin-qing; LUOXiao-shu; WENGJia-qiang; ZHULun-wu

    2003-01-01

    Neural network has some advantages of adaptation, learn-self, self-organization and suitable for high-dimension for various applications in many fields, especially among them the feed-forward back-propagating neural network self-adaptation method is suitable for control of nonlinear systems.

  19. Effectiveness of Adaptive Assessment versus Learner Control in a Multimedia Learning System

    Chen, Ching-Huei; Chang, Shu-Wei

    2015-01-01

    The purpose of this study was to explore the effectiveness of adaptive assessment versus learner control in a multimedia learning system designed to help secondary students learn science. Unlike other systems, this paper presents a workflow of adaptive assessment following instructional materials that better align with learners' cognitive…

  20. Improved Robust Adaptive Control of a Fluidized Bed Combustor for Sewage Sludge

    MENGHong-Xia; JIAYing-Min

    2005-01-01

    This paper presents a robust model reference adaptive control scheme to deal with uncertain time delay in the dynamical model of a fluidized bed combustor for sewage sludge. The theoretical analysis and simulation results show that the proposed scheme can guarantee not only stability and robustness, but also the adaptive decoupling performance of the system.