Optimal control of hybrid vehicles
Jager, Bram; Kessels, John
2013-01-01
Optimal Control of Hybrid Vehicles provides a description of power train control for hybrid vehicles. The background, environmental motivation and control challenges associated with hybrid vehicles are introduced. The text includes mathematical models for all relevant components in the hybrid power train. The power split problem in hybrid power trains is formally described and several numerical solutions detailed, including dynamic programming and a novel solution for state-constrained optimal control problems based on Pontryagin’s maximum principle. Real-time-implementable strategies that can approximate the optimal solution closely are dealt with in depth. Several approaches are discussed and compared, including a state-of-the-art strategy which is adaptive for vehicle conditions like velocity and mass. Two case studies are included in the book: · a control strategy for a micro-hybrid power train; and · experimental results obtained with a real-time strategy implemented in...
Hybrid optimization schemes for quantum control
Energy Technology Data Exchange (ETDEWEB)
Goerz, Michael H.; Koch, Christiane P. [Universitaet Kassel, Theoretische Physik, Kassel (Germany); Whaley, K. Birgitta [University of California, Department of Chemistry, Berkeley, CA (United States)
2015-12-15
Optimal control theory is a powerful tool for solving control problems in quantum mechanics, ranging from the control of chemical reactions to the implementation of gates in a quantum computer. Gradient-based optimization methods are able to find high fidelity controls, but require considerable numerical effort and often yield highly complex solutions. We propose here to employ a two-stage optimization scheme to significantly speed up convergence and achieve simpler controls. The control is initially parametrized using only a few free parameters, such that optimization in this pruned search space can be performed with a simplex method. The result, considered now simply as an arbitrary function on a time grid, is the starting point for further optimization with a gradient-based method that can quickly converge to high fidelities. We illustrate the success of this hybrid technique by optimizing a geometric phase gate for two superconducting transmon qubits coupled with a shared transmission line resonator, showing that a combination of Nelder-Mead simplex and Krotov's method yields considerably better results than either one of the two methods alone. (orig.)
A "Hybrid" Approach for Synthesizing Optimal Controllers of Hybrid Systems
DEFF Research Database (Denmark)
Zhao, Hengjun; Zhan, Naijun; Kapur, Deepak
2012-01-01
We propose an approach to reduce the optimal controller synthesis problem of hybrid systems to quantifier elimination; furthermore, we also show how to combine quantifier elimination with numerical computation in order to make it more scalable but at the same time, keep arising errors due...... to discretization manageable and within bounds. A major advantage of our approach is not only that it avoids errors due to numerical computation, but it also gives a better optimal controller. In order to illustrate our approach, we use the real industrial example of an oil pump provided by the German company HYDAC...
Stochastic Optimal Control for Series Hybrid Electric Vehicles
Energy Technology Data Exchange (ETDEWEB)
Malikopoulos, Andreas [ORNL
2013-01-01
Increasing demand for improving fuel economy and reducing emissions has stimulated significant research and investment in hybrid propulsion systems. In this paper, we address the problem of optimizing online the supervisory control in a series hybrid configuration by modeling its operation as a controlled Markov chain using the average cost criterion. We treat the stochastic optimal control problem as a dual constrained optimization problem. We show that the control policy that yields higher probability distribution to the states with low cost and lower probability distribution to the states with high cost is an optimal control policy, defined as an equilibrium control policy. We demonstrate the effectiveness of the efficiency of the proposed controller in a series hybrid configuration and compare it with a thermostat-type controller.
Study of optimal control problems for hybrid dynamical systems
Institute of Scientific and Technical Information of China (English)
Gao Rui; Wang Lei; Wang Yuzhen
2006-01-01
From the viewpoint of continuous systems, optimal control problem is proposed for a class of controlled Hybrid dynamical systems. Then a mathematical method- HDS minimum principle is put forward, which can solve the above problem. The HDS minimum principle is proved by means of Ekeland's variational principle.
Combined Optimal Sizing and Control for a Hybrid Tracked Vehicle
Directory of Open Access Journals (Sweden)
Huei Peng
2012-11-01
Full Text Available The optimal sizing and control of a hybrid tracked vehicle is presented and solved in this paper. A driving schedule obtained from field tests is used to represent typical tracked vehicle operations. Dynamics of the diesel engine-permanent magnetic AC synchronous generator set, the lithium-ion battery pack, and the power split between them are modeled and validated through experiments. Two coupled optimizations, one for the plant parameters, forming the outer optimization loop and one for the control strategy, forming the inner optimization loop, are used to achieve minimum fuel consumption under the selected driving schedule. The dynamic programming technique is applied to find the optimal controller in the inner loop while the component parameters are optimized iteratively in the outer loop. The results are analyzed, and the relationship between the key parameters is observed to keep the optimal sizing and control simultaneously.
Military Hybrid Vehicle Optimization and Control
2012-08-14
and energy security, as well as reduce overall energy u ’C the concept of a microgrid has been introduced [7 ]. A microgricl is defined as an...vehicle-to-grid (V2G) technology has been show to have the ability to upport the microgrid ru a source, but also a storage device for excess energy [9...understood. The scope of this proposal includes introducing the concept of regarding a military hybrid vehicle as a microgrid and utilizing battery state
Hybrid systems, optimal control and hybrid vehicles theory, methods and applications
Böhme, Thomas J
2017-01-01
This book assembles new methods showing the automotive engineer for the first time how hybrid vehicle configurations can be modeled as systems with discrete and continuous controls. These hybrid systems describe naturally and compactly the networks of embedded systems which use elements such as integrators, hysteresis, state-machines and logical rules to describe the evolution of continuous and discrete dynamics and arise inevitably when modeling hybrid electric vehicles. They can throw light on systems which may otherwise be too complex or recondite. Hybrid Systems, Optimal Control and Hybrid Vehicles shows the reader how to formulate and solve control problems which satisfy multiple objectives which may be arbitrary and complex with contradictory influences on fuel consumption, emissions and drivability. The text introduces industrial engineers, postgraduates and researchers to the theory of hybrid optimal control problems. A series of novel algorithmic developments provides tools for solving engineering pr...
Optimal Control for a Parallel Hybrid Hydraulic Excavator Using Particle Swarm Optimization
Directory of Open Access Journals (Sweden)
Dong-yun Wang
2013-01-01
Full Text Available Optimal control using particle swarm optimization (PSO is put forward in a parallel hybrid hydraulic excavator (PHHE. A power-train mathematical model of PHHE is illustrated along with the analysis of components’ parameters. Then, the optimal control problem is addressed, and PSO algorithm is introduced to deal with this nonlinear optimal problem which contains lots of inequality/equality constraints. Then, the comparisons between the optimal control and rule-based one are made, and the results show that hybrids with the optimal control would increase fuel economy. Although PSO algorithm is off-line optimization, still it would bring performance benchmark for PHHE and also help have a deep insight into hybrid excavators.
Hybrid Quantum-Classical Approach to Quantum Optimal Control.
Li, Jun; Yang, Xiaodong; Peng, Xinhua; Sun, Chang-Pu
2017-04-14
A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal control problem. We show that the most computationally demanding part of gradient-based algorithms, namely, computing the fitness function and its gradient for a control input, can be accomplished by the process of evolution and measurement on a quantum simulator. By posing queries to and receiving answers from the quantum simulator, classical computing devices update the control parameters until an optimal control solution is found. To demonstrate the quantum-classical scheme in experiment, we use a seven-qubit nuclear magnetic resonance system, on which we have succeeded in optimizing state preparation without involving classical computation of the large Hilbert space evolution.
Optimal Control of Engine Warmup in Hybrid Vehicles
Directory of Open Access Journals (Sweden)
van Reeven Vital
2016-01-01
Full Text Available An Internal Combustion Engine (ICE under cold conditions experiences increased friction losses due to a high viscosity of the lubricant. With the additional control freedom present in hybrid electric vehicles, the losses during warmup can be minimized and fuel can be saved. In this paper, firstly, a control-oriented model of the ICE, describing the warmup behavior, is developed and validated on measured vehicle data. Secondly, the two-state, non-autonomous fuel optimization, for a parallel hybrid electric vehicle with stop-start functionality, is solved using optimal control theory. The principal behavior of the Lagrange multipliers is explicitly derived, including the discontinuities (jumps that are caused by the constraints on the lubricant temperature and the energy in the battery system. The minimization of the Hamiltonian for this two-state problem is also explicitly solved, resulting in a computationally efficient algorithm. The optimal controller shows the fuel benefit, as a function of the initial temperature, for a long-haul truck simulated on the FTP-75.
Optimal Control Policies of Pests for Hybrid Dynamical Systems
Directory of Open Access Journals (Sweden)
Baolin Kang
2013-01-01
Full Text Available We improve the traditional integrated pest management (IPM control strategies and formulate three specific management strategies, which can be described by hybrid dynamical systems. These strategies can not only effectively control pests but also reduce the abuse of pesticides and protect the natural enemies. The aim of this work is to study how the factors, such as natural enemies optimum choice in the two kinds of different pests, timings of natural enemy releases, dosages and timings of insecticide applications, and instantaneous killing rates of pesticides on both pests and natural enemies, can affect the success of IPM control programmes. The results indicate that the pests outbreak period or frequency largely depends on the optimal selective feeding of the natural enemy between one of the pests and the control tactics. Ultimately, we obtain the only pest needs to be controlled below a certain threshold while not supervising pest .
Fuel optimal control of parallel hybrid electric vehicles
Institute of Scientific and Technical Information of China (English)
Jinhuan PU; Chenliang YIN; Jianwu ZHANG
2008-01-01
A mathematical model for fuel optimal control and its corresponding dynamic programming (DP) recurs-ive equation were established for an existing parallel hybrid electric vehicle (HEV). Two augmented cost func-tions for gear shifting and engine stop-starting were designed to limit their frequency. To overcome the prob-lem of numerical DP dimensionality, an algorithm to restrict the exploring region was proposed. The algorithm significantly reduced the computational complexity. The system model was converted into real-time simulation code by using MATLAB/RTW to improve computation efficiency. Comparison between the results of a chassis dynamometer test, simulation, and DP proves that the proposed method can compute the performance limita-tion of the HEV within an acceptable time period and can be used to evaluate and optimize the control strategy.
Optimal traffic light control method for a single intersection based on hybrid systems
Institute of Scientific and Technical Information of China (English)
赵晓华; 陈阳舟; 崔平远
2003-01-01
A single intersection of two phases is selected as a model to put forward a new optimal time-planning scheme for traffic light based on the model of hybrid automata for single intersection. A method of optimization is proposed for hybrid systems, and the average queue length over all queues is used as an objective function to find an optimal switching scheme for traffic light. It is illustrated that traffic light control for single intersection is a typical hybrid system, and the optimal planning-time scheme can be obtained using the optimal hybrid systems control based on the two stages method.
Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control
Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.
2015-01-01
The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.
Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning
Englander, Jacob
2015-01-01
Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. Because low-thrust trajectory design is tightly coupled with systems design, power and propulsion characteristics must be chosen as well. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The methods is demonstrated on hypothetical mission to the main asteroid belt and to Deimos.
Keulen, T. van; Mullem, D. van; Jager, B. van; Kessels, J.T.B.A.; Steinbuch, M.
2012-01-01
Hybrid electric vehicles require an algorithm that controls the power split between the internal combustion engine and electric machine(s), and the opening and closing of the clutch. Optimal control theory is applied to derive a methodology for a real-time optimal-control-based power split
Approximate dynamic programming recurrence relations for a hybrid optimal control problem
Lu, W.; Ferrari, S.; Fierro, R.; Wettergren, T. A.
2012-06-01
This paper presents a hybrid approximate dynamic programming (ADP) method for a hybrid dynamic system (HDS) optimal control problem, that occurs in many complex unmanned systems which are implemented via a hybrid architecture, regarding robot modes or the complex environment. The HDS considered in this paper is characterized by a well-known three-layer hybrid framework, which includes a discrete event controller layer, a discrete-continuous interface layer, and a continuous state layer. The hybrid optimal control problem (HOCP) is to nd the optimal discrete event decisions and the optimal continuous controls subject to a deterministic minimization of a scalar function regarding the system state and control over time. Due to the uncertainty of environment and complexity of the HOCP, the cost-to-go cannot be evaluated before the HDS explores the entire system state space; as a result, the optimal control, neither continuous nor discrete, is not available ahead of time. Therefore, ADP is adopted to learn the optimal control while the HDS is exploring the environment, because of the online advantage of ADP method. Furthermore, ADP can break the curses of dimensionality which other optimizing methods, such as dynamic programming (DP) and Markov decision process (MDP), are facing due to the high dimensions of HOCP.
DEFF Research Database (Denmark)
Liu, Chengxi; Qin, Nan; Bak, Claus Leth;
2015-01-01
This paper proposes a hybrid optimization method to optimally control the voltage and reactive power with minimum power loss in transmission grid. This approach is used for the Danish automatic voltage control (AVC) system which is typically a non-linear non-convex problem mixed with both continu...
Optimal planning of LEO active debris removal based on hybrid optimal control theory
Yu, Jing; Chen, Xiao-qian; Chen, Li-hu
2015-06-01
The mission planning of Low Earth Orbit (LEO) active debris removal problem is studied in this paper. Specifically, the Servicing Spacecraft (SSc) and several debris exist on near-circular near-coplanar LEOs. The SSc should repeatedly rendezvous with the debris, and de-orbit them until all debris are removed. Considering the long-duration effect of J2 perturbation, a linear dynamics model is used for each rendezvous. The purpose of this paper is to find the optimal service sequence and rendezvous path with minimum total rendezvous cost (Δv) for the whole mission, and some complex constraints (communication time window constraint, terminal state constraint, and time distribution constraint) should be satisfied meanwhile. Considering this mission as a hybrid optimal control problem, a mathematical model is proposed, as well as the solution method. The proposed approach is demonstrated by a typical active debris removal problem. Numerical experiments show that (1) the model and solution method proposed in this paper can effectively address the planning problem of LEO debris removal; (2) the communication time window constraint and the J2 perturbation have considerable influences on the optimization results; and (3) under the same configuration, some suboptimal sequences are equivalent to the optimal one since their difference in Δv cost is very small.
The Development of an Optimal Control Strategy for a Series Hydraulic Hybrid Vehicle
Directory of Open Access Journals (Sweden)
Chih-Wei Hung
2016-03-01
Full Text Available In this work, a Truck Class II series hydraulic hybrid model is established. Dynamic Programming (DP methodology is applied to derive the optimal power-splitting factor for the hybrid system for preselected driving schedules. Implementable rules are derived by extracting the optimal trajectory features from a DP scheme. The system behaviors illustrate that the improved control strategy gives a highly effective operation region for the engine and high power density characteristics for the hydraulic components.
CONGESTION MANAGEMENT BY OPTIMAL ALLOCATION OF FACTS CONTROLLERS USING HYBRID FISH BEE OPTIMIZATION
Directory of Open Access Journals (Sweden)
S. Thangalakshmi
2014-01-01
Full Text Available The role of Independent System Operator (ISO in the restructured power industry includes system control, capacity planning, transmission tariff and congestion management; the challenging task being minimizing the congestion. One of the popular techniques used to alleviate congestion is using Flexible AC Transmission Systems (FACTS devices. The power system generally operates near its rated capacity in deregulated market because of intensive usage of transmission grids. So, the major issues that need to be addressed are improving the voltage profile and reducing the power loss in the electrical network. Motivation: The location of FACTS devices can improve the power flow in the line, maintain the bus profile and reduce the losses. However locating the ideal location is a NP problem. This study presents a novel heuristic method to determine the types of FACTS devices and its optimal location in a power system without violating the thermal and voltage limits. Power flow sensitivity index to find the optimal location of UPFC is suggested in this study. A hybrid fish bee swarm optimization is proposed which is based on Artificial Bee Colony (ABC and Fish School Search (FSS methods. This proposed algorithm is tested based on IEEE 30 bus system and line performances are studied.
Verma, Harish Kumar; Jain, Cheshta
2016-09-01
In this article, a hybrid algorithm of particle swarm optimization (PSO) with statistical parameter (HSPSO) is proposed. Basic PSO for shifted multimodal problems have low searching precision due to falling into a number of local minima. The proposed approach uses statistical characteristics to update the velocity of the particle to avoid local minima and help particles to search global optimum with improved convergence. The performance of the newly developed algorithm is verified using various standard multimodal, multivariable, shifted hybrid composition benchmark problems. Further, the comparative analysis of HSPSO with variants of PSO is tested to control frequency of hybrid renewable energy system which comprises solar system, wind system, diesel generator, aqua electrolyzer and ultra capacitor. A significant improvement in convergence characteristic of HSPSO algorithm over other variants of PSO is observed in solving benchmark optimization and renewable hybrid system problems.
Directory of Open Access Journals (Sweden)
Ru Wang
2017-01-01
Full Text Available In order to improve the performance of the hydraulic support electro-hydraulic control system test platform, a self-tuning proportion integration differentiation (PID controller is proposed to imitate the actual pressure of the hydraulic support. To avoid the premature convergence and to improve the convergence velocity for tuning PID parameters, the PID controller is optimized with a hybrid optimization algorithm integrated with the particle swarm algorithm (PSO and genetic algorithm (GA. A selection probability and an adaptive cross probability are introduced into the PSO to enhance the diversity of particles. The proportional overflow valve is installed to control the pressure of the pillar cylinder. The data of the control voltage of the proportional relief valve amplifier and pillar pressure are collected to acquire the system transfer function. Several simulations with different methods are performed on the hydraulic cylinder pressure system. The results demonstrate that the hybrid algorithm for a PID controller has comparatively better global search ability and faster convergence velocity on the pressure control of the hydraulic cylinder. Finally, an experiment is conducted to verify the validity of the proposed method.
Hybrid optimization of dynamic deployment for networked fire control system
Institute of Scientific and Technical Information of China (English)
Chen Chen; Jie Chen; Bin Xin
2013-01-01
With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make ful use of limited battle-field resources and maximal y destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Con-sidering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the ene-my target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the ar-tificial potential field (APF) method with a memetic algorithm. The APF method is employed to solve the constraint handling prob-lem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF para-meters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.
A Hybrid Bacterial Foraging - PSO Algorithm Based Tuning of Optimal FOPI Speed Controller
Directory of Open Access Journals (Sweden)
Rajasekhar Anguluri
2011-11-01
Full Text Available Bacterial Foraging Optimization Algorithm (BFOA has recently emerged as a very powerful technique for real parameteroptimization. In order to overcome the delay in optimization and to further enhance the performance of BFO, this paper proposeda new hybrid algorithm combining the features of BFOA and Particle Swarm Optimization (PSO for tuning a Fractional orderspeed controller in a Permanent Magnet Synchronous Motor (PMSM Drive. Computer simulations illustrate the effectiveness of theproposed approach compared to that of basic versions of PSO and BFO.
Stochastic Optimal Control of Parallel Hybrid Electric Vehicles
Directory of Open Access Journals (Sweden)
Feiyan Qin
2017-02-01
Full Text Available Energy management strategies (EMSs in hybrid electric vehicles (HEVs are highly related to the fuel economy and emission performances. However, EMS constitutes a challenging problem due to the complex structure of a HEV and the unknown or partially known driving cycles. To meet this problem, this paper adopts a stochastic dynamic programming (SDP method for the EMS of a specially designed vehicle, a pre-transmission single-shaft torque-coupling parallel HEV. In this parallel HEV, the auto clutch output is connected to the transmission input through an electric motor, which benefits an efficient motor assist operation. In this EMS, demanded torque of driver is modeled as a one-state Markov process to represent the uncertainty of future driving situations. The obtained EMS has been evaluated with ADVISOR2002 over two standard government drive cycles and a self-defined one, and compared with a dynamic programming (DP one and a rule-based one. Simulation results have shown the real-time performance of the proposed approach, and potential vehicle performance improvement relative to the rule-based one.
Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control.
Deshpande, Sunil; Nandola, Naresh N; Rivera, Daniel E; Younger, Jarred W
2014-12-01
The term adaptive intervention is used in behavioral health to describe individually-tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health.
Optimal Design and Hybrid Control for the Electro-Hydraulic Dual-Shaking Table System
Directory of Open Access Journals (Sweden)
Lianpeng Zhang
2016-08-01
Full Text Available This paper is to develop an optimal electro-hydraulic dual-shaking table system with high waveform replication precision. The parameters of hydraulic cylinders, servo valves, hydraulic supply power and gravity balance system are designed and optimized in detail. To improve synchronization and tracking control precision, a hybrid control strategy is proposed. The cross-coupled control using a novel based on sliding mode control based on adaptive reaching law (ASMC, which can adaptively tune the parameters of sliding mode control (SMC, is proposed to reduce the synchronization error. To improve the tracking performance, the observer-based inverse control scheme combining the feed-forward inverse model controller and disturbance observer is proposed. The system model is identified applying the recursive least squares (RLS algorithm and then the feed-forward inverse controller is designed based on zero phase error tracking controller (ZPETC technique. To compensate disturbance and model errors, disturbance observer is used cooperating with the designed inverse controller. The combination of the novel ASMC cross-coupled controller and proposed observer-based inverse controller can improve the control precision noticeably. The dual-shaking table experiment system is built and various experiments are performed. The experimental results indicate that the developed system with the proposed hybrid control strategy is feasible and efficient and can reduce the tracking errors to 25% and synchronization error to 16% compared with traditional control schemes.
Control Strategy Optimization for Parallel Hybrid Electric Vehicles Using a Memetic Algorithm
Directory of Open Access Journals (Sweden)
Yu-Huei Cheng
2017-03-01
Full Text Available Hybrid electric vehicle (HEV control strategy is a management approach for generating, using, and saving energy. Therefore, the optimal control strategy is the sticking point to effectively manage hybrid electric vehicles. In order to realize the optimal control strategy, we use a robust evolutionary computation method called a “memetic algorithm (MA” to optimize the control parameters in parallel HEVs. The “local search” mechanism implemented in the MA greatly enhances its search capabilities. In the implementation of the method, the fitness function combines with the ADvanced VehIcle SimulatOR (ADVISOR and is set up according to an electric assist control strategy (EACS to minimize the fuel consumption (FC and emissions (HC, CO, and NOx of the vehicle engine. At the same time, driving performance requirements are also considered in the method. Four different driving cycles, the new European driving cycle (NEDC, Federal Test Procedure (FTP, Economic Commission for Europe + Extra-Urban driving cycle (ECE + EUDC, and urban dynamometer driving schedule (UDDS are carried out using the proposed method to find their respectively optimal control parameters. The results show that the proposed method effectively helps to reduce fuel consumption and emissions, as well as guarantee vehicle performance.
A Frequency Control Approach for Hybrid Power System Using Multi-Objective Optimization
Directory of Open Access Journals (Sweden)
Mohammed Elsayed Lotfy
2017-01-01
Full Text Available A hybrid power system uses many wind turbine generators (WTG and solar photovoltaics (PV in isolated small areas. However, the output power of these renewable sources is not constant and can diverge quickly, which has a serious effect on system frequency and the continuity of demand supply. In order to solve this problem, this paper presents a new frequency control scheme for a hybrid power system to ensure supplying a high-quality power in isolated areas. The proposed power system consists of a WTG, PV, aqua-electrolyzer (AE, fuel cell (FC, battery energy storage system (BESS, flywheel (FW and diesel engine generator (DEG. Furthermore, plug-in hybrid electric vehicles (EVs are implemented at the customer side. A full-order observer is utilized to estimate the supply error. Then, the estimated supply error is considered in a frequency domain. The high-frequency component is reduced by BESS and FW; while the low-frequency component of supply error is mitigated using FC, EV and DEG. Two PI controllers are implemented in the proposed system to control the system frequency and reduce the supply error. The epsilon multi-objective genetic algorithm ( ε -MOGA is applied to optimize the controllers’ parameters. The performance of the proposed control scheme is compared with that of recent well-established techniques, such as a PID controller tuned by the quasi-oppositional harmony search algorithm (QOHSA. The effectiveness and robustness of the hybrid power system are investigated under various operating conditions.
Optimal control on hybrid ode systems with application to a tick disease model.
Ding, Wandi
2007-10-01
We are considering an optimal control problem for a type of hybrid system involving ordinary differential equations and a discrete time feature. One state variable has dynamics in only one season of the year and has a jump condition to obtain the initial condition for that corresponding season in the next year. The other state variable has continuous dynamics. Given a general objective functional, existence, necessary conditions and uniqueness for an optimal control are established. We apply our approach to a tick-transmitted disease model with age structure in which the tick dynamics changes seasonally while hosts have continuous dynamics. The goal is to maximize disease-free ticks and minimize infected ticks through an optimal control strategy of treatment with acaricide. Numerical examples are given to illustrate the results.
A novel hybrid optimization algorithm for diferential-algebraic control problems
Directory of Open Access Journals (Sweden)
F. S. Lobato
2007-09-01
Full Text Available Dynamic optimization problems can be numerically solved by direct, indirect and Hamilton-Jacobi-Bellman methods. In this paper, the differential-algebraic approach is incorporated into a hybrid method, extending the concepts of structural and differential indexes, consistent initialization analysis, index reduction and dynamic degrees of freedom to the optimal control problem. The resultant differential-algebraic optimal control problem is solved in the following steps: transformation of the original problem into a standard nonlinear programming problem that provides control and state variables, switching time estimates and costate variables profiles with the DIRCOL code; definition of the switching function and the automatically generated sequence of index-1 differential-algebraic boundary value problems from Pontryagin’s minimum principle by using the developed Otima code; and finally, application of the COLDAE code with the results of the direct method as an initial guess. The proposed hybrid method is illustrated with a pressure-constrained batch reactor optimization problem associated with the slack variable method.
Chong, Lee Wai; Wong, Yee Wan; Rajkumar, Rajprasad Kumar; Isa, Dino
2016-11-01
This paper proposes an optimal control strategy for a standalone PV system with Battery-Supercapacitor Hybrid Energy Storage System to prolong battery lifespan by reducing the dynamic stress and peak current demand of the battery. Unlike the conventional methods which only use either filtration based controller (FBC) or fuzzy logic controller (FLC), the proposed control strategy comprises of a low-pass filter (LPF) and FLC. Firstly, LPF removes the high dynamic components from the battery demand. FLC minimizes the battery peak current demand while constantly considering the state-of-charge of the supercapacitor. Particle swarm optimization (PSO) algorithm optimizes the membership functions of the FLC to achieve optimal battery peak current reduction. The proposed system is compared to the conventional system with battery-only storage and the systems with conventional control strategies (Rule Based Controller and FBC). The proposed system reduces the battery peak current, battery peak power, maximum absolute value of the rate of change of power and average absolute value of the rate of change of power by 16.05%, 15.19%, 77.01%, and 95.59%, respectively as compared to the conventional system with battery-only storage. Moreover, he proposed system increases the level of supercapacitor utilization up to 687.122% in comparison to the conventional control strategies.
Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle
Directory of Open Access Journals (Sweden)
Linhui Li
2014-01-01
Full Text Available Energy management control strategy of hybrid electric vehicle has a great influence on the vehicle fuel consumption with electric motors adding to the traditional vehicle power system. As vehicle real driving cycles seem to be uncertain, the dynamic driving cycles will have an impact on control strategy’s energy-saving effect. In order to better adapt the dynamic driving cycles, control strategy should have the ability to recognize the real-time driving cycle and adaptively adjust to the corresponding off-line optimal control parameters. In this paper, four types of representative driving cycles are constructed based on the actual vehicle operating data, and a fuzzy driving cycle recognition algorithm is proposed for online recognizing the type of actual driving cycle. Then, based on the equivalent fuel consumption minimization strategy, an ant colony optimization algorithm is utilized to search the optimal control parameters “charge and discharge equivalent factors” for each type of representative driving cycle. At last, the simulation experiments are conducted to verify the accuracy of the proposed fuzzy recognition algorithm and the validity of the designed control strategy optimization method.
Directory of Open Access Journals (Sweden)
Xiangyong Chen
2014-01-01
hybrid dynamic systems is established based on Lanchester equation in a (n,1 battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation, and discrete event systems (described by variable tactics. Furthermore, an expository discussion is presented on an optimal variable tactics control problem for warfare hybrid dynamic system. The optimal control strategies are designed based on dynamic programming and differential game theory. As an example of the consequences of this optimal control problem, we take the (2, 1 case and solve the optimal strategies in a (2, 1 case. Simulation results show the feasibility of warfare hybrid system model and the effectiveness of the optimal control strategies designed.
Dynamic Modeling and Control Strategy Optimization for a Hybrid Electric Tracked Vehicle
Directory of Open Access Journals (Sweden)
Hong Wang
2015-01-01
Full Text Available A new hybrid electric tracked bulldozer composed of an engine generator, two driving motors, and an ultracapacitor is put forward, which can provide high efficiencies and less fuel consumption comparing with traditional ones. This paper first presents the terramechanics of this hybrid electric tracked bulldozer. The driving dynamics for this tracked bulldozer is then analyzed. After that, based on analyzing the working characteristics of the engine, generator, and driving motors, the power train system model and control strategy optimization is established by using MATLAB/Simulink and OPTIMUS software. Simulation is performed under a representative working condition, and the results demonstrate that fuel economy of the HETV can be significantly improved.
Institute of Scientific and Technical Information of China (English)
GU Yanchun; YIN Chengliang; ZHANG Jianwu
2007-01-01
In parallel hybrid electrical vehicle (PHEV) equipped with automatic mechanical transmission (AMT), the driving smoothness and the clutch abrasion are the primary considerations for powertrain control during gearshift and clutch operation. To improve these performance indexes of PHEV, a coordinated control system is proposed through the analyzing of HEV powertrain dynamic characteristics. Using the method of minimum principle, the input torque of transmission is optimized to improve the driving sinoothness of vehicle. Using the methods of fuzzy logic and fuzzy-PID, the engaging speed of clutch and the throttle opening of engine are manipulated to ensure the smoothness of clutch engagement and reduce the abrasion of clutch friction plates. The motor provides the difference between the required input torque of transmission and the torque transmitted through clutch plates. Results of simulation and experiments show that the proposed control strategy performs better than the contrastive control system, the smoothness of driving and the abrasion of clutch can be improved simultaneously.
Kanno, Masaaki; Hara, Shinji
2012-01-01
This paper proposes a plant/controller design integration method for H_∞ loop-shaping design based on symbolic-numeric hybrid optimization. This approach firstly employs parametric polynomial spectral factorization to accomplish parametric optimization and derive an expression for the optimal cost. Owing to the obtained expression, sensitivity analysis of the achievable performance level with respect to plant parameters is amenable, which allows numerical optimization methods to seek the opti...
Multi-Objective Hybrid Optimal Control for Multiple-Flyby Low-Thrust Mission Design
Englander, Jacob A.; Vavrina, Matthew A.; Ghosh, Alexander R.
2015-01-01
Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. In addition, a time-history of control variables must be chosen that defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on a hypothetical mission to the main asteroid belt.
Dynamic simulation and optimal control strategy for a parallel hybrid hydraulic excavator
Institute of Scientific and Technical Information of China (English)
Xiao LIN; Shuang-xia PAN; Dong-yun WANG
2008-01-01
The primary focus of this study is to investigate the control strategies of a hybrid system used in hydraulic excavators. First, the structure and evaluation target of hybrid hydraulic excavators are analyzed. Then the dynamic system model including batteries, motor and engine is built as the simulation environment to obtain control results. A so-called multi-work-point dynamic control strategy, which has both closed-loop speed PI (proportion integral) control and direct torque control, is proposed and studied in the simulation model. Simulation results indicate that the hybrid system with this strategy can meet the power demand and achieve better system stability and higher fuel efficiency.
Hybrid Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2012-01-01
Bayesian Optimization aims at optimizing an unknown non-convex/concave function that is costly to evaluate. We are interested in application scenarios where concurrent function evaluations are possible. Under such a setting, BO could choose to either sequentially evaluate the function, one input at a time and wait for the output of the function before making the next selection, or evaluate the function at a batch of multiple inputs at once. These two different settings are commonly referred to as the sequential and batch settings of Bayesian Optimization. In general, the sequential setting leads to better optimization performance as each function evaluation is selected with more information, whereas the batch setting has an advantage in terms of the total experimental time (the number of iterations). In this work, our goal is to combine the strength of both settings. Specifically, we systematically analyze Bayesian optimization using Gaussian process as the posterior estimator and provide a hybrid algorithm t...
Optimal control of a repowered vehicle: Plug-in fuel cell against plug-in hybrid electric powertrain
Energy Technology Data Exchange (ETDEWEB)
Tribioli, L., E-mail: laura.tribioli@unicusano.it; Cozzolino, R. [Dept. of Industrial Engineering, University of Rome Niccolo’ Cusano (Italy); Barbieri, M. [Engineering Dept., University of Naples Parthenope, Centro Direzionale-Isola C4, 80143 Naples (Italy)
2015-03-10
This paper describes two different powertrain configurations for the repowering of a conventional vehicle, equipped with an internal combustion engine (ICE). A model of a mid-sized ICE-vehicle is realized and then modified to model both a parallel plug-in hybrid electric powertrain and a proton electrolyte membrane (PEM) fuel cell (FC) hybrid powertrain. The vehicle behavior under the application of an optimal control algorithm for the energy management is analyzed for the different scenarios and results are compared.
Directory of Open Access Journals (Sweden)
Benxian Xiao
2014-01-01
Full Text Available Implicit Generalized Predictive Control (IGPC algorithm can directly identify controller parameters without the need of solving Diophantine equation, thus can reduce the on-line algorithm computation time. In order to improve IGPC performance and extend its application, modified Particle Swarm Optimization (PSO algorithm is introduced into IGPC rolling horizon optimization, combined with general IGPC gradient optimization method under unconstrained condition, a new hybrid optimization method is obtained, this modified IGPC can be used to both of the non-constraint industry process control and the constraint industry process control. Aiming at the superheated steam temperature control of sub-critical 600MW boiler, a new cascade compound control strategy that combines an outer loop IGPC master adjuster and an inner loop PID auxiliary adjuster is adopted. Finally the simulation results have shown that the proposed method can constrain the control action, prevent dramatic change of the input signal, thus can achieve good static and dynamic performances.
DEFF Research Database (Denmark)
Chen, Shuheng; Hu, Weihao; Su, Chi
2015-01-01
A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid PSO (FAHPSO) is proposed. The objective is to minimize comprehensive cost, consisting of power loss and operation cost of transformers...... and capacitors, and subject to constraints such as minimum and maximum reactive power limits of distributed generators, maximum deviation of bus voltages, maximum allowable daily switching operation number (MADSON). Particle swarm optimization (PSO) is used to solve the corresponding mixed integer non......-linear programming problem (MINLP) and the hybrid PSO method (HPSO), consisting of three PSO variants, is presented. In order to mitigate the local convergence problem, fuzzy adaptive inference is used to improve the searching process and the final fuzzy adaptive inference based hybrid PSO is proposed. The proposed...
Das, Saptarshi; Pan, Indranil; Das, Shantanu
2013-07-01
Fuzzy logic based PID controllers have been studied in this paper, considering several combinations of hybrid controllers by grouping the proportional, integral and derivative actions with fuzzy inferencing in different forms. Fractional order (FO) rate of error signal and FO integral of control signal have been used in the design of a family of decomposed hybrid FO fuzzy PID controllers. The input and output scaling factors (SF) along with the integro-differential operators are tuned with real coded genetic algorithm (GA) to produce optimum closed loop performance by simultaneous consideration of the control loop error index and the control signal. Three different classes of fractional order oscillatory processes with various levels of relative dominance between time constant and time delay have been used to test the comparative merits of the proposed family of hybrid fractional order fuzzy PID controllers. Performance comparison of the different FO fuzzy PID controller structures has been done in terms of optimal set-point tracking, load disturbance rejection and minimal variation of manipulated variable or smaller actuator requirement etc. In addition, multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used to study the Pareto optimal trade-offs between the set point tracking and control signal, and the set point tracking and load disturbance performance for each of the controller structure to handle the three different types of processes. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
L. I. Rozonoer
1999-01-01
Full Text Available Necessary and sufficient conditions for existence of optimal control for all initial data are proved for LQ-optimization problem. If these conditions are fulfilled, necessary and sufficient conditions of optimality are formulated. Basing on the results, some general hypotheses on optimal control in terms of Pontryagin's maximum condition and Bellman's equation are proposed.
Powertrain Controls Optimization for HD Hybrid Line Haul Trucks - FY2014 Annual Report
Energy Technology Data Exchange (ETDEWEB)
Smith, David E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2014-12-01
This is a vehicle system level project, encompassing analytical modeling and supervisory controls development as well as experimental verification/validation testing at the component, powertrain, and full vehicle system level. This project supports the goal of petroleum consumption reduction for medium and heavy trucks through the development of advanced hybrid technologies and control systems. VSST has invested previously in R&D to support hybrid energy storage systems (Li-ion plus ultra-caps) for light duty, passenger car applications. This research will be extended to the MD and HD sector where current battery technology is not mature enough to handle the substantial regenerative braking power levels these trucks are capable of producing. With this hybrid energy storage system, substantial gains in overall vehicle efficiency are possible. In addition, advanced combustion technologies, such as RCCI, will be implemented into an advanced hybrid powertrain for a Class 8 line haul application. This powertrain, leveraged from other VSST work (Meritor, a current ORNL/VSST partner), is ideal for taking advantage of the benefits of RCCI operation due to its series hybrid mode of operation. Emissions control is also a focus of this project, especially due to the fact that RCCI creates a low temperature exhaust stream that must addressed.
Directory of Open Access Journals (Sweden)
DAHIYA, P.
2015-05-01
Full Text Available This paper presents the application of hybrid opposition based disruption operator in gravitational search algorithm (DOGSA to solve automatic generation control (AGC problem of four area hydro-thermal-gas interconnected power system. The proposed DOGSA approach combines the advantages of opposition based learning which enhances the speed of convergence and disruption operator which has the ability to further explore and exploit the search space of standard gravitational search algorithm (GSA. The addition of these two concepts to GSA increases its flexibility for solving the complex optimization problems. This paper addresses the design and performance analysis of DOGSA based proportional integral derivative (PID and fractional order proportional integral derivative (FOPID controllers for automatic generation control problem. The proposed approaches are demonstrated by comparing the results with the standard GSA, opposition learning based GSA (OGSA and disruption based GSA (DGSA. The sensitivity analysis is also carried out to study the robustness of DOGSA tuned controllers in order to accommodate variations in operating load conditions, tie-line synchronizing coefficient, time constants of governor and turbine. Further, the approaches are extended to a more realistic power system model by considering the physical constraints such as thermal turbine generation rate constraint, speed governor dead band and time delay.
Optimization and Optimal Control
Chinchuluun, Altannar; Enkhbat, Rentsen; Tseveendorj, Ider
2010-01-01
During the last four decades there has been a remarkable development in optimization and optimal control. Due to its wide variety of applications, many scientists and researchers have paid attention to fields of optimization and optimal control. A huge number of new theoretical, algorithmic, and computational results have been observed in the last few years. This book gives the latest advances, and due to the rapid development of these fields, there are no other recent publications on the same topics. Key features: Provides a collection of selected contributions giving a state-of-the-art accou
On a Variational Approach to Optimization of Hybrid Mechanical Systems
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Vadim Azhmyakov
2010-01-01
Full Text Available This paper deals with multiobjective optimization techniques for a class of hybrid optimal control problems in mechanical systems. We deal with general nonlinear hybrid control systems described by boundary-value problems associated with hybrid-type Euler-Lagrange or Hamilton equations. The variational structure of the corresponding solutions makes it possible to reduce the original “mechanical” problem to an auxiliary multiobjective programming reformulation. This approach motivates possible applications of theoretical and computational results from multiobjective optimization related to the original dynamical optimization problem. We consider first order optimality conditions for optimal control problems governed by hybrid mechanical systems and also discuss some conceptual algorithms.
Directory of Open Access Journals (Sweden)
Minseok Song
2014-05-01
Full Text Available An optimal line pressure control algorithm was proposed for the fuel economy improvement of an AT-based parallel hybrid electric vehicle (HEV. By performing lever analysis at each gear step, the required line pressure was obtained considering the torque ratio of the friction elements. In addition, the required line pressure of the mode clutch was calculated. Based on these results, the optimal line pressure map at each gear step of the EV and HEV modes was presented. Using the line pressure map, an optimal line pressure was performed for the AT input torque and mode. To investigate the proposed line pressure control algorithm, a HEV performance simulator was developed based on the powertrain model of the target HEV, and fuel economy improvement was evaluated. Simulation results showed that as the gear step became higher, the optimal line pressure control could reduce the hydraulic power loss, which gave a 2.2% fuel economy improvement compared to the existing line pressure control for the FTP-72 mode.
Chakrabortty, S; Sen, M; Pal, P
2014-03-01
A simulation software (ARRPA) has been developed in Microsoft Visual Basic platform for optimization and control of a novel membrane-integrated arsenic separation plant in the backdrop of absence of such software. The user-friendly, menu-driven software is based on a dynamic linearized mathematical model, developed for the hybrid treatment scheme. The model captures the chemical kinetics in the pre-treating chemical reactor and the separation and transport phenomena involved in nanofiltration. The software has been validated through extensive experimental investigations. The agreement between the outputs from computer simulation program and the experimental findings are excellent and consistent under varying operating conditions reflecting high degree of accuracy and reliability of the software. High values of the overall correlation coefficient (R (2) = 0.989) and Willmott d-index (0.989) are indicators of the capability of the software in analyzing performance of the plant. The software permits pre-analysis, manipulation of input data, helps in optimization and exhibits performance of an integrated plant visually on a graphical platform. Performance analysis of the whole system as well as the individual units is possible using the tool. The software first of its kind in its domain and in the well-known Microsoft Excel environment is likely to be very useful in successful design, optimization and operation of an advanced hybrid treatment plant for removal of arsenic from contaminated groundwater.
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Aiyun Gao
2017-01-01
Full Text Available A real-time optimal control of parallel hybrid electric vehicles (PHEVs with the equivalent consumption minimization strategy (ECMS is presented in this paper, whose purpose is to achieve the total equivalent fuel consumption minimization and to maintain the battery state of charge (SOC within its operation range at all times simultaneously. Vehicle and assembly models of PHEVs are established, which provide the foundation for the following calculations. The ECMS is described in detail, in which an instantaneous cost function including the fuel energy and the electrical energy is proposed, whose emphasis is the computation of the equivalent factor. The real-time optimal control strategy is designed through regarding the minimum of the total equivalent fuel consumption as the control objective and the torque split factor as the control variable. The validation of the control strategy proposed is demonstrated both in the MATLAB/Simulink/Advisor environment and under actual transportation conditions by comparing the fuel economy, the charge sustainability, and parts performance with other three control strategies under different driving cycles including standard, actual, and real-time road conditions. Through numerical simulations and real vehicle tests, the accuracy of the approach used for the evaluation of the equivalent factor is confirmed, and the potential of the proposed control strategy in terms of fuel economy and keeping the deviations of SOC at a low level is illustrated.
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Zhenzhen Lei
2017-01-01
Full Text Available The driving pattern has an important influence on the parameter optimization of the energy management strategy (EMS for hybrid electric vehicles (HEVs. A new algorithm using simulated annealing particle swarm optimization (SA-PSO is proposed for parameter optimization of both the power system and control strategy of HEVs based on multiple driving cycles in order to realize the minimum fuel consumption without impairing the dynamic performance. Furthermore, taking the unknown of the actual driving cycle into consideration, an optimization method of the dynamic EMS based on driving pattern recognition is proposed in this paper. The simulation verifications for the optimized EMS based on multiple driving cycles and driving pattern recognition are carried out using Matlab/Simulink platform. The results show that compared with the original EMS, the former strategy reduces the fuel consumption by 4.36% and the latter one reduces the fuel consumption by 11.68%. A road test on the prototype vehicle is conducted and the effectiveness of the proposed EMS is validated by the test data.
Optimal control of a fuel cell/wind/PV/grid hybrid system with thermal heat pump load
CSIR Research Space (South Africa)
Sichilalu, S
2016-10-01
Full Text Available This paper presents an optimal energy management strategy for a grid-tied photovoltaic–wind-fuel cell hybrid power supply system. The hybrid system meets the load demand consisting of an electrical load and a heat pump water heater supplying thermal...
Hybrid undulator numerical optimization
Energy Technology Data Exchange (ETDEWEB)
Hairetdinov, A.H. [Kurchatov Institute, Moscow (Russian Federation); Zukov, A.A. [Solid State Physics Institute, Chernogolovka (Russian Federation)
1995-12-31
3D properties of the hybrid undulator scheme arc studied numerically using PANDIRA code. It is shown that there exist two well defined sets of undulator parameters which provide either maximum on-axis field amplitude or minimal higher harmonics amplitude of the basic undulator field. Thus the alternative between higher field amplitude or pure sinusoidal field exists. The behavior of the undulator field amplitude and harmonics structure for a large set of (undulator gap)/(undulator wavelength) values is demonstrated.
Optimal vehicle control strategy of a fuel cell/battery hybrid city bus
Energy Technology Data Exchange (ETDEWEB)
Xu, Liangfei; Li, Jianqiu; Hua, Jianfeng; Li, Xiangjun; Ouyang, Minggao [State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084 (China)
2009-09-15
In this article, an optimal vehicle control strategy based on a time-triggered controller area network (TTCAN) system for a polymer electrolyte membrane (PEM) fuel cell/nickel-metal hydride (Ni-MH) battery powered city bus is presented. Aiming at improving the fuel economy of the city bus, the control strategy comprises an equivalent consumption minimization strategy (ECMS) and a braking energy regeneration strategy (BERS). On the basis of the introduction of a battery equivalent hydrogen consumption model incorporating a charge-sustaining coefficient, an analytical solution to the equivalent consumption minimization problem is given. The proposed strategy has been applied in several city buses for the Beijing Olympic Games of 2008. Results of the ''China city bus typical cycle'' testing show that, the ECMS and the BERS lowered hydrogen consumption by 2.5% and 15.3% respectively, compared with a rule-based strategy. The BERS contributes much more than the ECMS to the fuel economy, because the fuel cell system does not leave much room for the optimal algorithm in improving the efficiency. (author)
Aschepkov, Leonid T; Kim, Taekyun; Agarwal, Ravi P
2016-01-01
This book is based on lectures from a one-year course at the Far Eastern Federal University (Vladivostok, Russia) as well as on workshops on optimal control offered to students at various mathematical departments at the university level. The main themes of the theory of linear and nonlinear systems are considered, including the basic problem of establishing the necessary and sufficient conditions of optimal processes. In the first part of the course, the theory of linear control systems is constructed on the basis of the separation theorem and the concept of a reachability set. The authors prove the closure of a reachability set in the class of piecewise continuous controls, and the problems of controllability, observability, identification, performance and terminal control are also considered. The second part of the course is devoted to nonlinear control systems. Using the method of variations and the Lagrange multipliers rule of nonlinear problems, the authors prove the Pontryagin maximum principle for prob...
Directory of Open Access Journals (Sweden)
Yong Li
2012-05-01
Full Text Available Wind power parallel operation is an effective way to realize the large scale use of wind power, but the fluctuations of power output from wind power units may have great influence on power quality, hence a new method of power smoothing and capacity optimized allocation based on hybrid energy storage technology is proposed in terms of the uncontrollable and unexpected characteristics of wind speed in wind farms. First, power smoothing based on a traditional Inertial Filter is introduced and the relationship between the time constant, its smoothing effect and capacity allocation are analyzed and combined with Proportional Integral Differential (PID control to realize power smoothing control of wind power. Then wavelet theory is adopted to realize a multi-layer decomposition of power output in some wind farms, a power smoothing model based on hybrid energy storage technology is constructed combining the characteristics of the Super Capacitor (SC and Battery Energy Storage System (BESS technologies. The hybrid energy storage system is available for power fluctuations with high frequency-low energy and low frequency-high energy to achieve good smoothing effects compared with a single energy storage system. The power fluctuations filtered by the Wavelet Transform is regarded as the target value of BESS, the charging and discharging control for battery is completed quickly by Model Algorithm Control (MAC. Because of the influence of the inertia and the response speed of the battery, its actual output is not completely equal to the target value which mainly reflects in high-frequency part, the difference part uses SC to compensate and makes the output of battery and SC closer to the target value on the whole. Compared with the traditional Inertial Filter and PID control method, the validity of the model was verified by simulation results. Finally under the premise of power grid standards, the corresponding capacity design had been given to reduce the
Optimizing Hybrid Spreading in Metapopulations
Zhang, Changwang; Cox, Ingemar J; Chain, Benjamin M
2014-01-01
Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by \\textit{local spreading}, where infected nodes can only infect a limited set of direct target nodes and \\textit{global spreading}, where an infected node can infect every other node. In reality, many epidemics spread using a hybrid mixture of both types of spreading. In this study we develop a theoretical framework for studying hybrid epidemics, and examine the optimum balance between spreading mechanisms in terms of achieving the maximum outbreak size. In a metapopulation, made up of many weakly connected subpopulations, we show that one can calculate an optimal tradeoff between local and global spreading which will maximise the extent of the epidemic. As an example we analyse the 2008 outbreak of the Internet worm Conficker, which uses hybrid spreading to propagate through the internet. Our results suggests that the worm would have been eve...
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V Soni
2016-04-01
Full Text Available The combination of Grey Wolf Optimization and Pattern Search Technique (hGWO-PS has been introduced to optimize the parameters of two Degree of Freedom Proportional-Integral-Derivative Controller (2DOF-PID for controlling the load frequency in Automatic Generation Control (AGC for interconnected power system. The interconnected two area power system of non-reheat thermal power plants consisting of 2DOF-PID controller in each area has been considered for design and analysis. Firstly, the proposed approach has been implemented in the aforementioned standard test system and thereafter, the robustness of the system consisting 2DOF-PID controller optimized by proposed technique has been estimated using the sensitivity analysis for the same. The robustness of the system consisting of 2DOF-PID controller optimized by proposed scheme is examined by varying the parameters of standard test system, loading conditions during operation, size and location of the disturbances. The performance of the 2DOF-PID controller optimized by proposed approach has also been compared with recently published approaches in the literature. The simulation results show that the proposed hGWOPS optimized 2DOF-PID controller shows far better performance than recently published approaches in the literature in terms of dynamic response. The simulation results also show that system performances hardly change when the operating load condition and system parameters are changed by ±50% from their nominal values, i.e. the proposed controllers are quite robust for a wide range of the system parameters and operating load conditions from their nominal values.
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V. Dvadnenko
2016-06-01
Full Text Available The hybrid vehicle control system includes a start–stop system for an internal combustion engine. The system works in a hybrid mode and normal vehicle operation. To simplify the start–stop system, there were user new possibilities of a hybrid car, which appeared after the conversion. Results of the circuit design of the proposed system of basic blocks are analyzed.
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Ali Reza Pakkhesal
2015-03-01
Full Text Available Despite the high potential of distributed and renewable sources, their operation may cause problems because of their variability. Moreover, wind fluctuations or extreme weather changes may lead to temporary voltage fluctuations. Researches show that the energy storage can compensate this random nature effect and also it can be effective in a short duration, without requiring the load cut-off. Furthermore, utilizing the energy storing instruments provides more suitable conditions to use produced power and it can be considered as an economic solution. Therefore, in this paper a Smart Energy Management System has been designed in order to optimize the operation of a sample system, production planning, and energy storage. This study suggests the optimized method which can determine the optimized point depending on different goals and their relative effective coefficients. In this method, the usage time and the amount of usage of different energy sources have been determined so that the lowest cost and minimum environmental pollution has been achieved based on Pareto optimization. Eventually, in order to validate the proposed algorithm, this method has been implemented on an electrical propulsion sample system by MATLAB & GAMS software and related results are discussed.
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Hamid Tikani
2016-11-01
Full Text Available In this paper, we study the problem of integrated capacitated hub location problem and seat inventory control considering concept and techniques of revenue management. We consider an airline company maximizes its revenue by utilizing the best network topology and providing proper booking limits for all itineraries and fare classes. The transportation system arises in the form of a star/star network and includes both hub-stop and non-stop flights. This problem is formulated as a two-stage stochastic integer program with mixed-integer recourse. We solve various instances carried out from the Turkish network data set. Due to the NP-hardness of the problem, we propose a hybrid optimization method, consisting of an evolutionary algorithm based on genetic algorithm and exact solution. The quality of the solutions found by the proposed meta-heuristic is compared with the original version of GA and the mathematical programming model. The results obtained by the proposed model imply that integrating hub location and seat inventory control problem would help to increase the total revenue of airline companies. Also, in the case of serving non-stop flights, the model can provide more profit by employing less number of hubs.
Segmented Hybrid Gasostatic Bearing Optimization
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Prodan Nikolay Vasilevich
2014-07-01
Full Text Available The purpose of research-development of methods of numerical optimization rotatable support pads gasostatic hybrid bearing. In the world‘s aerospace engineering the gas-dynamic bearings are currently most common. They are characterized by the supporting layer of different designs, which ensures the workability of the rotors during starts and stops. The main problem of this bearing type, apart from the construction complexity is the wear of this supporting layer. Gas-static bearing has no such defect, since there is no physical contact between solid surfaces. This study presents the results of the hybrid bearing’s calculation, combining both technologies. The slotted nozzle of non-conventional shape that mirrors the solution of Reynolds equation’s isoline is studied. The dependences of the main parameters on the speed of the shaft’s rotation are discussed. The aerodynamic resistance of pads for different regimes of operation is investigated.
Nguyen, Gia Luong Huu
obtained experimental data, the research studied the control of airflow to regulate the temperature of reactors within the fuel processor. The dynamic model provided a platform to test the dynamic response for different control gains. With sufficient sensing and appropriate control, a rapid response to maintain the temperature of the reactor despite an increase in power was possible. The third part of the research studied the use of a fuel cell in conjunction with photovoltaic panels, and energy storage to provide electricity for buildings. This research developed an optimization framework to determine the size of each device in the hybrid energy system to satisfy the electrical demands of buildings and yield the lowest cost. The advantage of having the fuel cell with photovoltaic and energy storage was the ability to operate the fuel cell at baseload at night, thus reducing the need for large battery systems to shift the solar power produced in the day to the night. In addition, the dispatchability of the fuel cell provided an extra degree of freedom necessary for unforeseen disturbances. An operation framework based on model predictive control showed that the method is suitable for optimizing the dispatch of the hybrid energy system.
Hybrid Systems: Computation and Control.
2007-11-02
elbow) and a pinned first joint (shoul- der) (see Figure 2); it is termed an underactuated system since it is a mechanical system with fewer...Montreal, PQ, Canada, 1998. [10] M. W. Spong. Partial feedback linearization of underactuated mechanical systems . In Proceedings, IROS, pages 314-321...control mechanism and search for optimal combinations of control variables. Besides the nonlinear and hybrid nature of powertrain systems , hardware
HYBRID ALARM SYSTEMS: COMBINING SPATIAL ALARMS AND ALARM LISTS FOR OPTIMIZED CONTROL ROOM OPERATION
Energy Technology Data Exchange (ETDEWEB)
Ronald L. Boring; J.J. Persensky
2012-07-01
The US Department of Energy (DOE) is sponsoring research, development, and deployment on Light Water Reactor Sustainability (LWRS), in which the Idaho National Laboratory (INL) is working closely with nuclear utilities to develop technologies and solutions to help ensure the safe operational life extension of current nuclear power plants. One of the main areas of focus is control room modernization. Within control room modernization, alarm system upgrades present opportunities to meet the broader goals of the LWRS project in demonstrating the use and safety of the advanced instrumentation and control (I&C) technologies and the short-term and longer term objectives of the plant. In this paper, we review approaches for and human factors issues behind upgrading alarms in the main control room of nuclear power plants.
Zervas, P. L.; Sarimveis, H.; Palyvos, J. A.; Markatos, N. C. G.
Hybrid renewable energy systems are expected to become competitive to conventional power generation systems in the near future and, thus, optimization of their operation is of particular interest. In this work, a hybrid power generation system is studied consisting of the following main components: photovoltaic array (PV), electrolyser, metal hydride tanks, and proton exchange membrane fuel cells (PEMFC). The key advantage of the hybrid system compared to stand-alone photovoltaic systems is that it can store efficiently solar energy by transforming it to hydrogen, which is the fuel supplied to the fuel cell. However, decision making regarding the operation of this system is a rather complicated task. A complete framework is proposed for managing such systems that is based on a rolling time horizon philosophy.
IMPULSE CONTROL HYBRID ELECTRICAL SYSTEM
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A. A. Lobaty
2016-01-01
Full Text Available This paper extends the recently introduced approach for modeling and solving the optimal control problem of fixedswitched mode DC-DC power converter. DCDC converters are a class of electric power circuits that used extensively in regulated DC power supplies, DC motor drives of different types, in Photovoltaic Station energy conversion and other applications due to its advantageous features in terms of size, weight and reliable performance. The main problem in controlling this type converters is in their hybrid nature as the switched circuit topology entails different modes of operation, each of it with its own associated linear continuous-time dynamics.This paper analyses the modeling and controller synthesis of the fixed-frequency buck DC-DC converter, in which the transistor switch is operated by a pulse sequence with constant frequency. In this case the regulation of the DC component of the output voltage is via the duty cycle. The optimization of the control system is based on the formation of the control signal at the output.It is proposed to solve the problem of optimal control of a hybrid system based on the formation of the control signal at the output of the controller, which minimizes a given functional integral quality, which is regarded as a linear quadratic Letov-Kalman functional. Search method of optimal control depends on the type of mathematical model of control object. In this case, we consider a linear deterministic model of the control system, which is common for the majority of hybrid electrical systems. For this formulation of the optimal control problem of search is a problem of analytical design of optimal controller, which has the analytical solution.As an example of the hybrid system is considered a step-down switching DC-DC converter, which is widely used in various electrical systems: as an uninterruptible power supply, battery charger for electric vehicles, the inverter in solar photovoltaic power plants.. A
HOPSPACK: Hybrid Optimization Parallel Search Package.
Energy Technology Data Exchange (ETDEWEB)
Gray, Genetha Anne.; Kolda, Tamara G.; Griffin, Joshua; Taddy, Matt; Martinez-Canales, Monica L.
2008-12-01
In this paper, we describe the technical details of HOPSPACK (Hybrid Optimization Parallel SearchPackage), a new software platform which facilitates combining multiple optimization routines into asingle, tightly-coupled, hybrid algorithm that supports parallel function evaluations. The frameworkis designed such that existing optimization source code can be easily incorporated with minimalcode modification. By maintaining the integrity of each individual solver, the strengths and codesophistication of the original optimization package are retained and exploited.4
Hanho Son; Hyunsoo Kim
2016-01-01
A near-optimal rule-based mode control (RBC) strategy was proposed for a target plug-in hybrid electric vehicle (PHEV) taking into account the drivetrain losses. Individual loss models were developed for drivetrain components including the gears, planetary gear (PG), bearings, and oil pump, based on experimental data and mathematical governing equations. Also, a loss model for the power electronic system was constructed, including loss from the motor-generator while rotating in the unloaded s...
A hybrid fly fruit algorithm for PID control parameters optimization%一种用于PID控制参数优化的混合果蝇算法
Institute of Scientific and Technical Information of China (English)
宋娟
2015-01-01
In order to improve optimization performance of fly fruit optimization algorithm( FOA),put forward an assemblage of subsection optimization of a hybrid fly fruit optimization algorithm( hybrid FOA,HFOA),which introduces steady particle swarm optimization( PSO )algorithm into FOA parameters optimization of individual flying distance and smell concentration judgement value,meanwhile,the hybrid method adopts ITAE as fitness function and is applied to a class of unstable systems in PID control. Matlab simulation verification show that HFOA algorithm has fast convergence,good stability and high precision,and it verifies that application of HFOA in PID control parameter optimization are feasible and effective.%针对果蝇优化算法（ FOA）收敛速度快但寻优精度低的缺点，为了改善果蝇算法的优化性能，提出一种混合果蝇优化算法（ HFOA）。HFOA采用分段优化的思想，在优化过程后期采用收敛稳定性较好的粒子群优化（ PSO）算法优化果蝇算法中果蝇个体飞行距离和味道浓度的判定值，采用误差性能指标积分准则ITAE作为适应度函数，并将优化方案应用于一类不稳定系统的PID控制。Matlab仿真验证表明：HFOA计算高效，具有良好的稳定性，收敛精度高，进而验证了HFOA应用于PID控制参数优化是可行而有效的。
Directory of Open Access Journals (Sweden)
Chih-Hong Lin
2015-01-01
Full Text Available Because the V-belt continuously variable transmission (CVT system driven by permanent magnet synchronous motor (PMSM has much unknown nonlinear and time-varying characteristics, the better control performance design for the linear control design is a time consuming procedure. In order to overcome difficulties for design of the linear controllers, the hybrid recurrent Laguerre-orthogonal-polynomial neural network (NN control system which has online learning ability to respond to the system’s nonlinear and time-varying behaviors is proposed to control PMSM servo-driven V-belt CVT system under the occurrence of the lumped nonlinear load disturbances. The hybrid recurrent Laguerre-orthogonal-polynomial NN control system consists of an inspector control, a recurrent Laguerre-orthogonal-polynomial NN control with adaptive law, and a recouped control with estimated law. Moreover, the adaptive law of online parameters in the recurrent Laguerre-orthogonal-polynomial NN is derived using the Lyapunov stability theorem. Furthermore, the optimal learning rate of the parameters by means of modified particle swarm optimization (PSO is proposed to achieve fast convergence. Finally, to show the effectiveness of the proposed control scheme, comparative studies are demonstrated by experimental results.
一种求解最优控制问题的混合WNN-PSO算法%Hybrid WNN-PSO Algorithm for Optimal Control Problems
Institute of Scientific and Technical Information of China (English)
李树荣; 雷阳; 张强; 张晓东
2013-01-01
To solve optimal control problems with numerical methods, a hybrid wavelet neural network -particle swarm optimization (WNN-PSO) algorithm was developed. The first step of WNN-PSO was to parameterize the optimal control trajectory based on the non-linear approximation capability of the wavelet neural network. Then the optimal control problem was transformed into a non-linear programming problem where the decision variables are the parameters of the wavelet neural network. Lastly, the parameters of the network were optimized by the particle swarm optimization (PSO) algorithm and the global optimal solution of the NLP was obtained. Simulation study on a Bang-Bang optimal control problem and a benchmark chemical process optimal control problem shows the feasibility and effectiveness of the proposed method.%针对最优控制问题的数值求解,提出了一种混合小波神经网络粒子群(WNN-PSO)算法,算法首先利用小波神经网络的非线性逼近能力参数化最优控制轨迹,将最优控制问题转化为非线性规划(NLP)问题,其决策变量为小波神经网络的参数,然后采用粒子群(PSO)算法优化小波神经网络参数,获得NLP问题的全局最优解.针对Bang-Bang最优控制问题和一个经典的化工过程最优控制问题进行仿真研究,验证了所提出算法的可行性和有效性.
HEV车载复合电源系统控制策略优化研究%Optimization of hybrid power system control strategy for HEV
Institute of Scientific and Technical Information of China (English)
张丹红; 汪江卫; 刘开培; 苏义鑫
2012-01-01
HEV车载复合电源是将高比功率的超级电容与高比能量的蓄电池复合使用,通过合理的能量管理策略,以提高HEV汽车能源系统性能的技术.在分析车载复合电源系统的结构、功率需求及电源约束条件的基础上,建立了以车辆燃油消耗率和再生制动能量回收率为优化目标函数的能量管理问题数学模型.然后,根据复合电源系统的工作模式设计了基于模糊逻辑的能量管理控制器,利用遗传算法对功率分配因子的隶属度函数参数进行优化.基于ADVISOR的仿真研究表明,与未优化的模糊能量管理策略相比,经过优化的模糊能量管理策略能够更有效地降低混合动力汽车的燃油消耗,提高了制动能量回收率.%Hybrid power system for hybrid electric vehicle ( HEV )is a kind of technology to adopt the rational management strategy to improve the performance of HEV energy systems by combining high power density super capacitor and high specific energy batteries. Based on the analysis of the hybrid energy system structure, the power demand and supply constraints, a hybrid power mathematical model of energy management system was established, whose optimal objective functions were fuel consumption ratio and regenerative braking energy recovery. Then, a fuzzy logic energy management controller was designed according to the operation mode of hybrid power system, and the genetic algorithm was used to optimize the power allocation factor's parameters of membership function. The simulation results in ADVISOR show that the optimized fuzzy energy management strategy is more effective to reduce the fuel consumption of hybrid vehicles and improve the regenerative braking energy recovery than the non-optimized fuzzy energy management strategy.
Optimization problems for switched systems with impulsive control
Institute of Scientific and Technical Information of China (English)
Junhao HU; Huayou WANG; Xinzhi LIU; Bin LIU
2005-01-01
By using Impulsive Maximum Principal and three stage optimization method,this paper discusses optimization problems for linear impulsive switched systems with hybrid controls,which includes continuous control and impulsive control.The linear quadratic optimization problems without constraints such as optimal hybrid control,optimal stability and optimal switching instants are addressed in detail.These results are applicable to optimal control problems in economics,mechanics,and management.
Continuity Controlled Hybrid Automata
Bergstra, J. A.; Middelburg, C.A.
2004-01-01
We investigate the connections between the process algebra for hybrid systems of Bergstra and Middelburg and the formalism of hybrid automata of Henzinger et al. We give interpretations of hybrid automata in the process algebra for hybrid systems and compare them with the standard interpretation of hybrid automata as timed transition systems. We also relate the synchronized product operator on hybrid automata to the parallel composition operator of the process algebra. It turns out that the f...
Meyer, Richard; DeCarlo, Raymond A
2012-01-01
This paper compares the embedding approach for solving hybrid optimal control problems to multi-parameter programming, mixed-integer programming, and gradient-descent based methods in the context of four published examples. The four examples include a spring-mass system, moving-target tracking for a mobile robot, two-tank filling, and a DC-DC boost converter. Numerical advantages of the embedding approach are set forth and validated for each example: significantly faster solution time, no ad hoc assumptions (such as predetermined mode sequences) or control models, lower performance index costs, and algorithm convergence when other methods fail. Specific (theoretical) advantages of the embedding approach over the other methods are also described: guaranteed existence of a solution under mild conditions, convexity of the embedded optimization problem solvable with traditional techniques such as sequential quadratic programming with no need for any mixed-integer programming, applicability to nonlinear systems, e...
Continuity Controlled Hybrid Automata
Bergstra, J.A.; Middelburg, C.A.
2004-01-01
We investigate the connections between the process algebra for hybrid systems of Bergstra and Middelburg and the formalism of hybrid automata of Henzinger et al. We give interpretations of hybrid automata in the process algebra for hybrid systems and compare them with the standard interpretation of
Continuity controlled Hybrid Automata
Bergstra, J.A.; Middelburg, C.A.
2008-01-01
We investigate the connections between the process algebra for hybrid systems of Bergstra and Middelburg and the formalism of hybrid automata of Henzinger et al. We give interpretations of hybrid automata in the process algebra for hybrid systems and compare them with the standard interpretation of
Aerodynamic Shape Optimization Using Hybridized Differential Evolution
Madavan, Nateri K.
2003-01-01
An aerodynamic shape optimization method that uses an evolutionary algorithm known at Differential Evolution (DE) in conjunction with various hybridization strategies is described. DE is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Various hybridization strategies for DE are explored, including the use of neural networks as well as traditional local search methods. A Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the hybrid DE optimizer. The method is implemented on distributed parallel computers so that new designs can be obtained within reasonable turnaround times. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. (The final paper will include at least one other aerodynamic design application). The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated.
Original Framework for Optimizing Hybrid Energy Supply
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Amevi Acakpovi
2016-01-01
Full Text Available This paper proposes an original framework for optimizing hybrid energy systems. The recent growth of hybrid energy systems in remote areas across the world added to the increasing cost of renewable energy has triggered the inevitable development of hybrid energy systems. Hybrid energy systems always pose a problem of optimization of cost which has been approached with different perspectives in the recent past. This paper proposes a framework to guide the techniques of optimizing hybrid energy systems in general. The proposed framework comprises four stages including identification of input variables for energy generation, establishment of models of energy generation by individual sources, development of artificial intelligence, and finally summation of selected sources. A case study of a solar, wind, and hydro hybrid system was undertaken with a linear programming approach. Substantial results were obtained with regard to how load requests were constantly satisfied while minimizing the cost of electricity. The developed framework gained its originality from the fact that it has included models of individual sources of energy that even make the optimization problem more complex. This paper also has impacts on the development of policies which will encourage the integration and development of renewable energies.
Hybrid Predictive Control for Dynamic Transport Problems
Núñez, Alfredo A; Cortés, Cristián E
2013-01-01
Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...
Stillwater Hybrid Geo-Solar Power Plant Optimization Analyses
Energy Technology Data Exchange (ETDEWEB)
Wendt, Daniel S.; Mines, Gregory L.; Turchi, Craig S.; Zhu, Guangdong; Cohan, Sander; Angelini, Lorenzo; Bizzarri, Fabrizio; Consoli, Daniele; De Marzo, Alessio
2015-09-02
The Stillwater Power Plant is the first hybrid plant in the world able to bring together a medium-enthalpy geothermal unit with solar thermal and solar photovoltaic systems. Solar field and power plant models have been developed to predict the performance of the Stillwater geothermal / solar-thermal hybrid power plant. The models have been validated using operational data from the Stillwater plant. A preliminary effort to optimize performance of the Stillwater hybrid plant using optical characterization of the solar field has been completed. The Stillwater solar field optical characterization involved measurement of mirror reflectance, mirror slope error, and receiver position error. The measurements indicate that the solar field may generate 9% less energy than the design value if an appropriate tracking offset is not employed. A perfect tracking offset algorithm may be able to boost the solar field performance by about 15%. The validated Stillwater hybrid plant models were used to evaluate hybrid plant operating strategies including turbine IGV position optimization, ACC fan speed and turbine IGV position optimization, turbine inlet entropy control using optimization of multiple process variables, and mixed working fluid substitution. The hybrid plant models predict that each of these operating strategies could increase net power generation relative to the baseline Stillwater hybrid plant operations.
Optimization of Renewable Energy Hybrid System for Grid Connected Application
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Mustaqimah Mustaqimah
2012-10-01
Full Text Available ABSTRACT. Hybrid energy systems are pollution free, takes low cost and less gestation period, user and social friendly. Such systems are important sources of energy for shops, schools, and clinics in village communities especially in remote areas. Hybrid systems can provide electricity at a comparatively economic price in many remote areas. This paper presents a method to jointly determine the sizing and operation control of hybrid energy systems. The model, PV wind hydro and biomass hybrid system connects to grid. The system configuration of the hybrid is derived based on a theoretical domestic load at a typical location and local solar radiation, wind and water flow rate data and biomass availability. The hybrid energy system is proposed for 10 of teacher’s houses of Industrial Training Institute, Mersing. It is predicted 10 kW load consumption per house. The hybrid energy system consists of wind, solar, biomass, hydro, and grid power. Approximately energy consumption is 860 kWh/day with a 105 kW peak demand load. The proposed hybrid renewable consists of solar photovoltaic (PV panels, wind turbine, hydro turbine and biomass. Battery and inverter are included as part of back-up and storage system. It provides the economic sensitivity of hybridization and the economic and environmental benefits of using a blend of technologies. It also presents the trade off that is involved in optimizing a hybrid energy system to harness and utilize the available renewable energy resources efficiently.
Multiphase Return Trajectory Optimization Based on Hybrid Algorithm
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Yi Yang
2016-01-01
Full Text Available A hybrid trajectory optimization method consisting of Gauss pseudospectral method (GPM and natural computation algorithm has been developed and utilized to solve multiphase return trajectory optimization problem, where a phase is defined as a subinterval in which the right-hand side of the differential equation is continuous. GPM converts the optimal control problem to a nonlinear programming problem (NLP, which helps to improve calculation accuracy and speed of natural computation algorithm. Through numerical simulations, it is found that the multiphase optimal control problem could be solved perfectly.
Bizon, Nicu; Mahdavi Tabatabaei, Naser
2014-01-01
This book explains and analyzes the dynamic performance of linear and nonlinear systems, particularly for Power Systems including Hybrid Power Sources. Offers a detailed description of system stability using state space energy conservation principle, and more.
Hybrid optimization model of product concepts
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Deficiencies of applying the simple genetic algorithm to generate concepts were specified. Based on analyzing conceptual design and the morphological matrix of an excavator, the hybrid optimization model of generating its concepts was proposed, viz. an improved adaptive genetic algorithm was applied to explore the excavator concepts in the searching space of conceptual design, and a neural network was used to evaluate the fitness of the population. The optimization of generating concepts was finished through the "evolution - evaluation" iteration. The results show that by using the hybrid optimization model, not only the fitness evaluation and constraint conditions are well processed, but also the search precision and convergence speed of the optimization process are greatly improved. An example is presented to demonstrate the advantages of the proposed method and associated algorithms.
Directory of Open Access Journals (Sweden)
Hanho Son
2016-05-01
Full Text Available A near-optimal rule-based mode control (RBC strategy was proposed for a target plug-in hybrid electric vehicle (PHEV taking into account the drivetrain losses. Individual loss models were developed for drivetrain components including the gears, planetary gear (PG, bearings, and oil pump, based on experimental data and mathematical governing equations. Also, a loss model for the power electronic system was constructed, including loss from the motor-generator while rotating in the unloaded state. To evaluate the effect of the drivetrain losses on the operating mode control strategy, backward simulations were performed using dynamic programming (DP. DP selects the operating mode, which provides the highest efficiency for given driving conditions. It was found that the operating mode selection changes when drivetrain losses are included, depending on driving conditions. An operating mode schedule was developed with respect to the wheel power and vehicle speed, and based on the operating mode schedule, a RBC was obtained, which can be implemented in an on-line application. To evaluate the performance of the RBC, a forward simulator was constructed for the target PHEV. The simulation results show near-optimal performance of the RBC compared with dynamic-programming-based mode control in terms of the mode operation time and fuel economy. The RBC developed with drivetrain losses taken into account showed a 4%–5% improvement of the fuel economy over a similar RBC, which neglected the drivetrain losses.
Directory of Open Access Journals (Sweden)
Meng Xiong
2015-08-01
Full Text Available Energy storage devices are expected to be more frequently implemented in wind farms in near future. In this paper, both pumped hydro and fly wheel storage systems are used to assist a wind farm to smooth the power fluctuations. Due to the significant difference in the response speeds of the two storages types, the wind farm coordination with two types of energy storage is a problem. This paper presents two methods for the coordination problem: a two-level hierarchical model predictive control (MPC method and a single-level MPC method. In the single-level MPC method, only one MPC controller coordinates the wind farm and the two storage systems to follow the grid scheduling. Alternatively, in the two-level MPC method, two MPC controllers are used to coordinate the wind farm and the two storage systems. The structure of two level MPC consists of outer level and inner level MPC. They run alternatively to perform real-time scheduling and then stop, thus obtaining long-term scheduling results and sending some results to the inner level as input. The single-level MPC method performs both long- and short-term scheduling tasks in each interval. The simulation results show that the methods proposed can improve the utilization of wind power and reduce wind power spillage. In addition, the single-level MPC and the two-level MPC are not interchangeable. The single-level MPC has the advantage of following the grid schedule while the two-level MPC can reduce the optimization time by 60%.
Optimal obstacle control problem
Institute of Scientific and Technical Information of China (English)
ZHU Li; LI Xiu-hua; GUO Xing-ming
2008-01-01
In the paper we discuss some properties of the state operators of the optimal obstacle control problem for elliptic variational inequality. Existence, uniqueness and regularity of the optimal control problem are established. In addition, the approximation of the optimal obstacle problem is also studied.
Directory of Open Access Journals (Sweden)
Ravi Shankar
2012-11-01
Full Text Available The adoption of Plug-in Hybrid Electric Vehicles (PHEVs is widely seen as an interim solution for the decarbonization of the transport sector. Within a PHEV, determining the required energy storage capacity of the battery remains one of the primary concerns for vehicle manufacturers and system integrators. This fact is particularly pertinent since the battery constitutes the largest contributor to vehicle mass. Furthermore, the financial cost associated with the procurement, design and integration of battery systems is often cited as one of the main barriers to vehicle commercialization. The ability to integrate the optimization of the energy management control system with the sizing of key PHEV powertrain components presents a significant area of research. Contained within this paper is an optimization study in which a charge blended strategy is used to facilitate the downsizing of the electrical machine, the internal combustion engine and the high voltage battery. An improved Equivalent Consumption Method has been used to manage the optimal power split within the powertrain as the PHEV traverses a range of different drivecycles. For a target CO2 value and drivecycle, results show that this approach can yield significant downsizing opportunities, with cost reductions on the order of 2%–9% being realizable.
Operations Optimization of Hybrid Energy Systems under Variable Markets
Energy Technology Data Exchange (ETDEWEB)
Chen, Jun; Garcia, Humberto E.
2016-07-01
Hybrid energy systems (HES) have been proposed to be an important element to enable increasing penetration of clean energy. This paper investigates the operations flexibility of HES, and develops a methodology for operations optimization to maximize its economic value based on predicted renewable generation and market information. The proposed operations optimizer allows systematic control of energy conversion for maximal economic value, and is illustrated by numerical results.
Hybrid spacecraft attitude control system
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Renuganth Varatharajoo
2016-02-01
Full Text Available The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.
Analysis and design of hybrid control systems
Energy Technology Data Exchange (ETDEWEB)
Malmborg, J.
1998-05-01
Different aspects of hybrid control systems are treated: analysis, simulation, design and implementation. A systematic methodology using extended Lyapunov theory for design of hybrid systems is developed. The methodology is based on conventional control designs in separate regions together with a switching strategy. Dynamics are not well defined if the control design methods lead to fast mode switching. The dynamics depend on the salient features of the implementation of the mode switches. A theorem for the stability of second order switching together with the resulting dynamics is derived. The dynamics on an intersection of two sliding sets are defined for two relays working on different time scales. The current simulation packages have problems modeling and simulating hybrid systems. It is shown how fast mode switches can be found before or during simulation. The necessary analysis work is a very small overhead for a modern simulation tool. To get some experience from practical problems with hybrid control the switching strategy is implemented in two different software environments. In one of them a time-optimal controller is added to an existing PID controller on a commercial control system. Successful experiments with this hybrid controller shows the practical use of the method 78 refs, 51 figs, 2 tabs
A Hybrid Evolutionary Algorithm for Discrete Optimization
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J. Bhuvana
2015-03-01
Full Text Available Most of the real world multi-objective problems demand us to choose one Pareto optimal solution out of a finite set of choices. Flexible job shop scheduling problem is one such problem whose solutions are required to be selected from a discrete solution space. In this study we have designed a hybrid genetic algorithm to solve this scheduling problem. Hybrid genetic algorithms combine both the aspects of the search, exploration and exploitation of the search space. Proposed algorithm, Hybrid GA with Discrete Local Search, performs global search through the GA and exploits the locality through discrete local search. Proposed hybrid algorithm not only has the ability to generate Pareto optimal solutions and also identifies them with less computation. Five different benchmark test instances are used to evaluate the performance of the proposed algorithm. Results observed shown that the proposed algorithm has produced the known Pareto optimal solutions through exploration and exploitation of the search space with less number of functional evaluations.
Optimization methods applied to hybrid vehicle design
Donoghue, J. F.; Burghart, J. H.
1983-01-01
The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.
Control and optimization system
Xinsheng, Lou
2013-02-12
A system for optimizing a power plant includes a chemical loop having an input for receiving an input parameter (270) and an output for outputting an output parameter (280), a control system operably connected to the chemical loop and having a multiple controller part (230) comprising a model-free controller. The control system receives the output parameter (280), optimizes the input parameter (270) based on the received output parameter (280), and outputs an optimized input parameter (270) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Directory of Open Access Journals (Sweden)
Verdonck N.
2010-01-01
Full Text Available Systematic optimization of modern powertrains, and hybrids in particular, requires the representation of the system by means of Backward Quasistatic Models (BQM. In contrast, the models used in realistic powertrain simulators are often of the Forward Dynamic Model (FDM type. The paper presents a methodology to derive BQM’s of modern powertrain components, as parametric, steady-state limits of their FDM counterparts. The parametric nature of this procedure implies that changing the system modeled does not imply relaunching a simulation campaign, but only adjusting the corresponding parameters in the BQM. The approach is illustrated with examples concerning turbocharged engines, electric motors, and electrochemical batteries, and the influence of a change in parameters on the supervisory control of an hybrid vehicle is then studied offline, in co-simulation and on an HiL test bench adapted to hybrid vehicles (HyHiL. L’optimisation de l’utilisation des groupes moto-propulseurs (GMP modernes nécessite de modéliser le système de manière quasi-statique avec une logique inverse (“Backward Quasistatic Model” – BQM, en particulier dans le cas des GMP hybrides. Cependant, les modèles utilisés pour la simulation réaliste de ces GMP sont souvent dynamiques à logique directe (“Forward Dynamic Model” – FDM. Cet article présente une méthodologie pour obtenir les BQM des composants de GMP actuels directement issus de la limite quasi-statique des FDM correspondants de manière analytique. Grâce à l’aspect paramétrique de cette procédure, il n’est pas nécessaire de relancer une campagne de simulations après chaque changement du système modélisé: il suffit de modifier les paramètres correspondants dans le BQM. Cette approche est illustrée par trois cas d’étude (moteur turbo, moteur électrique et batterie, et l’effet d’un changement de paramètre sur le contrôle de supervision d’un véhicule hybride est
Hybrid Disease Diagnosis Using Multiobjective Optimization with Evolutionary Parameter Optimization
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MadhuSudana Rao Nalluri
2017-01-01
Full Text Available With the widespread adoption of e-Healthcare and telemedicine applications, accurate, intelligent disease diagnosis systems have been profoundly coveted. In recent years, numerous individual machine learning-based classifiers have been proposed and tested, and the fact that a single classifier cannot effectively classify and diagnose all diseases has been almost accorded with. This has seen a number of recent research attempts to arrive at a consensus using ensemble classification techniques. In this paper, a hybrid system is proposed to diagnose ailments using optimizing individual classifier parameters for two classifier techniques, namely, support vector machine (SVM and multilayer perceptron (MLP technique. We employ three recent evolutionary algorithms to optimize the parameters of the classifiers above, leading to six alternative hybrid disease diagnosis systems, also referred to as hybrid intelligent systems (HISs. Multiple objectives, namely, prediction accuracy, sensitivity, and specificity, have been considered to assess the efficacy of the proposed hybrid systems with existing ones. The proposed model is evaluated on 11 benchmark datasets, and the obtained results demonstrate that our proposed hybrid diagnosis systems perform better in terms of disease prediction accuracy, sensitivity, and specificity. Pertinent statistical tests were carried out to substantiate the efficacy of the obtained results.
Optimization strategy for element sizing in hybrid power systems
del Real, Alejandro J.; Arce, Alicia; Bordons, Carlos
This paper presents a procedure to evaluate the optimal element sizing of hybrid power systems. In order to generalize the problem, this work exploits the "energy hub" formulation previously presented in the literature, defining an energy hub as an interface among energy producers, consumers and the transportation infrastructure. The resulting optimization minimizes an objective function which is based on costs and efficiencies of the system elements, while taking into account the hub model, energy and power constraints and estimated operational conditions, such as energy prices, input power flow availability and output energy demand. The resulting optimal architecture also constitutes a framework for further real-time control designs. Moreover, an example of a hybrid storage system is considered. In particular, the architecture of a hybrid plant incorporating a wind generator, batteries and intermediate hydrogen storage is optimized, based on real wind data and averaged residential demands, also taking into account possible estimation errors. The hydrogen system integrates an electrolyzer, a fuel cell stack and hydrogen tanks. The resulting optimal cost of such hybrid power plant is compared with the equivalent hydrogen-only and battery-only systems, showing improvements in investment costs of almost 30% in the worst case.
Optimization strategy for element sizing in hybrid power systems
Energy Technology Data Exchange (ETDEWEB)
del Real, Alejandro J.; Arce, Alicia; Bordons, Carlos [Departamento de Ingenieria de Sistemas y Automatica, Universidad de Sevilla, 41092 Sevilla (Spain)
2009-08-01
This paper presents a procedure to evaluate the optimal element sizing of hybrid power systems. In order to generalize the problem, this work exploits the ''energy hub'' formulation previously presented in the literature, defining an energy hub as an interface among energy producers, consumers and the transportation infrastructure. The resulting optimization minimizes an objective function which is based on costs and efficiencies of the system elements, while taking into account the hub model, energy and power constraints and estimated operational conditions, such as energy prices, input power flow availability and output energy demand. The resulting optimal architecture also constitutes a framework for further real-time control designs. Moreover, an example of a hybrid storage system is considered. In particular, the architecture of a hybrid plant incorporating a wind generator, batteries and intermediate hydrogen storage is optimized, based on real wind data and averaged residential demands, also taking into account possible estimation errors. The hydrogen system integrates an electrolyzer, a fuel cell stack and hydrogen tanks. The resulting optimal cost of such hybrid power plant is compared with the equivalent hydrogen-only and battery-only systems, showing improvements in investment costs of almost 30% in the worst case. (author)
Schaft, A.J. van der
1987-01-01
It is argued that the existence of symmetries may simplify, as in classical mechanics, the solution of optimal control problems. A procedure for obtaining symmetries for the optimal Hamiltonian resulting from the Maximum Principle is given; this avoids the actual calculation of the optimal
Solid Rocket Motor Design Using Hybrid Optimization
Directory of Open Access Journals (Sweden)
Kevin Albarado
2012-01-01
Full Text Available A particle swarm/pattern search hybrid optimizer was used to drive a solid rocket motor modeling code to an optimal solution. The solid motor code models tapered motor geometries using analytical burn back methods by slicing the grain into thin sections along the axial direction. Grains with circular perforated stars, wagon wheels, and dog bones can be considered and multiple tapered sections can be constructed. The hybrid approach to optimization is capable of exploring large areas of the solution space through particle swarming, but is also able to climb “hills” of optimality through gradient based pattern searching. A preliminary method for designing tapered internal geometry as well as tapered outer mold-line geometry is presented. A total of four optimization cases were performed. The first two case studies examines designing motors to match a given regressive-progressive-regressive burn profile. The third case study studies designing a neutrally burning right circular perforated grain (utilizing inner and external geometry tapering. The final case study studies designing a linearly regressive burning profile for right circular perforated (tapered grains.
Institute of Scientific and Technical Information of China (English)
Y Hashemi; H Shayeghi; M Moradzadeh; ASafari
2016-01-01
A mathematical approach was proposed to investigate the impact of high penetration of large-scale photovoltaic park (LPP) on small-signal stability of a power network and design of hybrid controller for these units. A systematic procedure was performed to obtain the complete model of a multi-machine power network including LPP. For damping of oscillations focusing on inter-area oscillatory modes, a hybrid controller for LPP was proposed. The performance of the suggested controller was tested using a 16-machine 5-area network. The results indicate that the proposed hybrid controller for LPP provides sufficient damping to the low-frequency modes of power system for a wide range of operating conditions. The method presented in this work effectively indentifies the impact of increased PV penetration and its controller on dynamic performance of multi-machine power network containing LPP. Simulation results demonstrate that the model presented can be used in designing of essential controllers for LPP.
Optimal control computer programs
Kuo, F.
1992-01-01
The solution of the optimal control problem, even with low order dynamical systems, can usually strain the analytical ability of most engineers. The understanding of this subject matter, therefore, would be greatly enhanced if a software package existed that could simulate simple generic problems. Surprisingly, despite a great abundance of commercially available control software, few, if any, address the part of optimal control in its most generic form. The purpose of this paper is, therefore, to present a simple computer program that will perform simulations of optimal control problems that arise from the first necessary condition and the Pontryagin's maximum principle.
Integrated controls design optimization
Lou, Xinsheng; Neuschaefer, Carl H.
2015-09-01
A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.
Hybrid Optimization for Wind Turbine Thick Airfoils
Energy Technology Data Exchange (ETDEWEB)
Grasso, F. [ECN Wind Energy, Petten (Netherlands)
2012-06-15
One important element in aerodynamic design of wind turbines is the use of specially tailored airfoils to increase the ratio of energy capture and reduce cost of energy. This work is focused on the design of thick airfoils for wind turbines by using numerical optimization. A hybrid scheme is proposed in which genetic and gradient based algorithms are combined together to improve the accuracy and the reliability of the design. Firstly, the requirements and the constraints for this class of airfoils are described; then, the hybrid approach is presented. The final part of this work is dedicated to illustrate a numerical example regarding the design of a new thick airfoil. The results are discussed and compared to existing airfoils.
Energy Technology Data Exchange (ETDEWEB)
Shallvari, Iva; Velnati, Sashidhar; DeGroot, Kenneth P.
2015-07-28
A method and apparatus for heating a catalytic converter's catalyst to an efficient operating temperature in a hybrid electric vehicle when the vehicle is in a charge limited mode such as e.g., the charge depleting mode or when the vehicle's high voltage battery is otherwise charge limited. The method and apparatus determine whether a high voltage battery of the vehicle is incapable of accepting a first amount of charge associated with a first procedure to warm-up the catalyst. If it is determined that the high voltage battery is incapable of accepting the first amount of charge, a second procedure with an acceptable amount of charge is performed to warm-up the catalyst.
Shallvari, Iva; Velnati, Sashidhar; DeGroot, Kenneth P.
2015-07-28
A method and apparatus for heating a catalytic converter's catalyst to an efficient operating temperature in a hybrid electric vehicle when the vehicle is in a charge limited mode such as e.g., the charge depleting mode or when the vehicle's high voltage battery is otherwise charge limited. The method and apparatus determine whether a high voltage battery of the vehicle is incapable of accepting a first amount of charge associated with a first procedure to warm-up the catalyst. If it is determined that the high voltage battery is incapable of accepting the first amount of charge, a second procedure with an acceptable amount of charge is performed to warm-up the catalyst.
Hybrid Optimization in the Design of Reciprocal Structures
DEFF Research Database (Denmark)
Parigi, Dario; Kirkegaard, Poul Henning; Sassone, Mario
2012-01-01
that explore the global domain of solutions as genetic algorithms (GAs). The benchmark tests show that when the control on the topology is required the best result is obtained by a hybrid approach that combines the global search of the GA with the local search of a GB algorithm. The optimization method......The paper presents a method to generate the geometry of reciprocal structures by means of a hybrid optimization procedure. The geometry of reciprocal structures where elements are sitting on the top or in the bottom of each other is extremely difficult to predict because of the non....... In this paper it is shown that the geometrically compatible position of the elements could be determined by local search algorithm gradient-based (GB). However the control on which bar sit on the top or in the bottom at each connection can be regarded as a topological problem and require the use of algorithms...
Colonius, Fritz
1988-01-01
This research monograph deals with optimal periodic control problems for systems governed by ordinary and functional differential equations of retarded type. Particular attention is given to the problem of local properness, i.e. whether system performance can be improved by introducing periodic motions. Using either Ekeland's Variational Principle or optimization theory in Banach spaces, necessary optimality conditions are proved. In particular, complete proofs of second-order conditions are included and the result is used for various versions of the optimal periodic control problem. Furthermore a scenario for local properness (related to Hopf bifurcation) is drawn up, giving hints as to where to look for optimal periodic solutions. The book provides mathematically rigorous proofs for results which are potentially of importance in chemical engineering and aerospace engineering.
Optimizing the specificity of nucleic acid hybridization.
Zhang, David Yu; Chen, Sherry Xi; Yin, Peng
2012-01-22
The specific hybridization of complementary sequences is an essential property of nucleic acids, enabling diverse biological and biotechnological reactions and functions. However, the specificity of nucleic acid hybridization is compromised for long strands, except near the melting temperature. Here, we analytically derived the thermodynamic properties of a hybridization probe that would enable near-optimal single-base discrimination and perform robustly across diverse temperature, salt and concentration conditions. We rationally designed 'toehold exchange' probes that approximate these properties, and comprehensively tested them against five different DNA targets and 55 spurious analogues with energetically representative single-base changes (replacements, deletions and insertions). These probes produced discrimination factors between 3 and 100+ (median, 26). Without retuning, our probes function robustly from 10 °C to 37 °C, from 1 mM Mg(2+) to 47 mM Mg(2+), and with nucleic acid concentrations from 1 nM to 5 µM. Experiments with RNA also showed effective single-base change discrimination.
Discrete Variational Optimal Control
Jimenez, Fernando; de Diego, David Martin
2012-01-01
This paper develops numerical methods for optimal control of mechanical systems in the Lagrangian setting. It extends the theory of discrete mechanics to enable the solutions of optimal control problems through the discretization of variational principles. The key point is to solve the optimal control problem as a variational integrator of a specially constructed higher-dimensional system. The developed framework applies to systems on tangent bundles, Lie groups, underactuated and nonholonomic systems with symmetries, and can approximate either smooth or discontinuous control inputs. The resulting methods inherit the preservation properties of variational integrators and result in numerically robust and easily implementable algorithms. Several theoretical and a practical examples, e.g. the control of an underwater vehicle, will illustrate the application of the proposed approach.
Discrete Variational Optimal Control
Jiménez, Fernando; Kobilarov, Marin; Martín de Diego, David
2013-06-01
This paper develops numerical methods for optimal control of mechanical systems in the Lagrangian setting. It extends the theory of discrete mechanics to enable the solutions of optimal control problems through the discretization of variational principles. The key point is to solve the optimal control problem as a variational integrator of a specially constructed higher dimensional system. The developed framework applies to systems on tangent bundles, Lie groups, and underactuated and nonholonomic systems with symmetries, and can approximate either smooth or discontinuous control inputs. The resulting methods inherit the preservation properties of variational integrators and result in numerically robust and easily implementable algorithms. Several theoretical examples and a practical one, the control of an underwater vehicle, illustrate the application of the proposed approach.
A Hybrid Aggressive Space Mapping Algorithm for EM Optimization
DEFF Research Database (Denmark)
Bakr, M.; Bandler, J. W.; Georgieva, N.;
1999-01-01
We present a novel, Hybrid Aggressive Space Mapping (HASM) optimization algorithm. HASM is a hybrid approach exploiting both the Trust Region Aggressive Space Mapping (TRASM) algorithm and direct optimization. It does not assume that the final space-mapped design is the true optimal design and is...
Optimal Lunar Landing Trajectory Design for Hybrid Engine
Directory of Open Access Journals (Sweden)
Dong-Hyun Cho
2015-01-01
Full Text Available The lunar landing stage is usually divided into two parts: deorbit burn and powered descent phases. The optimal lunar landing problem is likely to be transformed to the trajectory design problem on the powered descent phase by using continuous thrusters. The optimal lunar landing trajectories in general have variety in shape, and the lunar lander frequently increases its altitude at the initial time to obtain enough time to reduce the horizontal velocity. Due to the increment in the altitude, the lunar lander requires more fuel for lunar landing missions. In this work, a hybrid engine for the lunar landing mission is introduced, and an optimal lunar landing strategy for the hybrid engine is suggested. For this approach, it is assumed that the lunar lander retrofired the impulsive thruster to reduce the horizontal velocity rapidly at the initiated time on the powered descent phase. Then, the lunar lander reduced the total velocity and altitude for the lunar landing by using the continuous thruster. In contradistinction to other formal optimal lunar landing problems, the initial horizontal velocity and mass are not fixed at the start time. The initial free optimal control theory is applied, and the optimal initial value and lunar landing trajectory are obtained by simulation studies.
Jianwen Guo; Zhenzhong Sun; Hong Tang; Xuejun Jia; Song Wang; Xiaohui Yan; Guoliang Ye; Guohong Wu
2016-01-01
All equipment must be maintained during its lifetime to ensure normal operation. Maintenance is one of the critical roles in the success of manufacturing enterprises. This paper proposed a preventive maintenance period optimization model (PMPOM) to find an optimal preventive maintenance period. By making use of the advantages of particle swarm optimization (PSO) and cuckoo search (CS) algorithm, a hybrid optimization algorithm of PSO and CS is proposed to solve the PMPOM problem. The test fun...
Modelling supervisory controller for hybrid power systems
Energy Technology Data Exchange (ETDEWEB)
Pereira, A.; Bindner, H.; Lundsager, P. [Risoe National Lab., Roskilde (Denmark); Jannerup, O. [Technical Univ. of Denmark, Dept. of Automation, Lyngby (Denmark)
1999-03-01
Supervisory controllers are important to achieve optimal operation of hybrid power systems. The performance and economics of such systems depend mainly on the control strategy for switching on/off components. The modular concept described in this paper is an attempt to design standard supervisory controllers that could be used in different applications, such as village power and telecommunication applications. This paper presents some basic aspects of modelling and design of modular supervisory controllers using the object-oriented modelling technique. The functional abstraction hierarchy technique is used to formulate the control requirements and identify the functions of the control system. The modular algorithm is generic and flexible enough to be used with any system configuration and several goals (different applications). The modularity includes accepting modification of system configuration and goals during operation with minor or no changes in the supervisory controller. (au)
Optimized Vertex Method and Hybrid Reliability
Smith, Steven A.; Krishnamurthy, T.; Mason, B. H.
2002-01-01
A method of calculating the fuzzy response of a system is presented. This method, called the Optimized Vertex Method (OVM), is based upon the vertex method but requires considerably fewer function evaluations. The method is demonstrated by calculating the response membership function of strain-energy release rate for a bonded joint with a crack. The possibility of failure of the bonded joint was determined over a range of loads. After completing the possibilistic analysis, the possibilistic (fuzzy) membership functions were transformed to probability density functions and the probability of failure of the bonded joint was calculated. This approach is called a possibility-based hybrid reliability assessment. The possibility and probability of failure are presented and compared to a Monte Carlo Simulation (MCS) of the bonded joint.
POWER OPTIMIZED DATAPATH UNITS OF HYBRID EMBEDDED CORE ARCHITECTURE USING CLOCK GATING TECHNIQUE
National Research Council Canada - National Science Library
T.Subhashini; M.Kamaraju
2015-01-01
...% of the total power dissipation. The main goal of this work is to implement a prototype power optimized datapath unit and ALU of Hybrid Embedded Controller Architecture targeted on to the FPGA chip and analyze the power consumption...
On Symmetries in Optimal Control
van der Schaft, A. J.
1986-01-01
We discuss the use of symmetries in solving optimal control problems. In particular a procedure for obtaining symmetries is given which can be performed before the actual calculation of the optimal control and optimal Hamiltonian.
On Symmetries in Optimal Control
Schaft, A.J. van der
1986-01-01
We discuss the use of symmetries in solving optimal control problems. In particular a procedure for obtaining symmetries is given which can be performed before the actual calculation of the optimal control and optimal Hamiltonian.
Optimized joystick controller.
Ding, D; Cooper, R A; Spaeth, D
2004-01-01
The purpose of the study was to develop an optimized joystick control interface for electric powered wheelchairs and thus provide safe and effective control of electric powered wheelchairs to people with severe physical disabilities. The interface enables clinicians to tune joystick parameters for each individual subject through selecting templates, dead zones, and bias axes. In terms of hand tremor usually associated with people with traumatic brain injury, cerebral palsy, and multiple sclerosis, fuzzy logic rules were applied to suppress erratic hand movements and extract the intended motion from the joystick. Simulation results were presented to show the graphical tuning interface as well as the performance of the fuzzy logic controller.
Hybrid Optimized and Localized Vibrational Coordinates.
Klinting, Emil Lund; König, Carolin; Christiansen, Ove
2015-11-01
We present a new type of vibrational coordinates denoted hybrid optimized and localized coordinates (HOLCs) aiming at a good set of rectilinear vibrational coordinates supporting fast convergence in vibrational stucture calculations. The HOLCs are obtained as a compromise between the recently promoted optimized coordinates (OCs) and localized coordinates (LCs). The three sets of coordinates are generally different from each other and differ from standard normal coordinates (NCs) as well. In determining the HOLCs, we optimize the vibrational self-consistent field (VSCF) energy with respect to orthogonal transformation of the coordinates, which is similar to determining OCs but for HOLCs we additionally introduce a penalty for delocalization, by using a measure of localization similar to that employed in determining LCs. The same theory and implementation covers OCs, LCs, and HOLCs. It is shown that varying one penalty parameter allows for connecting OCs and LCs. The HOLCs are compared to NCs, OCs, and LCs in their nature and performance as basis for vibrational coupled cluster (VCC) response calculations of vibrational anharmonic energies for a small set of simple systems comprising water, formaldehyde, and ethylene. It is found that surprisingly good results can be obtained with HOLCs by using potential energy surfaces as simple as quadratic Taylor expansions. Quite similar coordinates are found for the already established OCs but obtaining these OCs requires much more elaborate and expensive potential energy surfaces and localization is generally not guaranteed. The ability to compute HOLCs for somewhat larger systems is demonstrated for coumarin and the alanine quadramer. The good agreement between HOLCs and OCs, together with the much easier applicability of HOLCs for larger systems, suggests that HOLCs may be a pragmatically very interesting option for anharmonic calculations on medium to large molecular systems.
HYBRID FUZZY CONTROL FOR ELECTRO-HYDRAULIC ACTIVE DAMPING SUSPENSION
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
A new control scheme, the hybrid fuzzy control method, for active damping suspension system is presented. The scheme is the result of effective combination of the statistical optimal control method based on the statistical property of suspension system, with the bang-bang control method based on the real-time characteristics of suspension system. Computer simulations are performed to compare the effectiveness of hybrid fuzzy control scheme with that of optimal damping control, bang-bang control, and passive suspension. It takes the effects of time-variant factors into full account. The superiority of the proposed hybrid fuzzy control scheme for active damping suspension to the passive suspension is verified in the experiment study.
Linear optimal control of tokamak fusion devices
Energy Technology Data Exchange (ETDEWEB)
Kessel, C.E.; Firestone, M.A.; Conn, R.W.
1989-05-01
The control of plasma position, shape and current in a tokamak fusion reactor is examined using linear optimal control. These advanced tokamaks are characterized by non up-down symmetric coils and structure, thick structure surrounding the plasma, eddy currents, shaped plasmas, superconducting coils, vertically unstable plasmas, and hybrid function coils providing ohmic heating, vertical field, radial field, and shaping field. Models of the electromagnetic environment in a tokamak are derived and used to construct control gains that are tested in nonlinear simulations with initial perturbations. The issues of applying linear optimal control to advanced tokamaks are addressed, including complex equilibrium control, choice of cost functional weights, the coil voltage limit, discrete control, and order reduction. Results indicate that the linear optimal control is a feasible technique for controlling advanced tokamaks where the more common classical control will be severely strained or will not work. 28 refs., 13 figs.
ADОPTIVE CONTROL OF THE HYBRID VEHICLE POWER UNIT
Directory of Open Access Journals (Sweden)
S. Serikov
2014-10-01
Full Text Available The problem of adaptive control of the hybrid vehicle power unit, which makes it possible to minimize the quality criterion under constraints on the state parameters and the control vector is considered. A formal statement of the optimization problem is given. The solution of this problem by the method of neural network control based on the adaptive criticism is considered.
Control for a class of hybrid systems
J.H. van Schuppen (Jan)
1997-01-01
textabstractA hybrid control system is a control theoretic model for a computer controlled engineering system. A definition of a hybrid control system is formulated that consists of a product of a finite state automaton and of a family of continuous control systems. An example of a transportation
2017-03-21
BrightBox Optimization Modeling Platform ................................................................. 11 Figure 2. BrightBox Software Architecture and...2. BrightBox Software Architecture and Interaction with Building 12 We recognized the need for a dashboard and real-time savings reports for...account for equipment specifications, chilled water load and flow profile, and the coincident weather data. This program tests all of the possible
Directory of Open Access Journals (Sweden)
Pérez L.V.
2010-02-01
Full Text Available The optimization of the supervisory control of hybrid electric vehicles over predetermined driving cycles has been used as a previous study for determining on-line strategies and also for design and sizing purposes. This problem may be posed as an optimal control problem, in which the energy in the bank of batteries is often the state variable, and the power from any of the system sources is, the control action. As both of these quantities are bounded, the optimal control problem has control constraints or state constraints or both. Usually, the charge-sustaining mode of operation is ensured just by imposing a transversality condition, i.e. a fixed final energy, or including an additional term in the cost functional that penalizes the moving away of the state variable from the nominal value. We considered the problem where the state is allowed to move freely within a band. This led to an optimal control problem with control and state constraints. In this work we describe the difficulties that arise while solving the equations given by the Pontryagin’s Maximum Principle and how these difficulties can be overcome by using the so-called Direct Transcription approach that consists of a programming tool to solve the resultant large-scale finite dimensional optimization problem. L’optimisation de la commande au niveau superviseur de véhicules hybrides sur cycles d’usage prédéterminés a été utilisée comme une première étude pour déterminer des stratégies en ligne mais aussi avec des objectifs de conception et dimensionnement. Ce problème peut être posé comme un problème de commande optimale, où l’énergie dans les batteries est généralement la variable d’état et où la puissance de n’importe quelle source du système est l’action de commande. Comme ces deux quantités sont bornées, le problème de commande optimale a des restrictions sur la fonction de commande et sur l’état. Généralement, le fonctionnement
Centralized Stochastic Optimal Control of Complex Systems
Energy Technology Data Exchange (ETDEWEB)
Malikopoulos, Andreas [ORNL
2015-01-01
In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain using the long-run expected average cost per unit time criterion, and we show that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.
Hybrid upconversion nanomaterials for optogenetic neuronal control
Shah, Shreyas; Liu, Jing-Jing; Pasquale, Nicholas; Lai, Jinping; McGowan, Heather; Pang, Zhiping P.; Lee, Ki-Bum
2015-10-01
Nanotechnology-based approaches offer the chemical control required to develop precision tools suitable for applications in neuroscience. We report a novel approach employing hybrid upconversion nanomaterials, combined with the photoresponsive ion channel channelrhodopsin-2 (ChR2), to achieve near-infrared light (NIR)-mediated optogenetic control of neuronal activity. Current optogenetic methodologies rely on using visible light (e.g. 470 nm blue light), which tends to exhibit high scattering and low tissue penetration, to activate ChR2. In contrast, our approach enables the use of 980 nm NIR light, which addresses the short-comings of visible light as an excitation source. This was facilitated by embedding upconversion nanomaterials, which can convert NIR light to blue luminescence, into polymeric scaffolds. These hybrid nanomaterial scaffolds allowed for NIR-mediated neuronal stimulation, with comparable efficiency as that of 470 nm blue light. Our platform was optimized for NIR-mediated optogenetic control by balancing multiple physicochemical properties of the nanomaterial (e.g. size, morphology, structure, emission spectra, concentration), thus providing an early demonstration of rationally-designing nanomaterial-based strategies for advanced neural applications.Nanotechnology-based approaches offer the chemical control required to develop precision tools suitable for applications in neuroscience. We report a novel approach employing hybrid upconversion nanomaterials, combined with the photoresponsive ion channel channelrhodopsin-2 (ChR2), to achieve near-infrared light (NIR)-mediated optogenetic control of neuronal activity. Current optogenetic methodologies rely on using visible light (e.g. 470 nm blue light), which tends to exhibit high scattering and low tissue penetration, to activate ChR2. In contrast, our approach enables the use of 980 nm NIR light, which addresses the short-comings of visible light as an excitation source. This was facilitated by
Parallel Hybrid Vehicle Optimal Storage System
Bloomfield, Aaron P.
2009-01-01
A paper reports the results of a Hybrid Diesel Vehicle Project focused on a parallel hybrid configuration suitable for diesel-powered, medium-sized, commercial vehicles commonly used for parcel delivery and shuttle buses, as the missions of these types of vehicles require frequent stops. During these stops, electric hybridization can effectively recover the vehicle's kinetic energy during the deceleration, store it onboard, and then use that energy to assist in the subsequent acceleration.
Optimal control for chemical engineers
Upreti, Simant Ranjan
2013-01-01
Optimal Control for Chemical Engineers gives a detailed treatment of optimal control theory that enables readers to formulate and solve optimal control problems. With a strong emphasis on problem solving, the book provides all the necessary mathematical analyses and derivations of important results, including multiplier theorems and Pontryagin's principle.The text begins by introducing various examples of optimal control, such as batch distillation and chemotherapy, and the basic concepts of optimal control, including functionals and differentials. It then analyzes the notion of optimality, de
Power, control and optimization
Vasant, Pandian; Barsoum, Nader
2013-01-01
The book consists of chapters based on selected papers of international conference „Power, Control and Optimization 2012”, held in Las Vegas, USA. Readers can find interesting chapters discussing various topics from the field of power control, its distribution and related fields. Book discusses topics like energy consumption impacted by climate, mathematical modeling of the influence of thermal power plant on the aquatic environment, investigation of cost reduction in residential electricity bill using electric vehicle at peak times or allocation and size evaluation of distributed generation using ANN model and others. Chapter authors are to the best of our knowledge the originators or closely related to the originators of presented ideas and its applications. Hence, this book certainly is one of the few books discussing the benefit from intersection of those modern and fruitful scientific fields of research with very tight and deep impact on real life and industry. This book is devoted to the studies o...
Directory of Open Access Journals (Sweden)
Jianwen Guo
2016-01-01
Full Text Available All equipment must be maintained during its lifetime to ensure normal operation. Maintenance is one of the critical roles in the success of manufacturing enterprises. This paper proposed a preventive maintenance period optimization model (PMPOM to find an optimal preventive maintenance period. By making use of the advantages of particle swarm optimization (PSO and cuckoo search (CS algorithm, a hybrid optimization algorithm of PSO and CS is proposed to solve the PMPOM problem. The test functions show that the proposed algorithm exhibits more outstanding performance than particle swarm optimization and cuckoo search. Experiment results show that the proposed algorithm has advantages of strong optimization ability and fast convergence speed to solve the PMPOM problem.
Oil Reservoir Production Optimization using Optimal Control
DEFF Research Database (Denmark)
Völcker, Carsten; Jørgensen, John Bagterp; Stenby, Erling Halfdan
2011-01-01
Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using the adjo......Practical oil reservoir management involves solution of large-scale constrained optimal control problems. In this paper we present a numerical method for solution of large-scale constrained optimal control problems. The method is a single-shooting method that computes the gradients using...... the adjoint method. We use an Explicit Singly Diagonally Implicit Runge-Kutta (ESDIRK) method for the integration and a quasi-Newton Sequential Quadratic Programming (SQP) algorithm for the constrained optimization. We use this algorithm in a numerical case study to optimize the production of oil from an oil...... reservoir using water ooding and smart well technology. Compared to the uncontrolled case, the optimal operation increases the Net Present Value of the oil field by 10%....
2017-03-21
UNIT NUMBER None 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) B. PERFORMING ORGANIZATION AND ADDRESS(ES) REPORT NUMBER BrightBox...AutoCx Development .................................................................................................... 3 2.2 ADVANTAGES AND LIMITATIONS...control could eventually be deployed. Unfortunately, an adequate market for AutoCx products was not successfully developed despite the clear need and
The BLAIRR Irradiation Facility Hybrid Spallation Target Optimization
Energy Technology Data Exchange (ETDEWEB)
Simos N.; Hanson A.; Brown, D.; Elbakhshawn, M.
2016-04-11
BLAIRR STUDY STATUS OVERVIEW Beamline Complex Evaluation/Assessment and Adaptation to the Goals Facility Radiological Constraints ? Large scale analyses of conventional facility and integrated shield (concrete, soil)Target Optimization and Design: Beam-target interaction optimization Hadronic interaction and energy deposition limitations Single phase and Hybrid target concepts Irradiation Damage Thermo-mechanical considerations Spallation neutron fluence optimization for (a) fast neutron irradiation damage (b) moderator/reflector studies, (c) NTOF potential and optimization (d) mono-energetic neutron beam
Optimal Control of Mechanical Systems
Directory of Open Access Journals (Sweden)
Vadim Azhmyakov
2007-01-01
Full Text Available In the present work, we consider a class of nonlinear optimal control problems, which can be called “optimal control problems in mechanics.” We deal with control systems whose dynamics can be described by a system of Euler-Lagrange or Hamilton equations. Using the variational structure of the solution of the corresponding boundary-value problems, we reduce the initial optimal control problem to an auxiliary problem of multiobjective programming. This technique makes it possible to apply some consistent numerical approximations of a multiobjective optimization problem to the initial optimal control problem. For solving the auxiliary problem, we propose an implementable numerical algorithm.
Hybrid intelligent optimization methods for engineering problems
Pehlivanoglu, Yasin Volkan
quantification studies, we improved new mutation strategies and operators to provide beneficial diversity within the population. We called this new approach as multi-frequency vibrational GA or PSO. They were applied to different aeronautical engineering problems in order to study the efficiency of these new approaches. These implementations were: applications to selected benchmark test functions, inverse design of two-dimensional (2D) airfoil in subsonic flow, optimization of 2D airfoil in transonic flow, path planning problems of autonomous unmanned aerial vehicle (UAV) over a 3D terrain environment, 3D radar cross section minimization problem for a 3D air vehicle, and active flow control over a 2D airfoil. As demonstrated by these test cases, we observed that new algorithms outperform the current popular algorithms. The principal role of this multi-frequency approach was to determine which individuals or particles should be mutated, when they should be mutated, and which ones should be merged into the population. The new mutation operators, when combined with a mutation strategy and an artificial intelligent method, such as, neural networks or fuzzy logic process, they provided local and global diversities during the reproduction phases of the generations. Additionally, the new approach also introduced random and controlled diversity. Due to still being population-based techniques, these methods were as robust as the plain GA or PSO algorithms. Based on the results obtained, it was concluded that the variants of the present multi-frequency vibrational GA and PSO were efficient algorithms, since they successfully avoided all local optima within relatively short optimization cycles.
Smith, P J; Vigneswaran, S; Ngo, H H; Nguyen, H T; Ben-Aim, R
2006-01-01
The application of automation and supervisory control and data acquisition (SCADA) systems to municipal water and wastewater treatment plants is rapidly increasing. However, the application of these systems is less frequent in the research and development phases of emerging treatment technologies used in these industries. This study involved the implementation of automation and a SCADA system to the submerged membrane adsorption hybrid system for use in a semi-pilot scale research project. An incremental approach was used in the development of the automation and SCADA systems, leading to the development of two new control systems. The first system developed involved closed loop control of the backwash initiation, based upon a pressure increase, leading to productivity improvements as the backwash is only activated when required, not at a fixed time. This system resulted in a 40% reduction in the number of backwashes required and also enabled optimised operations under unsteady concentrations of wastewater. The second system developed involved closed loop control of the backwash duration, whereby the backwash was terminated when the pressure reached a steady state. This system resulted in a reduction of the duration of the backwash of up to 25% and enabled optimised operations as the foulant build-up within the reactor increased.
基于混沌粒子群算法的电梯混合能源系统控制优化%Optimization of Elevator Hybrid Energy Control Based on Chaos-PSO Algorithm
Institute of Scientific and Technical Information of China (English)
林尧; 刘艳斌; 吴城汀
2016-01-01
The optimization of elevator hybrid energy control is to optimize the control of the energy transfer among different energy supply equipment, such as elevator,solar energy,batteries and super capacitors. Based on the elevator system characteristics and on the premise of meeting the energy needed by the elevator and minimum grid energy consumption,the optimization function for the elevator hybrid energy is established. In the non-continuous switch variables in the objective optimization function,such as 0-1,the hybrid energy management optimization process is of non-linear variable parameter optimization problem,it is difficult to use the or￣dinary analytical methods to calculate it. This paper proposes to use the chaos particle swarm algorithm as the intel igent solving strat￣egy. Through simulation of the elevator, the effectiveness of the model and algorithm is verified.%电梯混合能源控制优化是对电梯、太阳能、蓄电池、超级电容等设备间的能量交换进行控制优化。根据电梯系统的特点，在满足电梯所需能量的前提下，以电网所需的耗电量最小为优化指标，建立电梯的混合能源优化目标函数。其中目标优化函数中的变量如0－1等非连续的开关变量，其混合能源管理优化过程是非线性变参数优化问题，难以用普通的解析方法进行计算。采用混沌粒子群算法的智能求解策略，通过对某电梯的仿真，验证了模型和算法的有效性。
Optimal Control of Evolutionary Dynamics
Chakrabarti, Raj; McLendon, George
2008-01-01
Elucidating the fitness measures optimized during the evolution of complex biological systems is a major challenge in evolutionary theory. We present experimental evidence and an analytical framework demonstrating how biochemical networks exploit optimal control strategies in their evolutionary dynamics. Optimal control theory explains a striking pattern of extremization in the redox potentials of electron transport proteins, assuming only that their fitness measure is a control objective functional with bounded controls.
Optimal Control of Mechanical Systems
Vadim Azhmyakov
2007-01-01
In the present work, we consider a class of nonlinear optimal control problems, which can be called “optimal control problems in mechanics.” We deal with control systems whose dynamics can be described by a system of Euler-Lagrange or Hamilton equations. Using the variational structure of the solution of the corresponding boundary-value problems, we reduce the initial optimal control problem to an auxiliary problem of multiobjective programming. This technique makes it possible to apply some ...
A Hybrid Aggressive Space Mapping Algorithm for EM Optimization
DEFF Research Database (Denmark)
Bakr, Mohamed H.; Bandler, John W.; Georgieva, N.;
1999-01-01
We propose a novel hybrid aggressive space-mapping (HASM) optimization algorithm. HASM exploits both the trust-region aggressive space-mapping (TRASM) strategy and direct optimization. Severe differences between the coarse and fine models and nonuniqueness of the parameter extraction procedure ma...
Institute of Scientific and Technical Information of China (English)
毛书军; 盛贤君
2014-01-01
In order to solve the challenging problem of optimization of five-dimensional parameters in fractional PID controller, based on the introduction of swarm intelligence algorithm and evolutionary computing, a hybrid computation intelligent learning algorithm was proposed, which combined Glowworm Swarm Optimization ( GSO) with Genetic Algorithm ( GA) . The hybrid algorithm was based on the swarm intelligence and individual evolution of creatures, which can greatly increase the accuracy of optimization and ensure that algorithm evolves to optimum. A series of experiments verify that the proposed hybrid algorithm can shorten the time of computing and increase the accuracy of simulation.%为解决分数阶PID控制器五维参数优化的难题，设计了一种把萤火虫算法和遗传算法相结合的混合计算智能算法，阐述了计算智能中的群智能算法和进化计算的基本原理和数学算法。该方法基于生物的群体智能和个体进化相结合的思想，能够有效地提高寻优精度，并使算法向最优方向不断进化。经过仿真验证，混合算法在分数阶PID参数整定方面具有运算时间短、仿真精度高等优点。
Hybrid Algorithm for Optimal Load Sharing in Grid Computing
Directory of Open Access Journals (Sweden)
A. Krishnan
2012-01-01
Full Text Available Problem statement: Grid Computing is the fast growing industry, which shares the resources in the organization in an effective manner. Resource sharing requires more optimized algorithmic structure, otherwise the waiting time and response time are increased and the resource utilization is reduced. Approach: In order to avoid such reduction in the performances of the grid system, an optimal resource sharing algorithm is required. In recent days, many load sharing technique are proposed, which provides feasibility but there are many critical issues are still present in these algorithms. Results: In this study a hybrid algorithm for optimization of load sharing is proposed. The hybrid algorithm contains two components which are Hash Table (HT and Distributed Hash Table (DHT. Conclusion: The results of the proposed study show that the hybrid algorithm will optimize the task than existing systems.
Intraply Hybrid Composites Would Contain Control Strips
Chamis, Christos C.; Shiao, Chi-Yu
1996-01-01
"Smart" structural components with sensors and/or actuators distributed throughout their volumes made of intraply hybrid composite materials, according to proposal. Strips of hybrid control material interspersed with strips of ordinary (passive) composite material in some layers, providing distributed control capability. For example, near and far edges of plate bent upward by commanding bottom control strips to expand and simultaneously commanding upper control strips to contract.
Velocity trajectory optimization in Hybrid Electric trucks
Keulen, T. van; Jager, B. de; Foster, D.L.; Steinbuch, M.
2010-01-01
Hybrid Electric Vehicles (HEVs) enable fuel savings by re-using kinetic and potential energy that was recovered and stored in a battery during braking or driving down hill. Besides, the vehicle itself can be seen as a storage device, where kinetic energy can be stored and retrieved by changing the
Fault tolerant control design for hybrid systems
Energy Technology Data Exchange (ETDEWEB)
Yang, Hao; Jiang, Bin [Nanjing University of Aeronautics and Astronautics, Nanjing (China); Cocquempot, Vincent [Universite des Sciences et Technologies de Lille, Villeneuve d' Ascq (France)
2010-07-01
This book intends to provide the readers a good understanding on how to achieve Fault Tolerant Control goal of Hybrid Systems. The book can be used as a reference for the academic research on Fault Tolerant Control and Hybrid Systems or used in Ph.D. study of control theory and engineering. The knowledge background for this monograph would be some undergraduate and graduate courses on Fault Diagnosis and Fault Tolerant Control theory, linear system theory, nonlinear system theory, Hybrid Systems theory and Discrete Event System theory. (orig.)
Power Management Optimization of an Experimental Fuel Cell/Battery/Supercapacitor Hybrid System
Farouk Odeim; Jürgen Roes; Angelika Heinzel
2015-01-01
In this paper, an experimental fuel cell/battery/supercapacitor hybrid system is investigated in terms of modeling and power management design and optimization. The power management strategy is designed based on the role that should be played by each component of the hybrid power source. The supercapacitor is responsible for the peak power demands. The battery assists the supercapacitor in fulfilling the transient power demand by controlling its state-of-energy, whereas the fuel cell system, ...
A Hybrid Algorithm for Optimizing Multi- Modal Functions
Institute of Scientific and Technical Information of China (English)
Li Qinghua; Yang Shida; Ruan Youlin
2006-01-01
A new genetic algorithm is presented based on the musical performance. The novelty of this algorithm is that a new genetic algorithm, mimicking the musical process of searching for a perfect state of harmony, which increases the robustness of it greatly and gives a new meaning of it in the meantime, has been developed. Combining the advantages of the new genetic algorithm, simplex algorithm and tabu search, a hybrid algorithm is proposed. In order to verify the effectiveness of the hybrid algorithm, it is applied to solving some typical numerical function optimization problems which are poorly solved by traditional genetic algorithms. The experimental results show that the hybrid algorithm is fast and reliable.
MAKHA—A New Hybrid Swarm Intelligence Global Optimization Algorithm
Directory of Open Access Journals (Sweden)
Ahmed M.E. Khalil
2015-06-01
Full Text Available The search for efficient and reliable bio-inspired optimization methods continues to be an active topic of research due to the wide application of the developed methods. In this study, we developed a reliable and efficient optimization method via the hybridization of two bio-inspired swarm intelligence optimization algorithms, namely, the Monkey Algorithm (MA and the Krill Herd Algorithm (KHA. The hybridization made use of the efficient steps in each of the two original algorithms and provided a better balance between the exploration/diversification steps and the exploitation/intensification steps. The new hybrid algorithm, MAKHA, was rigorously tested with 27 benchmark problems and its results were compared with the results of the two original algorithms. MAKHA proved to be considerably more reliable and more efficient in tested problems.
HYBRID CONTROL APPROACH FOR CONTAINER CRANES
Institute of Scientific and Technical Information of China (English)
Wang Xiaojun; Shao Huihe
2005-01-01
A hybrid control approach is proposed to achieve the desired performance. Firstly a robust input shaper is designed to reduce the transient vibration and residual vibration of the container efficiently. Then a simple fuzzy logic controller is designed to eliminate the residual vibration completely in order to guarantee the positioning precision. Such a hybrid approach is simple in structure and readily realizable. Simulation results verify the fine performance of this hybrid control approach. It can achieve perfect elimination of residual vibration and concise positioning of the container load, and it is robust to parameter variations (mainly for cable length) and external disturbances.
Real Time Energy Management Control Strategies for Hybrid Powertrains
Zaher, Mohamed Hegazi Mohamed
In order to improve fuel efficiency and reduce emissions of mobile vehicles, various hybrid power-train concepts have been developed over the years. This thesis focuses on embedded control of hybrid powertrain concepts for mobile vehicle applications. Optimal robust control approach is used to develop a real time energy management strategy for continuous operations. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in opposite direction to the applied force or torque. This is the case when the vehicle is braking, decelerating, or the motion is driven by gravitational force, or load driven. There are three main concepts for regernerative energy storing devices in hybrid vehicles: electric, hydraulic, and flywheel. The real time control challenge is to balance the system power demand from the engine and the hybrid storage device, without depleting the energy storage device or stalling the engine in any work cycle, while making optimal use of the energy saving opportunities in a given operational, often repetitive cycle. In the worst case scenario, only engine is used and hybrid system completely disabled. A rule based control is developed and tuned for different work cycles and linked to a gain scheduling algorithm. A gain scheduling algorithm identifies the cycle being performed by the machine and its position via GPS, and maps them to the gains.
Directory of Open Access Journals (Sweden)
Weichao Zhuang
2016-05-01
Full Text Available Hybrid powertrain technologies are successful in the passenger car market and have been actively developed in recent years. Optimal topology selection, component sizing, and controls are required for competitive hybrid vehicles, as multiple goals must be considered simultaneously: fuel efficiency, emissions, performance, and cost. Most of the previous studies explored these three design dimensions separately. In this paper, two novel frameworks combining these three design dimensions together are presented and compared. One approach is nested optimization which searches through the whole design space exhaustively. The second approach is called enhanced iterative optimization, which executes the topology optimization and component sizing alternately. A case study shows that the later method can converge to the global optimal design generated from the nested optimization, and is much more computationally efficient. In addition, we also address a known issue of optimal designs: their sensitivity to parameters, such as varying vehicle weight, which is a concern especially for the design of hybrid buses. Therefore, the iterative optimization process is applied to design a robust multi-mode hybrid electric bus under different loading scenarios as the final design challenge of this paper.
Institute of Scientific and Technical Information of China (English)
吴晓刚; 王旭东; 孙金磊; 崔明琦
2011-01-01
In the process of controlling the energy distribution of ISG hybrid vehicle, lower precision and limited adaptive capability were caused by using the traditional fuzzy control strategy. A novel particle swarm optimization fuzzy control strategy was proposed. By using particle swarm algorithm, the membership function was optimized based on the control model built by the traditional fuzzy logic. The fuzzy controller parameters that real-time traced by the optimized membership function with environment and load changing was realized.The simulation result shows that this method is able to reduce the change of battery SOC and improve the fuel economy of hybrid electric system compared with using Insight control strategy and the traditional fuzzy control strategy. The experimental result proves that the battery SOC can be controlled within a reasonable scope with this method.%针对ISG型混合动力汽车能量分配的控制过程,应用传统的模糊控制存在精度不高、自适应能力有限等问题.提出一种粒子群优化模糊控制的方法.在应用传统模糊逻辑建立控制模型基础上,利用粒子群算法对模糊控制中的隶属度函数进行优化,实现了优化的隶属度函数随环境变化以及负载变化实时跟踪模糊控制器的参数变化.仿真结果表明,与Insight控制策略和传统模糊控制策略相比,该方法能够降低电池组SOC变化,同时提高混合动力系统的燃油经济性.试验结果验证使用该方法能够在一定程度上将电池SOC控制在比较合理的范围.
GPAW optimized for Blue Gene/P using hybrid programming
DEFF Research Database (Denmark)
Kristensen, Mads Ruben Burgdorff; Happe, Hans Henrik; Vinter, Brian
2009-01-01
In this work we present optimizations of a Grid-based projector-augmented wave method software, GPAW for the Blue Gene/P architecture. The improvements are achieved by exploring the advantage of shared and distributed memory programming also known as hybrid programming. The work focuses on optimi......In this work we present optimizations of a Grid-based projector-augmented wave method software, GPAW for the Blue Gene/P architecture. The improvements are achieved by exploring the advantage of shared and distributed memory programming also known as hybrid programming. The work focuses...
An Effective Hybrid Optimization Algorithm for Capacitated Vehicle Routing Problem
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Capacitated vehicle routing problem (CVRP) is an important combinatorial optimization problem. However, it is quite difficult to achieve an optimal solution with the traditional optimization methods owing to the high computational complexity. A hybrid algorithm was developed to solve the problem, in which an artificial immune clonal algorithm (AICA) makes use of the global search ability to search the optimal results and simulated annealing (SA) algorithm employs certain probability to avoid becoming trapped in a local optimum. The results obtained from the computational study show that the proposed algorithm is a feasible and effective method for capacitated vehicle routing problem.
Directory of Open Access Journals (Sweden)
Serrao L.
2013-03-01
Full Text Available Energy management of hybrid propulsion systems is considered, presenting new issues that extend the energy management role beyond the standard torque splitting to maximize system efficiency. The new issues include additional optimization criteria, constraints and relevant dynamics to deal with. New optimization criteria in addition the sole fuel consumption minimization include engine-out pollutant emissions and battery aging. State constraints are modified to account for plug-in hybrid vehicles. Moreover, specific supervisory control problems are recognized to need additional state variables. The latter comprise: engine and catalyst temperature to deal with engine warm-up effects on fuel consumption and after-catalyst emissions; thermal dynamics of heat recovery systems (Rankine or Thermo-Electric Generators, TEGs; and battery temperature, which influences battery performance and aging. It is shown that all these control problems can be treated in an unified fashion by extending the well-known ECMS (Equivalent Consumption Minimization Strategy, which is an implementation of Pontryagin Minimum Principle (PMP as formulated by optimal control theory. Extended definitions of the Hamiltonian function and Lagrange multipliers are introduced. Optimization runs performed off line are reported. Results show the benefits of the proposed unified approach and enlighten some first online implementation issues. Cet article a pour objet la gestion optimale de l’énergie pour un système de propulsion hybride. Le problème traditionnel de répartition de la puissance est modifié avec des nouveaux objectifs d’optimisation et des nouvelles contraintes. Les nouveaux objectifs d’optimisation incluent les émissions de polluants et le vieillissement de la batterie. Les contraintes sont modifiées pour prendre en compte des batteries à recharge externe (hybrides plug-in. De plus, des problèmes spécifiques sont traités avec une modélisation plus d
OPTIMIZED GATEWAY DISCOVERY IN HYBRID MANETS
Directory of Open Access Journals (Sweden)
A.Triviño
2009-10-01
Full Text Available Mobile users are expected to demand access to the Internet anywhere and anytime. In a MANET context,a device which is about to connect to external hosts needs the route to the element which communicatesthe MANET with the Internet. This element is the Internet Gateway. To inform about its presence as wellas about some configuration parameters, the Gateway sends MRA messages. In a similar way to ad hocrouting protocols, the Gateway can generate the messages on demand (reactively, periodically(proactively or combining both previous strategies in a hybrid gateway discovery. Specifically, in thehybrid gateway discovery, the Gateway periodically sends the MRA messages in a restricted area. Thenodes that are outside this area demand the Gateway information reactively. This gateway discoveryrequires the setting of the number of hops that define the proactive area, also called the TTL value.Network performance can be improved when the Gateway uses information such as the position of thesources to adjust the TTL value. In this paper, we transfer the decision about the dimensions of theproactive zone to the mobile nodes so more network conditions are taken into account. Simulation resultsshow that the proposed gateway discovery outperforms other hybrid gateway discovery schemes.
Predictive cruise control in hybrid electric vehicles
Keulen, T. van; Naus, M.J.G.; Jager, B. de; Molengraft, G.J.L. van de; Steinbuch, M.; Aneke, N.P.I.
2009-01-01
Deceleration rates have considerable influence on the fuel economy of hybrid electric vehicles. Given the vehicle characteristics and actual/measured operating conditions, as well as upcoming route information, optimal velocity trajectories can be constructed that maximize energy recovery. To suppor
Cost Optimization Using Hybrid Evolutionary Algorithm in Cloud Computing
Directory of Open Access Journals (Sweden)
B. Kavitha
2015-07-01
Full Text Available The main aim of this research is to design the hybrid evolutionary algorithm for minimizing multiple problems of dynamic resource allocation in cloud computing. The resource allocation is one of the big problems in the distributed systems when the client wants to decrease the cost for the resource allocation for their task. In order to assign the resource for the task, the client must consider the monetary cost and computational cost. Allocation of resources by considering those two costs is difficult. To solve this problem in this study, we make the main task of client into many subtasks and we allocate resources for each subtask instead of selecting the single resource for the main task. The allocation of resources for the each subtask is completed through our proposed hybrid optimization algorithm. Here, we hybrid the Binary Particle Swarm Optimization (BPSO and Binary Cuckoo Search algorithm (BCSO by considering monetary cost and computational cost which helps to minimize the cost of the client. Finally, the experimentation is carried out and our proposed hybrid algorithm is compared with BPSO and BCSO algorithms. Also we proved the efficiency of our proposed hybrid optimization algorithm.
Review of the Optimal Design on a Hybrid Renewable Energy System
Directory of Open Access Journals (Sweden)
Wu Yuan-Kang
2016-01-01
Full Text Available Hybrid renewable energy systems, combining various kinds of technologies, have shown relatively high capabilities to solve reliability problems and have reduced cost challenges. The use of hybrid electricity generation/storage technologies is reasonable to overcome related shortcomings. While the hybrid renewable energy system is attractive, its design, specifically the determination of the size of PV, wind, and diesel power generators and the size of energy storage system in each power station, is very challenging. Therefore, this paper will focus on the system planning and operation of hybrid generation systems, and several corresponding topics and papers by using intelligent computing methods will be reviewed. They include typical case studies, modeling and system simulation, control and management, reliability and economic studies, and optimal design on a reliable hybrid generation system.
Optimal magnetic attitude control
DEFF Research Database (Denmark)
Wisniewski, Rafal; Markley, F.L.
1999-01-01
because control torques can only be generated perpendicular to the local geomagnetic field vector. This has been a serious obstacle for using magnetorquer based control for three-axis stabilization of a low earth orbit satellite. The problem of controlling the spacecraft attitude using only magnetic...
Non-binary Hybrid LDPC Codes: Structure, Decoding and Optimization
Sassatelli, Lucile
2007-01-01
In this paper, we propose to study and optimize a very general class of LDPC codes whose variable nodes belong to finite sets with different orders. We named this class of codes Hybrid LDPC codes. Although efficient optimization techniques exist for binary LDPC codes and more recently for non-binary LDPC codes, they both exhibit drawbacks due to different reasons. Our goal is to capitalize on the advantages of both families by building codes with binary (or small finite set order) and non-binary parts in their factor graph representation. The class of Hybrid LDPC codes is obviously larger than existing types of codes, which gives more degrees of freedom to find good codes where the existing codes show their limits. We give two examples where hybrid LDPC codes show their interest.
Optimal control studies for steamflooding
Energy Technology Data Exchange (ETDEWEB)
Liu, Wei.
1992-01-01
A system science approach using optimal control theory of distributed parameter systems has been developed to determine operating strategies that maximize the economic attractiveness of the steamflooding Enhanced Oil Recovery (EOR) process. Necessary conditions for optimization are established by using the calculus of variations and Pontryagin's Maximum Principle. The objective criterion is to maximize the difference between oil revenue and injected steam cost. A stable and efficient numerical algorithm, based on an iterative gradient method, is developed. The optimal control model is based on a three-dimensional, three-phase (oil, steam and water) steam injection numerical simulator. A discrete form of the model is formulated. The optimized operating variables are the optimal bottom-hole pressure, the optimal injection rate of steam and water, and the optimal steam quality policies. Another optimal control study is also conducted on a simplified one-dimensional model (the extended Neuman model) to provide quick and reliable preliminary information on the economic feasibility of steamflooding processes. The simplified control model only considers the injection rate of steam as the control variable. The performance of this system science approach is investigated through various one-, two- and three-dimensional steamflooding problems. The effects of reservoir properties and heterogeneity on optimal policies as well as the sensitivity of the control variables are also studied. Results show this approach yields significant insight into the steamflooding EOR process. Improvement of the economic objective is significant under optimal operation conditions. These optimization results are quite important in a successful application of the steamflooding EOR method.
Hybrid Optimization in the Design of Reciprocal Structures
DEFF Research Database (Denmark)
Parigi, Dario; Kirkegaard, Poul Henning; Sassone, Mario
2012-01-01
The paper presents a method to generate the geometry of reciprocal structures by means of a hybrid optimization procedure. The geometry of reciprocal structures where elements are sitting on the top or in the bottom of each other is extremely difficult to predict because of the non...... is then applied to a recent example of free-form reciprocal structure....
Directory of Open Access Journals (Sweden)
Hyo Seon Park
2014-01-01
Full Text Available Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.
1979-12-01
with Uncertain Components 44 13 Component Uncertainty Representation of Uncertain Pole-Zero Locations 46 12 A Feedback Control System 60 i 1 I vii €in...OF FEEDBACK SYSTEM ROBUSTNESS A feedback control system design is said to be robust if it is able to meet design specifications despite differences... feedback control system design problems, the design specifications usually demand that the system be "robust" against the effects of deviations within
A Hybrid Mutation Chemical Reaction Optimization Algorithm for Global Numerical Optimization
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Ransikarn Ngambusabongsopa
2015-01-01
Full Text Available This paper proposes a hybrid metaheuristic approach that improves global numerical optimization by increasing optimal quality and accelerating convergence. This algorithm involves a recently developed process for chemical reaction optimization and two adjustment operators (turning and mutation operators. Three types of mutation operators (uniform, nonuniform, and polynomial were combined with chemical reaction optimization and turning operator to find the most appropriate framework. The best solution among these three options was selected to be a hybrid mutation chemical reaction optimization algorithm for global numerical optimization. The optimal quality, convergence speed, and statistical hypothesis testing of our algorithm are superior to those previous high performance algorithms such as RCCRO, HP-CRO2, and OCRO.
Modular supervisory controller for hybrid power systems
Energy Technology Data Exchange (ETDEWEB)
Lemos Pereira, A. de
2000-06-01
The power supply of remote places has been commonly provided by thermal power plants, usually diesel generators. Although hybrid power systems may constitute the most economical solution in many applications their widespread application to the electrification schemes of remote areas still depends on improvements in the issues of design and operation control. The main limitations of the present hybrid power systems technology, which are identified in this work, are related to the control and supervision of the power system. Therefore this thesis focuses on the modularity of supervisory controllers in order to design cost-competitive and reliable hybrid power systems. The modular supervisory controller created in this project is considered an important part of a system design approach that aims to overcome the technical difficulties of the current engineering practice and contribute to open the market of hybrid power systems. The term modular refers to a set of design characteristics that allows the use of basically the same supervisory controller in different projects. The modularization and standardisation of the controller include several issues such as interfacing components, communication protocols, modelling, programming and control strategies. The modularity can reduce the highly specialised system engineering related to the integration of components, operation and control. It can also avoid the high costs for installation, service and maintenance. A modular algorithm for supervisory controllers has been developed (a Matlab program called SuperCon) using an object-oriented design and it has been tested through several simulations using different hybrid system configurations and different control strategies. This thesis presents a complete control system design process which can be used as the basis for the development and implementation of intelligent and autonomous supervisory controllers for hybrid power systems with modular characteristics. (au)
Evolved Finite State Controller For Hybrid System
DEFF Research Database (Denmark)
Dupuis, Jean-Francois; Fan, Zhun; Goodman, Erik
2009-01-01
This paper presents an evolutionary methodology to automatically generate nite state automata (FSA) controllers to control hybrid systems. FSA controllers for a case study of two-tank system have been successfully obtained using the proposed evolutionary approach. Experimental results show...
Optimal control in thermal engineering
Badescu, Viorel
2017-01-01
This book is the first major work covering applications in thermal engineering and offering a comprehensive introduction to optimal control theory, which has applications in mechanical engineering, particularly aircraft and missile trajectory optimization. The book is organized in three parts: The first part includes a brief presentation of function optimization and variational calculus, while the second part presents a summary of the optimal control theory. Lastly, the third part describes several applications of optimal control theory in solving various thermal engineering problems. These applications are grouped in four sections: heat transfer and thermal energy storage, solar thermal engineering, heat engines and lubrication.Clearly presented and easy-to-use, it is a valuable resource for thermal engineers and thermal-system designers as well as postgraduate students.
An Optimization Framework for Dynamic Hybrid Energy Systems
Energy Technology Data Exchange (ETDEWEB)
Wenbo Du; Humberto E Garcia; Christiaan J.J. Paredis
2014-03-01
A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problem takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.
Full Gradient Solution to Adaptive Hybrid Control
Bean, Jacob; Schiller, Noah H.; Fuller, Chris
2017-01-01
This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.
Hybrid dynamical systems observation and control
Defoort, Michael
2015-01-01
This book is a collection of contributions defining the state of current knowledge and new trends in hybrid systems – systems involving both continuous dynamics and discrete events – as described by the work of several well-known groups of researchers. Hybrid Dynamical Systems presents theoretical advances in such areas as diagnosability, observability and stabilization for various classes of system. Continuous and discrete state estimation and self-triggering control of nonlinear systems are advanced. The text employs various methods, among them, high-order sliding modes, Takagi–Sugeno representation and sampled-data switching to achieve its ends. The many applications of hybrid systems from power converters to computer science are not forgotten; studies of flexible-joint robotic arms and – as representative biological systems – the behaviour of the human heart and vasculature, demonstrate the wide-ranging practical significance of control in hybrid systems. The cross-disciplinary origins of study ...
Optimal Power Scheduling for an Islanded Hybrid Microgrid
DEFF Research Database (Denmark)
Hernández, Adriana Carolina Luna; Aldana, Nelson Leonardo Diaz; Savaghebi, Mehdi
2016-01-01
A microgrid is a system that integrates energy generation, energy storage, and loads and it is able to operate either in interconnected or islanded mode. Energy resources should be scheduled to supply the load properly in order to coordinate optimally the power exchange within the microgrid...... according to a defined objective function. In this paper, an optimal power scheduling for generation and demand side is presented to manage an islanded hybrid PV-wind-battery microgrid implemented in Shanghai-China. The optimization is addressed through a Mixed-Integer Linear Programming (MILP) mathematical......SPACE1006) in which a scaled down model of this microgrid is emulated....
A Hybrid Backtracking Search Optimization Algorithm with Differential Evolution
Directory of Open Access Journals (Sweden)
Lijin Wang
2015-01-01
Full Text Available The backtracking search optimization algorithm (BSA is a new nature-inspired method which possesses a memory to take advantage of experiences gained from previous generation to guide the population to the global optimum. BSA is capable of solving multimodal problems, but it slowly converges and poorly exploits solution. The differential evolution (DE algorithm is a robust evolutionary algorithm and has a fast convergence speed in the case of exploitive mutation strategies that utilize the information of the best solution found so far. In this paper, we propose a hybrid backtracking search optimization algorithm with differential evolution, called HBD. In HBD, DE with exploitive strategy is used to accelerate the convergence by optimizing one worse individual according to its probability at each iteration process. A suit of 28 benchmark functions are employed to verify the performance of HBD, and the results show the improvement in effectiveness and efficiency of hybridization of BSA and DE.
OPTIMIZATION OF HYBRID FINAL ADDER FOR THE HIGH PERFORMANCE MULTIPLIER
Directory of Open Access Journals (Sweden)
RAMKUMAR B.
2013-04-01
Full Text Available In this work we evaluated arrival profile of the HPM based multiplier partial products reduction tree in two ways: 1.manual delay, area calculation through logical effort, 2.ASIC implementation. Based on the arrival profile, we worked with some recently proposed optimal adders and finally we proposed an optimal hybrid adder for the final addition in HPM based parallel multiplier. This work derives some mathematical expressions to find the size of different regions in the partial product arrival profile which helps to design optimal adder for each region. This work evaluates the performance of proposed hybrid adder in terms of area, power and delay using 90nm technology. This work deals with manual calculation for 8-b and ASIC simulation of different adder designs for 8-b, 16-b, 32-b and 64-b multiplier bit sizes.
Symposium on Optimal Control Theory
1987-01-01
Control theory can be roughly classified as deterministic or stochastic. Each of these can further be subdivided into game theory and optimal control theory. The central problem of control theory is the so called constrained maximization (which- with slight modifications--is equivalent to minimization). One can then say, heuristically, that the major problem of control theory is to find the maximum of some performance criterion (or criteria), given a set of constraints. The starting point is, of course, a mathematical representation of the performance criterion (or criteria)- sometimes called the objective functional--along with the constraints. When the objective functional is single valued (Le. , when there is only one objective to be maximized), then one is dealing with optimal control theory. When more than one objective is involved, and the objectives are generally incompatible, then one is dealing with game theory. The first paper deals with stochastic optimal control, using the dynamic programming ...
Duan, Hai-Bin; Xu, Chun-Fang; Xing, Zhi-Hui
2010-02-01
In this paper, a novel hybrid Artificial Bee Colony (ABC) and Quantum Evolutionary Algorithm (QEA) is proposed for solving continuous optimization problems. ABC is adopted to increase the local search capacity as well as the randomness of the populations. In this way, the improved QEA can jump out of the premature convergence and find the optimal value. To show the performance of our proposed hybrid QEA with ABC, a number of experiments are carried out on a set of well-known Benchmark continuous optimization problems and the related results are compared with two other QEAs: the QEA with classical crossover operation, and the QEA with 2-crossover strategy. The experimental comparison results demonstrate that the proposed hybrid ABC and QEA approach is feasible and effective in solving complex continuous optimization problems.
Shankar, R; Marco, James; Assadian, Francis
2012-01-01
The adoption of Plug-in Hybrid Electric Vehicles (PHEVs) is widely seen as an interim solution for the decarbonization of the transport sector. Within a PHEV, determining the required energy storage capacity of the battery remains one of the primary concerns for vehicle manufacturers and system integrators. This fact is particularly pertinent since the battery constitutes the largest contributor to vehicle mass. Furthermore, the financial cost associated with the procurement, design and integ...
Armentum: a hybrid direct search optimization methodology
Briones, Francisco Zorrilla
2016-07-01
Design of experiments (DOE) offers a great deal of benefits to any manufacturing organization, such as characterization of variables and sets the path for the optimization of the levels of these variables (settings) trough the Response surface methodology, leading to process capability improvement, efficiency increase, cost reduction. Unfortunately, the use of these methodologies is very limited due to various situations. Some of these situations involve the investment on production time, materials, personnel, equipment; most of organizations are not willing to invest in these resources or are not capable because of production demands, besides the fact that they will produce non-conformant product (scrap) during the process of experimentation. Other methodologies, in the form of algorithms, may be used to optimize a process. Known as direct search methods, these algorithms search for an optimum on an unknown function, trough the search of the best combination of the levels on the variables considered in the analysis. These methods have a very different application strategy, they search on the best combination of parameters, during the normal production run, calculating the change in the input variables and evaluating the results in small steps until an optimum is reached. These algorithms are very sensible to internal noise (variation of the input variables), among other disadvantages. In this paper it is made a comparison between the classical experimental design and one of these direct search methods, developed by Nelder and Mead (1965), known as the Nelder Mead simplex (NMS), trying to overcome the disadvantages and maximize the advantages of both approaches, trough a proposed combination of the two methodologies.
Optimal control theory an introduction
Kirk, Donald E
2004-01-01
Optimal control theory is the science of maximizing the returns from and minimizing the costs of the operation of physical, social, and economic processes. Geared toward upper-level undergraduates, this text introduces three aspects of optimal control theory: dynamic programming, Pontryagin's minimum principle, and numerical techniques for trajectory optimization.Chapters 1 and 2 focus on describing systems and evaluating their performances. Chapter 3 deals with dynamic programming. The calculus of variations and Pontryagin's minimum principle are the subjects of chapters 4 and 5, and chapter
Hybrid Modeling and Optimization of Yogurt Starter Culture Continuous Fermentation
Directory of Open Access Journals (Sweden)
Silviya Popova
2009-10-01
Full Text Available The present paper presents a hybrid model of yogurt starter mixed culture fermentation. The main nonlinearities within a classical structure of continuous process model are replaced by neural networks. The new hybrid model accounts for the dependence of the two microorganisms' kinetics from the on-line measured characteristics of the culture medium - pH. Then the model was used further for calculation of the optimal time profile of pH. The obtained results are with agreement with the experimental once.
Advanced hybrid and electric vehicles system optimization and vehicle integration
2016-01-01
This contributed volume contains the results of the research program “Agreement for Hybrid and Electric Vehicles”, funded by the International Energy Agency. The topical focus lies on technology options for the system optimization of hybrid and electric vehicle components and drive train configurations which enhance the energy efficiency of the vehicle. The approach to the topic is genuinely interdisciplinary, covering insights from fields. The target audience primarily comprises researchers and industry experts in the field of automotive engineering, but the book may also be beneficial for graduate students.
Modeling, hybridization, and optimal charging of electrical energy storage systems
Parvini, Yasha
The rising rate of global energy demand alongside the dwindling fossil fuel resources has motivated research for alternative and sustainable solutions. Within this area of research, electrical energy storage systems are pivotal in applications including electrified vehicles, renewable power generation, and electronic devices. The approach of this dissertation is to elucidate the bottlenecks of integrating supercapacitors and batteries in energy systems and propose solutions by the means of modeling, control, and experimental techniques. In the first step, the supercapacitor cell is modeled in order to gain fundamental understanding of its electrical and thermal dynamics. The dependence of electrical parameters on state of charge (SOC), current direction and magnitude (20-200 A), and temperatures ranging from -40°C to 60°C was embedded in this computationally efficient model. The coupled electro-thermal model was parameterized using specifically designed temporal experiments and then validated by the application of real world duty cycles. Driving range is one of the major challenges of electric vehicles compared to combustion vehicles. In order to shed light on the benefits of hybridizing a lead-acid driven electric vehicle via supercapacitors, a model was parameterized for the lead-acid battery and combined with the model already developed for the supercapacitor, to build the hybrid battery-supercapacitor model. A hardware in the loop (HIL) setup consisting of a custom built DC/DC converter, micro-controller (muC) to implement the power management strategy, 12V lead-acid battery, and a 16.2V supercapacitor module was built to perform the validation experiments. Charging electrical energy storage systems in an efficient and quick manner, motivated to solve an optimal control problem with the objective of maximizing the charging efficiency for supercapacitors, lead-acid, and lithium ion batteries. Pontryagins minimum principle was used to solve the problems
Hybrid and adaptive meta-model-based global optimization
Gu, J.; Li, G. Y.; Dong, Z.
2012-01-01
As an efficient and robust technique for global optimization, meta-model-based search methods have been increasingly used in solving complex and computation intensive design optimization problems. In this work, a hybrid and adaptive meta-model-based global optimization method that can automatically select appropriate meta-modelling techniques during the search process to improve search efficiency is introduced. The search initially applies three representative meta-models concurrently. Progress towards a better performing model is then introduced by selecting sample data points adaptively according to the calculated values of the three meta-models to improve modelling accuracy and search efficiency. To demonstrate the superior performance of the new algorithm over existing search methods, the new method is tested using various benchmark global optimization problems and applied to a real industrial design optimization example involving vehicle crash simulation. The method is particularly suitable for design problems involving computation intensive, black-box analyses and simulations.
Design Optimization of a Hybrid Electric Vehicle Powertrain
Mangun, Firdause; Idres, Moumen; Abdullah, Kassim
2017-03-01
This paper presents an optimization work on hybrid electric vehicle (HEV) powertrain using Genetic Algorithm (GA) method. It focused on optimization of the parameters of powertrain components including supercapacitors to obtain maximum fuel economy. Vehicle modelling is based on Quasi-Static-Simulation (QSS) backward-facing approach. A combined city (FTP-75)-highway (HWFET) drive cycle is utilized for the design process. Seeking global optimum solution, GA was executed with different initial settings to obtain sets of optimal parameters. Starting from a benchmark HEV, optimization results in a smaller engine (2 l instead of 3 l) and a larger battery (15.66 kWh instead of 2.01 kWh). This leads to a reduction of 38.3% in fuel consumption and 30.5% in equivalent fuel consumption. Optimized parameters are also compared with actual values for HEV in the market.
Optimality principles in sensorimotor control.
Todorov, Emanuel
2004-09-01
The sensorimotor system is a product of evolution, development, learning and adaptation-which work on different time scales to improve behavioral performance. Consequently, many theories of motor function are based on 'optimal performance': they quantify task goals as cost functions, and apply the sophisticated tools of optimal control theory to obtain detailed behavioral predictions. The resulting models, although not without limitations, have explained more empirical phenomena than any other class. Traditional emphasis has been on optimizing desired movement trajectories while ignoring sensory feedback. Recent work has redefined optimality in terms of feedback control laws, and focused on the mechanisms that generate behavior online. This approach has allowed researchers to fit previously unrelated concepts and observations into what may become a unified theoretical framework for interpreting motor function. At the heart of the framework is the relationship between high-level goals, and the real-time sensorimotor control strategies most suitable for accomplishing those goals.
Optimal design of a hybridization scheme with a fuel cell using genetic optimization
Rodriguez, Marco A.
Fuel cell is one of the most dependable "green power" technologies, readily available for immediate application. It enables direct conversion of hydrogen and other gases into electric energy without any pollution of the environment. However, the efficient power generation is strictly stationary process that cannot operate under dynamic environment. Consequently, fuel cell becomes practical only within a specially designed hybridization scheme, capable of power storage and power management functions. The resultant technology could be utilized to its full potential only when both the fuel cell element and the entire hybridization scheme are optimally designed. The design optimization in engineering is among the most complex computational tasks due to its multidimensionality, nonlinearity, discontinuity and presence of constraints in the underlying optimization problem. this research aims at the optimal utilization of the fuel cell technology through the use of genetic optimization, and advance computing. This study implements genetic optimization in the definition of optimum hybridization rules for a PEM fuel cell/supercapacitor power system. PEM fuel cells exhibit high energy density but they are not intended for pulsating power draw applications. They work better in steady state operation and thus, are often hybridized. In a hybrid system, the fuel cell provides power during steady state operation while capacitors or batteries augment the power of the fuel cell during power surges. Capacitors and batteries can also be recharged when the motor is acting as a generator. Making analogies to driving cycles, three hybrid system operating modes are investigated: 'Flat' mode, 'Uphill' mode, and 'Downhill' mode. In the process of discovering the switching rules for these three modes, we also generate a model of a 30W PEM fuel cell. This study also proposes the optimum design of a 30W PEM fuel cell. The PEM fuel cell model and hybridization's switching rules are postulated
Novel hybrid method: pulse CO2 laser-TIG hybrid welding by coordinated control
Institute of Scientific and Technical Information of China (English)
Chen Yanbin; Lei Zhenglong; Li Liqun; Wu Lin; Xie Cheng
2006-01-01
In continuous wave CO2 laser-TIG hybrid welding process, the laser energy is not fully utilized because of the absorption and defocusing by plasma in the arc space. Therefore, the optimal welding result can only be achieved in a limited energy range. In order to improve the welding performance further, a novel hybrid welding method-pulse CO2 laser-TIG arc hybrid welding by coordinated control is proposed and investigated. The experimental results indicate that, compared with continuous wave CO2 laser-TIG hybrid welding, the absorption and defocusing of laser energy by plasma are decreased further, and at the same time, the availability ratio of laser and arc energy can be increased when a coordinated frequency is controlled. As a result, the weld appearance is also improved as well as the weld depth is deepened. Furthermore, the effect of frequency and phase of pulse laser and TIG arc on the arc images and welding characteristics is also studied. However, the novel hybrid method has great potentials in the application of industrials from views of techniques and economy.
Verification and optimization of a PLC control schedule
Brinksma, Ed; Mader, Angelika; Fehnker, Ansgar
2002-01-01
We report on the use of model checking techniques for both the verification of a process control program and the derivation of optimal control schedules. Most of this work has been carried out as part of a case study for the EU VHS project (Verification of Hybrid Systems), in which the program for a
Energy Optimization for a Weak Hybrid Power System of an Automobile Exhaust Thermoelectric Generator
Fang, Wei; Quan, Shuhai; Xie, Changjun; Tang, Xinfeng; Ran, Bin; Jiao, Yatian
2017-07-01
An integrated starter generator (ISG)-type hybrid electric vehicle (HEV) scheme is proposed based on the automobile exhaust thermoelectric generator (AETEG). An eddy current dynamometer is used to simulate the vehicle's dynamic cycle. A weak ISG hybrid bench test system is constructed to test the 48 V output from the power supply system, which is based on engine exhaust-based heat power generation. The thermoelectric power generation-based system must ultimately be tested when integrated into the ISG weak hybrid mixed power system. The test process is divided into two steps: comprehensive simulation and vehicle-based testing. The system's dynamic process is simulated for both conventional and thermoelectric powers, and the dynamic running process comprises four stages: starting, acceleration, cruising and braking. The quantity of fuel available and battery pack energy, which are used as target vehicle energy functions for comparison with conventional systems, are simplified into a single energy target function, and the battery pack's output current is used as the control variable in the thermoelectric hybrid energy optimization model. The system's optimal battery pack output current function is resolved when its dynamic operating process is considered as part of the hybrid thermoelectric power generation system. In the experiments, the system bench is tested using conventional power and hybrid thermoelectric power for the four dynamic operation stages. The optimal battery pack curve is calculated by functional analysis. In the vehicle, a power control unit is used to control the battery pack's output current and minimize energy consumption. Data analysis shows that the fuel economy of the hybrid power system under European Driving Cycle conditions is improved by 14.7% when compared with conventional systems.
A hybrid optimization approach in non-isothermal glass molding
Vu, Anh-Tuan; Kreilkamp, Holger; Krishnamoorthi, Bharathwaj Janaki; Dambon, Olaf; Klocke, Fritz
2016-10-01
Intensively growing demands on complex yet low-cost precision glass optics from the today's photonic market motivate the development of an efficient and economically viable manufacturing technology for complex shaped optics. Against the state-of-the-art replication-based methods, Non-isothermal Glass Molding turns out to be a promising innovative technology for cost-efficient manufacturing because of increased mold lifetime, less energy consumption and high throughput from a fast process chain. However, the selection of parameters for the molding process usually requires a huge effort to satisfy precious requirements of the molded optics and to avoid negative effects on the expensive tool molds. Therefore, to reduce experimental work at the beginning, a coupling CFD/FEM numerical modeling was developed to study the molding process. This research focuses on the development of a hybrid optimization approach in Non-isothermal glass molding. To this end, an optimal configuration with two optimization stages for multiple quality characteristics of the glass optics is addressed. The hybrid Back-Propagation Neural Network (BPNN)-Genetic Algorithm (GA) is first carried out to realize the optimal process parameters and the stability of the process. The second stage continues with the optimization of glass preform using those optimal parameters to guarantee the accuracy of the molded optics. Experiments are performed to evaluate the effectiveness and feasibility of the model for the process development in Non-isothermal glass molding.
Raza, Syed Ahsan; Hassan, Syed Ali; Pervaiz, Haris Bin; Ni, Qiang; Musavian, Leila
2016-01-01
Millimeter wave (mmWave) and Device-to-Device (D2D) communications have been considered as the key enablers of the next generation networks. We consider a D2D-enabled hybrid cellular network compromising of μW macro-cells coexisting with mmWave small cells. We investigate the dynamic resource sharing in downlink transmission to maximize the energy efficiency (EE) of the priority, or cellular users (CUs), that are opportunistically served by either macrocells or mmWave small cells, while satis...
Locomotion control of hybrid cockroach robots
Sanchez, Carlos J.; Chiu, Chen-Wei; Zhou, Yan; González, Jorge M.; Vinson, S. Bradleigh; Liang, Hong
2015-01-01
Natural systems retain significant advantages over engineered systems in many aspects, including size and versatility. In this research, we develop a hybrid robotic system using American (Periplaneta americana) and discoid (Blaberus discoidalis) cockroaches that uses the natural locomotion and robustness of the insect. A tethered control system was firstly characterized using American cockroaches, wherein implanted electrodes were used to apply an electrical stimulus to the prothoracic ganglia. Using this approach, larger discoid cockroaches were engineered into a remotely controlled hybrid robotic system. Locomotion control was achieved through electrical stimulation of the prothoracic ganglia, via a remotely operated backpack system and implanted electrodes. The backpack consisted of a microcontroller with integrated transceiver protocol, and a rechargeable battery. The hybrid discoid roach was able to walk, and turn in response to an electrical stimulus to its nervous system with high repeatability of 60%. PMID:25740855
A hybrid genetic algorithm to optimize simple distillation column sequences
Institute of Scientific and Technical Information of China (English)
GAN YongSheng; Andreas Linninger
2004-01-01
Based on the principles of Genetic Algorithms (GAs), a hybrid genetic algorithm used to optimize simple distillation column sequences was established. A new data structure, a novel arithmetic crossover operator and a dynamic mutation operator were proposed. Together with the feasibility test of distillation columns, they are capable to obtain the optimum simple column sequence at one time without the limitation of the number of mixture components, ideal or non-ideal mixtures and sloppy or sharp splits. Compared with conventional algorithms, this hybrid genetic algorithm avoids solving complicated nonlinear equations and demands less derivative information and computation time. Result comparison between this genetic algorithm and Underwood method and Doherty method shows that this hybrid genetic algorithm is reliable.
NEURAL NETWORKS CONTROL OF THE HYBRID POWER UNIT BASED ON THE METHOD OF ADAPTIVE CRITICS
Directory of Open Access Journals (Sweden)
S. Serikov
2012-01-01
Full Text Available The formal statement of the optimization problem of hybrid vehicle power unit control is given. Its solving by neural networks method application on the basis of adaptive critic is considered.
Optimal actuation in vibration control
Guzzardo, C. A.; Pang, S. S.; Ram, Y. M.
2013-02-01
The paper addresses the problem of finding the optimal location of actuators and their relative gain so that the control effort in an actively controlled vibrating system is minimized. In technical terms the problem is finding the optimal input vector of unit norm that minimizes the norm of the control gain vector. This problem is addressed in the context of the active natural frequency modification problem associated with resonance avoidance in undamped systems, and in the context of the single-input-multi-output pole assignment problem for second order systems.
Optimal Control of Teaching Process
Institute of Scientific and Technical Information of China (English)
BAO Man; ZHANG Guo-zhi
2002-01-01
The authors first put forward quadratic form performance index as a criterion of measuringmerits and demerits of teaching process. On this base, we got a low of optimal control after the quantificationof the teacher's functions. It must play a leading role on how the teacher fully controls the whole teachingprocess.
Optimal control of quantum measurement
Energy Technology Data Exchange (ETDEWEB)
Egger, Daniel; Wilhelm, Frank [Theoretical Physics, Saarland University, 66123 Saarbruecken (Germany)
2015-07-01
Pulses to steer the time evolution of quantum systems can be designed with optimal control theory. In most cases it is the coherent processes that can be controlled and one optimizes the time evolution towards a target unitary process, sometimes also in the presence of non-controllable incoherent processes. Here we show how to extend the GRAPE algorithm in the case where the incoherent processes are controllable and the target time evolution is a non-unitary quantum channel. We perform a gradient search on a fidelity measure based on Choi matrices. We illustrate our algorithm by optimizing a measurement pulse for superconducting phase qubits. We show how this technique can lead to large measurement contrast close to 99%. We also show, within the validity of our model, that this algorithm can produce short 1.4 ns pulses with 98.2% contrast.
Hybrid Intelligent Control for Submarine Stabilization
Directory of Open Access Journals (Sweden)
Minghui Wang
2013-05-01
Full Text Available While sailing near the sea surface, submarines will often undergo rolling motion caused by wave disturbance. Fierce rolling motion seriously affects their normal operation and even threatens their security. We propose a new control method for roll stabilization. This paper studies hybrid intelligent control combining a fuzzy control, a neural network and extension control technology. Every control strategy can achieve the ideal control effect within the scope of its effective control. The neuro‐fuzzy control strategy is used to improve the robustness of the controller. The speed control strategy and the course control strategy are conducted to extend the control range. The paper also proposes the design of the controller and carries out the simulation experiment in different sea conditions. The simulation results show that the control method proposed can indeed effectively improve the control performance of submarine stabilization.
Hybrid Intelligent Control for Submarine Stabilization
Directory of Open Access Journals (Sweden)
Minghui Wang
2013-05-01
Full Text Available Abstract While sailing near the sea surface, submarines will often undergo rolling motion caused by wave disturbance. Fierce rolling motion seriously affects their normal operation and even threatens their security. We propose a new control method for roll stabilization. This paper studies hybrid intelligent control combining a fuzzy control, a neural network and extension control technology. Every control strategy can achieve the ideal control effect within the scope of its effective control. The neuro-fuzzy control strategy is used to improve the robustness of the controller. The speed control strategy and the course control strategy are conducted to extend the control range. The paper also proposes the design of the controller and carries out the simulation experiment in different sea conditions. The simulation results show that the control method proposed can indeed effectively improve the control performance of submarine stabilization.
Directory of Open Access Journals (Sweden)
A. P. Karpenko
2014-01-01
Full Text Available We consider a class of stochastic search algorithms of global optimization which in various publications are called behavioural, intellectual, metaheuristic, inspired by the nature, swarm, multi-agent, population, etc. We use the last term.Experience in using the population algorithms to solve challenges of global optimization shows that application of one such algorithm may not always effective. Therefore now great attention is paid to hybridization of population algorithms of global optimization. Hybrid algorithms unite various algorithms or identical algorithms, but with various values of free parameters. Thus efficiency of one algorithm can compensate weakness of another.The purposes of the work are development of hybrid algorithm of global optimization based on known algorithms of harmony search (HS and swarm of particles (PSO, software implementation of algorithm, study of its efficiency using a number of known benchmark problems, and a problem of dimensional optimization of truss structure.We set a problem of global optimization, consider basic algorithms of HS and PSO, give a flow chart of the offered hybrid algorithm called PSO HS , present results of computing experiments with developed algorithm and software, formulate main results of work and prospects of its development.
Optimization of the fission--fusion hybrid concept
Energy Technology Data Exchange (ETDEWEB)
Saltmarsh, M.J.; Grimes, W.R.; Santoro, R.T.
1979-04-01
One of the potentially attractive applications of controlled thermonuclear fusion is the fission--fusion hybrid concept. In this report we examine the possible role of the hybrid as a fissile fuel producer. We parameterize the advantages of the concept in terms of the performance of the fusion device and the breeding blanket and discuss some of the more troublesome features of existing design studies. The analysis suggests that hybrids based on deuterium--tritium (D--T) fusion devices are unlikely to be economically attractive and that they present formidable blanket technology problems. We suggest an alternative approach based on a semicatalyzed deuterium--deuterium (D--D) fusion reactor and a molten salt blanket. This concept is shown to emphasize the desirable features of the hybrid, to have considerably greater economic potential, and to mitigate many of the disadvantages of D--T-based systems.
Multiview coding mode decision with hybrid optimal stopping model.
Zhao, Tiesong; Kwong, Sam; Wang, Hanli; Wang, Zhou; Pan, Zhaoqing; Kuo, C-C Jay
2013-04-01
In a generic decision process, optimal stopping theory aims to achieve a good tradeoff between decision performance and time consumed, with the advantages of theoretical decision-making and predictable decision performance. In this paper, optimal stopping theory is employed to develop an effective hybrid model for the mode decision problem, which aims to theoretically achieve a good tradeoff between the two interrelated measurements in mode decision, as computational complexity reduction and rate-distortion degradation. The proposed hybrid model is implemented and examined with a multiview encoder. To support the model and further promote coding performance, the multiview coding mode characteristics, including predicted mode probability and estimated coding time, are jointly investigated with inter-view correlations. Exhaustive experimental results with a wide range of video resolutions reveal the efficiency and robustness of our method, with high decision accuracy, negligible computational overhead, and almost intact rate-distortion performance compared to the original encoder.
Strength Pareto particle swarm optimization and hybrid EA-PSO for multi-objective optimization.
Elhossini, Ahmed; Areibi, Shawki; Dony, Robert
2010-01-01
This paper proposes an efficient particle swarm optimization (PSO) technique that can handle multi-objective optimization problems. It is based on the strength Pareto approach originally used in evolutionary algorithms (EA). The proposed modified particle swarm algorithm is used to build three hybrid EA-PSO algorithms to solve different multi-objective optimization problems. This algorithm and its hybrid forms are tested using seven benchmarks from the literature and the results are compared to the strength Pareto evolutionary algorithm (SPEA2) and a competitive multi-objective PSO using several metrics. The proposed algorithm shows a slower convergence, compared to the other algorithms, but requires less CPU time. Combining PSO and evolutionary algorithms leads to superior hybrid algorithms that outperform SPEA2, the competitive multi-objective PSO (MO-PSO), and the proposed strength Pareto PSO based on different metrics.
Optimality Conditions for Inventory Control
Feinberg, Eugene A.
2016-01-01
This tutorial describes recently developed general optimality conditions for Markov Decision Processes that have significant applications to inventory control. In particular, these conditions imply the validity of optimality equations and inequalities. They also imply the convergence of value iteration algorithms. For total discounted-cost problems only two mild conditions on the continuity of transition probabilities and lower semi-continuity of one-step costs are needed. For average-cost pr...
DEFF Research Database (Denmark)
Awasthi, Abhishek; Venkitusamy, Karthikeyan; Padmanaban, Sanjeevikumar
2017-01-01
, a hybrid algorithm based on genetic algorithm and improved version of conventional particle swarm optimization is utilized for finding optimal placement of charging station in the Allahabad distribution system. The particle swarm optimization algorithm re-optimizes the received sub-optimal solution (site...... and the size of the station) which leads to an improvement in the algorithm functionality and enhances quality of solution. The genetic algorithm and improved version of conventional particle swarm optimization algorithm will also be compared with a conventional genetic algorithm and particle swarm...... optimization. Through simulation studies on a real time system of Allahabad city, the superior performance of the aforementioned technique with respect to genetic algorithm and particle swarm optimization in terms of improvement in voltage profile and quality....
Hybrid particle swarm optimization for solving resource-constrained FMS
Institute of Scientific and Technical Information of China (English)
Dongyun Wang; Liping Liu
2008-01-01
In this paper,an approach for resource-constrained flexible manufacturing system(FMS)scheduling was proposed,which is based on the particle swarm optimization(PSO)algorithm and simulated annealing(SA)algorithm.First,the formulation for resource-con-strained FMS scheduling problem was introduced and cost function for this problem was obtained.Then.a hybrid algorithm of PSO and SA was employed to obtain optimal solution.The simulated results show that the approach can dislodge a state from a local min-imum and guide it to the global minimum.
Hybrid Optimization of Support Vector Machine for Intrusion Detection
Institute of Scientific and Technical Information of China (English)
XI Fu-li; YU Song-nian; HAO Wei
2005-01-01
Support vector machine (SVM) technique has recently become a research focus in intrusion detection field for its better generalization performance when given less priori knowledge than other soft-computing techniques. But the randomicity of parameter selection in its implement often prevents it achieving expected performance. By utilizing genetic algorithm (GA) to optimize the parameters in data preprocessing and the training model of SVM simultaneously, a hybrid optimization algorithm is proposed in the paper to address this problem. The experimental results demonstrate that it's an effective method and can improve the perfornance of SVM-based intrusion detection system further.
Optimizing Hybrid Wind/Diesel Generator System Using BAT Algorithm
Directory of Open Access Journals (Sweden)
Sudhir Sharma,
2016-01-01
Full Text Available Hybrid system comprising of Wind/Diesel generation system for a practical standalone application considers Wind turbine generators and diesel generator as primary power sources for generating electricity. Battery banks are considered as a backup power source. The total value of cost is reduced by meeting energy demand required by the customers. Bat optimization technique is implemented to optimize wind and battery modules. Wind and battery banks are considered as primary sources and diesel generator as a secondary power source for the system
A New Class of Hybrid Particle Swarm Optimization Algorithm
Institute of Scientific and Technical Information of China (English)
Da-Qing Guo; Yong-Jin Zhao; Hui Xiong; Xiao Li
2007-01-01
A new class of hybrid particle swarm optimization (PSO) algorithm is developed for solving the premature convergence caused by some particles in standard PSO fall into stagnation. In this algorithm, the linearly decreasing inertia weight technique (LDIW) and the mutative scale chaos optimization algorithm (MSCOA) are combined with standard PSO, which are used to balance the global and local exploration abilities and enhance the local searching abilities, respectively. In order to evaluate the performance of the new method, three benchmark functions are used. The simulation results confirm the proposed algorithm can greatly enhance the searching ability and effectively improve the premature convergence.
Predictive control strategy for power management in parallel hybrid-electric vehicle
DEFF Research Database (Denmark)
Nodeh, Mohammad Taqi; Gholizade, Hossein; Hajizadeh, Amin
2016-01-01
In this paper, a hybrid model-based nonlinear optimal control method is used to compute the optimal power distribution and power management in parallel hybrid electric vehicles. In the power management strategy, for optimal power distribution between the internal combustion engine, electrical...... system and the other subsystems, nonlinear predictive control is applied. In order to achieve this goal, a hierarchical control structure is utilized. This type of control structure consists of three levels of monitoring, coordinating and local controllers. Nonlinear modeling and performance index...... in the proposed method should be formulated at the regulatory level of the controller. Discrete dynamic mode of operation (motor-generator) in hybrid electric vehicle requires to use a dual-mode switch model and to define an alternative expression of performance index for the optimal control problem...
Hybrid Algorithm for the Optimization of Training Convolutional Neural Network
Directory of Open Access Journals (Sweden)
Hayder M. Albeahdili
2015-10-01
Full Text Available The training optimization processes and efficient fast classification are vital elements in the development of a convolution neural network (CNN. Although stochastic gradient descend (SGD is a Prevalence algorithm used by many researchers for the optimization of training CNNs, it has vast limitations. In this paper, it is endeavor to diminish and tackle drawbacks inherited from SGD by proposing an alternate algorithm for CNN training optimization. A hybrid of genetic algorithm (GA and particle swarm optimization (PSO is deployed in this work. In addition to SGD, PSO and genetic algorithm (PSO-GA are also incorporated as a combined and efficient mechanism in achieving non trivial solutions. The proposed unified method achieves state-of-the-art classification results on the different challenge benchmark datasets such as MNIST, CIFAR-10, and SVHN. Experimental results showed that the results outperform and achieve superior results to most contemporary approaches.
Improved hybrid optimization algorithm for 3D protein structure prediction.
Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang
2014-07-01
A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins.
Multiobjective muffler shape optimization with hybrid acoustics modeling.
Airaksinen, Tuomas; Heikkola, Erkki
2011-09-01
This paper considers the combined use of a hybrid numerical method for the modeling of acoustic mufflers and a genetic algorithm for multiobjective optimization. The hybrid numerical method provides accurate modeling of sound propagation in uniform waveguides with non-uniform obstructions. It is based on coupling a wave based modal solution in the uniform sections of the waveguide to a finite element solution in the non-uniform component. Finite element method provides flexible modeling of complicated geometries, varying material parameters, and boundary conditions, while the wave based solution leads to accurate treatment of non-reflecting boundaries and straightforward computation of the transmission loss (TL) of the muffler. The goal of optimization is to maximize TL at multiple frequency ranges simultaneously by adjusting chosen shape parameters of the muffler. This task is formulated as a multiobjective optimization problem with the objectives depending on the solution of the simulation model. NSGA-II genetic algorithm is used for solving the multiobjective optimization problem. Genetic algorithms can be easily combined with different simulation methods, and they are not sensitive to the smoothness properties of the objective functions. Numerical experiments demonstrate the accuracy and feasibility of the model-based optimization method in muffler design.
Active Vibration Control of Plate Partly Treated with ACLD Using Hybrid Control
Directory of Open Access Journals (Sweden)
Dongdong Zhang
2014-01-01
Full Text Available A finite element model of plate partly treated with ACLD treatments is developed based on the constitutive equations of elastic, piezoelectric, viscoelastic materials and Hamilton’s principle. The Golla-Hughes-Mctavish (GHM method is employed to describe the frequency-dependent characteristics of viscoelastic material (VEM. A model reduction is completed by using iterative dynamic condensation and balance model reduction method to design an effective control system. The emphasis is concerned on hybrid (combined feedback/feedforward control system to attenuate the vibration of plates with ACLD treatments. The optimal linear quadratic Gaussian (LQG controller is considered as a feedback channel and the adaptive filtered-reference LMS (FxLMS controller is used as a feedforward channel. They can be utilized individually or in a hybrid way to suppress the vibration of plate/ACLD system. The results show that the hybrid controller which combines feedback/feedforward together can reduce the displacement amplitude of plate/ACLD system subjected to a complicated disturbance substantially without requiring more control effort. Furthermore, the hybrid controller has more rapid and stable convergence rate than the adaptive feedforward FxLMS controller. Meanwhile, perfect robustness to phase error of the cancellation path in feedforward controller and the weight matrices in feedback LQG controller is demonstrated in proposed hybrid controller. Therefore, its application in structural engineering can be highly appreciated.
Institute of Scientific and Technical Information of China (English)
卢芸; 赵永来
2014-01-01
The use of wind power energy storage system is an effective measure to stabilize fluctuations in wind power today, however, the energy storage system control strategy has a direct impact on the wind power system's technical and economic performance. Based on the complementary in function of super-capacitor and battery, its application in wind farms based DFIG and the topology control structures for wind farm with distributed rectifier and centralized inverter are adopted, fuzzy neural PID controller is designed, and fuzzy neural network algorithm is used to optimize PID control parameters for hybrid energy storage system on line. Based on MATLAB / SIMULINK platform, the control system simulation model is established and analyzed. Simulation results show that the hybrid energy storage system can improve the life of the energy storage device. According to the compensate power and the fluctuation range of the state of charge of the energy storage systems, as well as wind power fluctuations in the degree of smoothing, the effectiveness of the control system is verified.%采用风电储能系统来平抑风电波动功率在当今是一个有效的措施，然而储能系统控制策略的好坏直接影响风电系统的技术性能和经济性能。根据超级电容器和蓄电池在功能上的互补性，将其应用在基于双馈电机的风电场中，风电场采用分布整流集中逆变拓扑控制结构，并对其设计模糊神经PID控制器，采用模糊神经网络算法对混合储能系统PID控制参数进行在线优化。基于Matlab/Simulink平台搭建控制系统仿真模型，并进行仿真分析，验证了混合储能系统能够提高储能装置的使用寿命。根据储能系统补偿功率和其荷电状态的波动范围，以及对风电波动功率的平滑程度，验证了该控制系统的有效性。
Infinite Dimensional Differential Games with Hybrid Controls
Indian Academy of Sciences (India)
A J Shaiju; Sheetal Dharmatti
2007-05-01
A two-person zero-sum infinite dimensional differential game of infinite duration with discounted payoff involving hybrid controls is studied. The minimizing player is allowed to take continuous, switching and impulse controls whereas the maximizing player is allowed to take continuous and switching controls. By taking strategies in the sense of Elliott–Kalton, we prove the existence of value and characterize it as the unique viscosity solution of the associated system of quasi-variational inequalities.
Application of Hybrid Optimization Algorithm in the Synthesis of Linear Antenna Array
Directory of Open Access Journals (Sweden)
Ezgi Deniz Ülker
2014-01-01
Full Text Available The use of hybrid algorithms for solving real-world optimization problems has become popular since their solution quality can be made better than the algorithms that form them by combining their desirable features. The newly proposed hybrid method which is called Hybrid Differential, Particle, and Harmony (HDPH algorithm is different from the other hybrid forms since it uses all features of merged algorithms in order to perform efficiently for a wide variety of problems. In the proposed algorithm the control parameters are randomized which makes its implementation easy and provides a fast response. This paper describes the application of HDPH algorithm to linear antenna array synthesis. The results obtained with the HDPH algorithm are compared with three merged optimization techniques that are used in HDPH. The comparison shows that the performance of the proposed algorithm is comparatively better in both solution quality and robustness. The proposed hybrid algorithm HDPH can be an efficient candidate for real-time optimization problems since it yields reliable performance at all times when it gets executed.
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
A discrete-time hybrid model of a permanent magnet synchronous motor (PMSM) with saturation in voltage and current is formulated.The controller design with incorporated constraints is achieved in a systematic way from modeling to control synthesis and implementation.The Hybrid System Description Language is used to obtain a mixed-logical dynamical (MLD) model.Based on the MLD model,a model predictive controller is designed for an optimal speed regulation of the motor.For reducing computation complexity and ...
Hybridization of Meta-heuristics for Optimizing Routing protocol in VANETs
Directory of Open Access Journals (Sweden)
R.R Sedamkar
2016-02-01
Full Text Available The goal of VANET is to establish a vehicular communication system which is reliable and fast which caters to road safety and road safety. In VANET where network fragmentation is frequent with no central control, routing becomes a challenging task. Planning an optimal routing plan for tuning parameter configuration of routing protocol for setting up VANET is very crucial. This is done by defining an optimization problem where hybridization of meta-heuristics is defined. The paper contributes the idea of combining meta-heuristic algorithm to enhance the performance of individual search method for optimization problem
Real-Time Energy Management Control for Hybrid Electric Powertrains
Directory of Open Access Journals (Sweden)
Mohamed Zaher
2013-01-01
Full Text Available This paper focuses on embedded control of a hybrid powertrain concepts for mobile vehicle applications. Optimal robust control approach is used to develop a real-time energy management strategy. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in the opposite direction to the applied force or torque. This is the case when the vehicle is braking, decelerating, the motion is driven by gravitational force, or load driven. There are three main concepts for energy storing devices in hybrid vehicles: electric, hydraulic, and mechanical (flywheel. The real-time control challenge is to balance the system power demands from the engine and the hybrid storage device, without depleting the energy storage device or stalling the engine in any work cycle. In the worst-case scenario, only the engine is used and the hybrid system is completely disabled. A rule-based control algorithm is developed and is tuned for different work cycles and could be linked to a gain scheduling algorithm. A gain scheduling algorithm identifies the cycle being performed by the work machine and its position via GPS and maps both of them to the gains.
A Dynamic Multistage Hybrid Swarm Intelligence Optimization Algorithm for Function Optimization
Directory of Open Access Journals (Sweden)
Daqing Wu
2012-01-01
Full Text Available A novel dynamic multistage hybrid swarm intelligence optimization algorithm is introduced, which is abbreviated as DM-PSO-ABC. The DM-PSO-ABC combined the exploration capabilities of the dynamic multiswarm particle swarm optimizer (PSO and the stochastic exploitation of the cooperative artificial bee colony algorithm (CABC for solving the function optimization. In the proposed hybrid algorithm, the whole process is divided into three stages. In the first stage, a dynamic multiswarm PSO is constructed to maintain the population diversity. In the second stage, the parallel, positive feedback of CABC was implemented in each small swarm. In the third stage, we make use of the particle swarm optimization global model, which has a faster convergence speed to enhance the global convergence in solving the whole problem. To verify the effectiveness and efficiency of the proposed hybrid algorithm, various scale benchmark problems are tested to demonstrate the potential of the proposed multistage hybrid swarm intelligence optimization algorithm. The results show that DM-PSO-ABC is better in the search precision, and convergence property and has strong ability to escape from the local suboptima when compared with several other peer algorithms.
Optimal control linear quadratic methods
Anderson, Brian D O
2007-01-01
This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory from an engineering viewpoint, with step-by-step explanations that show clearly how to make practical use of the material.The three-part treatment begins with the basic theory of the linear regulator/tracker for time-invariant and time-varying systems. The Hamilton-Jacobi equation is introduced using the Principle of Optimality, and the infinite-time problem is considered. The second part outlines the
Optimal control of motorsport differentials
Tremlett, A. J.; Massaro, M.; Purdy, D. J.; Velenis, E.; Assadian, F.; Moore, A. P.; Halley, M.
2015-12-01
Modern motorsport limited slip differentials (LSD) have evolved to become highly adjustable, allowing the torque bias that they generate to be tuned in the corner entry, apex and corner exit phases of typical on-track manoeuvres. The task of finding the optimal torque bias profile under such varied vehicle conditions is complex. This paper presents a nonlinear optimal control method which is used to find the minimum time optimal torque bias profile through a lane change manoeuvre. The results are compared to traditional open and fully locked differential strategies, in addition to considering related vehicle stability and agility metrics. An investigation into how the optimal torque bias profile changes with reduced track-tyre friction is also included in the analysis. The optimal LSD profile was shown to give a performance gain over its locked differential counterpart in key areas of the manoeuvre where a quick direction change is required. The methodology proposed can be used to find both optimal passive LSD characteristics and as the basis of a semi-active LSD control algorithm.
Momoh, James; Chattopadhyay, Deb; Basheer, Omar Ali AL
1996-01-01
The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10
Energy Technology Data Exchange (ETDEWEB)
Centioli, C. [Associazione Euratom/ENEA Sulla Fusione, Centro Ricerche Frascati, Via E. Fermi 45, CP 65, 00044 Frascati, Rome (Italy); Iannone, F. [Associazione Euratom/ENEA Sulla Fusione, Centro Ricerche Frascati, Via E. Fermi 45, CP 65, 00044 Frascati, Rome (Italy); Mazza, G. [Associazione Euratom/ENEA Sulla Fusione, Centro Ricerche Frascati, Via E. Fermi 45, CP 65, 00044 Frascati, Rome (Italy); Panella, M. [Associazione Euratom/ENEA Sulla Fusione, Centro Ricerche Frascati, Via E. Fermi 45, CP 65, 00044 Frascati, Rome (Italy); Pangione, L. [Dipartimento di Informatica, Sistemi e Produzione, Universita di Roma, Tor Vergata, Via del Politecnico 1, 00133 Rome (Italy)]. E-mail: pangione@frascati.enea.it; Podda, S. [Associazione Euratom/ENEA Sulla Fusione, Centro Ricerche Frascati, Via E. Fermi 45, CP 65, 00044 Frascati, Rome (Italy); Tuccillo, A. [Associazione Euratom/ENEA Sulla Fusione, Centro Ricerche Frascati, Via E. Fermi 45, CP 65, 00044 Frascati, Rome (Italy); Vitale, V. [Associazione Euratom/ENEA Sulla Fusione, Centro Ricerche Frascati, Via E. Fermi 45, CP 65, 00044 Frascati, Rome (Italy); Zaccarian, L. [Dipartimento di Informatica, Sistemi e Produzione, Universita di Roma, Tor Vergata, Via del Politecnico 1, 00133 Rome (Italy)
2005-11-15
In this paper, we will report on the experimental results arising from the implementation of optimization techniques to maximize the RF power coupling versus the plasma conditions in the FTU experimental facility. These experiments are carried out by employing the open-source Linux-RTAI control system currently running on the FTU digital feedback loop. The RF power source under consideration is a lower hybrid system (LH) based on six gyrotrons with a nominal power output capability of 1.1 MW each. The optimization of the coupling level between the plasma and the emitting antenna reduces the reflected power, thus maximizing the heating effects in addition to avoiding danger to the emitter (equivalently, annoying safety shutdowns of the system). To this aim, the plasma displacement is modified by suitably adjusting the reference input to the stabilizing feedback, according to a steepest descent algorithm. It will be shown in the paper how this algorithm achieves a satisfactory level of robustness with respect to measurement errors and well performs both in simulation and in experimental tests, thus leading to an improved effectiveness of the RF heating system.
MERCURY CONTROL WITH ADVANCED HYBRID PARTICULATE COLLECTOR
Energy Technology Data Exchange (ETDEWEB)
Ye Zhuang; Stanley J. Miller
2005-05-01
This project was awarded under U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) Program Solicitation DE-PS26-00NT40769 and specifically addressed Technical Topical Area 4-Testing Novel and Less Mature Control Technologies on Actual Flue Gas at the Pilot Scale. The project team included the Energy & Environmental Research Center (EERC) as the main contractor; W.L. Gore & Associates, Inc., as a technical and financial partner; and the Big Stone Power Plant operated by Otter Tail Power Company, host for the field-testing portion of the research. Since 1995, DOE has supported development of a new concept in particulate control called the advanced hybrid particulate collector (AHPC). The AHPC has been licensed to W.L. Gore & Associates, Inc., and has been marketed as the Advanced Hybrid{trademark} filter by Gore. The Advanced Hybrid{trademark} filter combines the best features of electrostatic precipitators (ESPs) and baghouses in a unique configuration, providing major synergism between the two collection methods, both in the particulate collection step and in the transfer of dust to the hopper. The Advanced Hybrid{trademark} filter provides ultrahigh collection efficiency, overcoming the problem of excessive fine-particle emissions with conventional ESPs, and it solves the problem of reentrainment and re-collection of dust in conventional baghouses. The Advanced Hybrid{trademark} filter also appears to have unique advantages for mercury control over baghouses or ESPs as an excellent gas--solid contactor. The objective of the project was to demonstrate 90% total mercury control in the Advanced Hybrid{trademark} filter at a lower cost than current mercury control estimates. The approach included bench-scale batch tests, larger-scale pilot testing with real flue gas on a coal-fired combustion system, and field demonstration at the 2.5-MW (9000-acfm) scale at a utility power plant to prove scale-up and demonstrate longer-term mercury control
Real-time optimization power-split strategy for hybrid electric vehicles
Institute of Scientific and Technical Information of China (English)
XIA ChaoYing; ZHANG Cong
2016-01-01
Energy management strategies based on optimal control theory can achieve minimum fuel consumption for hybrid electric vehicles,but the requirement for driving cycles known in prior leads to a real-time problem.A real-time optimization power-split strategy is proposed based on linear quadratic optimal control.The battery state of charge sustainability and fuel economy are ensured by designing a quadratic performance index combined with two rules.The engine power and motor power of this strategy are calculated in real-time based on current system state and command,and not related to future driving conditions.The simulation results in ADVISOR demonstrate that,under the conditions of various driving cycles,road slopes and vehicle parameters,the proposed strategy significantly improves fuel economy,which is very close to that of the optimal control based on Pontryagin's minimum principle,and greatly reduces computation complexity.
Institute of Scientific and Technical Information of China (English)
SUN Fan; DU Wenli; QI Rongbin; QIAN Feng; ZHONG Weimin
2013-01-01
The solutions of dynamic optimization problems are usually very difficult due to their highly nonlinear and multidimensional nature.Genetic algorithm(GA)has been proved to be a feasible method when the gradient is difficult to calculate.Its advantage is that the control profiles at all time stages are optimized simultaneously,but its convergence is very slow in the later period of evolution and it is easily trapped in the local optimum.In this study,a hybrid improved genetic algorithm(HIGA)for solving dynamic optimization problems is proposed to overcome these defects.Simplex method(SM)is used to perform the local search in the neighborhood of the optimal solution.By using SM,the ideal searching direction of global optimal solution could be found as soon as possible and the convergence speed of the algorithm is improved.The hybrid algorithm presents some improvements,such as protecting the best individual,accepting immigrations,as well as employing adaptive crossover and Gaussian mutation operators.The efficiency of the proposed algorithm is demonstrated by solving several dynamic optimization problems.At last,HIGA is applied to the optimal production of secreted protein in a fed batch reactor and the optimal feed-rate found by HIGA is effective and relatively stable.
Energy control strategy for parallel hydrostatic transmission hybrid vehicles
Institute of Scientific and Technical Information of China (English)
SUN Hui; JIANG Ji-hai; WANG Xin
2009-01-01
Aimed at the relatively lower energy density and complicated coordinating operation between two power sources, a special energy control strategy is required to maximize the fuel saving potential. Then a new type of configuration for hydrostatic transmission hybrid vehicles (PHHV) and the selection criterion for impor-tant components are proposed. Based on the optimization of planet gear transmission ratio and the analysis of op-timal energy distribution for the proposed PHHV on a representative urban driving cycle, a fuzzy torque control strategy and a braking energy regeneration strategy are designed and developed to realize the real-time control of energy for the proposed PHHV. Simulation results demonstrate that the energy control strategy effectively im-proves the fuel economy of PHHV.
A Hybrid Approach to the Optimization of Multiechelon Systems
Directory of Open Access Journals (Sweden)
Paweł Sitek
2015-01-01
Full Text Available In freight transportation there are two main distribution strategies: direct shipping and multiechelon distribution. In the direct shipping, vehicles, starting from a depot, bring their freight directly to the destination, while in the multiechelon systems, freight is delivered from the depot to the customers through an intermediate points. Multiechelon systems are particularly useful for logistic issues in a competitive environment. The paper presents a concept and application of a hybrid approach to modeling and optimization of the Multi-Echelon Capacitated Vehicle Routing Problem. Two ways of mathematical programming (MP and constraint logic programming (CLP are integrated in one environment. The strengths of MP and CLP in which constraints are treated in a different way and different methods are implemented and combined to use the strengths of both. The proposed approach is particularly important for the discrete decision models with an objective function and many discrete decision variables added up in multiple constraints. An implementation of hybrid approach in the ECLiPSe system using Eplex library is presented. The Two-Echelon Capacitated Vehicle Routing Problem (2E-CVRP and its variants are shown as an illustrative example of the hybrid approach. The presented hybrid approach will be compared with classical mathematical programming on the same benchmark data sets.
OPTIMIZATION APPROACH FOR HYBRID ELECTRIC VEHICLE POWERTRAIN DESIGN
Institute of Scientific and Technical Information of China (English)
Zhu Zhengli; Zhang Jianwu; Yin Chengliang
2005-01-01
According to bench test results of fuel economy and engine emission for the real powertrain system of EQ7200HEV car, a 3-D performance map oriented quasi-linear model is developed for the configuration of the powertrain components such as internal combustion engine, traction electric motor, transmission, main retarder and energy storage unit. A genetic algorithm based on optimization procedure is proposed and applied for parametric optimization of the key components by consideration of requirements of some driving cycles. Through comparison of numerical results obtained by the genetic algorithm with those by traditional optimization methods, it is shown that the present approach is quite effective and efficient in emission reduction and fuel economy for the design of the hybrid electric car powertrain.
Design Optimization of Gas Generator Hybrid Propulsion Boosters
Weldon, Vincent; Phillips, Dwight; Fink, Larry
1990-01-01
A methodology used in support of a study for NASA/MSFC to optimize the design of gas generator hybrid propulsion booster for uprating the National Space Transportation System (NSTS) is presented. The objective was to compare alternative configurations for this booster approach, optimizing each candidate concept on different bases, in order to develop data for a trade table on which a final decision was based. The methodology is capable of processing a large number of independent and dependent variables, adjusting the overall subsystems characteristics to arrive at a best compromise integrated design to meet various specific optimization criteria subject to selected constraints. For each system considered, a detailed weight statement was generated along with preliminary cost and reliability estimates.
Control and optimal control theories with applications
Burghes, D N
2004-01-01
This sound introduction to classical and modern control theory concentrates on fundamental concepts. Employing the minimum of mathematical elaboration, it investigates the many applications of control theory to varied and important present-day problems, e.g. economic growth, resource depletion, disease epidemics, exploited population, and rocket trajectories. An original feature is the amount of space devoted to the important and fascinating subject of optimal control. The work is divided into two parts. Part one deals with the control of linear time-continuous systems, using both transfer fun
Optimal control with aerospace applications
Longuski, James M; Prussing, John E
2014-01-01
Want to know not just what makes rockets go up but how to do it optimally? Optimal control theory has become such an important field in aerospace engineering that no graduate student or practicing engineer can afford to be without a working knowledge of it. This is the first book that begins from scratch to teach the reader the basic principles of the calculus of variations, develop the necessary conditions step-by-step, and introduce the elementary computational techniques of optimal control. This book, with problems and an online solution manual, provides the graduate-level reader with enough introductory knowledge so that he or she can not only read the literature and study the next level textbook but can also apply the theory to find optimal solutions in practice. No more is needed than the usual background of an undergraduate engineering, science, or mathematics program: namely calculus, differential equations, and numerical integration. Although finding optimal solutions for these problems is a...
Institute of Scientific and Technical Information of China (English)
米阳; 王成山
2013-01-01
A new frequency optimization control method for the photovoltaic (PV)/diesel hybrid microgrid was proposed based on the disturbance observer. The disturbance observer was constructed to estimate the fluctuating load value in the microgrid. The PV system was tuned by maximum power point tracking (MPPT) control, and the sliding mode compensation controller was designed based on the estimated load value and the variation of microgrid frequency to tune the power of diesel generator system. The simulation results prove that the proposed optimization control method can assure the maximum power output of PV system, improve the utilization efficiency of PV energy, and reduce the frequency deviation induced by the load changes and the PV power fluctuation, and the energy storage device hardware investment are reduced by using the control method in the microgrid large-scale construction.%针对光柴互补的独立型微网，利用设计的干扰观测器估计的负荷值，提出了新的微网频率优化控制策略。构造干扰观测器估计出微网中不断变化的负荷值，在光伏(photovoltaic，PV)系统采取最大功率跟踪(maximum power point tracking，MPPT)控制条件下，基于估计的负荷值和微网频率的变化，设计滑模补偿控制器，并将设计的滑模控制器应用到柴油发电系统的有功功率调节中。仿真结果表明，所提出的频率优化控制策略不仅能够保证光伏系统的最大功率输出，提高光伏能源利用率，同时可减小由于负荷变化和光伏输出功率波动引起的较大微网频率偏差，而且利用所设计控制算法调频可以减少储能设备的硬件投入，为微网的大规模建设节约成本。
Directory of Open Access Journals (Sweden)
Trevor Davies
2008-08-01
Full Text Available This paper presents the development and implementation a hybrid control architecture to direct a collective of three X80 mobile robots to multiple user-defined waypoints. The Genetic Algorithm Path Planner created an optimized, reduction in the time to complete the task, path plan for each robot in the collective such that each waypoint was visited once without colliding with a priori obstacles. The deliberative Genetic Algorithm Path Planner was then coupled with a reactive Potential Field Trajectory Planner and kinematic based controller to create a hybrid control architecture allowing the mobile robot to navigate between multiple user-defined waypoints, while avoiding a priori obstacles and obstacles detected using the robots' range sensors. The success of this hybrid control architecture was proven through simulation and experimentation using three of Dr. Robot's ™ wireless X80 mobile robots.
A Hybrid Optimization Approach for SRM FINOCYL Grain Design
Institute of Scientific and Technical Information of China (English)
Khurram Nisar; Liang Guozhu; Qasim Zeeshan
2008-01-01
This article presents a method to design and optimize 3D FINOCYL grain (FCG) configuration for solid rocket motors (SRMs). The design process of FCG configuration involves mathematical modeling of the geometry and parametric evaluation of various inde-pendent geometric variables that define the complex configuration. Vh'tually infinite combinations of these variables will satisfy the requirements of mass of propellant, thrust, and burning time in addition to satisfying basic needs for volumetric loading fraction and web fraction. In order to ensure the acquisition of the best possible design to be acquired, a sound approach of design and optimization is essentially demanded. To meet this need, a method is introduced to acquire the finest possible performance. A series of computations are carried out to formulate the grain geometry in terms of various combinations of key shapes inclusive of ellipsoid, cone, cylinder, sphere, torus, and inclined plane. A hybrid optimization (HO) technique is established by associating genetic algorithm (GA) for global solution convergence with sequential quadratic programming (SQP) for further local convergence of the solution, thus achieving the final optimal design. A comparison of the optimal design results derived from SQP, GA, and HO algorithms is presented. By using HO technique, the parameter of propellant mass is optimized to the minimum value with the required level of thrust staying within the constrained burning time, nozzle and propellant parameters, and a fixed length and outer diameter of grain,
Wind hybrid electrical supply system: behaviour simulation and sizing optimization
Notton, G.; Cristofari, C.; Poggi, P.; Muselli, M.
2001-04-01
Using a global approach, a wind hybrid system operation is simulated and the evolution of several parameters is analysed, such as the wasted energy, the fuel consumption and the role of the wind turbine subsystem in the global production. This analysis shows that all the energies which take part in the system operation are more dependent on the wind turbine size than on the battery storage capacity. A storage of 2 or 3 days is sufficient, because an increase in storage beyond these values does not have a notable impact on the performance of the wind hybrid system. Finally, a cost study is performed to determine the optimal configuration of the system conducive to the lowest cost of electricity production.
Energy Technology Data Exchange (ETDEWEB)
Patil, Chinmaya; Naghshtabrizi, Payam; Verma, Rajeev; Tang, Zhijun; Smith, Kandler; Shi, Ying
2016-08-01
This paper presents a control strategy to maximize fuel economy of a parallel hybrid electric vehicle over a target life of the battery. Many approaches to maximizing fuel economy of parallel hybrid electric vehicle do not consider the effect of control strategy on the life of the battery. This leads to an oversized and underutilized battery. There is a trade-off between how aggressively to use and 'consume' the battery versus to use the engine and consume fuel. The proposed approach addresses this trade-off by exploiting the differences in the fast dynamics of vehicle power management and slow dynamics of battery aging. The control strategy is separated into two parts, (1) Predictive Battery Management (PBM), and (2) Predictive Power Management (PPM). PBM is the higher level control with slow update rate, e.g. once per month, responsible for generating optimal set points for PPM. The considered set points in this paper are the battery power limits and State Of Charge (SOC). The problem of finding the optimal set points over the target battery life that minimize engine fuel consumption is solved using dynamic programming. PPM is the lower level control with high update rate, e.g. a second, responsible for generating the optimal HEV energy management controls and is implemented using model predictive control approach. The PPM objective is to find the engine and battery power commands to achieve the best fuel economy given the battery power and SOC constraints imposed by PBM. Simulation results with a medium duty commercial hybrid electric vehicle and the proposed two-level hierarchical control strategy show that the HEV fuel economy is maximized while meeting a specified target battery life. On the other hand, the optimal unconstrained control strategy achieves marginally higher fuel economy, but fails to meet the target battery life.
Optimization and optimal control in automotive systems
Kolmanovsky, Ilya; Steinbuch, Maarten; Re, Luigi
2014-01-01
This book demonstrates the use of the optimization techniques that are becoming essential to meet the increasing stringency and variety of requirements for automotive systems. It shows the reader how to move away from earlier approaches, based on some degree of heuristics, to the use of more and more common systematic methods. Even systematic methods can be developed and applied in a large number of forms so the text collects contributions from across the theory, methods and real-world automotive applications of optimization. Greater fuel economy, significant reductions in permissible emissions, new drivability requirements and the generally increasing complexity of automotive systems are among the criteria that the contributing authors set themselves to meet. In many cases multiple and often conflicting requirements give rise to multi-objective constrained optimization problems which are also considered. Some of these problems fall into the domain of the traditional multi-disciplinary optimization applie...
Optimal control of hydroelectric facilities
Zhao, Guangzhi
This thesis considers a simple yet realistic model of pump-assisted hydroelectric facilities operating in a market with time-varying but deterministic power prices. Both deterministic and stochastic water inflows are considered. The fluid mechanical and engineering details of the facility are described by a model containing several parameters. We present a dynamic programming algorithm for optimizing either the total energy produced or the total cash generated by these plants. The algorithm allows us to give the optimal control strategy as a function of time and to see how this strategy, and the associated plant value, varies with water inflow and electricity price. We investigate various cases. For a single pumped storage facility experiencing deterministic power prices and water inflows, we investigate the varying behaviour for an oversimplified constant turbine- and pump-efficiency model with simple reservoir geometries. We then generalize this simple model to include more realistic turbine efficiencies, situations with more complicated reservoir geometry, and the introduction of dissipative switching costs between various control states. We find many results which reinforce our physical intuition about this complicated system as well as results which initially challenge, though later deepen, this intuition. One major lesson of this work is that the optimal control strategy does not differ much between two differing objectives of maximizing energy production and maximizing its cash value. We then turn our attention to the case of stochastic water inflows. We present a stochastic dynamic programming algorithm which can find an on-average optimal control in the face of this randomness. As the operator of a facility must be more cautious when inflows are random, the randomness destroys facility value. Following this insight we quantify exactly how much a perfect hydrological inflow forecast would be worth to a dam operator. In our final chapter we discuss the
Directory of Open Access Journals (Sweden)
Kaijiang YU
2015-10-01
Full Text Available As the conventional control method for hybrid electric vehicle doesn’t consider the effect of known traffic light information on the vehicle energy management, this paper proposes a model predictive control intelligent optimization strategies based on traffic light information for hybrid electric vehicles. By building the simplified model of the hybrid electric vehicle and adopting the continuation/generalized minimum residual method, the model prediction problem is solved. The simulation is conducted by using MATLAB/Simulink platform. The simulation results show the effectiveness of the proposed model of the traffic light information, and that the proposed model predictive control method can improve fuel economy and the real-time control performance significantly. The research conclusions show that the proposed control strategy can achieve optimal control of the vehicle trajectory, significantly improving fuel economy of the vehicle, and meet the system requirements for the real-time optimal control.
Battery control system for hybrid vehicle and method for controlling a hybrid vehicle battery
Bockelmann, Thomas R [Battle Creek, MI; Hope, Mark E [Marshall, MI; Zou, Zhanjiang [Battle Creek, MI; Kang, Xiaosong [Battle Creek, MI
2009-02-10
A battery control system for hybrid vehicle includes a hybrid powertrain battery, a vehicle accessory battery, and a prime mover driven generator adapted to charge the vehicle accessory battery. A detecting arrangement is configured to monitor the vehicle accessory battery's state of charge. A controller is configured to activate the prime mover to drive the generator and recharge the vehicle accessory battery in response to the vehicle accessory battery's state of charge falling below a first predetermined level, or transfer electrical power from the hybrid powertrain battery to the vehicle accessory battery in response to the vehicle accessory battery's state of charge falling below a second predetermined level. The invention further includes a method for controlling a hybrid vehicle powertrain system.
Institute of Scientific and Technical Information of China (English)
耿俊利; 梁晖; 金渊
2015-01-01
The working modes of hybrid cascaded 7-level inverter with dead zone are analyzed and analysis results show that there are different jumping situations of inverter voltage under different working modes. On this basis, based on space vector pulse width modulation (SVPWM) strategy an optimal control method is proposed. In the premise that the supporting capacitor voltage is under the control, through analyzing the jumping of output voltage level and the valve action times corresponding to the charging/discharging process of supporting capacity voltage switching in each interval an optimal control strategy to reduce the jumping of output voltage is put forward; besides, the output voltage loss due to the existence of dead zone time is analyzed and calculated according to the principle of volt-second balance, and the dead zone compensation for its modulation wave is performed. The effectiveness of the proposed control strategy is validated by results of simulation and experiments.%分析混合级联七电平逆变器带死区时的工作模式，不同工作模式下其逆变器电压的跳变情况不同。在此基础上，提出了基于空间矢量脉冲调制(space vector pulse width modulation，SVPWM)策略的优化控制方法。以控制支撑电容电压为前提，通过对每个区间支撑电容充放电切换过程所对应的开关动作次数、输出电压电平跳变情况的分析，提出了一种减小输出电压跳变的优化控制策略；此外，分析了死区时间的存在所带来的输出电压损失，根据伏秒平衡原理进行计算，并对其调制波进行死区补偿。仿真及实验结果验证了该控制策略的有效性。
Series hybrid vehicles and optimized hydrogen engine design
Energy Technology Data Exchange (ETDEWEB)
Smith, J.R.; Aceves, S. [Lawrence Livermore National Lab., CA (United States); Van Blarigan, P. [Sandia National Labs., Livermore, CA (United States)
1995-05-10
Lawrence Livermore, Sandia Livermore and Los Alamos National Laboratories have a joint project to develop an optimized hydrogen fueled engine for series hybrid automobiles. The major divisions of responsibility are: system analysis, engine design and kinetics modeling by LLNL; performance and emission testing, and friction reduction by SNL; computational fluid mechanics and combustion modeling by LANL. This project is a component of the Department of Energy, Office of Utility Technology, National Hydrogen Program. We report here on the progress on system analysis and preliminary engine testing. We have done system studies of series hybrid automobiles that approach the PNGV design goal of 34 km/liter (80 mpg), for 384 km (240 mi) and 608 km (380 mi) ranges. Our results indicate that such a vehicle appears feasible using an optimized hydrogen engine. The impact of various on-board storage options on fuel economy are evaluated. Experiments with an available engine at the Sandia Combustion Research Facility demonstrated NO{sub x} emissions of 10 to 20 ppm at an equivalence ratio of 0.4, rising to about 500 ppm at 0.5 equivalence ratio using neat hydrogen. Hybrid vehicle simulation studies indicate that exhaust NO{sub x} concentrations must be less than 180 ppm to meet the 0.2 g/mile California Air Resources Board ULEV or Federal Tier II emissions regulations. We have designed and fabricated a first generation optimized hydrogen engine head for use on an existing single cylinder Onan engine. This head currently features 14.8:1 compression ratio, dual ignition, water cooling, two valves and open quiescent combustion chamber to minimize heat transfer losses.
A fully adaptive hybrid optimization of aircraft engine blades
Dumas, L.; Druez, B.; Lecerf, N.
2009-10-01
A new fully adaptive hybrid optimization method (AHM) has been developed and applied to an industrial problem in the field of the aircraft engine industry. The adaptivity of the coupling between a global search by a population-based method (Genetic Algorithms or Evolution Strategies) and the local search by a descent method has been particularly emphasized. On various analytical test cases, the AHM method overperforms the original global search method in terms of computational time and accuracy. The results obtained on the industrial case have also confirmed the interest of AHM for the design of new and original solutions in an affordable time.
Hybrid PID and PSO-based control for electric power assist steering system for electric vehicle
Hanifah, R. A.; Toha, S. F.; Ahmad, S.
2013-12-01
Electric power assist steering (EPAS) system provides an important significance in enhancing the driving performance of a vehicle with its energy-conserving features. This paper presents a hybrid PID (Proportional-Integral-Derivative) and particle swarm optimization (PSO) based control scheme to minimize energy consumption for EPAS. This single objective optimization scheme is realized using the PSO technique in searching for best gain parameters of the PID controller. The fast tuning feature of this optimum PID controller produced high-quality solutions. Simulation results show the performance and effectiveness of the hybrid PSO-PID based controller as opposed to the conventional PID controller.
Wang, Yan; Huang, Song; Ji, Zhicheng
2017-07-01
This paper presents a hybrid particle swarm optimization and gravitational search algorithm based on hybrid mutation strategy (HGSAPSO-M) to optimize economic dispatch (ED) including distributed generations (DGs) considering market-based energy pricing. A daily ED model was formulated and a hybrid mutation strategy was adopted in HGSAPSO-M. The hybrid mutation strategy includes two mutation operators, chaotic mutation, Gaussian mutation. The proposed algorithm was tested on IEEE-33 bus and results show that the approach is effective for this problem.
Institute of Scientific and Technical Information of China (English)
Morteza Montazeri-Gh; Mehdi Mahmoodi-K
2015-01-01
Due to soaring fuel prices and environmental concerns, hybrid electric vehicle (HEV) technology attracts more attentions in last decade. Energy management system, configuration of HEV and traffic conditions are the main factors which affect HEV's fuel consumption, emission and performance. Therefore, optimal management of the energy components is a key element for the success of a HEV. An optimal energy management system is developed for HEV based on genetic algorithm. Then, different powertrain system component combinations effects are investigated in various driving cycles. HEV simulation results are compared for default rule-based, fuzzy and GA-fuzzy controllers by using ADVISOR. The results indicate the effectiveness of proposed optimal controller over real world driving cycles. Also, an optimal powertrain configuration to improve fuel consumption and emission efficiency is proposed for each driving condition. Finally, the effects of batteries in initial state of charge and hybridization factor are investigated on HEV performance to evaluate fuel consumption and emissions. Fuel consumption average reduction of about 14% is obtained for optimal configuration data in contrast to default configuration. Also results indicate that proposed controller has reduced emission of about 10% in various traffic conditions.
PEMFC Optimization Strategy with Auxiliary Power Source in Fuel Cell Hybrid Vehicle
Directory of Open Access Journals (Sweden)
Tinton Dwi Atmaja
2012-02-01
Full Text Available Page HeaderOpen Journal SystemsJournal HelpUser You are logged in as...aulia My Journals My Profile Log Out Log Out as UserNotifications View (27 new ManageJournal Content SearchBrowse By Issue By Author By Title Other JournalsFont SizeMake font size smaller Make font size default Make font size largerInformation For Readers For Authors For LibrariansKeywords CBPNN Displacement FLC LQG/LTR Mixed PMA Ventilation bottom shear stress direct multiple shooting effective fuzzy logic geoelectrical method hourly irregular wave missile trajectory panoramic image predator-prey systems seawater intrusion segmentation structure development pattern terminal bunt manoeuvre Home About User Home Search Current Archives ##Editorial Board##Home > Vol 23, No 1 (2012 > AtmajaPEMFC Optimization Strategy with Auxiliary Power Source in Fuel Cell Hybrid VehicleTinton Dwi Atmaja, Amin AminAbstractone of the present-day implementation of fuel cell is acting as main power source in Fuel Cell Hybrid Vehicle (FCHV. This paper proposes some strategies to optimize the performance of Polymer Electrolyte Membrane Fuel Cell (PEMFC implanted with auxiliary power source to construct a proper FCHV hybridization. The strategies consist of the most updated optimization method determined from three point of view i.e. Energy Storage System (ESS, hybridization topology and control system analysis. The goal of these strategies is to achieve an optimum hybridization with long lifetime, low cost, high efficiency, and hydrogen consumption rate improvement. The energy storage system strategy considers battery, supercapacitor, and high-speed flywheel as the most promising alternative auxiliary power source. The hybridization topology strategy analyzes the using of multiple storage devices injected with electronic components to bear a higher fuel economy and cost saving. The control system strategy employs nonlinear control system to optimize the ripple factor of the voltage and the current
Hybrid genetic optimization for design of photonic crystal emitters
Rammohan, R. R.; Farfan, B. G.; Su, M. F.; El-Kady, I.; Reda Taha, M. M.
2010-09-01
A unique hybrid-optimization technique is proposed, based on genetic algorithms (GA) and gradient descent (GD) methods, for the smart design of photonic crystal (PhC) emitters. The photonic simulation is described and the granularity of photonic crystal dimensions is considered. An innovative sliding-window method for performing local heuristic search is demonstrated. Finally, the application of the proposed method on two case studies for the design of a multi-pixel photonic crystal emitter and the design of thermal emitter in thermal photovoltaic is demonstrated. Discussion in the report includes the ability of the optimal PhC structures designed using the proposed method, to produce unprecedented high emission efficiencies of 54.5% in a significantly long wavelength region and 84.9% at significantly short wavelength region.
A dynamic hybrid framework for constrained evolutionary optimization.
Wang, Yong; Cai, Zixing
2012-02-01
Based on our previous work, this paper presents a dynamic hybrid framework, called DyHF, for solving constrained optimization problems. This framework consists of two major steps: global search model and local search model. In the global and local search models, differential evolution serves as the search engine, and Pareto dominance used in multiobjective optimization is employed to compare the individuals in the population. Unlike other existing methods, the above two steps are executed dynamically according to the feasibility proportion of the current population in this paper, with the purpose of reasonably distributing the computational resource for the global and local search during the evolution. The performance of DyHF is tested on 22 benchmark test functions. The experimental results clearly show that the overall performance of DyHF is highly competitive with that of a number of state-of-the-art approaches from the literature.
Optimal Control of Electrodynamic Tethers
2008-06-01
left with ( ) ( ) 1 2 1 2 23 3 3 32 1 2 1 2 3 3 ˆ ˆ 2 2 2 ˆ ˆ 6 6 t t t t t t m m m m m T m L m L M M m LM M M MLm M M... Contract RH4-394049, March 1985, p 31. 9 Pelaez, J. and Lorenzini, E. C., “Libration Control of Electrodynamic Tethers in Inclined Orbit,” Journal of...COVERED (From – To) Aug 2006 – Jul 2008 4. TITLE AND SUBTITLE Optimal Control of Electrodynamic Tethers 5a. CONTRACT NUMBER 5b
Energy Optimal Control Strategy of PHEV Based on PMP Algorithm
Directory of Open Access Journals (Sweden)
Tiezhou Wu
2017-01-01
Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
Optimal Selective Harmonic Control for Power Harmonics Mitigation
DEFF Research Database (Denmark)
Zhou, Keliang; Yang, Yongheng; Blaabjerg, Frede
2015-01-01
the cost, the complexity and the performance: high accuracy, fast transient response, easy-implementation, cost-effective, and also easy-to-design. The analysis and synthesis of the optimal SHC system are addressed. The proposed SHC offers power convert-ers a tailor-made optimal control solution......This paper proposes an Internal Model Principle (IMP) based optimal Selective Harmonic Controller (SHC) for power converters to mitigate power harmonics. According to the harmonics distribution caused by power converters, a universal recursive SHC module is developed to deal with a featured group...... of power harmonics. The proposed optimal SHC is of hybrid structure: all recursive SHC modules with weighted gains are connected in parallel. It bridges the real “nk+-m order RC” and the complex “parallel structure RC”. Compared to other IMP based control solutions, it offers an optimal trade-off among...
Soft Computing Applications in Optimization, Control, and Recognition
Castillo, Oscar
2013-01-01
Soft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new models for achieving intelligent optimization in different application areas. The second part discusses hybrid intelligent systems for achieving control. Papers included in this part make use of nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for the optimal design of intelligent controllers for different kind of applications. Papers in the third part focus on intelligent techniques for pattern recognition and propose new methods to solve complex pattern recognition problems. The fourth part discusses new theoretical concepts ...
Adaptive and Reliable Control Algorithm for Hybrid System Architecture
Directory of Open Access Journals (Sweden)
Osama Abdel Hakeem Abdel Sattar
2012-01-01
Full Text Available A stand-alone system is defined as an autonomous system that supplies electricity without being connected to the electric grid. Hybrid systems combined renewable energy source, that are never depleted (such solar (photovoltaic (PV, wind, hydroelectric, etc. , With other sources of energy, like Diesel. If these hybrid systems are optimally designed, they can be more cost effective and reliable than single systems. However, the design of hybrid systems is complex because of the uncertain renewable energy supplies, load demands and the non-linear characteristics of some components, so the design problem cannot be solved easily by classical optimisation methods. The use of heuristic techniques, such as the genetic algorithms, can give better results than classical methods. This paper presents to a hybrid system control algorithm and also dispatches strategy design in which wind is the primary energy resource with photovoltaic cells. The dimension of the design (max. load is 2000 kW and the sources is implemented as flow 1500 kw from wind, 500 kw from solar and diesel 2000 kw. The main task of the preposed algorithm is to take full advantage of the wind energy and solar energy when it is available and to minimize diesel fuel consumption.
ε-MAXIMUM PRINCIPLE IN LINEAR PROBLEM OF HYBRID SYSTEM OPTIMUM CONTROL
Directory of Open Access Journals (Sweden)
O. R. Gabasova
2009-01-01
Full Text Available The paper reveals necessary and sufficient conditions of optimality and sub-optimality of the programs for a hybrid system in the class of discrete control actions. The conditions are formulated in the support terms of the initial problem.
Non-fragile hybrid guaranteed cost control for a class of uncertain switched linear systems
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
This paper focuses on the problem of non-fragile hybrid guaranteed cost control for a class of uncertain switched linear systems. The controller gain to be designed is assumed to have additive gain variations. Based on multiple-Lyapunov function technique, the design of non-fragile hybrid guaranteed cost controllers is derived to make the corresponding closed-loop system asymptotically stable for all admissible uncertainties. Furthermore, a convex optimization approach with LMIs constraints is introduced to select the optimal non-fragile guaranteed cost controllers. Finally, a simulation example illustrates the effectiveness of the proposed approach.
Hybrid Genetic Algorithms with Fuzzy Logic Controller
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In this paper, a new implementation of genetic algorithms (GAs) is developed for the machine scheduling problem, which is abundant among the modern manufacturing systems. The performance measure of early and tardy completion of jobs is very natural as one's aim, which is usually to minimize simultaneously both earliness and tardiness of all jobs. As the problem is NP-hard and no effective algorithms exist, we propose a hybrid genetic algorithms approach to deal with it. We adjust the crossover and mutation probabilities by fuzzy logic controller whereas the hybrid genetic algorithm does not require preliminary experiments to determine probabilities for genetic operators. The experimental results show the effectiveness of the GAs method proposed in the paper.``
Directory of Open Access Journals (Sweden)
Hao Zhu
2017-04-01
Full Text Available Design reliability and robustness are getting increasingly important for the general design of aerospace systems with many inherently uncertain design parameters. This paper presents a hybrid uncertainty-based design optimization (UDO method developed from probability theory and interval theory. Most of the uncertain design parameters which have sufficient information or experimental data are classified as random variables using probability theory, while the others are defined as interval variables with interval theory. Then a hybrid uncertainty analysis method based on Monte Carlo simulation and Taylor series interval analysis is developed to obtain the uncertainty propagation from the design parameters to system responses. Three design optimization strategies, including deterministic design optimization (DDO, probabilistic UDO and hybrid UDO, are applied to the conceptual design of a hybrid rocket motor (HRM used as the ascent propulsion system in Apollo lunar module. By comparison, the hybrid UDO is a feasible method and can be effectively applied to the general design of aerospace systems.
Directory of Open Access Journals (Sweden)
Nandakumar Sundararaju
2014-05-01
Full Text Available This paper proposes novel hybrid asymmetric space vector modulation technique for inverter operated direct torque control induction motor drive. The hybridization process is performed by the combination of continuous asymmetric space vector modulation pulse width technique (ASVPWM and fuzzy operated discontinuous ASVPWM technique. Combination process is based on pulse mismatching technique. Pulse mismatching technique helps to reduce the active region of the switch. Finally, optimal pulses are applied to control the inverter. The optimal hybrid pulse condense switching losses of the inverter and also improves the operating performance of the direct torque control (DTC based drive system like smooth dynamic response in speed reversal, minimum torque error, settling time of speed. Simulation results of proposed hybrid asymmetric space vector pulse width modulation technique to direct torque control (HASVPWM-DTC approach has been carried out by using Matlab-Simulink environment.
Directory of Open Access Journals (Sweden)
Jingxian Hao
2016-11-01
Full Text Available The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle performance at different driving cycles and conditions. For this reason, the optimization of key parameters is important to improve the fuel economy, dynamic performance, and drivability. In principle, this is a multiparameter nonlinear optimization problem. The logic threshold energy management strategy for an all-wheel-drive HEV is comprehensively analyzed and developed in this study. Seven key parameters to be optimized are extracted. The optimization model of key parameters is proposed from the perspective of fuel economy. The global optimization method, DIRECT algorithm, which has good real-time performance, low computational burden, rapid convergence, is selected to optimize the extracted key parameters globally. The results show that with the optimized parameters, the engine operates more at the high efficiency range resulting into a fuel savings of 7% compared with non-optimized parameters. The proposed method can provide guidance for calibrating the parameters of the vehicle energy management strategy from the perspective of fuel economy.
Optimal operation of hybrid-SITs under a SBO accident
Energy Technology Data Exchange (ETDEWEB)
Jeon, In Seop, E-mail: inseopjeon@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); Heo, Sun, E-mail: sunnysunny@khnp.co.kr [Central Research Institute, Korea Hydro & Nuclear Power Co., 70 Yuseong-daero 1312 beon-gil, Yuseong-gu, Daejeon 305-343 (Korea, Republic of); Kang, Hyun Gook, E-mail: hyungook@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of)
2016-02-15
Highlights: • Operation strategy of hybrid-SIT (H-SIT) in station blackout (SBO) is developed. • There are five main factors which have to be carefully treated in the development of the operation strategy. • Optimal value of each main factor is investigated analytically and then through thermal-hydraulic analysis using computer code. • The optimum operation strategy is suggested based on the optimal value of the main factors. - Abstract: A hybrid safety injection tank (H-SIT) is designed to enhance the capability of pressurized water reactors against high-pressure accidents which might be caused by the combined accidents accompanied by station blackout (SBO), and is suggested as a useful alternative to electricity-driven motor injection pumps. The main purpose of the H-SIT is to provide coolant to the core so that core safety can be maintained for a longer period. As H-SITs have a limited inventory, their efficient use in cooling down the core is paramount to maximize the available time for long-term cooling component restoration. Therefore, an optimum operation strategy must be developed to support the operators for the most efficient H-SIT use. In this study, the main factors which have to be carefully treated in the development of an operation strategy are first identified. Then the optimal value of each main factor is investigated analytically, a process useful to get the basis of the global optimum points. Based on these analytical optimum points, a thermal-hydraulic analysis using MARS code is performed to get more accurate values and to verify the results of the analytical study. The available time for long-term cooling component restoration is also estimated. Finally, an integrated optimum operation strategy for H-SITs in SBO is suggested.
Optimal Energy Management for a Complex Hybrid Electric Vehicle:Tolerating Power-loss of Motor
Institute of Scientific and Technical Information of China (English)
ZHANG Pei-zhi; YIN Cheng-liang; ZHANG Yong; WU Zhi-wei
2009-01-01
The energy management may perform well under normal conditions, but may lead to poor behavior under abnormal situations. To tackle this problem, an optimal control strategy called rule-based equivalent fuel consumption minimization strategy (RECMS) is developed for a new complex hybrid electric vehicle (CHEV).It optimizes the energy efficiency and drive performance to cater for normal and power-loss operations of the tractive motor. Firstly, the strategy formulates a novel objective function based on the equivalent fuel concept.By accounting for the actual fuel cost, the equivalent fuel cost for the electric machines and virtual fuel cost for the drivability, the cost function is obtained. Furthermore, some penalty factors are presented to optimize the performance target. Finally, experiments for a practical CHEV are performed to validate a simulation model.Then simulations are carried out for both rule-based and RECMS. The results show that the optimal energy management is working well.
Efficient Hybrid Optimal Design Method for Power Electronics Converters
AUTHOR|(SzGeCERN)697719; Aguglia, Davide; Viarouge, Philippe; Cros, Jérôme
2015-01-01
This paper presents a novel design methodology for dimensioning optimal power-electronic converters, which is able to achieve the precision of numerical simulation-based optimization procedures, however minimizing the overall computation time. The approach is based on the utilization of analytical and frequency-domain design models for a numerical optimization process, a validation with numerical simulations of the intermediate optimal solutions, and the correction of the analytical design models precision from the numerical simulation results. This method allows using the numerical simulation in an efficient way, where typically less than ten correction iterations are required. In order to demonstrate the performances of the proposed methodology, the calculation of the control parameters for an H-bridge DC-DC converter and the optimal dimensioning of a damped output filter for a buck converter using the proposed approach is presented.
Optimal air-supply mode of hybrid system with radiant cooling and dedicated outdoor air
Institute of Scientific and Technical Information of China (English)
丁研; 田喆; 朱能
2015-01-01
The hybrid system with radiant cooling and dedicated outdoor air not only possesses high energy efficiency, but also creates a healthy and comfortable indoor environment. Indoor air quality will be improved by the dedicated outdoor air system (DOAS) and indoor thermal comfort can be enhanced by the radiant cooling system (RCS). The optimal air-supply mode of the hybrid system and the corresponding design approach were investigated. A full-scale experimental chamber with various air outlets and the ceiling radiant cooling panels (CRCP) was designed and established. The performances of different air-supply modes along with CRCPs were analyzed by multi-index evaluations. Preliminary investigations were also conducted on the humidity stratification and the control effect of different airflow modes to prevent condensation on CRCP. The overhead supply air is recommended as the best combination mode for the hybrid system after comprehensive comparison of the experiment results. The optimal proportion of CRCP accounting for the total cooling capacities in accord with specific cooling loads is found, which may provide valuable reference for the design and operation of the hybrid system.
Institute of Scientific and Technical Information of China (English)
钱立军; 邱利宏; 辛付龙; 陈朋; 王金波
2015-01-01
为精确计算驾驶员请求转矩，克服模糊逻辑及模糊比例-积分-微分（proportion integration differentiation，PID）需要先验知识的固有缺陷，该文提出利用径向基函数（radial basis function，RBF）神经网络拟合转矩识别系数。考虑到动力部件的瞬态特性，建立了各动力部件及传动系统的动力学模型，制定了基于规则的控制策略并描述了各驱动模式的成立条件及其动力学方程。为减少程序运行时间，提出修正动态规划（correctional dynamic programming，CDP）算法对控制策略进行全局优化。搭建硬件在环试验台架，对控制策略进行了试验。试验结果表明，基于规则和修正动态规划的控制策略均能实现良好的控制效果。引入转矩识别后，车速误差明显减小，燃油经济性提高了4.54%。采用修正动态规划后，燃油经济性进一步提高了14.04%。该文研究方法可以为制定复杂混合动力系统控制策略提供理论依据。%For a plug-in four-wheel-drive hybrid electric vehicle (4WD PHEV), there are 3 power components which can work independently or cooperatively. Therefore, it has many work modes and the energy management control is relatively complicated. As the calculation of the torque request of the driver by the gas pedal travel only is not precise and that method can’t reflect the driver’s intention, especially the intensity of the acceleration, thus rendering bad power performances and fuel consumption. And to overcome the inherent defects of fuzzy logic and fuzzy PID (proportion integration differentiation) that they relied on prior knowledge to set the parameters and it was difficult to realize good control effect, it was put forward in this paper that the torque identification coefficient could be obtained through RBF (radial basis function) neural network, whose inputs were the gas pedal travel and its change rate, and the output was the torque
Hooke–Jeeves Method-used Local Search in a Hybrid Global Optimization Algorithm
Directory of Open Access Journals (Sweden)
V. D. Sulimov
2014-01-01
Full Text Available Modern methods for optimization investigation of complex systems are based on development and updating the mathematical models of systems because of solving the appropriate inverse problems. Input data desirable for solution are obtained from the analysis of experimentally defined consecutive characteristics for a system or a process. Causal characteristics are the sought ones to which equation coefficients of mathematical models of object, limit conditions, etc. belong. The optimization approach is one of the main ones to solve the inverse problems. In the main case it is necessary to find a global extremum of not everywhere differentiable criterion function. Global optimization methods are widely used in problems of identification and computation diagnosis system as well as in optimal control, computing to-mography, image restoration, teaching the neuron networks, other intelligence technologies. Increasingly complicated systems of optimization observed during last decades lead to more complicated mathematical models, thereby making solution of appropriate extreme problems significantly more difficult. A great deal of practical applications may have the problem con-ditions, which can restrict modeling. As a consequence, in inverse problems the criterion functions can be not everywhere differentiable and noisy. Available noise means that calculat-ing the derivatives is difficult and unreliable. It results in using the optimization methods without calculating the derivatives.An efficiency of deterministic algorithms of global optimization is significantly restrict-ed by their dependence on the extreme problem dimension. When the number of variables is large they use the stochastic global optimization algorithms. As stochastic algorithms yield too expensive solutions, so this drawback restricts their applications. Developing hybrid algo-rithms that combine a stochastic algorithm for scanning the variable space with deterministic local search
HCCI Engine Optimization and Control
Energy Technology Data Exchange (ETDEWEB)
Rolf D. Reitz
2005-09-30
The goal of this project was to develop methods to optimize and control Homogeneous-Charge Compression Ignition (HCCI) engines, with emphasis on diesel-fueled engines. HCCI offers the potential of nearly eliminating IC engine NOx and particulate emissions at reduced cost over Compression Ignition Direct Injection engines (CIDI) by controlling pollutant emissions in-cylinder. The project was initiated in January, 2002, and the present report is the final report for work conducted on the project through December 31, 2004. Periodic progress has also been reported at bi-annual working group meetings held at USCAR, Detroit, MI, and at the Sandia National Laboratories. Copies of these presentation materials are available on CD-ROM, as distributed by the Sandia National Labs. In addition, progress has been documented in DOE Advanced Combustion Engine R&D Annual Progress Reports for FY 2002, 2003 and 2004. These reports are included as the Appendices in this Final report.
Power optimized programmable embedded controller
Kamaraju, M; Tilak, A V N; 10.5121/ijcnc.2010.2409
2010-01-01
Now a days, power has become a primary consideration in hardware design, and is critical in computer systems especially for portable devices with high performance and more functionality. Clock-gating is the most common technique used for reducing processor's power. In this work clock gating technique is applied to optimize the power of fully programmable Embedded Controller (PEC) employing RISC architecture. The CPU designed supports i) smart instruction set, ii) I/O port, UART iii) on-chip clocking to provide a range of frequencies , iv) RISC as well as controller concepts. The whole design is captured using VHDL and is implemented on FPGA chip using Xilinx .The architecture and clock gating technique together is found to reduce the power consumption by 33.33% of total power consumed by this chip.
A Novel Hybrid Safety-control Strategy for a Manipulator
Directory of Open Access Journals (Sweden)
Jing Xia
2014-04-01
Full Text Available As robots tend to work cooperatively with humans in shared workplaces, safety as regards robot- human interactions has caused a great deal of concern in the robot community, and control strategies have become a hot topic in robotics research. In order to guarantee the robot’s safety and continuous motions, this paper proposes a novel safety-control strategy, which is strictly conservative and which consists of a pre-contact and post-contact safety strategy. We adopt an optimal motion trajectory-planning method, by use of which the jerk, acceleration and velocity of the robot’s motion can be limited and a time-optimal motion can be obtained as a post-contact safety strategy for a position-controlled manipulator. The optimal motion trajectory planning not only reduces the impact forces during the collision period, but also maintains the efficiency of the manipulator and preserves continuous motions. Next, we describe a novel collision detection method as a pre-contact safety strategy to avoid collisions. The method proposed here can compute security warning region to handle the effect of robot motion on collision detection and detect collisions between non-convex polygon soups. Finally, the control strategy is implemented for a 7-DOF humanoid manipulator and the experimental results demonstrate the validity of this novel hybrid safety-control strategy.
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.
Hybrid Bacterial Foraging and Particle Swarm Optimization for detecting Bundle Branch Block.
Kora, Padmavathi; Kalva, Sri Ramakrishna
2015-01-01
Abnormal cardiac beat identification is a key process in the detection of heart diseases. Our present study describes a procedure for the detection of left and right bundle branch block (LBBB and RBBB) Electrocardiogram (ECG) patterns. The electrical impulses that control the cardiac beat face difficulty in moving inside the heart. This problem is termed as bundle branch block (BBB). BBB makes it harder for the heart to pump blood effectively through the heart circulatory system. ECG feature extraction is a key process in detecting heart ailments. Our present study comes up with a hybrid method combining two heuristic optimization methods: Bacterial Forging Optimization (BFO) and Particle Swarm Optimization (PSO) for the feature selection of ECG signals. One of the major controlling forces of BFO algorithm is the chemotactic movement of a bacterium that models a test solution. The chemotaxis process of the BFO depends on random search directions which may lead to a delay in achieving the global optimum solution. The hybrid technique: Bacterial Forging-Particle Swarm Optimization (BFPSO) incorporates the concepts from BFO and PSO and it creates individuals in a new generation. This BFPSO method performs local search through the chemotactic movement of BFO and the global search over the entire search domain is accomplished by a PSO operator. The BFPSO feature values are given as the input for the Levenberg-Marquardt Neural Network classifier.
Power Management Optimization of an Experimental Fuel Cell/Battery/Supercapacitor Hybrid System
Directory of Open Access Journals (Sweden)
Farouk Odeim
2015-06-01
Full Text Available In this paper, an experimental fuel cell/battery/supercapacitor hybrid system is investigated in terms of modeling and power management design and optimization. The power management strategy is designed based on the role that should be played by each component of the hybrid power source. The supercapacitor is responsible for the peak power demands. The battery assists the supercapacitor in fulfilling the transient power demand by controlling its state-of-energy, whereas the fuel cell system, with its slow dynamics, controls the state-of-charge of the battery. The parameters of the power management strategy are optimized by a genetic algorithm and Pareto front analysis in a framework of multi-objective optimization, taking into account the hydrogen consumption, the battery loading and the acceleration performance. The optimization results are validated on a test bench composed of a fuel cell system (1.2 kW, 26 V, lithium polymer battery (30 Ah, 37 V, and a supercapacitor (167 F, 48 V.
Parametric optimization of a new hybrid pneumatic-combustion engine
Energy Technology Data Exchange (ETDEWEB)
Higelin, P.; Vasile, I.; Charlet, A.; Chamaillard, Y. [Universite d' Orleans, LME-ESEM, Orleans (France)
2004-06-01
Although internal combustion engines display high overall maximum global efficiencies, this potential cannot be fully exploited in automotive applications: in real conditions, the average engine load (and thus efficiency) is quite low and the kinetic energy during a braking phase is lost. One solution to this problem is to switch to a new hybrid pneumatic-combustion engine concept, which is able to store energy in the form of compressed air. This energy can be issued from a braking phase or from a combustion phase at low power. The potential energy from the air tank can then be restored to start the engine, use the stored air to drive the engine as a pneumatic motor at low load or charge the engine at full load. Optimization of the compressed air tank maximum pressure and volume as well as the operating mode switching strategy provides an improvement in terms of fuel economy as high as 31 per cent if combined with engine downsizing. (Author)
Indoor Wireless Localization-hybrid and Unconstrained Nonlinear Optimization Approach
Directory of Open Access Journals (Sweden)
R. Jayabharathy
2013-07-01
Full Text Available In this study, a hybrid TOA/RSSI wireless localization is proposed for accurate positioning in indoor UWB systems. The major problem in indoor localization is the effect of Non-Line of Sight (NLOS propagation. To mitigate the NLOS effects, an unconstrained nonlinear optimization approach is utilized to process Time-of-Arrival (TOA and Received Signal Strength (RSS in the location system.TOA range measurements and path loss model are used to discriminate LOS and NLOS conditions. The weighting factors assigned by hypothesis testing, is used for solving the objective function in the proposed approach. This approach is used for describing the credibility of the TOA range measurement. Performance of the proposed technique is done based on MATLAB simulation. The result shows that the proposed technique performs well and achieves improved positioning under severe NLOS conditions.
Hybrid Neural Network and Support Vector Machine Method for Optimization
Rai, Man Mohan (Inventor)
2007-01-01
System and method for optimization of a design associated with a response function, using a hybrid neural net and support vector machine (NN/SVM) analysis to minimize or maximize an objective function, optionally subject to one or more constraints. As a first example, the NN/SVM analysis is applied iteratively to design of an aerodynamic component, such as an airfoil shape, where the objective function measures deviation from a target pressure distribution on the perimeter of the aerodynamic component. As a second example, the NN/SVM analysis is applied to data classification of a sequence of data points in a multidimensional space. The NN/SVM analysis is also applied to data regression.
Hybrid vehicle system studies and optimized hydrogen engine design
Energy Technology Data Exchange (ETDEWEB)
Smith, J.R.; Aceves, S.
1995-04-26
We have done system studies of series hydrogen hybrid automobiles that approach the PNGV design goal of 34 km/liter (80 mpg), for 384 km (240 mi) and 608 km (380 mi) ranges. Our results indicate that such a vehicle appears feasible using an optimized hydrogen engine. We have evaluated the impact of various on-board storage options on fuel economy. Experiments in an available engine at the Sandia CRF demonstrated NO{sub x} emissions of 10 to 20 ppM at an equivalence ratio of 0.4, rising to about 500 ppm at 0.5 equivalence ratio using neat hydrogen. Hybrid simulation studies indicate that exhaust NO{sub x} concentrations must be less than 180 ppM to meet the 0.2 g/mile ULEV or Federal Tier II emissions regulations. LLNL has designed and fabricated a first generation optimized hydrogen engine head for use on an existing Onan engine. This head features 15:1 compression ratio, dual ignition, water cooling, two valves and open quiescent combustion chamber to minimize heat transfer losses. Initial testing shows promise of achieving an indicated efficiency of nearly 50% and emissions of less than 100 ppM NO{sub x}. Hydrocarbons and CO are to be measured, but are expected to be very low since their only source is engine lubricating oil. A successful friction reduction program on the Onan engine should result in a brake thermal efficiency of about 42% compared to today`s gasoline engines of 32%. Based on system studies requirements, the next generation engine will be about 2 liter displacement and is projected to achieve 46% brake thermal efficiency with outputs of 15 kW for cruise and 40 kW for hill climb.
Optimal control of induction heating processes
Rapoport, Edgar
2006-01-01
This book introduces new approaches to solving optimal control problems in induction heating process applications. Optimal Control of Induction Heating Processes demonstrates how to apply and use new optimization techniques for different types of induction heating installations. Focusing on practical methods for solving real engineering optimization problems, the text features a variety of specific optimization examples for induction heater modes and designs, particularly those used in industrial applications. The book describes basic physical phenomena in induction heating and induction
Directory of Open Access Journals (Sweden)
Mohamed Zellagui
2017-09-01
Full Text Available The paper presents a new hybrid global optimization algorithm based on Chemical Reaction based Optimization (CRO and Di¤erential evolution (DE algorithm for nonlinear constrained optimization problems. This approach proposed for the optimal coordination and setting relays of directional overcurrent relays in complex power systems. In protection coordination problem, the objective function to be minimized is the sum of the operating time of all main relays. The optimization problem is subject to a number of constraints which are mainly focused on the operation of the backup relay, which should operate if a primary relay fails to respond to the fault near to it, Time Dial Setting (TDS, Plug Setting (PS and the minimum operating time of a relay. The hybrid global proposed optimization algorithm aims to minimize the total operating time of each protection relay. Two systems are used as case study to check the effeciency of the optimization algorithm which are IEEE 4-bus and IEEE 6-bus models. Results are obtained and presented for CRO and DE and hybrid CRO-DE algorithms. The obtained results for the studied cases are compared with those results obtained when using other optimization algorithms which are Teaching Learning-Based Optimization (TLBO, Chaotic Differential Evolution Algorithm (CDEA and Modiffied Differential Evolution Algorithm (MDEA, and Hybrid optimization algorithms (PSO-DE, IA-PSO, and BFOA-PSO. From analysing the obtained results, it has been concluded that hybrid CRO-DO algorithm provides the most optimum solution with the best convergence rate.
Optimization and field demonstration of hybrid hydrogen generator/high efficiency furnace system
Energy Technology Data Exchange (ETDEWEB)
Entchev, E.; Coyle, I.; Szadkowski, F. [CANMET Energy Technology Centre, 1 Haanel Dr., Ottawa, Ontario K1A-1M1 (Canada); Manning, M.; Swinton, M. [National Research Council Ottawa, Ontario (Canada); Graydon, J.; Kirk, D. [University of Toronto, Toronto, Ontario (Canada)
2009-05-15
Hydrogen is seen as an energy carrier of the future and significant research on hydrogen generation, storage and utilization is accomplished around the world. However, an appropriate intermediate step before wide hydrogen introduction will be blending conventional fuels such as natural gas, oil or diesel with hydrogen and follow up combustion through conventional means. Due to changes in the combustion and flame characteristics of the system additional research is needed to access the limits and the impact of the fuel mix on the combustion systems performance. The hybrid system consists of a 5 kW{sub el} electrolyzer and a residential 15 kW{sub th} high efficiency gas fired furnace. The electrolyzer was integrated with the furnace gas supply and setup to replace 5-25% of the furnace natural gas flow with hydrogen. A mean for proper mixing of hydrogen with natural gas was provided and a control system for safe system operation was developed. Prior to the start of the field trial the hybrid system was investigated in laboratory environment. It was subjected to a variety of steady state and cycling conditions and a detailed performance and optimization analysis was performed with a range of hydrogen/natural gas mixtures. The optimized system was then installed at the Canadian Centre for Housing Technologies (CCHT) Experimental research house. The energy performance of the hybrid system was compared to the energy performance of an identical high efficiency furnace in the Control research house next door. (author)
Institute of Scientific and Technical Information of China (English)
赵治国; 吴朝春; 杨云云; 陈海军
2016-01-01
Taking the hybrid electric vehicle equipped with dual clutch transmission(DCT) as the object and considering the characteristics of fast responding and high accuracy of integrated starter and generator(ISG) motor speed and torque, the robust control issue of torque coordination between twin clutches and power sources when ISG intervene with the gear-shifting process are investigated. The different dynamics models in the different phases of whole shifting process are established; Then, the power sources' synthesizing torque is optimally determined under the consideration of the responding characteristic of clutch actuators in the torque phase and the model uncertainty & external disturbance(measurement noise and engine torque’s lag) in the inertia phase; Afterwards, in the torque transition phase, the engine torque is switched into the level of driver demand and ISG torque is slowly come down. Finally, the torques of the power sources are distributed based on the optimization of system efficiency. The simulation results on the Simulink software platform illustrate that the proposed control strategies possess the capabilities of strong anti-uncertainty and anti-disturbance. And the following bench test results further show that it can also effectively address the coordinating control problems between the twin clutches and power sources, ensure that the vehicle has good quality in shift.%针对双离合器自动变速器(Dual clutch transmission，DCT)变速弱混合动力轿车，考虑到起动发电一体化电机(Integrated starter and generator，ISG)转矩响应特性较快、转速/转矩控制精度高等特点，对其介入到换档过程时不同动力源输出转矩和离合器传递转矩协调鲁棒控制问题进行研究。建立体现DCT换档切换过程阶段差异性的动力学模型；考虑转矩相的离合器执行机构的响应能力和惯性相的模型不确定性和外界干扰(转速量测噪声和发动机转矩响应滞后)，优化
Optimal control of sun tracking solar concentrators
Hughes, R. O.
1979-01-01
Application of the modern control theory to derive an optimal sun tracking control for a point focusing solar concentrator is presented. A standard tracking problem converted to regulator problem using a sun rate input achieves an almost zero steady state tracking error with the optimal control formulation. However, these control techniques are costly because optimal type algorithms require large computing systems, thus they will be used mainly as comparison standards for other types of control algorithms and help in their development.
CVT shift control for a hybrid driveline
Energy Technology Data Exchange (ETDEWEB)
Mueller, C. [VDI (Germany); Schroeder, D.
2002-07-01
In this contribution, chain drive CVTs will be investigated. Pushing belt CVTs are characterized by a different construction, but some basic concepts can be partly transferred. The identification results refer to the drive train of a parallel hybrid passenger car which is discussed as an example for application. It is equipped with a special CVT based gearbox. A set of clutches allows the squaring of the single CVT range of possible gear ratios. A detailed description of the system is given in [2]. CVT models discussed in literature [15],[10] focus primarily on component strain in order to support the design process. These models are usually rather complex and are not well-suited for control purposes. In the following, a short system description will be given. Properties relevant for control will be outlined. (orig.)
OPTIMIZED PARTICLE SWARM OPTIMIZATION BASED DEADLINE CONSTRAINED TASK SCHEDULING IN HYBRID CLOUD
Directory of Open Access Journals (Sweden)
Dhananjay Kumar
2016-01-01
Full Text Available Cloud Computing is a dominant way of sharing of computing resources that can be configured and provisioned easily. Task scheduling in Hybrid cloud is a challenge as it suffers from producing the best QoS (Quality of Service when there is a high demand. In this paper a new resource allocation algorithm, to find the best External Cloud provider when the intermediate provider’s resources aren’t enough to satisfy the customer’s demand is proposed. The proposed algorithm called Optimized Particle Swarm Optimization (OPSO combines the two metaheuristic algorithms namely Particle Swarm Optimization and Ant Colony Optimization (ACO. These metaheuristic algorithms are used for the purpose of optimization in the search space of the required solution, to find the best resource from the pool of resources and to obtain maximum profit even when the number of tasks submitted for execution is very high. This optimization is performed to allocate job requests to internal and external cloud providers to obtain maximum profit. It helps to improve the system performance by improving the CPU utilization, and handle multiple requests at the same time. The simulation result shows that an OPSO yields 0.1% - 5% profit to the intermediate cloud provider compared with standard PSO and ACO algorithms and it also increases the CPU utilization by 0.1%.
Temperature controller optimization by computational intelligence
Directory of Open Access Journals (Sweden)
Ćojbašić Žarko M.
2016-01-01
Full Text Available In this paper a temperature control system for an automated educational classroom is optimized with several advanced computationally intelligent methods. Controller development and optimization has been based on developed and extensively tested mathematical and simulation model of the observed object. For the observed object cascade P-PI temperature controller has been designed and conventionally tuned. To improve performance and energy efficiency of the system, several metaheuristic optimizations of the controller have been attempted, namely genetic algorithm optimization, simulated annealing optimization, particle swarm optimization and ant colony optimization. Efficiency of the best results obtained with proposed computationally intelligent optimization methods has been compared with conventional controller tuning. Results presented in this paper demonstrate that heuristic optimization of advanced temperature controller can provide improved energy efficiency along with other performance improvements and improvements regarding equipment wear. Not only that presented methodology provides for determination and tuning of the core controller, but it also allows that advanced control concepts such as anti-windup controller gain are optimized simultaneously, which is of significant importance since interrelation of all control system parameters has important influence on the stability and performance of the system as a whole. Based on the results obtained, general conclusions are presented indicating that meta-heuristic computationally intelligent optimization of heating, ventilation, and air conditioning control systems is a feasible concept with strong potential in providing improved performance, comfort and energy efficiency. [Projekat Ministarstva nauke Republike Srbije, br. TR 33047 i br. TR 35016
Intelligent Control Scheme of Engineering Machinery of Cluster Hybrid System
Institute of Scientific and Technical Information of China (English)
GAO Qiang; WANG Hongli
2005-01-01
In a hybrid system, the subsystems with discrete dynamics play a central role in a hybrid system. In the course of engineering machinery of cluster construction, the discrete control law is hard to obtain because the construction environment is complex and there exist many affecting factors. In this paper, hierarchically intelligent control, expert control and fuzzy control are introduced into the discrete subsystems of engineering machinery of cluster hybrid system, so as to rebuild the hybrid system and make the discrete control law easily and effectively obtained. The structures, reasoning mechanism and arithmetic of intelligent control are replanted to discrete dynamic, conti-nuous process and the interface of the hybrid system. The structures of three types of intelligent hybrid system are presented and the human experiences summarized from engineering machinery of cluster are taken into account.
Novel hybrid coatings with controlled wettability by composite nanoparticle aggregation
Energy Technology Data Exchange (ETDEWEB)
Hritcu, Doina, E-mail: dhritcu@ch.tuiasi.ro; Dodi, Gianina; Iordache, Mirabela L.; Draganescu, Dan; Sava, Elena; Popa, Marcel I.
2016-11-30
Highlights: • Magnetite-grafted chitosan composite nanoparticles were synthesized. • The particles are able to assemble under the influence of a silane derivative. • Thin films containing composites, chitosan and hydrolyzed silane were optimized. • The novel hybrid coatings show hierarchical roughness and high wetting angle. - Abstract: The aim of this study is to evaluate novel hybrid materials as potential candidates for producing coatings with hierarchical roughness and controlled wetting behaviour. Magnetite (Fe{sub 3}O{sub 4}) nanoparticles obtained by co-precipitation were embedded in matrices synthesized by radical graft co-polymerization of butyl acrylate (BA), butyl methacrylate (BMA), hexyl acrylate (HA) or styrene (ST) with ethylene glycol di-methacrylate (EGDMA) onto previously modified chitosan bearing surface vinyl groups. The resulting composite particles were characterized regarding their average size, composition and magnetic properties. Hybrid thin films containing suspension of composite particles in ethanol and pre-hydrolysed hexadecyltrimethoxysilane (HDTS) as a coupling/crosslinking agent were deposited by spin coating or spraying. The films were cured by heating and subsequently characterized regarding their morphology (scanning electron microscopy), contact angle with water and adhesion to substrate (scratch test). The structure-property relationship is discussed.
Directory of Open Access Journals (Sweden)
José F. Herbert-Acero
2014-01-01
Full Text Available This work presents a novel framework for the aerodynamic design and optimization of blades for small horizontal axis wind turbines (WT. The framework is based on a state-of-the-art blade element momentum model, which is complemented with the XFOIL 6.96 software in order to provide an estimate of the sectional blade aerodynamics. The framework considers an innovative nested-hybrid solution procedure based on two metaheuristics, the virtual gene genetic algorithm and the simulated annealing algorithm, to provide a near-optimal solution to the problem. The objective of the study is to maximize the aerodynamic efficiency of small WT (SWT rotors for a wide range of operational conditions. The design variables are (1 the airfoil shape at the different blade span positions and the radial variation of the geometrical variables of (2 chord length, (3 twist angle, and (4 thickness along the blade span. A wind tunnel validation study of optimized rotors based on the NACA 4-digit airfoil series is presented. Based on the experimental data, improvements in terms of the aerodynamic efficiency, the cut-in wind speed, and the amount of material used during the manufacturing process were achieved. Recommendations for the aerodynamic design of SWT rotors are provided based on field experience.
Constrained Optimization and Optimal Control for Partial Differential Equations
Leugering, Günter; Griewank, Andreas
2012-01-01
This special volume focuses on optimization and control of processes governed by partial differential equations. The contributors are mostly participants of the DFG-priority program 1253: Optimization with PDE-constraints which is active since 2006. The book is organized in sections which cover almost the entire spectrum of modern research in this emerging field. Indeed, even though the field of optimal control and optimization for PDE-constrained problems has undergone a dramatic increase of interest during the last four decades, a full theory for nonlinear problems is still lacking. The cont
Fuzzy logic control and optimization system
Lou, Xinsheng [West Hartford, CT
2012-04-17
A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
Hybrid NN/SVM Computational System for Optimizing Designs
Rai, Man Mohan
2009-01-01
A computational method and system based on a hybrid of an artificial neural network (NN) and a support vector machine (SVM) (see figure) has been conceived as a means of maximizing or minimizing an objective function, optionally subject to one or more constraints. Such maximization or minimization could be performed, for example, to optimize solve a data-regression or data-classification problem or to optimize a design associated with a response function. A response function can be considered as a subset of a response surface, which is a surface in a vector space of design and performance parameters. A typical example of a design problem that the method and system can be used to solve is that of an airfoil, for which a response function could be the spatial distribution of pressure over the airfoil. In this example, the response surface would describe the pressure distribution as a function of the operating conditions and the geometric parameters of the airfoil. The use of NNs to analyze physical objects in order to optimize their responses under specified physical conditions is well known. NN analysis is suitable for multidimensional interpolation of data that lack structure and enables the representation and optimization of a succession of numerical solutions of increasing complexity or increasing fidelity to the real world. NN analysis is especially useful in helping to satisfy multiple design objectives. Feedforward NNs can be used to make estimates based on nonlinear mathematical models. One difficulty associated with use of a feedforward NN arises from the need for nonlinear optimization to determine connection weights among input, intermediate, and output variables. It can be very expensive to train an NN in cases in which it is necessary to model large amounts of information. Less widely known (in comparison with NNs) are support vector machines (SVMs), which were originally applied in statistical learning theory. In terms that are necessarily
AN APPLICATION OF OPTIMAL CONTROL THEORY.
The purpose of this article is to show that optimal control theory can be used to develop a control strategy for a practical system, namely a distillation column. The approach will be to model the complex system with a simple model, use optimal control theory to determine a control strategy for the simple model, and then apply the results to the original system. (Author)
Control of aggregation-induced emission by DNA hybridization
Li, Shaoguang; Langenegger, Simon Matthias; Häner, Robert
2013-01-01
Aggregation-induced emission (AIE) was studied by hybridization of dialkynyl-tetraphenylethylene (DATPE) modified DNA strands. Molecular aggregation and fluorescence of DATPEs are controlled by duplex formation.
Directory of Open Access Journals (Sweden)
Cong Zhang
2015-01-01
Full Text Available Although both battery and super-capacitor are important power sources for hybrid electric vehicles, there is no accurate configuration theory to match the above two kinds of power sources which have significantly different characteristics on energy and power storage for the goal of making good use of their individual features without size wasting. In this paper, a new performance is presented that is used for analysis and optimal design method of battery and super-capacitor for hybrid energy storage system of a parallel hybrid electrical vehicle. In order to achieve optimal design with less consumption, the power-energy function is applied to establish direct mathematical relationship between demand power and the performance. During matching process, firstly, three typical operating conditions are chosen as the basis of design; secondly, the energy and power capacity evaluation methods for the parameters of battery and super-capacitor in hybrid energy storage system are proposed; thirdly, the mass, volume, and cost of the system are optimized simultaneously by using power-energy function. As a result, there are significant advantages on mass, volume, and cost for the hybrid energy storage system with the matching method. Simulation results fit well with the results of analysis, which confirms that the optimized design can meet the demand of hybrid electric vehicle well.
A Quasi Time Optimal Receding Horizon Control
Bania, Piotr
2007-01-01
This paper presents a quasi time optimal receding horizon control algorithm. The proposed algorithm generates near time optimal control when the state of the system is far from the target. When the state attains a certain neighbourhood of the aim, it begins the adaptation of the cost function. The purpose of this adaptation is to move from the time optimal control to the stabilizing control. Sufficient conditions for the stability of the closed loop system and the manner of the adaptation of ...
Hybrid Design Optimization of High Voltage Pulse Transformers for Klystron Modulators
Sylvain, Candolfi; Davide, Aguglia; Jerome, Cros
2015-01-01
This paper presents a hybrid optimization methodology for the design of high voltage pulse transformers used in klystron modulators. The optimization process is using simplified 2D FEA design models of the 3D transformer structure. Each intermediate optimal solution is evaluated by 3D FEA and correction coefficients of the 2D FEA models are derived. A new optimization process using 2D FEA models is then performed. The convergence of this hybrid optimal design methodology is obtained with a limited number of time consuming 3D FEA simulations. The method is applied to the optimal design of a monolithic high voltage pulse transformer for the CLIC klystron modulator.
Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam
2015-01-01
The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.
A hybrid multi-swarm particle swarm optimization to solve constrained optimization problems
Institute of Scientific and Technical Information of China (English)
Yong WANG; Zixing CAI
2009-01-01
In the real-world applications, most optimization problems are subject to different types of constraints. These problems are known as constrained optimization problems (COPs). Solving COPs is a very important area in the optimization field. In this paper, a hybrid multi-swarm particle swarm optimization (HMPSO) is proposed to deal with COPs. This method adopts a parallel search operator in which the current swarm is partitioned into several subswarms and particle swarm optimization (PSO) is severed as the search engine for each sub-swarm. Moreover, in order to explore more promising regions of the search space, differential evolution (DE) is incorporated to improve the personal best of each particle. First, the method is tested on 13 benchmark test functions and compared with three stateof-the-art approaches. The simulation results indicate that the proposed HMPSO is highly competitive in solving the 13 benchmark test functions. Afterward, the effectiveness of some mechanisms proposed in this paper and the effect of the parameter setting were validated by various experiments. Finally, HMPSO is further applied to solve 24 benchmark test functions collected in the 2006 IEEE Congress on Evolutionary Computation (CEC2006) and the experimental results indicate that HMPSO is able to deal with 22 test functions.
Directory of Open Access Journals (Sweden)
Ranganathan Mohanasundaram
2015-01-01
Full Text Available The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches.
Optimizing Armed Forces Capabilities for Hybrid Warfare – New Challenge for Slovak Armed Forces
Directory of Open Access Journals (Sweden)
Peter PINDJÁK
2015-09-01
Full Text Available The paper deals with the optimization of military capabilities of the Slovak Armed Forces for conducting operations in a hybrid conflict, which represents one of the possible scenarios of irregular warfare. Whereas in the regular warfare adversaries intend to eliminate the centers of gravity of each other, most often command and control structures, in irregular conflicts, the center of gravity shifts towards the will and cognitive perception of the target population. Hybrid warfare comprises a thoroughly planned combination of conventional military approaches and kinetic operations with subversive, irregular activities, including information and cyber operations. These efforts are often accompanied by intensified activities of intelligence services, special operation forces, and even mercenary and other paramilitary groups. The development of irregular warfare capabilities within the Slovak Armed Forces will require a progressive transformation process that may turn the armed forces into a modern and adaptable element of power, capable of deployment in national and international crisis management operations.
A Comparative Study of Several Hybrid Particle Swarm Algorithms for Function Optimization
Directory of Open Access Journals (Sweden)
Yanhua Zhong
2012-11-01
Full Text Available Currently, the researchers have made a lot of hybrid particle swarm algorithm in order to solve the shortcomings that the Particle Swarm Algorithms is easy to converge to local extremum, these algorithms declare that there has been better than the standard particle swarm. This study selects three kinds of representative hybrid particle swarm optimizations (differential evolution particle swarm optimization, GA particle swarm optimization, quantum particle swarm optimization and the standard particle swarm optimization to test with three objective functions. We compare evolutionary algorithm performance by a fixed number of iterations of the convergence speed and accuracy and the number of iterations under the fixed convergence precision; analyzing these types of hybrid particle swarm optimization results and practical performance. Test results show hybrid particle algorithm performance has improved significantly.
A Comparative Study of Several Hybrid Particle Swarm Algorithms for Function Optimization
Directory of Open Access Journals (Sweden)
Yanhua Zhong
2013-01-01
Full Text Available Currently, the researchers have made a lot of hybrid particle swarm algorithm in order to solve the shortcomings that the Particle Swarm Algorithms is easy to converge to local extremum, these algorithms declare that there has been better than the standard particle swarm. This study selects three kinds of representative hybrid particle swarm optimizations (differential evolution particle swarm optimization, GA particle swarm optimization, quantum particle swarm optimization and the standard particle swarm optimization to test with three objective functions. We compare evolutionary algorithm performance by a fixed number of iterations of the convergence speed and accuracy and the number of iterations under the fixed convergence precision, analyzing these types of hybrid particle swarm optimization results and practical performance. Test results show hybrid particle algorithm performance has improved significantly.
Free chattering hybrid sliding mode control for a class of non-linear systems
DEFF Research Database (Denmark)
Khooban, Mohammad-Hassan; Niknam, Taher; Blaabjerg, Frede
2016-01-01
In current study, in order to find the control of general uncertain nonlinear systems, a new optimal hybrid control approach called Optimal General Type II Fuzzy Sliding Mode (OGT2FSM) is presented. In order to estimate unknown nonlinear activities in monitoring dynamic uncertainties, the benefits...... on the same topic, which are an Adaptive Interval Type-2 Fuzzy Logic Controller (AGT2FLC) and Conventional Sliding Mode Controller (CSMC), to assess the efficiency of the suggested controller. The suggested control scheme is finally used to the Electric Vehicles type as a case study. Results of simulation...
Institute of Scientific and Technical Information of China (English)
王琪; 孙玉坤
2014-01-01
ABSTRACT:To the power allocation problems of battery and ultracapacitor (UC) of hybrid energy storage (HES) in a hybrid electric vehicle (HEV), we proposed an adaptive filter power splitting (AFPS) control strategy. At the same time, the parameters of AFPS had been optimized so as to the UC was mainly responsible for the peak power of the load power and battery assumed the average power. UC cut the peak and valley current of battery, and the charging and discharging process of battery had been optimized. Re-developed the HES and AFPS under Matlab/ADVISOR simulation environment, and used the CVX toolbox to achieve the optimization of AFPS. At the same time, the experimental platform had been established with the experimental study being achieved. The simulation and experimental results indicate that AFPS realizes the power allocation of battery and UC in reason, and the optimization method enhances the utilization of UC to minimize the magnitude and fluctuation of battery current effectively, so battery has been protected.%针对混合动力汽车复合电源能量管理系统中蓄电池和超级电容器的功率合理分配问题，提出一种自适应滤波器功率分配控制策略，同时对该控制策略参数进行优化设计研究，使得超级电容器主要承担负载需求功率中的峰值功率，蓄电池则承担平均功率，从而达到超级电容器对蓄电池的“削峰填谷”，优化蓄电池充放电过程。在Matlab/ADVISOR仿真环境下，对混合动力汽车复合电源及自适应滤波器功率分流控制策略进行二次开发，采用CVX工具箱实现控制策略的优化设计，同时搭建了复合电源系统的试验平台，并进行了相应试验研究。仿真和试验结果表明，自适应滤波器功率分流控制策略实现了蓄电池和超级电容器功率的合理分配，优化方法提高了超级电容器的利用率，有效地降低了蓄电池电流的幅值和波动范围，进而保护了蓄电池。
Improved Aerodynamic Analysis for Hybrid Wing Body Conceptual Design Optimization
Gern, Frank H.
2012-01-01
This paper provides an overview of ongoing efforts to develop, evaluate, and validate different tools for improved aerodynamic modeling and systems analysis of Hybrid Wing Body (HWB) aircraft configurations. Results are being presented for the evaluation of different aerodynamic tools including panel methods, enhanced panel methods with viscous drag prediction, and computational fluid dynamics. Emphasis is placed on proper prediction of aerodynamic loads for structural sizing as well as viscous drag prediction to develop drag polars for HWB conceptual design optimization. Data from transonic wind tunnel tests at the Arnold Engineering Development Center s 16-Foot Transonic Tunnel was used as a reference data set in order to evaluate the accuracy of the aerodynamic tools. Triangularized surface data and Vehicle Sketch Pad (VSP) models of an X-48B 2% scale wind tunnel model were used to generate input and model files for the different analysis tools. In support of ongoing HWB scaling studies within the NASA Environmentally Responsible Aviation (ERA) program, an improved finite element based structural analysis and weight estimation tool for HWB center bodies is currently under development. Aerodynamic results from these analyses are used to provide additional aerodynamic validation data.
Beam Pattern Synthesis Based on Hybrid Optimization Algorithm
Institute of Scientific and Technical Information of China (English)
YU Yan-li; WANG Ying-min; LI Lei
2010-01-01
As conventional methods for beam pattern synthesis can not always obtain the desired optimum pattern for the arbitrary underwater acoustic sensor arrays, a hybrid numerical synthesis method based on adaptive principle and genetic algorithm was presented in this paper. First, based on the adaptive theory, a given array was supposed as an adaptive array and its sidelobes were reduced by assigning a number of interference signals in the sidelobe region. An initial beam pattern was obtained after several iterations and adjustments of the interference intensity, and based on its parameters, a desired pattern was created. Then, an objective function based on the difference between the designed and desired patterns can be constructed. The pattern can be optimized by using the genetic algorithm to minimize the objective function. A design example for a double-circular array demonstrates the effectiveness of this method. Compared with the approaches existing before, the proposed method can reduce the sidelobe effectively and achieve less synthesis magnitude error in the mainlobe.The method can search for optimum attainable pattern for the specific elements if the desired pattern can not be found.
A Controlled Particle Filter for Global Optimization
Zhang, Chi; Taghvaei, Amirhossein; Mehta, Prashant G.
2017-01-01
A particle filter is introduced to numerically approximate a solution of the global optimization problem. The theoretical significance of this work comes from its variational aspects: (i) the proposed particle filter is a controlled interacting particle system where the control input represents the solution of a mean-field type optimal control problem; and (ii) the associated density transport is shown to be a gradient flow (steepest descent) for the optimal value function, with respect to th...
Directory of Open Access Journals (Sweden)
Zeyu Chen
2015-04-01
Full Text Available Plug-in hybrid electric vehicles (PHEVs have been recognized as one of the most promising vehicle categories nowadays due to their low fuel consumption and reduced emissions. Energy management is critical for improving the performance of PHEVs. This paper proposes an energy management approach based on a particle swarm optimization (PSO algorithm. The optimization objective is to minimize total energy cost (summation of oil and electricity from vehicle utilization. A main drawback of optimal strategies is that they can hardly be used in real-time control. In order to solve this problem, a rule-based strategy containing three operation modes is proposed first, and then the PSO algorithm is implemented on four threshold values in the presented rule-based strategy. The proposed strategy has been verified by the US06 driving cycle under the MATLAB/Simulink software environment. Two different driving cycles are adopted to evaluate the generalization ability of the proposed strategy. Simulation results indicate that the proposed PSO-based energy management method can achieve better energy efficiency compared with traditional blended strategies. Online control performance of the proposed approach has been demonstrated through a driver-in-the-loop real-time experiment.
Directory of Open Access Journals (Sweden)
Maytham S. Ahmed
2016-09-01
Full Text Available Demand response (DR program can shift peak time load to off-peak time, thereby reducing greenhouse gas emissions and allowing energy conservation. In this study, the home energy management scheduling controller of the residential DR strategy is proposed using the hybrid lightning search algorithm (LSA-based artificial neural network (ANN to predict the optimal ON/OFF status for home appliances. Consequently, the scheduled operation of several appliances is improved in terms of cost savings. In the proposed approach, a set of the most common residential appliances are modeled, and their activation is controlled by the hybrid LSA-ANN based home energy management scheduling controller. Four appliances, namely, air conditioner, water heater, refrigerator, and washing machine (WM, are developed by Matlab/Simulink according to customer preferences and priority of appliances. The ANN controller has to be tuned properly using suitable learning rate value and number of nodes in the hidden layers to schedule the appliances optimally. Given that finding proper ANN tuning parameters is difficult, the LSA optimization is hybridized with ANN to improve the ANN performances by selecting the optimum values of neurons in each hidden layer and learning rate. Therefore, the ON/OFF estimation accuracy by ANN can be improved. Results of the hybrid LSA-ANN are compared with those of hybrid particle swarm optimization (PSO based ANN to validate the developed algorithm. Results show that the hybrid LSA-ANN outperforms the hybrid PSO based ANN. The proposed scheduling algorithm can significantly reduce the peak-hour energy consumption during the DR event by up to 9.7138% considering four appliances per 7-h period.
Optimizing Dynamical Network Structure for Pinning Control
Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo
2016-04-01
Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights.
Adaptive optimization and control using neural networks
Energy Technology Data Exchange (ETDEWEB)
Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.
1993-10-22
Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.
Optimal Control of Switched Systems based on Bezier Control Points
FatemeGhomanjani; Mohammad HadiFarahi
2012-01-01
This paper presents a new approach for solving optimal control problems for switched systems. We focus on problems in which a pre-specified sequence of active subsystems is given. For such problems, we need to seek both the optimal switching instants and the optimal continuous inputs. A Bezier control points method is applied for solving an optimal control problem which is supervised by a switched dynamic system. Two steps of approximation exist here. First, the time interval is divided into ...
Optimal Control and Optimization of Stochastic Supply Chain Systems
Song, Dong-Ping
2013-01-01
Optimal Control and Optimization of Stochastic Supply Chain Systems examines its subject in the context of the presence of a variety of uncertainties. Numerous examples with intuitive illustrations and tables are provided, to demonstrate the structural characteristics of the optimal control policies in various stochastic supply chains and to show how to make use of these characteristics to construct easy-to-operate sub-optimal policies. In Part I, a general introduction to stochastic supply chain systems is provided. Analytical models for various stochastic supply chain systems are formulated and analysed in Part II. In Part III the structural knowledge of the optimal control policies obtained in Part II is utilized to construct easy-to-operate sub-optimal control policies for various stochastic supply chain systems accordingly. Finally, Part IV discusses the optimisation of threshold-type control policies and their robustness. A key feature of the book is its tying together of ...
DSP Control of Line Hybrid Active Filter
DEFF Research Database (Denmark)
Dan, Stan George; Benjamin, Doniga Daniel; Magureanu, R.;
2005-01-01
Active Power Filters have been intensively explored in the past decade. Hybrid active filters inherit the efficiency of passive filters and the improved performance of active filters, and thus constitute a viable improved approach for harmonic compensation. In this paper a parallel hybrid filter ...
A hybrid electromechanical solid state switch for ac power control
1972-01-01
Bidirectional thyristor coupled to a series of actuator driven electromechanical contacts generates hybrid electromechanical solid state switch for ac power control. Device is useful in power control applications where zero crossover switching is required.
CURRENT VECTOR CONTROL OF PERMANENT-MAGNET SYNCHRONOUS MOTOR OF HYBRID VEHICLE ENGINE
Directory of Open Access Journals (Sweden)
S. Serikov
2009-01-01
Full Text Available Characteristics of traction permanent-magnet synchronous motor under current vector optimum control in the possible traction-speed mode area which are relevant for hybrid vehicle engine have been investigated. As a criterion of optimality a maximum of electromagnetic moment per unit of current have been taken.
Optimal design of structures for earthquake loads by a hybrid RBF-BPSO method
Institute of Scientific and Technical Information of China (English)
Eysa Salajegheh; Saeed Gholizadeh; Mohsen Khatibina
2008-01-01
The optimal seismic design of structures requires that time history analyses (THA) be carried out repeatedly. This makes the optimal design process inefficient, in particular, if an evolutionary algorithm is used. To reduce the overall time required for structural optimization, two artificial intelligence strategies are employed. In the first strategy, radial basis function (RBF) neural networks are used to predict the time history responses of structures in the optimization flow. In the second strategy, a binary particle swarm optimization (BPSO) is used to find the optimum design. Combining the RBF and BPSO, a hybrid RBF-BPSO optimization method is proposed in this paper, which achieves fast optimization with high computational performance. Two examples are presented and compared to determine the optimal weight of structures under earthquake loadings using both exact and approximate analyses. The numerical results demonstrate the computational advantages and effectiveness of the proposed hybrid RBF-BPSO optimization method for the seismic design of structures.
Optimization of Temperature Controller for Electric Furnace
Institute of Scientific and Technical Information of China (English)
2000-01-01
Genetic algorithms are based on the principle of natural selection and the optimization of natural generation. We can select the number of the bit strings and mutation rate reasonably, the global optimal solution can be obtained. GAs adopt the binary code as optimizing parameter and this binary code can be used in computer controller easily. This paper studies the application of the GAs to the electric furnace temperature control. When the electric furnace mathematics model varies with the working condition, the parameter of controller can be optimized on line. So the system performance can be improved effectively.
OPTIMAL CONTROL PROBLEM FOR PARABOLIC VARIATIONAL INEQUALITIES
Institute of Scientific and Technical Information of China (English)
汪更生
2001-01-01
This paper deals with the optimal control problems of systems governed by a parabolic variational inequality coupled with a semilinear parabolic differential equations.The maximum principle and some kind of approximate controllability are studied.
PSO based Optimal Power Flow with Hybrid Distributed Generators and UPFC
Directory of Open Access Journals (Sweden)
S.G. Bharathi dasan
2012-09-01
Full Text Available Distributed Generation (DG is a small source of electric power conversion from nonconventionalenergy sources and Hybrid DGs is often the most cost-effective and reliable way toproduce power. Optimal Power flow (OPF study is conducted on a power system to achieve one of the following objectives: cost/loss minimization or Available transfer capability (ATCcalculation in a deregulated environment. The optimality of control variables would definitely change with respect to the location, quantity and combination of power injection by DGs. On the other hand, FACTS controllers are effective in utilizing the existing transmission network whichis very important especially in a deregulated system. Unified Power flow controller (UPFC, a second generation FACTS controller, is well known for minimizing the cost of generation/losses with a good voltage profile as well as for ATC improvement. This paper conducts a detailed OPF study on a 9 bus system [7] for the above mentioned three objectives, with DGs and UPFC. To solve the OPF problem, Particle Swarm Optimization (PSO, a non conventional technique is used.
Fast Solvers of Fredholm Optimal Control Problems
Institute of Scientific and Technical Information of China (English)
Mario; Borzì
2010-01-01
The formulation of optimal control problems governed by Fredholm integral equations of second kind and an efficient computational framework for solving these control problems is presented. Existence and uniqueness of optimal solutions is proved.A collective Gauss-Seidel scheme and a multigrid scheme are discussed. Optimal computational performance of these iterative schemes is proved by local Fourier analysis and demonstrated by results of numerical experiments.
Institute of Scientific and Technical Information of China (English)
CHEN Jie; XIN Bin; PENG ZhiHong; PAN Feng
2009-01-01
This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics-differential evolution (DE) and particle swarm optimization (PSO). In the hybrid denoted by DEPSO, each individual in one generation chooses its evolution method, DE or PSO, in a statistical learning way. The choice depends on the relative success ratio of the two methods in a previous learning period. The proposed DEPSO is compared with its PSO and DE parents, two advanced DE variants one of which is suggested by the originators of DE, two advanced PSO variants one of which is acknowledged as a recent standard by PSO community, and also a previous DEPSO. Benchmark tests demonstrate that the DEPSO is more competent for the global optimization of multimodal functions due to its high optimization quality.
Almost optimal adaptive LQ control: SISO case
Polderman, Jan W.; Daams, Jasper
2002-01-01
In this paper an almost optimal indirect adaptive controller for input/output dynamical systems is proposed. The control part of the adaptive control scheme is based on a modified LQ control law: by adding a time-varying gain to the certainty equivalent control law the conflict between
Efficient evolutionary algorithms for optimal control
López Cruz, I.L.
2002-01-01
If optimal control problems are solved by means of gradient based local search methods, convergence to local solutions is likely. Recently, there has been an increasing interest in the use of global optimisation algorithms to solve optimal control problems, wh
Connections Between Singular Control and Optimal Switching
Guo, Xin; Tomecek, Pascal
2007-01-01
This paper builds a new theoretical connection between singular control of finite variation and optimal switching problems. This correspondence provides a novel method for solving high-dimensional singular control problems, and enables us to extend the theory of reversible investment: sufficient conditions are derived for the existence of optimal controls and for the regularity of value functions. Consequently, our regularity result links singular controls and Dynkin games through sequential ...
Directory of Open Access Journals (Sweden)
Sai Ram Inkollu
2016-09-01
Full Text Available This paper presents a novel technique for optimizing the FACTS devices, so as to maintain the voltage stability in the power transmission systems. Here, the particle swarm optimization algorithm (PSO and the adaptive gravitational search algorithm (GSA technique are proposed for improving the voltage stability of the power transmission systems. In the proposed approach, the PSO algorithm is used for optimizing the gravitational constant and to improve the searching performance of the GSA. Using the proposed technique, the optimal settings of the FACTS devices are determined. The proposed algorithm is an effective method for finding out the optimal location and the sizing of the FACTS controllers. The optimal locations and the power ratings of the FACTS devices are determined based on the voltage collapse rating as well as the power loss of the system. Here, two FACTS devices are used to evaluate the performance of the proposed algorithm, namely, the unified power flow controller (UPFC and the interline power flow controller (IPFC. The Newton–Raphson load flow study is used for analyzing the power flow in the transmission system. From the power flow analysis, bus voltages, active power, reactive power, and power loss of the transmission systems are determined. Then, the voltage stability is enhanced while satisfying a given set of operating and physical constraints. The proposed technique is implemented in the MATLAB platform and consequently, its performance is evaluated and compared with the existing GA based GSA hybrid technique. The performance of the proposed technique is tested with the benchmark system of IEEE 30 bus using two FACTS devices such as, the UPFC and the IPFC.
A Single-Degree-of-Freedom Energy Optimization Strategy for Power-Split Hybrid Electric Vehicles
Directory of Open Access Journals (Sweden)
Chaoying Xia
2017-07-01
Full Text Available This paper presents a single-degree-of-freedom energy optimization strategy to solve the energy management problem existing in power-split hybrid electric vehicles (HEVs. The proposed strategy is based on a quadratic performance index, which is innovatively designed to simultaneously restrict the fluctuation of battery state of charge (SOC and reduce fuel consumption. An extended quadratic optimal control problem is formulated by approximating the fuel consumption rate as a quadratic polynomial of engine power. The approximated optimal control law is obtained by utilizing the solution properties of the Riccati equation and adjoint equation. It is easy to implement in real-time and the engineering significance is explained in details. In order to validate the effectiveness of the proposed strategy, the forward-facing vehicle simulation model is established based on the ADVISOR software (Version 2002, National Renewable Energy Laboratory, Golden, CO, USA. The simulation results show that there is only a little fuel consumption difference between the proposed strategy and the Pontryagin’s minimum principle (PMP-based global optimal strategy, and the proposed strategy also exhibits good adaptability under different initial battery SOC, cargo mass and road slope conditions.
Asfoor, Mostafa
The gradual decline of oil reserves and the increasing demand for energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall energy conversion efficiencies is the hybridization of conventional vehicle drive systems. This dissertation builds on prior hybrid powertrain development at the University of Idaho. Advanced vehicle models of a passenger car with a conventional powertrain and three different hybrid powertrain layouts were created using GT-Suite. These different powertrain models were validated against a variety of standard driving cycles. The overall fuel economy, energy consumption, and losses were monitored, and a comprehensive energy analysis was performed to compare energy sources and sinks. The GT-Suite model was then used to predict the formula hybrid SAE vehicle performance. Inputs to this model were a numerically predicted engine performance map, an electric motor torque curve, vehicle geometry, and road load parameters derived from a roll-down test. In this case study, the vehicle had a supervisory controller that followed a rule-based energy management strategy to insure a proper power split during hybrid mode operation. The supervisory controller parameters were optimized using discrete grid optimization method that minimized the total amount of fuel consumed during a specific urban driving cycle with an average speed of approximately 30 [mph]. More than a 15% increase in fuel economy was achieved by adding supervisory control and managing power split. The vehicle configuration without the supervisory controller displayed a fuel economy of 25 [mpg]. With the supervisory controller this rose to 29 [mpg]. Wider applications of this research include hybrid vehicle controller designs that can extend the range and survivability of military combat platforms. Furthermore, the
Controllable hybrid shape of correlation and squeezing
Abdisa, Garuma; Ahmed, Irfan; Wang, Xiuxiu; Liu, Zongchen; Wang, Hongxing; Zhang, Yanpeng
2016-08-01
Two- and three-mode correlation and squeezing of spontaneous parametric four-wave mixing (SPFWM) and fourth-order fluorescence (FL) composite signals are investigated theoretically and experimentally in both homonuclear (two-level) and heteronuclearlike (V-type level) molecular systems of P r3 + :YSO. By selecting different time positions, changing the power, and changing the frequency detuning of the laser field, the competition between the composite signals is demonstrated. It is found that as the laser parameters change, the signal evolves from a nonlinear χ(4 ) process resulting in a FL signal to a SPFWM signal (χ(3 ) process). In addition, the competition effect between the signals determines the evolution of the shape of the correlation from a pure sharp to a two-stage (mixed) shape and finally to a pure broad peak amplitude. Furthermore, the signal evolution determines the magnitude of squeezing, which can control the noise level. Such progress may find potential applications in optical hybrid communication and information processing.
Review of hybrid laminar flow control systems
Krishnan, K. S. G.; Bertram, O.; Seibel, O.
2017-08-01
The aeronautic community always strived for fuel efficient aircraft and presently, the need for ecofriendly aircraft is even more, especially with the tremendous growth of air traffic and growing environmental concerns. Some of the important drivers for such interests include high fuel prices, less emissions requirements, need for more environment friendly aircraft to lessen the global warming effects. Hybrid laminar flow control (HLFC) technology is promising and offers possibility to achieve these goals. This technology was researched for decades for its application in transport aircraft, and it has achieved a new level of maturity towards integration and safety and maintenance aspects. This paper aims to give an overview of HLFC systems research and associated flight tests in the past years both in the US and in Europe. The review makes it possible to distinguish between the successful approaches and the less successful or outdated approaches in HLFC research. Furthermore, the technology status shall try to produce first estimations regarding the mass, power consumption and performance of HLFC systems as well as estimations regarding maintenance requirements and possible subsystem definitions.
Energy and Propulsion Optimization of Solid-Propellant Grain of a Hybrid Power Device
Bondarchuk Sergey S.; Bondarchuk Iliya S.; Borisov Boris V.; Zhukov Alexandr S.
2016-01-01
A method of distribution of an additional solid-phase component (oxidizer) providing uniformity of grain burning for the purpose of evaluation and optimization of energy and propulsion parameters of hybrid solid-propellant motor is proposed in the paper.
Energy and Propulsion Optimization of Solid-Propellant Grain of a Hybrid Power Device
Bondarchuk, Sergey S.; Bondarchuk, Iliya S.; Borisov, Boris V.; Zhukov, Alexandr S.
2016-02-01
A method of distribution of an additional solid-phase component (oxidizer) providing uniformity of grain burning for the purpose of evaluation and optimization of energy and propulsion parameters of hybrid solid-propellant motor is proposed in the paper.
Optimization of Hybrid PV/Wind Energy System Using Genetic Algorithm (GA
Directory of Open Access Journals (Sweden)
Satish Kumar Ramoji
2014-01-01
Full Text Available In this paper, a new approach of optimum design for a Hybrid PV/Wind energy system is presented in order to assist the designers to take into consideration both the economic and ecological aspects. When the stand alone energy system having photovoltaic panels only or wind turbine only are compared with the hybrid PV/wind energy systems, the hybrid systems are more economical and reliable according to climate changes. This paper presents an optimization technique to design the hybrid PV/wind system. The hybrid system consists of photovoltaic panels, wind turbines and storage batteries. Genetic Algorithm (GA optimization technique is utilized to minimize the formulated objective function, i.e. total cost which includes initial costs, yearly replacement cost, yearly operating costs and maintenance costs and salvage value of the proposed hybrid system. A computer program is designed, using MATLAB code to formulate the optimization problem by computing the coefficients of the objective function. The method mentioned in this article is proved to be effective using an example of hybrid energy system. Finally, the optimal solution is achieved by Genetic Algorithm (GA optimization method.
Neural Networks for Optimal Control
DEFF Research Database (Denmark)
Sørensen, O.
1995-01-01
Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....
Neural Networks for Optimal Control
DEFF Research Database (Denmark)
Sørensen, O.
1995-01-01
Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....
Optimization of Performance Characteristics of Hybrid Wind Photovoltaic System with Battery Storage
Directory of Open Access Journals (Sweden)
C. Kathirvel
2014-03-01
Full Text Available This study concentrates on the Design and Implementation of a multi source hybrid Wind-Photovoltaic stand alone system with proposed energy management strategy. The method of investigation concerned with the definition of the system topology, interconnection of the various sources with maximum energy transfer, optimum control and energy management in order to maintain the DC bus voltage into a fixed value. An Energy management strategy was proposed using the Fuzzy logic controller such that enhancement in the performance of the system and optimization can be done. The Fuzzy logic controller takes the input from Solar (irradiation, Wind (speed, Power demand and the battery voltage which controls the respective subsystem and formulates into different operational modes of energy management. The role of Fuzzy threshold controller is to adjust continuously the threshold value for optimal performance based on expected wind, solar conditions, battery voltage and power demand. It is shown that when the fuzzy logic controller is used, the proposed DC bus voltage regulation strategy with different modes of operation have fast response and efficient operation which leads to a reduced operating cost.
Directory of Open Access Journals (Sweden)
Junwei Sun
2014-01-01
Full Text Available Some important dynamical properties of the memristor chaotic oscillator system have been studied in the paper. A novel hybrid dislocated control method and a general hybrid projective dislocated synchronization scheme have been realized for memristor chaotic oscillator system. The paper firstly presents hybrid dislocated control method for stabilizing chaos to the unstable equilibrium point. Based on the Lyapunov stability theorem, general hybrid projective dislocated synchronization has been studied for the drive memristor chaotic oscillator system and the same response memristor chaotic oscillator system. For the different dimensions, the memristor chaotic oscillator system and the other chaotic system have realized general hybrid projective dislocated synchronization. Numerical simulations are given to show the effectiveness of these methods.
Optimal switching using coherent control
DEFF Research Database (Denmark)
Kristensen, Philip Trøst; Heuck, Mikkel; Mørk, Jesper
2013-01-01
that the switching time, in general, is not limited by the cavity lifetime. Therefore, the total energy required for switching is a more relevant figure of merit than the switching speed, and for a particular two-pulse switching scheme we use calculus of variations to optimize the switching in terms of input energy....
Optimal control, optimization and asymptotic analysis of Purcell's microswimmer model
Wiezel, Oren; Or, Yizhar
2016-11-01
Purcell's swimmer (1977) is a classic model of a three-link microswimmer that moves by performing periodic shape changes. Becker et al. (2003) showed that the swimmer's direction of net motion is reversed upon increasing the stroke amplitude of joint angles. Tam and Hosoi (2007) used numerical optimization in order to find optimal gaits for maximizing either net displacement or Lighthill's energetic efficiency. In our work, we analytically derive leading-order expressions as well as next-order corrections for both net displacement and energetic efficiency of Purcell's microswimmer. Using these expressions enables us to explicitly show the reversal in direction of motion, as well as obtaining an estimate for the optimal stroke amplitude. We also find the optimal swimmer's geometry for maximizing either displacement or energetic efficiency. Additionally, the gait optimization problem is revisited and analytically formulated as an optimal control system with only two state variables, which can be solved using Pontryagin's maximum principle. It can be shown that the optimal solution must follow a "singular arc". Numerical solution of the boundary value problem is obtained, which exactly reproduces Tam and Hosoi's optimal gait.
Hybrid discrete particle swarm optimization algorithm for capacitated vehicle routing problem
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Capacitated vehicle routing problem (CVRP) is an NP-hard problem. For large-scale problems, it is quite difficult to achieve an optimal solution with traditional optimization methods due to the high computational complexity. A new hybrid approximation algorithm is developed in this work to solve the problem. In the hybrid algorithm, discrete particle swarm optimization (DPSO) combines global search and local search to search for the optimal results and simulated annealing (SA) uses certain probability to avoid being trapped in a local optimum. The computational study showed that the proposed algorithm is a feasible and effective approach for capacitated vehicle routing problem, especially for large scale problems.
USING OPTIMAL FEEDBACK CONTROL FOR CHAOS TARGETING
Institute of Scientific and Technical Information of China (English)
PENG ZHAO-WANG; ZHONG TING-XIU
2000-01-01
Since the conventional open-loop optimal targeting of chaos is very sensitive to noise, a close-loop optimal targeting method is proposed to improve the targeting performance under noise. The present optimal targeting model takes into consideration both precision and speed of the targeting procedure. The parameters, rather than the output, of the targeting controller, are directly optimized to obtain optimal chaos targeting. Analysis regarding the mechanism is given from physics aspect and numerical experiment on the Hénon map is carried out to compare the targeting performance under noise between the close-loop and the open-loop methods.
Control system for a hybrid powertrain system
Energy Technology Data Exchange (ETDEWEB)
Naqvi, Ali K.; Demirovic, Besim; Gupta, Pinaki; Kaminsky, Lawrence A.
2014-09-09
A vehicle includes a powertrain with an engine, first and second torque machines, and a hybrid transmission. A method for operating the vehicle includes operating the engine in an unfueled state, releasing an off-going clutch which when engaged effects operation of the hybrid transmission in a first continuously variable mode, and applying a friction braking torque to a wheel of the vehicle to compensate for an increase in an output torque of the hybrid transmission resulting from releasing the off-going clutch. Subsequent to releasing the off-going clutch, an oncoming clutch which when engaged effects operation of the hybrid transmission in a second continuously variable mode is synchronized. Subsequent to synchronization of the oncoming clutch, the oncoming clutch is engaged.
Robust Power Management Control for Stand-Alone Hybrid Power Generation System
Kamal, Elkhatib; Adouane, Lounis; Aitouche, Abdel; Mohammed, Walaa
2017-01-01
This paper presents a new robust fuzzy control of energy management strategy for the stand-alone hybrid power systems. It consists of two levels named centralized fuzzy supervisory control which generates the power references for each decentralized robust fuzzy control. Hybrid power systems comprises: a photovoltaic panel and wind turbine as renewable sources, a micro turbine generator and a battery storage system. The proposed control strategy is able to satisfy the load requirements based on a fuzzy supervisor controller and manage power flows between the different energy sources and the storage unit by respecting the state of charge and the variation of wind speed and irradiance. Centralized controller is designed based on If-Then fuzzy rules to manage and optimize the hybrid power system production by generating the reference power for photovoltaic panel and wind turbine. Decentralized controller is based on the Takagi-Sugeno fuzzy model and permits us to stabilize each photovoltaic panel and wind turbine in presence of disturbances and parametric uncertainties and to optimize the tracking reference which is given by the centralized controller level. The sufficient conditions stability are formulated in the format of linear matrix inequalities using the Lyapunov stability theory. The effectiveness of the proposed Strategy is finally demonstrated through a SAHPS (stand-alone hybrid power systems) to illustrate the effectiveness of the overall proposed method.
Dopamine-induced silica-polydopamine hybrids with controllable morphology.
Ho, Chia-Che; Ding, Shinn-Jyh
2014-04-01
Novel silica-polydopamine hybrids, with controllable morphology, are facilely fabricated in an emulsion system consisting of tetraethyl orthosilicate, dopamine, water, and NaOH under weakly basic conditions (pH 8.5-10). An increase in initial pH favors the formation of nano-structured spherical silica-PDA hybrids from a flocculated structure.
Investigating Transgenic Corn Hybrids as a Method for Mycotoxin Control
Transgenic Bt corn hybrids have been available for more than 10 years and are known to control specific insects. More recently, so-called “stacked-gene” hybrids, have been released with multiple insect resistance genes and genes for herbicide resistance, resulting in up to 6 traits per plant. Beca...
Supermarket Refrigeration System - Benchmark for Hybrid System Control
DEFF Research Database (Denmark)
Sloth, Lars Finn; Izadi-Zamanabadi, Roozbeh; Wisniewski, Rafal
2007-01-01
This paper presents a supermarket refrigeration system as a benchmark for development of new ideas and a comparison of methods for hybrid systems' modeling and control. The benchmark features switch dynamics and discrete valued input making it a hybrid system, furthermore the outputs are subjected...
Hybrid viscous damper with filtered integral force feedback control
DEFF Research Database (Denmark)
Høgsberg, Jan; Brodersen, Mark L.
2016-01-01
In hybrid damper systems active control devices are usually introduced to enhance the performance of otherwise passive dampers. In the present paper a hybrid damper concept is comprised of a passive viscous damper placed in series with an active actuator and a force sensor. The actuator motion...
Optimal control of Formula One car energy recovery systems
Limebeer, D. J. N.; Perantoni, G.; Rao, A. V.
2014-10-01
The utility of orthogonal collocation methods in the solution of optimal control problems relating to Formula One racing is demonstrated. These methods can be used to optimise driver controls such as the steering, braking and throttle usage, and to optimise vehicle parameters such as the aerodynamic down force and mass distributions. Of particular interest is the optimal usage of energy recovery systems (ERSs). Contemporary kinetic energy recovery systems are studied and compared with future hybrid kinetic and thermal/heat ERSs known as ERS-K and ERS-H, respectively. It is demonstrated that these systems, when properly controlled, can produce contemporary lap time using approximately two-thirds of the fuel required by earlier generation (2013 and prior) vehicles.
Hybrid Testing of Composite Structures with Single-Axis Control
DEFF Research Database (Denmark)
Waldbjørn, Jacob Paamand; Høgh, Jacob Herold; Stang, Henrik
2013-01-01
a hybrid testing platform is introduced for single-component hybrid testing. In this case, the boundary between the numerical model and experimental setup is defined by multiple Degrees-Of-Freedoms (DOFs) which highly complicate the transferring of response between the two substructures. Digital Image......Hybrid testing is a substructuring technique where a structure is emulated by modelling a part of it in a numerical model while testing the remainder experimentally. Previous research in hybrid testing has been performed on multi-component structures e.g. damping fixtures, however in this paper...... Correlation (DIC) is therefore implemented for displacement control of the experimental setup. The hybrid testing setup was verified on a multicomponent structure consisting of a beam loaded in three point bending and a numerical structure of a frame. Furthermore, the stability of the hybrid testing loop...
Hybrid Force Motion Synchronization Control of Robot Manipulators
Fikkan, Kristoffer
2010-01-01
The main objective of this thesis was to combine the theory on synchronization of robot manipulators with the concept of hybrid force/motion control; resulting in a controller capable of following both the trajectory of another robot and a desired force trajectory at the same time. This report includes a short introduction to synchronization theory for robot manipulators, and a more thorough summary of existing hybrid control schemes. An intuitive method for describing constraints caused...
A Hybrid Intelligent Algorithm for Optimal Birandom Portfolio Selection Problems
Directory of Open Access Journals (Sweden)
Qi Li
2014-01-01
Full Text Available Birandom portfolio selection problems have been well developed and widely applied in recent years. To solve these problems better, this paper designs a new hybrid intelligent algorithm which combines the improved LGMS-FOA algorithm with birandom simulation. Since all the existing algorithms solving these problems are based on genetic algorithm and birandom simulation, some comparisons between the new hybrid intelligent algorithm and the existing algorithms are given in terms of numerical experiments, which demonstrate that the new hybrid intelligent algorithm is more effective and precise when the numbers of the objective function computations are the same.
Optimal Control of Switched Systems based on Bezier Control Points
Directory of Open Access Journals (Sweden)
FatemeGhomanjani
2012-06-01
Full Text Available This paper presents a new approach for solving optimal control problems for switched systems. We focus on problems in which a pre-specified sequence of active subsystems is given. For such problems, we need to seek both the optimal switching instants and the optimal continuous inputs. A Bezier control points method is applied for solving an optimal control problem which is supervised by a switched dynamic system. Two steps of approximation exist here. First, the time interval is divided into k sub-intervals. Second, the trajectory and control functions are approximatedby Bezier curves in each subinterval. Bezier curves have been considered as piecewise polynomials of degree n, then they will be determined by n+1 control points on any subinterval. The optimal control problem is there by converted into a nonlinear programming problem (NLP, which can be solved by known algorithms. However in this paper the MATLAB optimization routine FMINCON is used for solving resulting NLP.
System Optimization by Periodic Control.
1979-09-30
extended re- sults are now contained in a single report [3] which will appear as a regular paper in the December, 1979 issue of the IEEE Transactions on Automatic Control . The...Test Revisited, " to appear in the IEEE Transactions on Automatic Control . 4. D. J. Lyons, "Improved Aircraft Cruise by Periodic Control," Ph. D
Directory of Open Access Journals (Sweden)
T. Botmart
2013-01-01
Full Text Available The problem of guaranteed cost control for exponential synchronization of cellular neural networks with interval nondifferentiable and distributed time-varying delays via hybrid feedback control is considered. The interval time-varying delay function is not necessary to be differentiable. Based on the construction of improved Lyapunov-Krasovskii functionals is combined with Leibniz-Newton's formula and the technique of dealing with some integral terms. New delay-dependent sufficient conditions for the exponential synchronization of the error systems with memoryless hybrid feedback control are first established in terms of LMIs without introducing any free-weighting matrices. The optimal guaranteed cost control with linear error hybrid feedback is turned into the solvable problem of a set of LMIs. A numerical example is also given to illustrate the effectiveness of the proposed method.
SFC Optimization for Aero Engine Based on Hybrid GA-SQP Method
Li, Jie; Fan, Ding; Sreeram, Victor
2013-12-01
This study focuses on on-line specific fuel consumption (SFC) optimization of aero engines. For solving this optimization problem, a nonlinear pneumatic and thermodynamics model of the aero engine is built and a hybrid optimization technique which is formed by combining the genetic algorithm (GA) and the sequential quadratic programming (SQP) is presented. The ability of standard GA and standard SQP in solving this type of problem is investigated. It has been found that, although the SQP is fast, very little SFC reductions can be obtained. The GA is able to solve the problem well but a lot of computational time is needed. The presented hybrid GA-SQP gives a good SFC optimization effect and saves 76.6% computational time when compared to the standard GA. It has been shown that the hybrid GA-SQP is a more effective and higher real-time method for SFC on-line optimization of the aero engine.
High Precision Motion Control of Hybrid Five-Bar Mechanism with an Intelligent Control
Institute of Scientific and Technical Information of China (English)
ZHANG Ke; WANG Sheng-ze
2009-01-01
Hybrid mechanism is a new type of planar controllable mechanism. Position control accuracy of system determines the output acctracy of the mechanism In order to achieve the desired high accuracy, nonlinear factors as friction must be accurately compensated in the real-time servo control algarithm. In this paper, the model of a hybrid flve-bar mechanism is introduced In terms of the characteristics of the hybrid mechanism, a hybrid intelligent control algorithm based on proportional-integral-derivative(PID) control and cerebellar model articulation control techniques was presented and used to perform control of hybrid five-bar mechanism for the first time. The simulation results show that the hybrid control method can improve the control effect remarkably, compared with the traditional PID control strategy.
Optimal Control Development System for Electrical Drives
Directory of Open Access Journals (Sweden)
Marian GAICEANU
2008-08-01
Full Text Available In this paper the optimal electrical drive development system is presented. It consists of both electrical drive types: DC and AC. In order to implement the optimal control for AC drive system an Altivar 71 inverter, a Frato magnetic particle brake (as load, three-phase induction machine, and dSpace 1104 controller have been used. The on-line solution of the matrix Riccati differential equation (MRDE is computed by dSpace 1104 controller, based on the corresponding feedback signals, generating the optimal speed reference for the AC drive system. The optimal speed reference is tracked by Altivar 71 inverter, conducting to energy reduction in AC drive. The classical control (consisting of rotor field oriented control with PI controllers and the optimal one have been implemented by designing an adequate ControlDesk interface. The three-phase induction machine (IM is controlled at constant flux. Therefore, the linear dynamic mathematical model of the IM has been obtained. The optimal control law provides transient regimes with minimal energy consumption. The obtained solution by integration of the MRDE is orientated towards the numerical implementation-by using a zero order hold. The development system is very useful for researchers, doctoral students or experts training in electrical drive. The experimental results are shown.
Evolutionary design of discrete controllers for hybrid mechatronic systems
DEFF Research Database (Denmark)
Dupuis, Jean-Francois; Fan, Zhun; Goodman, Erik
2015-01-01
This paper investigates the issue of evolutionary design of controllers for hybrid mechatronic systems. Finite State Automaton (FSA) is selected as the representation for a discrete controller due to its interpretability, fast execution speed and natural extension to a statechart, which is very...... popular in industrial applications. A case study of a two-tank system is used to demonstrate that the proposed evolutionary approach can lead to a successful design of an FSA controller for the hybrid mechatronic system, represented by a hybrid bond graph. Generalisation of the evolved FSA controller...... of the evolutionary design of controllers for hybrid mechatronic systems. Finally, some important future research directions are pointed out, leading to the major work of the succeeding part of the research....
Dynamic optimization and adaptive controller design
Inamdar, S. R.
2010-10-01
In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.
Backstepping fuzzy-neural-network control design for hybrid maglev transportation system.
Wai, Rong-Jong; Yao, Jing-Xiang; Lee, Jeng-Dao
2015-02-01
This paper focuses on the design of a backstepping fuzzy-neural-network control (BFNNC) for the online levitated balancing and propulsive positioning of a hybrid magnetic levitation (maglev) transportation system. The dynamic model of the hybrid maglev transportation system including levitated hybrid electromagnets to reduce the suspension power loss and the friction force during linear movement and a propulsive linear induction motor based on the concepts of mechanical geometry and motion dynamics is first constructed. The ultimate goal is to design an online fuzzy neural network (FNN) control methodology to cope with the problem of the complicated control transformation and the chattering control effort in backstepping control (BSC) design, and to directly ensure the stability of the controlled system without the requirement of strict constraints, detailed system information, and auxiliary compensated controllers despite the existence of uncertainties. In the proposed BFNNC scheme, an FNN control is utilized to be the major control role by imitating the BSC strategy, and adaptation laws for network parameters are derived in the sense of projection algorithm and Lyapunov stability theorem to ensure the network convergence as well as stable control performance. The effectiveness of the proposed control strategy for the hybrid maglev transportation system is verified by experimental results, and the superiority of the BFNNC scheme is indicated in comparison with the BSC strategy and the backstepping particle-swarm-optimization control system in previous research.
Stability Optimization of a Disc Brake System with Hybrid Uncertainties for Squeal Reduction
Directory of Open Access Journals (Sweden)
Hui Lü
2016-01-01
Full Text Available A hybrid uncertain model is introduced to deal with the uncertainties existing in a disc brake system in this paper. By the hybrid uncertain model, the uncertain parameters of the brake with enough sampling data are treated as probabilistic variables, while the uncertain parameters with limited data are treated as interval probabilistic variables whose distribution parameters are expressed as interval variables. Based on the hybrid uncertain model, the reliability-based design optimization (RBDO of a disc brake with hybrid uncertainties is proposed to explore the optimal design for squeal reduction. In the optimization, the surrogate model of the real part of domain unstable eigenvalue of the brake system is established, and the upper bound of its expectation is adopted as the optimization objective. The lower bounds of the functions related to system stability, the mass, and the stiffness of design component are adopted as the optimization constraints. The combinational algorithm of Genetic Algorithm and Monte-Carlo method is employed to perform the optimization. The results of a numerical example demonstrate the effectiveness of the proposed optimization on improving system stability and reducing squeal propensity of a disc brake under hybrid uncertainties.
Optimal control of renewable economic resources
Energy Technology Data Exchange (ETDEWEB)
Adelani, L.A.
1987-01-01
Two main problems are studied: economic optimization, and determination of the optimal age of harvest for an initially immature population which follows a Bertalanffy-type growth law. Conditions are derived on the economic parameters that make maximization of economic rent biologically superior to maximization of sustainable yield. A general equation is derived for the optimal equilibrium biomass size when maximization of present value is the control objective. Also, it is shown that under perfectly elastic demand for the resource, a critical price level exists beyond which economic optimization has to be sacrificed in order to enhance conservation of the resource. An equation is derived whose solution represents the optimal age of harvest for an initially immature population stock. In certain circumstances, analytic forms are obtained for the optimal age of harvest. Some properties of the optimal age of harvest are also investigated.
Borhan, Hoseinali
Modern hybrid electric vehicles and many stationary renewable power generation systems combine multiple power generating and energy storage devices to achieve an overall system-level efficiency and flexibility which is higher than their individual components. The power or energy management control, "brain" of these "hybrid" systems, determines adaptively and based on the power demand the power split between multiple subsystems and plays a critical role in overall system-level efficiency. This dissertation proposes that a receding horizon optimal control (aka Model Predictive Control) approach can be a natural and systematic framework for formulating this type of power management controls. More importantly the dissertation develops new results based on the classical theory of optimal control that allow solving the resulting optimal control problem in real-time, in spite of the complexities that arise due to several system nonlinearities and constraints. The dissertation focus is on two classes of hybrid systems: hybrid electric vehicles in the first part and wind farms with battery storage in the second part. The first part of the dissertation proposes and fully develops a real-time optimization-based power management strategy for hybrid electric vehicles. Current industry practice uses rule-based control techniques with "else-then-if" logic and look-up maps and tables in the power management of production hybrid vehicles. These algorithms are not guaranteed to result in the best possible fuel economy and there exists a gap between their performance and a minimum possible fuel economy benchmark. Furthermore, considerable time and effort are spent calibrating the control system in the vehicle development phase, and there is little flexibility in real-time handling of constraints and re-optimization of the system operation in the event of changing operating conditions and varying parameters. In addition, a proliferation of different powertrain configurations may
Update on HCDstruct - A Tool for Hybrid Wing Body Conceptual Design and Structural Optimization
Gern, Frank H.
2015-01-01
HCDstruct is a Matlab® based software tool to rapidly build a finite element model for structural optimization of hybrid wing body (HWB) aircraft at the conceptual design level. The tool uses outputs from a Flight Optimization System (FLOPS) performance analysis together with a conceptual outer mold line of the vehicle, e.g. created by Vehicle Sketch Pad (VSP), to generate a set of MSC Nastran® bulk data files. These files can readily be used to perform a structural optimization and weight estimation using Nastran’s® Solution 200 multidisciplinary optimization solver. Initially developed at NASA Langley Research Center to perform increased fidelity conceptual level HWB centerbody structural analyses, HCDstruct has grown into a complete HWB structural sizing and weight estimation tool, including a fully flexible aeroelastic loads analysis. Recent upgrades to the tool include the expansion to a full wing tip-to-wing tip model for asymmetric analyses like engine out conditions and dynamic overswings, as well as a fully actuated trailing edge, featuring up to 15 independently actuated control surfaces and twin tails. Several example applications of the HCDstruct tool are presented.
Optimal Control of Isometric Muscle Dynamics
Directory of Open Access Journals (Sweden)
Robert Rockenfeller
2015-03-01
Full Text Available We use an indirect optimal control approach to calculate the optimal neural stimulation needed to obtain measured isometric muscle forces. The neural stimulation of the nerve system is hereby considered to be a control function (input of the system ’muscle’ that solely determines the muscle force (output. We use a well-established muscle model and experimental data of isometric contractions. The model consists of coupled activation and contraction dynamics described by ordinary differential equations. To validate our results, we perform a comparison with commercial optimal control software.
Optimal Control of Evolution Mixed Variational Inclusions
Energy Technology Data Exchange (ETDEWEB)
Alduncin, Gonzalo, E-mail: alduncin@geofisica.unam.mx [Universidad Nacional Autónoma de México, Departamento de Recursos Naturales, Instituto de Geofísica (Mexico)
2013-12-15
Optimal control problems of primal and dual evolution mixed variational inclusions, in reflexive Banach spaces, are studied. The solvability analysis of the mixed state systems is established via duality principles. The optimality analysis is performed in terms of perturbation conjugate duality methods, and proximation penalty-duality algorithms to mixed optimality conditions are further presented. Applications to nonlinear diffusion constrained problems as well as quasistatic elastoviscoplastic bilateral contact problems exemplify the theory.
Design of Magnetic Flux Feedback Controller in Hybrid Suspension System
Directory of Open Access Journals (Sweden)
Wenqing Zhang
2013-01-01
Full Text Available Hybrid suspension system with permanent magnet and electromagnet consumes little power consumption and can realize larger suspension gap. But realizing stable suspension of hybrid magnet is a tricky problem in the suspension control sphere. Considering from this point, we take magnetic flux signal as a state variable and put this signal back to suspension control system. So we can get the hybrid suspension mathematical model based on magnetic flux signal feedback. By application of MIMO feedback linearization theory, we can further realize linearization of the hybrid suspension system. And then proportion, integral, differentiation, magnetic flux density B (PIDB controller is designed. Some hybrid suspension experiments have been done on CMS04 magnetic suspension bogie of National University of Defense Technology (NUDT in China. The experiments denote that the new hybrid suspension control algorithm based on magnetic flux signal feedback designed in this paper has more advantages than traditional position-current double cascade control algorithm. Obviously, the robustness and stability of hybrid suspension system have been enhanced.
Hybrid particle swarm optimization for multiobjective resource allocation
Institute of Scientific and Technical Information of China (English)
Yi Yang; Li Xiaoxing; Gu Chunqin
2008-01-01
Resource allocation (RA) is the problem of allocating resources among various artifacts or business units to meet one or more expected goals,such as maximizing the profits,minimizing the costs,or achieving the best qualities.A complex multiobjective RA is addressed,and a multiobjective mathematical model is used to find solutions efficiently.Then,an improved particle swarm algorithm (mO_PSO) is proposed combined with a new particle diversity controller policies and dissipation operation.Meanwhile,a modified Pareto methods used in PSO to deal with multiobjectives optimization is presented.The effectiveness of the provided algorithm is validated by its application to some illustrative example dealing with multiobjective RA problems and with the comparative experiment with other algorithm.
A Muscle Synergy-inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis
Directory of Open Access Journals (Sweden)
Naji A Alibeji
2015-12-01
Full Text Available Abstract--- Abstract--- A hybrid neuroprosthesis that uses an electric motor-based wearable exoskeleton and functional electrical stimulation (FES has a promising potential to restore walking in persons with paraplegia. A hybrid actuation structure introduces effector redundancy, making its automatic control a challenging task because multiple muscles and additional electric motor need to be coordinated. Inspired by the muscle synergy principle, we designed a low dimensional controller to control multiple effectors: FES of multiple muscles and electric motors. The resulting control system may be less complex and easier to control. To obtain the muscle synergy-inspired low dimensional control, a subject-specific gait model was optimized to compute optimal control signals for the multiple effectors. The optimal control signals were then dimensionally reduced by using principal component analysis to extract synergies. Then, an adaptive feedforward controller with an update law for the synergy activation was designed. In addition, feedback control was used to provide stability and robustness to the control design. The adaptive-feedforward and feedback control structure makes the low dimensional controller more robust to disturbances and variations in the model parameters and may help to compensate for other time-varying phenomena (e.g., muscle fatigue. This is proven by using a Lyapunov stability analysis, which yielded semi-global uniformly ultimately bounded tracking. Computer simulations were performed to test the new controller on a 4 degree of freedom gait model.
Directory of Open Access Journals (Sweden)
Yingjie Xu
2016-03-01
Full Text Available Carbon fiber-reinforced multi-layered pyrocarbon–silicon carbide matrix (C/C–SiC composites are widely used in aerospace structures. The complicated spatial architecture and material heterogeneity of C/C–SiC composites constitute the challenge for tailoring their properties. Thus, discovering the intrinsic relations between the properties and the microstructures and sequentially optimizing the microstructures to obtain composites with the best performances becomes the key for practical applications. The objective of this work is to optimize the thermal-elastic properties of unidirectional C/C–SiC composites by controlling the multi-layered matrix thicknesses. A hybrid approach based on micromechanical modeling and back propagation (BP neural network is proposed to predict the thermal-elastic properties of composites. Then, a particle swarm optimization (PSO algorithm is interfaced with this hybrid model to achieve the optimal design for minimizing the coefficient of thermal expansion (CTE of composites with the constraint of elastic modulus. Numerical examples demonstrate the effectiveness of the proposed hybrid model and optimization method.
Control approach for comfortable power shifting in hybrid transmissions - ML 450 hybrid
Energy Technology Data Exchange (ETDEWEB)
Saenger Zetina, Siegfried; Neiss, Konstantin [Daimler AG, Hybrid Development Center, Troy, MI (United States)
2008-07-01
The comfortable shifting control in a luxury class vehicle is extremely important, due to competitive automatic transmissions with torque converters; clutch automated manual transmissions and dual clutch transmissions. Hybrid transmissions play a key role in comfort and performance enhancement while at the same time being fuel efficient with the aid of electric machines and battery packs. Here, the alternative to conventional add-on hybrid power head transmissions: the power split hybrid transmission is studied. As a practical example, the Two Mode of the Hybrid Development Center is used within the ML450 Hybrid. For achieving a smooth shifting, there are model based algorithms needed. As objective measure to evaluate the shifting the VDV (Vibration Dose Value) is used. (orig.)
MDP Optimal Control under Temporal Logic Constraints
Ding, Xu Chu; Belta, Calin; Rus, Daniela
2011-01-01
In this paper, we develop a method to automatically generate a control policy for a dynamical system modeled as a Markov Decision Process (MDP). The control specification is given as a Linear Temporal Logic (LTL) formula over a set of propositions defined on the states of the MDP. We synthesize a control policy such that the MDP satisfies the given specification almost surely, if such a policy exists. In addition, we designate an "optimizing proposition" to be repeatedly satisfied, and we formulate a novel optimization criterion in terms of minimizing the expected cost in between satisfactions of this proposition. We propose a sufficient condition for a policy to be optimal, and develop a dynamic programming algorithm that synthesizes a policy that is optimal under some conditions, and sub-optimal otherwise. This problem is motivated by robotic applications requiring persistent tasks, such as environmental monitoring or data gathering, to be performed.
Energy Optimal Control of Induction Motor Drives
DEFF Research Database (Denmark)
Abrahamsen, Flemming
This thesis deals with energy optimal control of small and medium-size variable speed induction motor drives for especially Heating, Ventilation and Air-Condition (HVAC) applications. Optimized efficiency is achieved by adapting the magnetization level in the motor to the load, and the basic...... purpose is demonstrate how this can be done for low-cost PWM-VSI drives without bringing the robustness of the drive below an acceptable level. Four drives are investigated with respect to energy optimal control: 2.2 kW standard and high-efficiency motor drives, 22 kW and 90 kW standard motor drives....... The method has been to make extensive efficiency measurements within the specified operating area with optimized efficiency and with constant air-gap flux, and to establish reliable converter and motor loss models based on those measurements. The loss models have been used to analyze energy optimal control...
A hybrid multi-objective evolutionary algorithm for wind-turbine blade optimization
Sessarego, M.; Dixon, K. R.; Rival, D. E.; Wood, D. H.
2015-08-01
A concurrent-hybrid non-dominated sorting genetic algorithm (hybrid NSGA-II) has been developed and applied to the simultaneous optimization of the annual energy production, flapwise root-bending moment and mass of the NREL 5 MW wind-turbine blade. By hybridizing a multi-objective evolutionary algorithm (MOEA) with gradient-based local search, it is believed that the optimal set of blade designs could be achieved in lower computational cost than for a conventional MOEA. To measure the convergence between the hybrid and non-hybrid NSGA-II on a wind-turbine blade optimization problem, a computationally intensive case was performed using the non-hybrid NSGA-II. From this particular case, a three-dimensional surface representing the optimal trade-off between the annual energy production, flapwise root-bending moment and blade mass was achieved. The inclusion of local gradients in the blade optimization, however, shows no improvement in the convergence for this three-objective problem.
Hybrid genetic algorithm approach for selective harmonic control
Energy Technology Data Exchange (ETDEWEB)
Dahidah, Mohamed S.A. [Faculty of Engineering, Multimedia University, 63100, Jalan Multimedia-Cyberjaya, Selangor (Malaysia); Agelidis, Vassilios G. [School of Electrical and Information Engineering, The University of Sydney, NSW (Australia); Rao, Machavaram V. [Faculty of Engineering and Technology, Multimedia University, 75450, Jalan Ayer Keroh Lama-Melaka (Malaysia)
2008-02-15
The paper presents an optimal solution for a selective harmonic elimination pulse width modulated (SHE-PWM) technique suitable for a high power inverter used in constant frequency utility applications. The main challenge of solving the associated non-linear equations, which are transcendental in nature and, therefore, have multiple solutions, is the convergence, and therefore, an initial point selected considerably close to the exact solution is required. The paper discusses an efficient hybrid real coded genetic algorithm (HRCGA) that reduces significantly the computational burden, resulting in fast convergence. An objective function describing a measure of the effectiveness of eliminating selected orders of harmonics while controlling the fundamental, namely a weighted total harmonic distortion (WTHD) is derived, and a comparison of different operating points is reported. It is observed that the method was able to find the optimal solution for a modulation index that is higher than unity. The theoretical considerations reported in this paper are verified through simulation and experimentally on a low power laboratory prototype. (author)
Optimal Speed Control for Cruising
DEFF Research Database (Denmark)
Blanke, M.
1994-01-01
With small profit margins in merchant shipping and more than eighty percent of sailing time being cross ocean voyages, speed control is crucial for vessel profitability......With small profit margins in merchant shipping and more than eighty percent of sailing time being cross ocean voyages, speed control is crucial for vessel profitability...
Optimal Speed Control for Cruising
DEFF Research Database (Denmark)
Blanke, M.
1994-01-01
With small profit margins in merchant shipping and more than eighty percent of sailing time being cross ocean voyages, speed control is crucial for vessel profitability......With small profit margins in merchant shipping and more than eighty percent of sailing time being cross ocean voyages, speed control is crucial for vessel profitability...
Dynamical control of quantum state transfer within hybrid open systems
Escher, B M; Clausen, J; Kurizki, G; Davidovich, L
2010-01-01
We analyze quantum state-transfer optimization within hybrid open systems, from a "noisy" (write-in) qubit to its "quiet" counterpart (storage qubit). Intriguing interplay is revealed between our ability to avoid bath-induced errors that profoundly depend on the bath-memory time and the limitations imposed by leakage out of the operational subspace. Counterintuitively, under no circumstances is the fastest transfer optimal (for a given transfer energy).
Modeling, Optimization & Control of Hydraulic Networks
DEFF Research Database (Denmark)
Tahavori, Maryamsadat
2014-01-01
to check if the network is controllable. Afterward the pressure control problem in water supply systems is formulated as an optimal control problem. The goal is to minimize the power consumption in pumps and also to regulate the pressure drop at the end-users to a desired value. The formulated optimal...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...... systems. To have better understanding of water leakage, to control pressure and leakage effectively and for optimal design of water supply system, suitable modeling is an important prerequisite. Therefore a model with the main objective of pressure control and consequently leakage reduction is presented...
Greenhouse climate management : an optimal control approach
Henten, van E.J.
1994-01-01
In this thesis a methodology is developed for the construction and analysis of an optimal greenhouse climate control system.
In chapter 1, the results of a literature survey are presented and the research objectives are defined. In the literature, optimal greenhouse climate
Optimal control and the calculus of variations
Pinch, Enid R
1993-01-01
This introduction to optimal control theory is intended for undergraduate mathematicians and for engineers and scientists with some knowledge of classical analysis. It includes sections on classical optimization and the calculus of variations. All the important theorems are carefully proved. There are many worked examples and exercises for the reader to attempt.
Optimization and control of metal forming processes
Havinga, Gosse Tjipke
2016-01-01
Inevitable variations in process and material properties limit the accuracy of metal forming processes. Robust optimization methods or control systems can be used to improve the production accuracy. Robust optimization methods are used to design production processes with low sensitivity to the distu
Greenhouse climate management: an optimal control approach.
Henten, van E.J.
1994-01-01
In this thesis a methodology is developed for the construction and analysis of an optimal greenhouse climate control system.In chapter 1, the results of a literature survey are presented and the research objectives are defined. In the literature, optimal greenhouse climate management systems have be
A Hybrid Ant Colony Optimization for the Prediction of Protein Secondary Structure
Institute of Scientific and Technical Information of China (English)
Chao CHEN; Yuan Xin TIAN; Xiao Yong ZOU; Pei Xiang CAI; Jin Yuan MO
2005-01-01
Based on the concept of ant colony optimization and the idea of population in genetic algorithm, a novel global optimization algorithm, called the hybrid ant colony optimization (HACO), is proposed in this paper to tackle continuous-space optimization problems. It was compared with other well-known stochastic methods in the optimization of the benchmark functions and was also used to solve the problem of selecting appropriate dilation efficiently by optimizing the wavelet power spectrum of the hydrophobic sequence of protein, which is thc key step on using continuous wavelet transform (CWT) to predict a-helices and connecting peptides.
Hybrid stabilizing control on a real mobile robot
Oelen, Wilco; Berghuis, Harry; Nijmeijer, Henk; Canudas de Wit, Carlos
1995-01-01
To establish empirical verification of a stabilizing controller for nonholonomic systems, the authors implement a hybrid control concept on a 2-DOF mobile robot. Practical issues of velocity control are also addressed through a velocity controller which transforms the mobile robot to a new system wi
Optimal control problems with switching points
Seywald, Hans
1991-09-01
An overview is presented of the problems and difficulties that arise in solving optimal control problems with switching points. A brief discussion of existing optimality conditions is given and a numerical approach for solving the multipoint boundary value problems associated with the first-order necessary conditions of optimal control is presented. Two real-life aerospace optimization problems are treated explicitly. These are altitude maximization for a sounding rocket (Goddard Problem) in the presence of a dynamic pressure limit, and range maximization for a supersonic aircraft flying in the vertical, also in the presence of a dynamic pressure limit. In the second problem singular control appears along arcs with active dynamic pressure limit, which in the context of optimal control, represents a first-order state inequality constraint. An extension of the Generalized Legendre-Clebsch Condition to the case of singular control along state/control constrained arcs is presented and is applied to the aircraft range maximization problem stated above. A contribution to the field of Jacobi Necessary Conditions is made by giving a new proof for the non-optimality of conjugate paths in the Accessory Minimum Problem. Because of its simple and explicit character, the new proof may provide the basis for an extension of Jacobi's Necessary Condition to the case of the trajectories with interior point constraints. Finally, the result that touch points cannot occur for first-order state inequality constraints is extended to the case of vector valued control functions.
Control of DNA hybridization by photoswitchable molecular glue.
Dohno, Chikara; Nakatani, Kazuhiko
2011-12-01
Hybridization of DNA is one of the most intriguing events in molecular recognition and is essential for living matter to inherit life beyond generations. In addition to the function of DNA as genetic material, DNA hybridization is a key to control the function of DNA-based materials in nanoscience. Since the hybridization of two single stranded DNAs is a thermodynamically favorable process, dissociation of the once formed DNA duplex is normally unattainable under isothermal conditions. As the progress of DNA-based nanoscience, methodology to control the DNA hybridization process has become increasingly important. Besides many reports using the chemically modified DNA for the regulation of hybridization, we focused our attention on the use of a small ligand as the molecular glue for the DNA. In 2001, we reported the first designed molecule that strongly and specifically bound to the mismatched base pairs in double stranded DNA. Further studies on the mismatch binding molecules provided us a key discovery of a novel mode of the binding of a mismatch binding ligand that induced the base flipping. With these findings we proposed the concept of molecular glue for DNA for the unidirectional control of DNA hybridization and, eventually photoswitchable molecular glue for DNA, which enabled the bidirectional control of hybridization under photoirradiation. In this tutorial review, we describe in detail how we integrated the mismatch binding ligand into photoswitchable molecular glue for DNA, and the application and perspective in DNA-based nanoscience.
A Feedback Optimal Control Algorithm with Optimal Measurement Time Points
Directory of Open Access Journals (Sweden)
Felix Jost
2017-02-01
Full Text Available Nonlinear model predictive control has been established as a powerful methodology to provide feedback for dynamic processes over the last decades. In practice it is usually combined with parameter and state estimation techniques, which allows to cope with uncertainty on many levels. To reduce the uncertainty it has also been suggested to include optimal experimental design into the sequential process of estimation and control calculation. Most of the focus so far was on dual control approaches, i.e., on using the controls to simultaneously excite the system dynamics (learning as well as minimizing a given objective (performing. We propose a new algorithm, which sequentially solves robust optimal control, optimal experimental design, state and parameter estimation problems. Thus, we decouple the control and the experimental design problems. This has the advantages that we can analyze the impact of measurement timing (sampling independently, and is practically relevant for applications with either an ethical limitation on system excitation (e.g., chemotherapy treatment or the need for fast feedback. The algorithm shows promising results with a 36% reduction of parameter uncertainties for the Lotka-Volterra fishing benchmark example.
Optimized chaos control with simple limiters.
Wagner, C; Stoop, R
2001-01-01
We present an elementary derivation of chaos control with simple limiters using the logistic map and the Henon map as examples. This derivation provides conditions for optimal stabilization of unstable periodic orbits of a chaotic attractor.
The optimal control and its multiple applications
2009-01-01
In this work we refer to motivations, applications, and relations of control theory with other areas of mathematics. We present a brief historical review of optimal control theory, from its roots in the calculus of variations and the classical theory of control to the present time, giving particular emphasis to the Pontryagin maximum principle.
Multiple Objective Optimization and Optimal Control of Fermentation Processes
Directory of Open Access Journals (Sweden)
Mitko Petrov
2008-10-01
Full Text Available A multiple objective optimization is applied for finding an optimum policy of fed-batch processes of whey fermentation and L-lysine production. The multiple objective optimization problems are transformed to a standard problem of optimization with single objective function by a general utility function with weight coefficients for each single utility coefficient criteria. A combined algorithm is applied when solving the maximizing decision problem. The algorithm includes a method for random search of finding an initial point and a method based on the fuzzy sets theory, combined in order to find the best solution of the optimization problem. The application of the combined algorithm eliminates the main disadvantage of the used fuzzy optimization method, namely it decreases the number of discrete values of the control variables. Thus, the algorithm allows problems with larger scale to be solved. After this multiple optimization, the useful product quality rises and the residual substrate concentration at the end of the process decreases. In this way, the process productivity is increased.
Directory of Open Access Journals (Sweden)
Mehdi Neshat
2015-11-01
Full Text Available In this article, the objective was to present effective and optimal strategies aimed at improving the Swallow Swarm Optimization (SSO method. The SSO is one of the best optimization methods based on swarm intelligence which is inspired by the intelligent behaviors of swallows. It has been able to offer a relatively strong method for solving optimization problems. However, despite its many advantages, the SSO suffers from two shortcomings. Firstly, particles movement speed is not controlled satisfactorily during the search due to the lack of an inertia weight. Secondly, the variables of the acceleration coefficient are not able to strike a balance between the local and the global searches because they are not sufficiently flexible in complex environments. Therefore, the SSO algorithm does not provide adequate results when it searches in functions such as the Step or Quadric function. Hence, the fuzzy adaptive Swallow Swarm Optimization (FASSO method was introduced to deal with these problems. Meanwhile, results enjoy high accuracy which are obtained by using an adaptive inertia weight and through combining two fuzzy logic systems to accurately calculate the acceleration coefficients. High speed of convergence, avoidance from falling into local extremum, and high level of error tolerance are the advantages of proposed method. The FASSO was compared with eleven of the best PSO methods and SSO in 18 benchmark functions. Finally, significant results were obtained.
Optimal impulse control problems and linear programming.
Bauso, D.
2009-01-01
Optimal impulse control problems are, in general, difficult to solve. A current research goal is to isolate those problems that lead to tractable solutions. In this paper, we identify a special class of optimal impulse control problems which are easy to solve. Easy to solve means that solution algorithms are polynomial in time and therefore suitable to the on-line implementation in real-time problems. We do this by using a paradigm borrowed from the Operations Research field. As main result, ...
Series Hybrid Electric Vehicle Power System Optimization Based on Genetic Algorithm
Zhu, Tianjun; Li, Bin; Zong, Changfu; Wu, Yang
2017-09-01
Hybrid electric vehicles (HEV), compared with conventional vehicles, have complex structures and more component parameters. If variables optimization designs are carried on all these parameters, it will increase the difficulty and the convergence of algorithm program, so this paper chooses the parameters which has a major influence on the vehicle fuel consumption to make it all work at maximum efficiency. First, HEV powertrain components modelling are built. Second, taking a tandem hybrid structure as an example, genetic algorithm is used in this paper to optimize fuel consumption and emissions. Simulation results in ADVISOR verify the feasibility of the proposed genetic optimization algorithm.
Neuro-optimal control of helicopter UAVs
Nodland, David; Ghosh, Arpita; Zargarzadeh, H.; Jagannathan, S.
2011-05-01
Helicopter UAVs can be extensively used for military missions as well as in civil operations, ranging from multirole combat support and search and rescue, to border surveillance and forest fire monitoring. Helicopter UAVs are underactuated nonlinear mechanical systems with correspondingly challenging controller designs. This paper presents an optimal controller design for the regulation and vertical tracking of an underactuated helicopter using an adaptive critic neural network framework. The online approximator-based controller learns the infinite-horizon continuous-time Hamilton-Jacobi-Bellman (HJB) equation and then calculates the corresponding optimal control input that minimizes the HJB equation forward-in-time. In the proposed technique, optimal regulation and vertical tracking is accomplished by a single neural network (NN) with a second NN necessary for the virtual controller. Both of the NNs are tuned online using novel weight update laws. Simulation results are included to demonstrate the effectiveness of the proposed control design in hovering applications.
The effects of redundant control inputs in optimal control
Institute of Scientific and Technical Information of China (English)
DUAN ZhiSheng; HUANG Lin; YANG Ying
2009-01-01
For a stabillzable system,the extension of the control inputs has no use for stabllizability,but it is important for optimal control.In this paper,a necessary and sufficient condition is presented to strictly decrease the quadratic optimal performance index after control input extensions.A similar result is also provided for H_2 optimal control problem.These results show an essential difference between single-input and multi-input control systems.Several examples are taken to illustrate related problems.
Novel hybrid adaptive controller for manipulation in complex perturbation environments.
Directory of Open Access Journals (Sweden)
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.
Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments
Smith, Alex M. C.; Yang, Chenguang; Ma, Hongbin; Culverhouse, Phil; Cangelosi, Angelo; Burdet, Etienne
2015-01-01
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. PMID:26029916
A novel hybrid algorithm of GSA with Kepler algorithm for numerical optimization
Directory of Open Access Journals (Sweden)
Soroor Sarafrazi
2015-07-01
Full Text Available It is now well recognized that pure algorithms can be promisingly improved by hybridization with other techniques. One of the relatively new metaheuristic algorithms is Gravitational Search Algorithm (GSA which is based on the Newton laws. In this paper, to enhance the performance of GSA, a novel algorithm called “Kepler”, inspired by the astrophysics, is introduced. The Kepler algorithm is based on the principle of the first Kepler law. The hybridization of GSA and Kepler algorithm is an efficient approach to provide much stronger specialization in intensification and/or diversification. The performance of GSA–Kepler is evaluated by applying it to 14 benchmark functions with 20–1000 dimensions and the optimal approximation of linear system as a practical optimization problem. The results obtained reveal that the proposed hybrid algorithm is robust enough to optimize the benchmark functions and practical optimization problems.
Topology optimization of bounded acoustic problems using the hybrid finite element-wave based method
DEFF Research Database (Denmark)
Goo, Seongyeol; Wang, Semyung; Kook, Junghwan
2017-01-01
This paper presents an alternative topology optimization method for bounded acoustic problems that uses the hybrid finite element-wave based method (FE-WBM). The conventional method for the topology optimization of bounded acoustic problems is based on the finite element method (FEM), which...... is limited to low frequency applications due to considerable computational efforts. To this end, we propose a gradient-based topology optimization method that uses the hybrid FE-WBM whereby the entire domain of a problem is partitioned into design and non-design domains. In this respect, the FEM is used...... as a design domain of topology optimization, and the WBM is used as a non-design domain to increase computational efficiency. The adjoint variable method based on the hybrid FE-WBM is also proposed as a means of computing design sensitivities. Numerical examples are presented to demonstrate the effectiveness...
Chemical optimization algorithm for fuzzy controller design
Astudillo, Leslie; Castillo, Oscar
2014-01-01
In this book, a novel optimization method inspired by a paradigm from nature is introduced. The chemical reactions are used as a paradigm to propose an optimization method that simulates these natural processes. The proposed algorithm is described in detail and then a set of typical complex benchmark functions is used to evaluate the performance of the algorithm. Simulation results show that the proposed optimization algorithm can outperform other methods in a set of benchmark functions. This chemical reaction optimization paradigm is also applied to solve the tracking problem for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on fuzzy logic theory. Computer simulations are presented confirming that this optimization paradigm is able to outperform other optimization techniques applied to this particular robot application
Energy Technology Data Exchange (ETDEWEB)
Bocklisch, Thilo
2010-03-29
The dissertation presents a new optimizing energy management concept for fuel cell-direct storage-hybrid systems. Initially, the characteristics of specific energy time series are investigated on the basis of real measurement data. A new concept for the multi-scale analysis, modelling and prediction of fluctuating photovoltaic supply and electric load demand profiles is developed. The second part of the dissertation starts with a discussion of the benefits of and the basic coupling and control principles for fuel cell-direct storage-hybrid systems. The typical characteristics of a PEM-fuel cell, a metal hydride hydrogen storage, a lithium-ion battery and a supercap unit are presented. A new modular DC/DC-converter is described. Results from experimental and theoretical investigations of the individual components and the overall hybrid system are discussed. New practicable models for the voltage-current-curve, the state of charge behaviour and the conversion losses are presented. The third part of the dissertation explains the new energy management concept. The optimization of power flows is achieved by a control-oriented approach, employing a) the primary control of bus voltage and fuel cell current, b) the secondary control to limit fuel cell current gradient and operating range and to perform direct storage charge control, and c) the system control to optimally adjust secondary control parameters aiming for a reduction of dynamic fuel cell stress and hydrogen consumption. Results from simulations and experimental investigations demonstrate the benefits and high capabilities of the new optimizing energy management concept. Examples of stationary and portable applications conclude the dissertation. (orig.)
OPTIMAL OPERATIONAL CONTROL OF INTERCEPTOR SEWER SYSTEM
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
In this paper, a mathematical model was built up to solve the problem of optimal operational control by analysing the factors on an interceptor sewer system and a Fortran program was produced for this model. This paper shows that the optimal control states can be determined by working out the optimal flow rates by means of Linear Programming (LP). The result is very sensitive to interception points and the concentration weight coefficients over time. The result further highlights some practical applications for the existing sewer systems or the sewer systems under design.
Investigation on evolutionary optimization of chaos control
Energy Technology Data Exchange (ETDEWEB)
Zelinka, Ivan [Faculty of Applied Informatics, Tomas Bata University in Zli' n, Nad Stranemi 4511, 762 72 Zli' n (Czech Republic)], E-mail: zelinka@fai.utb.cz; Senkerik, Roman [Faculty of Applied Informatics, Tomas Bata University in Zli' n, Nad Stranemi 4511, 762 72 Zli' n (Czech Republic)], E-mail: senkerik@fai.utb.cz; Navratil, Eduard [Faculty of Applied Informatics, Tomas Bata University in Zli' n, Nad Stranemi 4511, 762 72 Zli' n (Czech Republic)], E-mail: enavratil@fai.utb.cz
2009-04-15
This work deals with an investigation on optimization of the feedback control of chaos based on the use of evolutionary algorithms. The main objective is to show that evolutionary algorithms are capable of optimization of chaos control. As models of deterministic chaotic systems, one-dimensional Logistic equation and two-dimensional Henon map were used. The optimizations were realized in several ways, each one for another set of parameters of evolution algorithms or separate cost functions. The evolutionary algorithm SOMA (self-organizing migrating algorithm) was used in four versions. For each version simulations were repeated several times to show and check for robustness of the applied method.
Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.
2016-04-01
A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.
Energy Technology Data Exchange (ETDEWEB)
Lashkar Ara, A., E-mail: Lashkarara@iust.ac.i [Department of Electrical Engineering, Iran University of Science and Technology, Narmak, Tehran, P.O. Box 1684613114 (Iran, Islamic Republic of); Kazemi, A., E-mail: Kazemi@iust.ac.i [Department of Electrical Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of); Nabavi Niaki, S.A., E-mail: nabavi.niaki@utoronto.c [Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, M5 S 3G4 (Canada)
2011-02-15
In this paper a hybrid configuration of a FACTS controller called Optimal Unified Power Flow Controller (OUPFC) which is composed of a mechanical phase shifting transformer augmented with a small scale Unified Power Flow Controller (UPFC) is introduced. The steady-state model of OUPFC is developed as a power injection model. This model is used to develop an Optimal Power Flow (OPF) algorithm including OUPFC to find the optimum number, location, and settings of OUPFCs to minimize the total fuel cost and power losses. Simulation results are presented for the IEEE 14-, 30-, and 118-bus systems. The optimization method is numerically solved using Matlab and General Algebraic Modelling System (GAMS) software environments. The results demonstrate the effectiveness of the proposed approach to solve the optimal location and settings of OUPFCs incorporated in OPF problem and improve the power system operation. Furthermore, the ability of OUPFC to optimize the objective functions is compared to that of PST and UPFC.
Optimal Wentzell Boundary Control of Parabolic Equations
Energy Technology Data Exchange (ETDEWEB)
Luo, Yousong, E-mail: yousong.luo@rmit.edu.au [RMIT University, School of Mathematical and Geospatial Sciences (Australia)
2017-04-15
This paper deals with a class of optimal control problems governed by an initial-boundary value problem of a parabolic equation. The case of semi-linear boundary control is studied where the control is applied to the system via the Wentzell boundary condition. The differentiability of the state variable with respect to the control is established and hence a necessary condition is derived for the optimal solution in the case of both unconstrained and constrained problems. The condition is also sufficient for the unconstrained convex problems. A second order condition is also derived.
Optimal control problem for the extended Fisher–Kolmogorov equation
Indian Academy of Sciences (India)
Ning Duan
2016-02-01
In this paper, the optimal control problem for the extended Fisher–Kolmogorov equation is studied. The optimal control under boundary condition is given, the existence of optimal solution to the equation is proved and the optimality system is established.
Optimal control novel directions and applications
Aronna, Maria; Kalise, Dante
2017-01-01
Focusing on applications to science and engineering, this book presents the results of the ITN-FP7 SADCO network’s innovative research in optimization and control in the following interconnected topics: optimality conditions in optimal control, dynamic programming approaches to optimal feedback synthesis and reachability analysis, and computational developments in model predictive control. The novelty of the book resides in the fact that it has been developed by early career researchers, providing a good balance between clarity and scientific rigor. Each chapter features an introduction addressed to PhD students and some original contributions aimed at specialist researchers. Requiring only a graduate mathematical background, the book is self-contained. It will be of particular interest to graduate and advanced undergraduate students, industrial practitioners and to senior scientists wishing to update their knowledge.
OPTIMAL CONTROL FOR ELECTRIC VEHICLE STABILIZATION
Directory of Open Access Journals (Sweden)
MARIAN GAICEANU
2016-01-01
Full Text Available This main objective of the paper is to stabilize an electric vehicle in optimal manner to a step lane change maneuver. To define the mathematical model of the vehicle, the rigid body moving on a plane is taken into account. An optimal lane keeping controller delivers the adequate angles in order to stabilize the vehicle’s trajectory in an optimal way. Two degree of freedom linear bicycle model is adopted as vehicle model, consisting of lateral and yaw motion equations. The proposed control maintains the lateral stability by taking the feedback information from the vehicle transducers. In this way only the lateral vehicle’s dynamics are enough to considerate. Based on the obtained linear mathematical model the quadratic optimal control is designed in order to maintain the lateral stability of the electric vehicle. The numerical simulation results demonstrate the feasibility of the proposed solution.
Kanagaraj, G.; Ponnambalam, S. G.; Jawahar, N.; Mukund Nilakantan, J.
2014-10-01
This article presents an effective hybrid cuckoo search and genetic algorithm (HCSGA) for solving engineering design optimization problems involving problem-specific constraints and mixed variables such as integer, discrete and continuous variables. The proposed algorithm, HCSGA, is first applied to 13 standard benchmark constrained optimization functions and subsequently used to solve three well-known design problems reported in the literature. The numerical results obtained by HCSGA show competitive performance with respect to recent algorithms for constrained design optimization problems.
AN HYBRID STOCHASTIC-DETERMINISTIC OPTIMIZATION ALGORITHM FOR STRUCTURAL DAMAGE IDENTIFICATION
Nhamage, Idilson António; Lopez, Rafael Holdorf; Miguel, Leandro Fleck Fadel; Miguel, Letícia Fleck Fadel; Torii, André Jacomel
2017-01-01
Abstract. This paper presents a hybrid stochastic/deterministic optimization algorithm to solve the target optimization problem of vibration-based damage detection. The use of a numerical solution of the representation formula to locate the region of the global solution, i.e., to provide a starting point for the local optimizer, which is chosen to be the Nelder-Mead algorithm (NMA), is proposed. A series of numerical examples with different damage scenarios and noise levels was performed unde...
Stochastic Optimally-Tuned Ranged-Separated Hybrid Density Functional Theory
Neuhauser, Daniel; Cytter, Yael; Baer, Roi
2015-01-01
We develop a stochastic formulation of the optimally-tuned range-separated hybrid density functional theory which enables significant reduction of the computational effort and scaling of the non-local exchange operator at the price of introducing a controllable statistical error. Our method is based on stochastic representations of the Coulomb convolution integral and of the generalized Kohn-Sham density matrix. The computational cost of the approach is similar to that of usual Kohn-Sham density functional theory, yet it provides much more accurate description of the quasiparticle energies for the frontier orbitals. This is illustrated for a series of silicon nanocrystals up to sizes exceeding 3000 electrons. Comparison with the stochastic GW many-body perturbation technique indicates excellent agreement for the fundamental band gap energies, good agreement for the band-edge quasiparticle excitations, and very low statistical errors in the total energy for large systems. The present approach has a major advan...
Optimal control of a CSTR process
Directory of Open Access Journals (Sweden)
A. Soukkou
2008-12-01
Full Text Available Designing an effective criterion and learning algorithm for find the best structure is a major problem in the control design process. In this paper, the fuzzy optimal control methodology is applied to the design of the feedback loops of an Exothermic Continuous Stirred Tank Reactor system. The objective of design process is to find an optimal structure/gains of the Robust and Optimal Takagi Sugeno Fuzzy Controller (ROFLC. The control signal thus obtained will minimize a performance index, which is a function of the tracking/regulating errors, the quantity of the energy of the control signal applied to the system, and the number of fuzzy rules. The genetic learning is proposed for constructing the ROFLC. The chromosome genes are arranged into two parts, the binary-coded part contains the control genes and the real-coded part contains the genes parameters representing the fuzzy knowledge base. The effectiveness of this chromosome formulation enables the fuzzy sets and rules to be optimally reduced. The performances of the ROFLC are compared to these found by the traditional PD controller with Genetic Optimization (PD_GO. Simulations demonstrate that the proposed ROFLC and PD_GO has successfully met the design specifications.
Fitting method for hybrid temperature control in smart home environment
CHENG, Zhuo; TAN, Yasuo; Lim, Azman Osman
2014-01-01
The design of control system is crucial for improving the comfort level of home environment. Cyber-Physical Systems (CPSs) can offer numerous opportunities to design high efficient control systems. In this paper, we focus on the design of temperature control systems. By using the idea of CPS, a hybrid temperature control (HTC) system is proposed. It combines supervisory and proportional-integral-derivative (PID) controllers. Through an energy efficient temperature control (EETC) algorithm, HT...
Directory of Open Access Journals (Sweden)
Paweł Sitek
2016-01-01
Full Text Available This paper presents a hybrid method for modeling and solving supply chain optimization problems with soft, hard, and logical constraints. Ability to implement soft and logical constraints is a very important functionality for supply chain optimization models. Such constraints are particularly useful for modeling problems resulting from commercial agreements, contracts, competition, technology, safety, and environmental conditions. Two programming and solving environments, mathematical programming (MP and constraint logic programming (CLP, were combined in the hybrid method. This integration, hybridization, and the adequate multidimensional transformation of the problem (as a presolving method helped to substantially reduce the search space of combinatorial models for supply chain optimization problems. The operation research MP and declarative CLP, where constraints are modeled in different ways and different solving procedures are implemented, were linked together to use the strengths of both. This approach is particularly important for the decision and combinatorial optimization models with the objective function and constraints, there are many decision variables, and these are summed (common in manufacturing, supply chain management, project management, and logistic problems. The ECLiPSe system with Eplex library was proposed to implement a hybrid method. Additionally, the proposed hybrid transformed model is compared with the MILP-Mixed Integer Linear Programming model on the same data instances. For illustrative models, its use allowed finding optimal solutions eight to one hundred times faster and reducing the size of the combinatorial problem to a significant extent.
Kubota, Shigeru; Kanomata, Kensaku; Suzuki, Takahiko; Hirose, Fumihiko
2014-10-01
The antireflection structure (ARS) for solar cells is categorized to mainly two different techniques, i.e., the surface texturing and the single or multi-layer antireflection interference coating. In this study, we propose a novel hybrid ARS, which integrates moth eye texturing and multi-layer coat, for application to organic photovoltaics (OPVs). Using optical simulations based on the finite-difference time-domain (FDTD) method, we conduct nearly global optimization of the geometric parameters characterizing the hybrid ARS. The proposed optimization algorithm consists of two steps: in the first step, we optimize the period and height of moth eye array, in the absence of multi-layer coating. In the second step, we optimize the whole structure of hybrid ARS by using the solution obtained by the first step as the starting search point. The methods of the simple grid search and the Hooke and Jeeves pattern search are used for global and local searches, respectively. In addition, we study the effects of deviations in the geometric parameters of hybrid ARS from their optimized values. The design concept of hybrid ARS is highly beneficial for broadband light trapping in OPVs.
Optimal Control of Active Recoil Mechanisms
1977-02-01
pressures in different chambers, rod pull are available and can be plotted. A linear state feedback control system is proposed to adapt this...desirable. A linear state feedback control system with variable gains is proposed in the report. A separate control law is designed for each...optimization algorithm to choose a feasible solution. 27 3.3 Results for M-37 Recoil Mechanism The linear state feedback control system and
Multi-Objective Configuration Optimization of a Hybrid Energy Storage System
Directory of Open Access Journals (Sweden)
Shan Cheng
2017-02-01
Full Text Available This study aims to investigate multi-objective configuration optimization of a hybrid energy storage system (HESS. In order to maximize the stability of the wind power output with minimized HESS investment, a multi-objective model for optimal HESS configuration has been established, which proposes decreasing the installation and operation & maintenance costs of an HESS and improving the compensation satisfaction rate of wind power fluctuation. Besides, fuzzy control has been used to allocate power in the HESS for lengthening battery lifetime and ensuring HESS with enough energy to compensate the fluctuation of the next time interval. Instead of converting multiple objectives into one, a multi-objective particle swarm optimization with integration of bacteria quorum sensing and circular elimination (BC-MOPSO has been applied to provide diverse alternative solutions. In order to illustrate the feasibility and effectiveness of the proposed model and the application of BC-MOPSO, simulations along with analysis and discussion are carried out. The results verified the feasibility and effectiveness of the proposed approach.
Abdul Rani, Khairul Najmy; Abdulmalek, Mohamedfareq; A. Rahim, Hasliza; Siew Chin, Neoh; Abd Wahab, Alawiyah
2017-04-01
This research proposes the various versions of modified cuckoo search (MCS) metaheuristic algorithm deploying the strength Pareto evolutionary algorithm (SPEA) multiobjective (MO) optimization technique in rectangular array geometry synthesis. Precisely, the MCS algorithm is proposed by incorporating the Roulette wheel selection operator to choose the initial host nests (individuals) that give better results, adaptive inertia weight to control the positions exploration of the potential best host nests (solutions), and dynamic discovery rate to manage the fraction probability of finding the best host nests in 3-dimensional search space. In addition, the MCS algorithm is hybridized with the particle swarm optimization (PSO) and hill climbing (HC) stochastic techniques along with the standard strength Pareto evolutionary algorithm (SPEA) forming the MCSPSOSPEA and MCSHCSPEA, respectively. All the proposed MCS-based algorithms are examined to perform MO optimization on Zitzler-Deb-Thiele’s (ZDT’s) test functions. Pareto optimum trade-offs are done to generate a set of three non-dominated solutions, which are locations, excitation amplitudes, and excitation phases of array elements, respectively. Overall, simulations demonstrates that the proposed MCSPSOSPEA outperforms other compatible competitors, in gaining a high antenna directivity, small half-power beamwidth (HPBW), low average side lobe level (SLL) suppression, and/or significant predefined nulls mitigation, simultaneously.
Optimal control of radiator systems; Optimal reglering av radiatorsystem
Energy Technology Data Exchange (ETDEWEB)
Wollerstrand, J.; Ljunggren, P.; Johansson, P.O.
2007-07-01
This report presents results from a study aiming to considerably improve the development towards minimizing the primary return temperature from a district heating (DH) substation by optimizing the control algorithm for the space heating system. The investigation of this research field started about 20 years ago in Sweden when low flow operation of space heating systems was introduced. Following a couple of years of partly confused discussions, the method was accepted by many, but was rejected by others. Our thesis is that further improvement of cooling of DH water is possible when advanced, but robust, control algorithms are used for the space heating system. A space heating system is traditionally designed for a specific constant circulation flow combined with a suitable control curve for the space heating supply temperature as a function of the outdoor temperature. Optimal choice of the control curve varies from case to case and is an issue both we and others have dealt with in previous work. A large step was to derive theoretical control curves for optimal control of the space heating system, with an analysis of how temperature and circulation flow varies with heat load. The estimated gain varies strongly depending on the conditions, however, with realistic conditions it can be as much as 5 deg C decreased DH return temperature on yearly average. To be able to work properly under varying physical circumstances, a control algorithm must be able to combine variation of space heating supply temperature and circulation flow as a function of the heat load. By regulating the rotation speed of the circulation pump this can be achieved. Such regulation can be adjusted for each and every building by regulating a few parameters in a regulator. The results from this work are, that important theoretical knowledge has been completed, to show results systematically and to find support from practical experiments. A hands-on description of the method for optimizing DH water
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 showed enhanced performance. Work is in progress to extend this methodology to a five-fingered, three-dimensional prosthetic hand.
An efficient hybrid approach for multiobjective optimization of water distribution systems
Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.
2014-05-01
An efficient hybrid approach for the design of water distribution systems (WDSs) with multiple objectives is described in this paper. The objectives are the minimization of the network cost and maximization of the network resilience. A self-adaptive multiobjective differential evolution (SAMODE) algorithm has been developed, in which control parameters are automatically adapted by means of evolution instead of the presetting of fine-tuned parameter values. In the proposed method, a graph algorithm is first used to decompose a looped WDS into a shortest-distance tree (T) or forest, and chords (Ω). The original two-objective optimization problem is then approximated by a series of single-objective optimization problems of the T to be solved by nonlinear programming (NLP), thereby providing an approximate Pareto optimal front for the original whole network. Finally, the solutions at the approximate front are used to seed the SAMODE algorithm to find an improved front for the original entire network. The proposed approach is compared with two other conventional full-search optimization methods (the SAMODE algorithm and the NSGA-II) that seed the initial population with purely random solutions based on three case studies: a benchmark network and two real-world networks with multiple demand loading cases. Results show that (i) the proposed NLP-SAMODE method consistently generates better-quality Pareto fronts than the full-search methods with significantly improved efficiency; and (ii) the proposed SAMODE algorithm (no parameter tuning) exhibits better performance than the NSGA-II with calibrated parameter values in efficiently offering optimal fronts.
Directory of Open Access Journals (Sweden)
Nik Mizamzul Mehat
2014-01-01
Full Text Available The identification of optimal processing parameters is an important practice in the plastic injection moulding industry because of the significant effect of such parameters on plastic part quality and cost. However, the optimization design of injection moulding process parameters can be difficult because more than one quality characteristic is used in the evaluation. This study systematically develops a hybrid optimization method for multiple quality characteristics by integrating the Taguchi parameter design, grey relational analysis, and principal component analysis. A plastic gear is used to demonstrate the efficiency and validity of the proposed hybrid optimization method in controlling all influential injection moulding processing parameters during plastic gear manufacturing. To minimize the shrinkage behaviour in tooth thickness, addendum circle, and dedendum circle of moulded gear, the optimal combination of different process parameters is determined. The case study demonstrates that the proposed optimization method can produce plastic-moulded gear with minimum shrinkage behaviour of 1.8%, 1.53%, and 2.42% in tooth thickness, addendum circle, and dedendum circle, respectively; these values are less than the values in the main experiment. Therefore, shrinkage-related defects that lead to severe failure in plastic gears can be effectively minimized while satisfying the demand of the global plastic gear industry.
Itoh, Jyunpei; Yamamoto, Masayoshi; Funabiki, Shigeyuki
Electric power demand has an increasing tendency year by year. The fluctuation of the electric power causes further increase in the cost of the electric power facility and electricity charges. The development of the electric power-leveling systems (EPLS) using energy storage technology is desired to improve the electric power quality. The EPLS with a SMES is proposed as one of the countermeasures for the electric power quality improvement. However, the SMES is very expensive and it is difficult to decide the gains of the controller. It is essential in the practical use that the reduction of SMES capacity is realized. This paper proposes a new optimization method of the EPLS. The proposed algorithm is hybrid architecture with a combination of SimE (Simulated Evolution) and GA (Genetic Algorithms). The optimization of the EPLS can be achieved by the proposed hybrid algorithm compared to the SimE and the GA.
Direct switching control of DC-DC power electronic converters using hybrid system theory
Energy Technology Data Exchange (ETDEWEB)
Zhao, J.; Lin, F. [Wayne State Univ., Detroit, MI (United States). Dept. of Electrical and Computer Engineering; Wang, C. [Wayne State Univ., Detroit, MI (United States). Dept. of Electrical and Computer Engineering; Wayne State Univ., Detroit, MI (United States). Div. of Engineering Technology
2010-07-01
A direct switching control (DSC) scheme for power electronics converters was described. The system was designed for use in both traditional and renewable energy applications as well as in electric drive vehicles. The proposed control scheme was based on a detailed hybrid system converter model that used model predictive control (MPC), piecewise affine (PWA) approximations and constrained optimal control methods. A DC-DC converter was modelled as a hybrid machine. Switching among different modes of the DC-DC converter were modelled as discrete events controlled by the hybrid controller. The modelling scheme was applied to a Buck converter. The DSC was used to control the switch of the power converter based on a hybrid machine model. Results of the study showed that the method can be used to regulate output voltage and inductor currents. The method also provides fast transient responses and effectively regulates both currents and voltage. The controller can be used to provide immediate responses to dynamic disturbances and output voltage fluctuations. 23 refs., 7 figs.
Health benefit modelling and optimization of vehicular pollution control strategies
Sonawane, Nayan V.; Patil, Rashmi S.; Sethi, Virendra
2012-12-01
This study asserts that the evaluation of pollution reduction strategies should be approached on the basis of health benefits. The framework presented could be used for decision making on the basis of cost effectiveness when the strategies are applied concurrently. Several vehicular pollution control strategies have been proposed in literature for effective management of urban air pollution. The effectiveness of these strategies has been mostly studied as a one at a time approach on the basis of change in pollution concentration. The adequacy and practicality of such an approach is studied in the present work. Also, the assessment of respective benefits of these strategies has been carried out when they are implemented simultaneously. An integrated model has been developed which can be used as a tool for optimal prioritization of various pollution management strategies. The model estimates health benefits associated with specific control strategies. ISC-AERMOD View has been used to provide the cause-effect relation between control options and change in ambient air quality. BenMAP, developed by U.S. EPA, has been applied for estimation of health and economic benefits associated with various management strategies. Valuation of health benefits has been done for impact indicators of premature mortality, hospital admissions and respiratory syndrome. An optimization model has been developed to maximize overall social benefits with determination of optimized percentage implementations for multiple strategies. The model has been applied for sub-urban region of Mumbai city for vehicular sector. Several control scenarios have been considered like revised emission standards, electric, CNG, LPG and hybrid vehicles. Reduction in concentration and resultant health benefits for the pollutants CO, NOx and particulate matter are estimated for different control scenarios. Finally, an optimization model has been applied to determine optimized percentage implementation of specific
Robust spacecraft attitude tracking control using hybrid actuators with uncertainties
Cao, Xibin; Wu, Baolin
2017-07-01
The problem of spacecraft attitude tracking using hybrid actuators with uncertainties is addressed in this paper. A hybrid actuators configuration that combines reaction wheels for fine pointing and single gimbal control moment gyros for rapid maneuvering is employed for agile spacecraft. A robust control algorithm for the spacecraft attitude tracking problem when the torque axis direction and/or input scaling of the actuators are uncertain is developed. Furthermore, a torque allocation method is proposed for the hybrid actuator configuration to allow a smooth switch between single gimbal control moment gyros and reaction wheels. With this method, single gimbal control moment gyros are used for the phase of rapid maneuvering, while reaction wheels are used for the phase of fine pointing. Simulation results demonstrate the effectiveness of the proposed control scheme.
Filtering and control of stochastic jump hybrid systems
Yao, Xiuming; Zheng, Wei Xing
2016-01-01
This book presents recent research work on stochastic jump hybrid systems. Specifically, the considered stochastic jump hybrid systems include Markovian jump Ito stochastic systems, Markovian jump linear-parameter-varying (LPV) systems, Markovian jump singular systems, Markovian jump two-dimensional (2-D) systems, and Markovian jump repeated scalar nonlinear systems. Some sufficient conditions are first established respectively for the stability and performances of those kinds of stochastic jump hybrid systems in terms of solution of linear matrix inequalities (LMIs). Based on the derived analysis conditions, the filtering and control problems are addressed. The book presents up-to-date research developments and novel methodologies on stochastic jump hybrid systems. The contents can be divided into two parts: the first part is focused on robust filter design problem, while the second part is put the emphasis on robust control problem. These methodologies provide a framework for stability and performance analy...
Cyclic Control Optimization for a Smart Rotor
DEFF Research Database (Denmark)
Bergami, Leonardo; Henriksen, Lars Christian
2012-01-01
The paper presents a method to determine cyclic control trajectories for a smart rotor undergoing periodic-deterministic load variations. The control trajectories result from a constrained optimization problem, where the cost function to minimize is given by the variation of the blade root flapwise...... bending moment within a rotor revolution. The method is applied to a rotor equipped with trailing edge flaps, and capable of individual blade pitching. Results show that the optimized cyclic control significantly alleviates the load variations from periodic disturbances; the combination of both cyclic...
An example in linear quadratic optimal control
Weiss, George; Zwart, Heiko J.
1998-01-01
We construct a simple example of a quadratic optimal control problem for an infinite-dimensional linear system based on a shift semigroup. This system has an unbounded control operator. The cost is quadratic in the input and the state, and the weighting operators are bounded. Despite its extreme
An example in linear quadratic optimal control
Weiss, George; Zwart, Heiko J.
1998-01-01
We construct a simple example of a quadratic optimal control problem for an infinite-dimensional linear system based on a shift semigroup. This system has an unbounded control operator. The cost is quadratic in the input and the state, and the weighting operators are bounded. Despite its extreme sim
Optimal control of nonsmooth distributed parameter systems
Tiba, Dan
1990-01-01
The book is devoted to the study of distributed control problems governed by various nonsmooth state systems. The main questions investigated include: existence of optimal pairs, first order optimality conditions, state-constrained systems, approximation and discretization, bang-bang and regularity properties for optimal control. In order to give the reader a better overview of the domain, several sections deal with topics that do not enter directly into the announced subject: boundary control, delay differential equations. In a subject still actively developing, the methods can be more important than the results and these include: adapted penalization techniques, the singular control systems approach, the variational inequality method, the Ekeland variational principle. Some prerequisites relating to convex analysis, nonlinear operators and partial differential equations are collected in the first chapter or are supplied appropriately in the text. The monograph is intended for graduate students and for resea...
1995-05-01
A HYBRID ANALYTICAL/ SIMULATION MODELING APPROACH FOR PLANNING AND OPTIMIZING MASS TACTICAL AIRBORNE OPERATIONS by DAVID DOUGLAS BRIGGS M.S.B.A...COVERED MAY 1995 TECHNICAL REPORT THESIS 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS A HYBRID ANALYTICAL SIMULATION MODELING APPROACH FOR PLANNING AND...are present. Thus, simulation modeling presents itself as an excellent alternate tool for planning because it allows for the modeling of highly complex
A hybrid optimization method for biplanar transverse gradient coil design
Energy Technology Data Exchange (ETDEWEB)
Qi Feng [Key Laboratory for Quantum Information and Measurements, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871 (China); Tang Xin [Beijing Key Laboratory of Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871 (China); Jin Zhe [Key Laboratory for Quantum Information and Measurements, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871 (China); Jiang Zhongde [Beijing Key Laboratory of Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871 (China); Shen Yifei [Key Laboratory for Quantum Information and Measurements, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871 (China); Meng Bin [Key Laboratory for Quantum Information and Measurements, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871 (China); Zu Donglin [Beijing Key Laboratory of Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871 (China); Wang Weimin [Key Laboratory for Quantum Information and Measurements, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871 (China)
2007-05-07
The optimization of transverse gradient coils is one of the fundamental problems in designing magnetic resonance imaging gradient systems. A new approach is presented in this paper to optimize the transverse gradient coils' performance. First, in the traditional spherical harmonic target field method, high order coefficients, which are commonly ignored, are used in the first stage of the optimization process to give better homogeneity. Then, some cosine terms are introduced into the series expansion of stream function. These new terms provide simulated annealing optimization with new freedoms. Comparison between the traditional method and the optimized method shows that the inhomogeneity in the region of interest can be reduced from 5.03% to 1.39%, the coil efficiency increased from 3.83 to 6.31 mT m{sup -1} A{sup -1} and the minimum distance of these discrete coils raised from 1.54 to 3.16 mm.
Hybrid Control Design for a Wheeled Mobile Robot
DEFF Research Database (Denmark)
Bak, Thomas; Bendtsen, Jan Dimon; Ravn, Anders Peter
2003-01-01
We present a hybrid systems solution to the problem of trajectory tracking for a four-wheel steered four-wheel driven mobile robot. The robot is modelled as a non-holonomic dynamic system subject to pure rolling, no-slip constraints. Under normal driving conditions, a nonlinear trajectory trackin....... The stability of the hybrid control scheme is finally analyzed using Lyapunov-like arguments....
Optimum Performance-Based Seismic Design Using a Hybrid Optimization Algorithm
Directory of Open Access Journals (Sweden)
S. Talatahari
2014-01-01
Full Text Available A hybrid optimization method is presented to optimum seismic design of steel frames considering four performance levels. These performance levels are considered to determine the optimum design of structures to reduce the structural cost. A pushover analysis of steel building frameworks subject to equivalent-static earthquake loading is utilized. The algorithm is based on the concepts of the charged system search in which each agent is affected by local and global best positions stored in the charged memory considering the governing laws of electrical physics. Comparison of the results of the hybrid algorithm with those of other metaheuristic algorithms shows the efficiency of the hybrid algorithm.
Optimal performance of constrained control systems
Harvey, P. Scott, Jr.; Gavin, Henri P.; Scruggs, Jeffrey T.
2012-08-01
This paper presents a method to compute optimal open-loop trajectories for systems subject to state and control inequality constraints in which the cost function is quadratic and the state dynamics are linear. For the case in which inequality constraints are decentralized with respect to the controls, optimal Lagrange multipliers enforcing the inequality constraints may be found at any time through Pontryagin’s minimum principle. In so doing, the set of differential algebraic Euler-Lagrange equations is transformed into a nonlinear two-point boundary-value problem for states and costates whose solution meets the necessary conditions for optimality. The optimal performance of inequality constrained control systems is calculable, allowing for comparison to previous, sub-optimal solutions. The method is applied to the control of damping forces in a vibration isolation system subjected to constraints imposed by the physical implementation of a particular controllable damper. An outcome of this study is the best performance achievable given a particular objective, isolation system, and semi-active damper constraints.
Computational Methods for Design, Control and Optimization
2007-10-01
34scenario" that applies to channel flows ( Poiseuille flows , Couette flow ) and pipe flows . Over the past 75 years many complex "transition theories" have...other areas of flow control, optimization and aerodynamic design. approximate sensitivity calculations and optimization codes. The effort was built on a...for fluid flow problems. The improved robustness and computational efficiency of this approach makes it practical for a wide class of problems. The
Institute of Scientific and Technical Information of China (English)
曾育平; 秦大同; 杨官龙; 姚明尧
2015-01-01
为了缩短发动机的冷机工作时间,降低发动机的油耗和排放,以计及发动机冷热效应的燃油消耗最小为目标函数,依据庞特里亚金极小值原理建立了Hamilton函数,对目标泛函进行求解,获得了计及发动机冷热效应的最优控制策略,并将该控制策略分别与CD-CS模式控制策略和忽略发动机冷热效应的最优控制策略进行了比较.研究结果表明:计及发动机冷热效应的最优控制策略与CD-CS模式控制策略相比可使整车百公里油耗降低9.64％;与忽略发动机冷热效应的最优控制策略相比,可使整车百公里油耗降低2.34％,使三元催化器的起燃时间缩短21.3％;该策略可使插电式混合动力汽车具有更好的燃油经济性和排放性.%In order to shorten engine's cold working time and reduce engine's fuel consumption and emission,with the minimum engine fuel consumption considering engine cold effect as objective function,Hamilton function was established based on Pontryagin's minimum principle,and the optimal control strategy considering engine cold effect was obtained after solving the objective function.Then this control strategy was compared with CD-CS mode control strategy and the optimal control strategy without considering engine cold effect respectively.The results show that in contrast to CDCS mode control strategy,the presented optimal control strategy makes fuel consumption per 100 kilometers reduce 9.64％.In contrast to the optimal control strategy without considering engine cold effect,the presented optimal control strategy makes fuel consumption per 100 kilometers reduce 2.34％ and the light-off time of three-way catalytic converter shorten 21.3％.The control strategy makes the plug-in hybrid electric vehicle have better fuel economy and emission performance.
FEEDBACK CONTROL OPTIMIZATION FOR SEISMICALLY EXCITED BUILDINGS
Institute of Scientific and Technical Information of China (English)
Xueping Li; Zuguang Ying
2007-01-01
A feedback control optimization method of partially observable linear structures via stationary response is proposed and analyzed with linear building structures equipped with control devices and sensors. First, the partially observable control problem of the structure under horizontal ground acceleration excitation is converted into a completely observable control problem. Then the It(o) stochastic differential equations of the system are derived based on the stochastic averaging method for quasi-integrable Hamiltonian systems and the stationary solution to the Fokker-Plank-Kolmogorov (FPK) equation associated with the It(o) equations is obtained.The performance index in terms of the mean system energy and mean square control force is established and the optimal control force is obtained by minimizing the performance index. Finally, the numerical results for a three-story building structure model under El Centro, Hachinohe,Northridge and Kobe earthquake excitations are given to illustrate the application and the effectiveness of the proposed method.
Dynamic ATC enhancement through optimal placement of FACTS controllers
Energy Technology Data Exchange (ETDEWEB)
Jain, T. [Department of Electrical Engineering, Madhav Institute of Technology and Science, Race Course Road, Gwalior 474005 (India); Singh, S.N.; Srivastava, S.C. [Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India)
2009-11-15
Flexible AC Transmission System (FACTS) controllers offer an effective means to enhance the power transfer capability of the network. However, the extent to which a FACTS controller can enhance Available Transfer Capability (ATC) depends on its optimal location in the system. This paper has proposed sensitivity analysis of structure preserving energy margin with respect to the control parameters of FACTS controllers for their optimal placement in the network. Two types of FACTS controllers, viz. Static Synchronous Compensator (STATCOM) and Unified Power Flow Controllers (UPFC) have been considered. The hybrid approach, combining a structure preserving and a time domain simulation method, has been utilized to compute the dynamic ATC in presence of these controllers and their impact on dynamic ATC has been analyzed. The potential energy, contributed by the STATCOM and the UPFC, has also been included in the structure preserving energy function to include their influence on transient stability. The proposed method has been tested on 39-bus New England system and a practical 246-bus Indian system. (author)
Viability of Hybrid Systems A Controllability Operator Approach
Labinaz, G
2012-01-01
The problem of viability of hybrid systems is considered in this work. A model for a hybrid system is developed including a means of including three forms of uncertainty: transition dynamics, structural uncertainty, and parametric uncertainty. A computational basis for viability of hybrid systems is developed and applied to three control law classes. An approach is developed for robust viability based on two extensions of the controllability operator. The three-tank example is examined for both the viability problem and robust viability problem. The theory is applied through simulation to an active magnetic bearing system and to a batch polymerization process showing that viability can be satisfied in practice. The problem of viable attainability is examined based on the controllability operator approach introduced by Nerode and colleagues. Lastly, properties of the controllability operator are presented.
Viewing hybrid systems as products of control systems and automata
Grossman, R. L.; Larson, R. G.
1992-01-01
The purpose of this note is to show how hybrid systems may be modeled as products of nonlinear control systems and finite state automata. By a hybrid system, we mean a network of consisting of continuous, nonlinear control system connected to discrete, finite state automata. Our point of view is that the automata switches between the control systems, and that this switching is a function of the discrete input symbols or letters that it receives. We show how a nonlinear control system may be viewed as a pair consisting of a bialgebra of operators coding the dynamics, and an algebra of observations coding the state space. We also show that a finite automata has a similar representation. A hybrid system is then modeled by taking suitable products of the bialgebras coding the dynamics and the observation algebras coding the state spaces.
Energy-Efficient Building HVAC Control Using Hybrid System LBMPC
Aswani, Anil; Taneja, Jay; Krioukov, Andrew; Culler, David; Tomlin, Claire
2012-01-01
Improving the energy-efficiency of heating, ventilation, and air-conditioning (HVAC) systems has the potential to realize large economic and societal benefits. This paper concerns the system identification of a hybrid system model of a building-wide HVAC system and its subsequent control using a hybrid system formulation of learning-based model predictive control (LBMPC). Here, the learning refers to model updates to the hybrid system model that incorporate the heating effects due to occupancy, solar effects, outside air temperature (OAT), and equipment, in addition to integrator dynamics inherently present in low-level control. Though we make significant modeling simplifications, our corresponding controller that uses this model is able to experimentally achieve a large reduction in energy usage without any degradations in occupant comfort. It is in this way that we justify the modeling simplifications that we have made. We conclude by presenting results from experiments on our building HVAC testbed, which s...
NASA Workshop on Hybrid (Mixed-Actuator) Spacecraft Attitude Control
Dennehy, Cornelius J.; Kunz, Nans
2014-01-01
At the request of the Science Mission Directorate Chief Engineer, the NASA Technical Fellow for Guidance, Navigation & Control assembled and facilitated a workshop on Spacecraft Hybrid Attitude Control. This multi-Center, academic, and industry workshop, sponsored by the NASA Engineering and Safety Center (NESC), was held in April 2013 to unite nationwide experts to present and discuss the various innovative solutions, techniques, and lessons learned regarding the development and implementation of the various hybrid attitude control system solutions investigated or implemented. This report attempts to document these key lessons learned with the 16 findings and 9 NESC recommendations.
Hybrid Control Design for a Wheeled Mobile Robot
DEFF Research Database (Denmark)
Bak, Thomas; Bendtsen, Jan Dimon; Ravn, Anders Peter
2003-01-01
We present a hybrid systems solution to the problem of trajectory tracking for a four-wheel steered four-wheel driven mobile robot. The robot is modelled as a non-holonomic dynamic system subject to pure rolling, no-slip constraints. Under normal driving conditions, a nonlinear trajectory tracking...... feedback control law based on dynamic feedback linearization is sufficient to stabilize the system and ensure asymptotically stable tracking. Transitions to other modes are derived systematically from this model, whenever the configuration space of the controlled system has some fundamental singular points....... The stability of the hybrid control scheme is finally analyzed using Lyapunov-like arguments....
Fuzzy portfolio optimization advances in hybrid multi-criteria methodologies
Gupta, Pankaj; Inuiguchi, Masahiro; Chandra, Suresh
2014-01-01
This monograph presents a comprehensive study of portfolio optimization, an important area of quantitative finance. Considering that the information available in financial markets is incomplete and that the markets are affected by vagueness and ambiguity, the monograph deals with fuzzy portfolio optimization models. At first, the book makes the reader familiar with basic concepts, including the classical mean–variance portfolio analysis. Then, it introduces advanced optimization techniques and applies them for the development of various multi-criteria portfolio optimization models in an uncertain environment. The models are developed considering both the financial and non-financial criteria of investment decision making, and the inputs from the investment experts. The utility of these models in practice is then demonstrated using numerical illustrations based on real-world data, which were collected from one of the premier stock exchanges in India. The book addresses both academics and professionals pursuin...
Multimodel methods for optimal control of aeroacoustics.
Energy Technology Data Exchange (ETDEWEB)
Chen, Guoquan (Rice University, Houston, TX); Collis, Samuel Scott
2005-01-01
A new multidomain/multiphysics computational framework for optimal control of aeroacoustic noise has been developed based on a near-field compressible Navier-Stokes solver coupled with a far-field linearized Euler solver both based on a discontinuous Galerkin formulation. In this approach, the coupling of near- and far-field domains is achieved by weakly enforcing continuity of normal fluxes across a coupling surface that encloses all nonlinearities and noise sources. For optimal control, gradient information is obtained by the solution of an appropriate adjoint problem that involves the propagation of adjoint information from the far-field to the near-field. This computational framework has been successfully applied to study optimal boundary-control of blade-vortex interaction, which is a significant noise source for helicopters on approach to landing. In the model-problem presented here, the noise propagated toward the ground is reduced by 12dB.
Optimal control applications in electric power systems
Christensen, G S; Soliman, S A
1987-01-01
Significant advances in the field of optimal control have been made over the past few decades. These advances have been well documented in numerous fine publications, and have motivated a number of innovations in electric power system engineering, but they have not yet been collected in book form. Our purpose in writing this book is to provide a description of some of the applications of optimal control techniques to practical power system problems. The book is designed for advanced undergraduate courses in electric power systems, as well as graduate courses in electrical engineering, applied mathematics, and industrial engineering. It is also intended as a self-study aid for practicing personnel involved in the planning and operation of electric power systems for utilities, manufacturers, and consulting and government regulatory agencies. The book consists of seven chapters. It begins with an introductory chapter that briefly reviews the history of optimal control and its power system applications and also p...
2016 Network Games, Control, and Optimization Conference
Jimenez, Tania; Solan, Eilon
2017-01-01
This contributed volume offers a collection of papers presented at the 2016 Network Games, Control, and Optimization conference (NETGCOOP), held at the University of Avignon in France, November 23-25, 2016. These papers highlight the increasing importance of network control and optimization in many networking application domains, such as mobile and fixed access networks, computer networks, social networks, transportation networks, and, more recently, electricity grids and biological networks. Covering a wide variety of both theoretical and applied topics in the areas listed above, the authors explore several conceptual and algorithmic tools that are needed for efficient and robust control operation, performance optimization, and better understanding the relationships between entities that may be acting cooperatively or selfishly in uncertain and possibly adversarial environments. As such, this volume will be of interest to applied mathematicians, computer scientists, engineers, and researchers in other relate...
Fang, Jiancheng; Wang, Tao; Zhang, Hong; Li, Yang; Zou, Sheng
2014-12-01
The hybrid optical pumping atomic magnetometers have not realized its theoretical sensitivity, the optimization is critical for optimal performance. The optimizations proposed in this paper are suitable for hybrid optical pumping atomic magnetometer, which contains two alkali species. To optimize the parameters, the dynamic equations of spin evolution with two alkali species were solved, whose steady-state solution is used to optimize the parameters. The demand of the power of the pump beam is large for hybrid optical pumping. Moreover, the sensitivity of the hybrid optical pumping magnetometer increases with the increase of the power density of the pump beam. The density ratio between the two alkali species is especially important for hybrid optical pumping magnetometer. A simple expression for optimizing the density ratio is proposed in this paper, which can help to determine the mole faction of the alkali atoms in fabricating the hybrid cell before the cell is sealed. The spin-exchange rate between the two alkali species is proportional to the saturated density of the alkali vapor, which is highly dependent on the temperature of the cell. Consequently, the sensitivity of the hybrid optical pumping magnetometer is dependent on the temperature of the cell. We proposed the thermal optimization of the hybrid cell for a hybrid optical pumping magnetometer, which can improve the sensitivity especially when the power of the pump beam is low. With these optimizations, a sensitivity of approximately 5 fT/Hz(1/2) is achieved with gradiometer arrangement.
Hybrid-impulsive second order sliding mode control: Lyapunov approach
Shtessel, Y.; Glumineau, A.; Plestan, F.; Weiss, M.
2013-01-01
A perturbed nonlinear system of relative degree two controlled by discontinuous-impulsive feedbacks is studied. The hybrid-impulsive terms serve to drive instantaneously the system trajectories to the origin or to its small vicinity. In particular, impulsive-twisting control exhibits an uniform exac
Spontaneous emission control in a tunable hybrid photonic system
Frimmer, M.; Koenderink, A.F.
2013-01-01
We experimentally demonstrate control of the rate of spontaneous emission in a tunable hybrid photonic system that consists of two canonical building blocks for spontaneous emission control, an optical antenna and a mirror, each providing a modification of the local density of optical states (LDOS).
Hybrid-impulsive second order sliding mode control: Lyapunov approach
Shtessel, Y.; Glumineau, A.; Plestan, F.; Weiss, M.
2013-01-01
A perturbed nonlinear system of relative degree two controlled by discontinuous-impulsive feedbacks is studied. The hybrid-impulsive terms serve to drive instantaneously the system trajectories to the origin or to its small vicinity. In particular, impulsive-twisting control exhibits an uniform
Route-Based Control of Hybrid Electric Vehicles: Preprint
Energy Technology Data Exchange (ETDEWEB)
Gonder, J. D.
2008-01-01
Today's hybrid electric vehicle controls cannot always provide maximum fuel savings over all drive cycles. Route-based controls could improve HEV fuel efficiency by 2%-4% and help save nearly 6.5 million gallons of fuel annually.
Stochastic Optimal Control Models for Online Stores
Bradonjić, Milan
2011-01-01
We present a model for the optimal design of an online auction/store by a seller. The framework we use is a stochastic optimal control problem. In our setting, the seller wishes to maximize her average wealth level, where she can control her price per unit via her reputation level. The corresponding Hamilton-Jacobi-Bellmann equation is analyzed for an introductory case. We then turn to an empirically justified model, and present introductory analysis. In both cases, {\\em pulsing} advertising strategies are recovered for resource allocation. Further numerical and functional analysis will appear shortly.
Igeta, Hideki; Hasegawa, Mikio
Chaotic dynamics have been effectively applied to improve various heuristic algorithms for combinatorial optimization problems in many studies. Currently, the most used chaotic optimization scheme is to drive heuristic solution search algorithms applicable to large-scale problems by chaotic neurodynamics including the tabu effect of the tabu search. Alternatively, meta-heuristic algorithms are used for combinatorial optimization by combining a neighboring solution search algorithm, such as tabu, gradient, or other search method, with a global search algorithm, such as genetic algorithms (GA), ant colony optimization (ACO), or others. In these hybrid approaches, the ACO has effectively optimized the solution of many benchmark problems in the quadratic assignment problem library. In this paper, we propose a novel hybrid method that combines the effective chaotic search algorithm that has better performance than the tabu search and global search algorithms such as ACO and GA. Our results show that the proposed chaotic hybrid algorithm has better performance than the conventional chaotic search and conventional hybrid algorithms. In addition, we show that chaotic search algorithm combined with ACO has better performance than when combined with GA.
Optimal control application to an Ebola model
Institute of Scientific and Technical Information of China (English)
Ebenezer Bonyah; Kingsley Badu; Samuel Kwesi Asiedu-Addo
2016-01-01
Ebola virus is a severe,frequently fatal illness,with a case fatality rate up to 90%.The outbreak of the disease has been acknowledged by World Health Organization as Public Health Emergency of International Concern.The threat of Ebola in West Africa is still a major setback to the socioeconomic development.Optimal control theory is applied to a system of ordinary differential equations which is modeling Ebola infection through three different routes including contact between humans and a dead body.In an attempt to reduce infection in susceptible population,a preventive control is put in the form of education and campaign and two treatment controls are applied to infected and late-stage infected(super) human population.The Pontryagins maximum principle is employed to characterize optimality control,which is then solved numerically.It is observed that time optimal control is existed in the model.The activation of each control showed a positive reduction of infection.The overall effect of activation of all the controls simultaneously reduced the effort required for the reduction of the infection quickly.The obtained results present a good framework for planning and designing cost-effective strategies for good interventions in dealing with Ebola disease.It is established that in order to reduce Ebola threat all the three controls must be taken into consideration concurrently.
OPTIMAL CONTROL ALGORITHMS FOR SECOND ORDER SYSTEMS
Directory of Open Access Journals (Sweden)
Danilo Pelusi
2013-01-01
Full Text Available Proportional Integral Derivative (PID controllers are widely used in industrial processes for their simplicity and robustness. The main application problems are the tuning of PID parameters to obtain good settling time, rise time and overshoot. The challenge is to improve the timing parameters to achieve optimal control performances. Remarkable findings are obtained through the use of Artificial Intelligence techniques as Fuzzy Logic, Genetic Algorithms and Neural Networks. The combination of these theories can give good results in terms of settling time, rise time and overshoot. In this study, suitable controllers able of improving timing performance of second order plants are proposed. The results show that the PID controller has good overshoot values and shows optimal robustness. The genetic-fuzzy controller gives a good value of settling time and a very good overshoot value. The neural-fuzzy controller gives the best timing parameters improving the control performances of the others two approaches. Further improvements are achieved designing a real-time optimization algorithm which works on a genetic-neuro-fuzzy controller.
Modeling and control of a hybrid-electric vehicle for drivability and fuel economy improvements
Koprubasi, Kerem
The gradual decline of oil reserves and the increasing demand for energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall tank-to-wheel vehicle energy conversion efficiencies is the hybridization of electrical and conventional drive systems. Sophisticated hybrid powertrain configurations require careful coordination of the actuators and the onboard energy sources for optimum use of the energy saving benefits. The term optimality is often associated with fuel economy, although other measures such as drivability and exhaust emissions are also equally important. This dissertation focuses on the design of hybrid-electric vehicle (HEV) control strategies that aim to minimize fuel consumption while maintaining good vehicle drivability. In order to facilitate the design of controllers based on mathematical models of the HEV system, a dynamic model that is capable of predicting longitudinal vehicle responses in the low-to-mid frequency region (up to 10 Hz) is developed for a parallel HEV configuration. The model is validated using experimental data from various driving modes including electric only, engine only and hybrid. The high fidelity of the model makes it possible to accurately identify critical drivability issues such as time lags, shunt, shuffle, torque holes and hesitation. Using the information derived from the vehicle model, an energy management strategy is developed and implemented on a test vehicle. The resulting control strategy has a hybrid structure in the sense that the main mode of operation (the hybrid mode) is occasionally interrupted by event-based rules to enable the use of the engine start-stop function. The changes in the driveline dynamics during this transition further contribute to the hybrid nature of the system. To address the unique characteristics of the HEV
A hybrid nonlinear programming method for design optimization
Rajan, S. D.
1986-01-01
Solutions to engineering design problems formulated as nonlinear programming (NLP) problems usually require the use of more than one optimization technique. Moreover, the interaction between the user (analysis/synthesis) program and the NLP system can lead to interface, scaling, or convergence problems. An NLP solution system is presented that seeks to solve these problems by providing a programming system to ease the user-system interface. A simple set of rules is used to select an optimization technique or to switch from one technique to another in an attempt to detect, diagnose, and solve some potential problems. Numerical examples involving finite element based optimal design of space trusses and rotor bearing systems are used to illustrate the applicability of the proposed methodology.
Directory of Open Access Journals (Sweden)
Alireza Khosravi
2012-03-01
Full Text Available This paper deals with the design of optimal backstepping controller, by using the chaotic particle swarm optimization (CPSO algorithm to control of chaos in Lure like chaotic system. The backstepping method consists of parameters which could have positive values. The parameters are usually chosen optional by trial and error method. The controlled system provides different behaviors for different values of the parameters. It is necessary to select proper parameters to obtain a good response, because the improper selection of the parameters leads to inappropriate responses or even may lead to instability of the system. The proposed optimal backstepping controller without trial and error determines the parameters of backstepping controller automatically and intelligently by minimizing the Integral of Time multiplied Absolute Error (ITAE and squared controller output. Finally, the efficiency of the proposed optimal backstepping controller (OBSC is illustrated by implementing the method on the Lure like chaotic system.
Adaptive powertrain control for plugin hybrid electric vehicles
Kedar-Dongarkar, Gurunath; Weslati, Feisel
2013-10-15
A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.
Adaptive powertrain control for plugin hybrid electric vehicles
Energy Technology Data Exchange (ETDEWEB)
Kedar-Dongarkar, Gurunath; Weslati, Feisel
2013-10-15
A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.
A New Chaotic Genetic Hybrid Algorithm and Its Applications in Mechanical Optimization Design
Institute of Scientific and Technical Information of China (English)
WANG Zhong-min; DAI Yi
2010-01-01
A new chaotic genetic hybrid algorithm (CGHA) based on float point coding was put forward in this paper.Firstly, it used chaos optimization to search coarsely and produced a better initial population. Then, a power function carri-er was adopted to improve the ergodicity and the sufficiency of the chaos optimization. Secondly, the genetic algorithm (GA) was used to search finely and guaranteed the population's evolution. To avoid the search being trapped in local minimum, a chaos degenerate mutation operator was designed to make the search converge to a global optimum quickly. Finally, CGHA was used to solve a typical mechanical optimization problem of shear stress checking for a cylinder helix spring.Compared with traditional penalty function method, chaos-Powell hybrid algorithm and standard GA, CGHA shows better performance in solution precision and convergence speed than those of the algorithms. Therefore, CGHA is a new effective way to solve the problems in mechanical optimization design.
Chiadamrong, N.; Piyathanavong, V.
2017-04-01
Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.
Optimal Investment Control of Macroeconomic Systems
Institute of Scientific and Technical Information of China (English)
ZHAO Ke-jie; LIU Chuan-zhe
2006-01-01
Economic growth is always accompanied by economic fluctuation. The target of macroeconomic control is to keep a basic balance of economic growth, accelerate the optimization of economic structures and to lead a rapid, sustainable and healthy development of national economies, in order to propel society forward. In order to realize the above goal, investment control must be regarded as the most important policy for economic stability. Readjustment and control of investment includes not only control of aggregate investment, but also structural control which depends on economic-technology relationships between various industries of a national economy. On the basis of the theory of a generalized system, an optimal investment control model for government has been developed. In order to provide a scientific basis for government to formulate a macroeconomic control policy, the model investigates the balance of total supply and aggregate demand through an adjustment in investment decisions realizes a sustainable and stable growth of the national economy. The optimal investment decision function proposed by this study has a unique and specific expression, high regulating precision and computable characteristics.
Optimal control of anthracnose using mixed strategies.
Fotsa Mbogne, David Jaures; Thron, Christopher
2015-11-01
In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. Copyright © 2015 Elsevier Inc. All rights reserved.
Toward hybrid force/position control for the Cerberus epicardial robot.
Breault, Macauley S; Costanza, Adam D; Wood, Nathan A; Passineau, Michael J; Riviere, Cameron N
2015-01-01
Gene therapies have emerged as a promising treatment for congestive heart failure, yet they lack a method for minimally invasive, uniform delivery. To address this need we developed Cerberus, a minimally invasive parallel wire robot for cardiac interventions. Prior work on Cerberus was limited to controlling the device using only position feedback. In order to ensure safety for both the patient and the device, as well as to improve the performance of the device, this paper presents work on enhancing the existing system with force feedback capabilities. By modeling the statics of the system and developing a tension distribution optimization technique, existing position control schemes were modified to a hybrid force/position controller. Experimental results show that using a hybrid force-position control scheme as opposed to position decreases positioning error by 38%.
Adaptive Hybrid Control of Vehicle Semiactive Suspension Based on Road Profile Estimation
Directory of Open Access Journals (Sweden)
Yechen Qin
2015-01-01
Full Text Available A new road estimation based suspension hybrid control strategy is proposed. Its aim is to adaptively change control gains to improve both ride comfort and road handling with the constraint of rattle space. To achieve this, analytical expressions for ride comfort, road handling, and rattle space with respect to road input are derived based on the hybrid control, and the problem is transformed into a MOOP (Multiobjective Optimization Problem and has been solved by NSGA-II (Nondominated Sorting Genetic Algorithm-II. A new road estimation and classification method, which is based on ANFIS (Adaptive Neurofuzzy Inference System and wavelet transforms, is then presented as a means of detecting the road profile level, and a Kalman filter is designed for observing unknown states. The results of simulations conducted with random road excitation show that the efficiency of the proposed control strategy compares favourably to that of a passive system.
Directory of Open Access Journals (Sweden)
S. Meenakshi Sundaram
2014-04-01
Full Text Available The aim of this research is to evaluate the performance of OLSR using swarm intelligence and HPSO with Gravitational search algorithm to lower the jitter time, data drop and end to end delay and improve the network throughput. Simulation was carried out for multimedia traffic and video streamed network traffic using OPNET Simulator. Routing is exchanging of information from one host to another in a network. Routing forwards packets to destination using an efficient path. Path efficiency is measured through metrics like hop number, traffic and security. Each host node acts as a specialized router in Ad-hoc networks. A table driven proactive routing protocol Optimized Link State Protocol (OLSR has available topology information and routes. OLSR’s efficiency depends on Multipoint relay selection. Various studies were conducted to decrease control traffic overheads through modification of existing OLSR routing protocol and traffic shaping based on packet priority. This study proposes a modification of OLSR using swarm intelligence, Hybrid Particle Swarm Optimization (HPSO using Gravitational Search Algorithm (GSA and evaluation of performance of jitter, end to end delay, data drop and throughput. Simulation was carried out to investigate the proposed method for the network’s multimedia traffic.
Optimal Design of Stochastic Distributed Order Linear SISO Systems Using Hybrid Spectral Method
Directory of Open Access Journals (Sweden)
Pham Luu Trung Duong
2015-01-01
Full Text Available The distributed order concept, which is a parallel connection of fractional order integrals and derivatives taken to the infinitesimal limit in delta order, has been the main focus in many engineering areas recently. On the other hand, there are few numerical methods available for analyzing distributed order systems, particularly under stochastic forcing. This paper proposes a novel numerical scheme for analyzing the behavior of a distributed order linear single input single output control system under random forcing. The method is based on the operational matrix technique to handle stochastic distributed order systems. The existing Monte Carlo, polynomial chaos, and frequency methods were first adapted to the stochastic distributed order system for comparison. Numerical examples were used to illustrate the accuracy and computational efficiency of the proposed method for the analysis of stochastic distributed order systems. The stability of the systems under stochastic perturbations can also be inferred easily from the moment of random output obtained using the proposed method. Based on the hybrid spectral framework, the optimal design was elaborated on by minimizing the suitably defined constrained-optimization problem.
Optimal Control Design with Limited Model Information
Farokhi, F; Johansson, K H
2011-01-01
We introduce the family of limited model information control design methods, which construct controllers by accessing the plant's model in a constrained way, according to a given design graph. We investigate the achievable closed-loop performance of discrete-time linear time-invariant plants under a separable quadratic cost performance measure with structured static state-feedback controllers. We find the optimal control design strategy (in terms of the competitive ratio and domination metrics) when the control designer has access to the local model information and the global interconnection structure of the plant-to-be-controlled. At last, we study the trade-off between the amount of model information exploited by a control design method and the best closed-loop performance (in terms of the competitive ratio) of controllers it can produce.
Application of Hybrid Genetic Algorithm Routine in Optimizing Food and Bioengineering Processes.
Tumuluru, Jaya Shankar; McCulloch, Richard
2016-11-09
Optimization is a crucial step in the analysis of experimental results. Deterministic methods only converge on local optimums and require exponentially more time as dimensionality increases. Stochastic algorithms are capable of efficiently searching the domain space; however convergence is not guaranteed. This article demonstrates the novelty of the hybrid genetic algorithm (HGA), which combines both stochastic and deterministic routines for improved optimization results. The new hybrid genetic algorithm developed is applied to the Ackley benchmark function as well as case studies in food, biofuel, and biotechnology processes. For each case study, the hybrid genetic algorithm found a better optimum candidate than reported by the sources. In the case of food processing, the hybrid genetic algorithm improved the anthocyanin yield by 6.44%. Optimization of bio-oil production using HGA resulted in a 5.06% higher yield. In the enzyme production process, HGA predicted a 0.39% higher xylanase yield. Hybridization of the genetic algorithm with a deterministic algorithm resulted in an improved optimum compared to statistical methods.
Optimization of concrete I-beams using a new hybrid glowworm swarm algorithm
García-Segura,Tatiana; Yepes, Víctor; Martí, José V.; Alcalá,Julián
2014-01-01
In this paper a new hybrid glowworm swarm algorithm (SAGSO) for solving structural optimization problems is presented. The structure proposed to be optimized here is a simply-supported concrete I-beam defined by 20 variables. Eight different concrete mixtures are studied, varying the compressive strength grade and compacting system. The solutions are evaluated following the Spanish Code for structural concrete. The algorithm is applied to two objective functions, namely the embedded CO2 emiss...
2015-01-01
Bankruptcy prediction has been extensively investigated by data mining techniques since it is a critical issue in the accounting and finance field. In this paper, a new hybrid algorithm combining switching particle swarm optimization (SPSO) and support vector machine (SVM) is proposed to solve the bankruptcy prediction problem. In particular, a recently developed SPSO algorithm is exploited to search the optimal parameter values of radial basis function (RBF) kernel of the SVM. The new algori...
Hybrid constraint programming and metaheuristic methods for large scale optimization problems
2011-01-01
This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatori...
Yamamoto, Takeyoshi; Cingoski, Vlatko; Kaneda, Kazufumi; Yamashita, Hideo
1996-01-01
In this paper, a hybrid method for inverse optimization of electromagnetic coils utilizing the multi-transition neural network and the Hopfield neural network is proposed. Due to the discrete character of the neural network, an optimization problem is transformed into a discrete problem through the division of the entire coil area into elemental coils with constant current density. The minimization of the objective function is performed by the multi-transition neural network and the Hopfield ...
Modelling and control of hybrid renewable energy system connected to AC grid
Directory of Open Access Journals (Sweden)
Sami Younsi
2011-12-01
Full Text Available This paper discusses the development of new control and supervision method for the optimum operation of hybrid renewable energy system (HRES connected to AC grid. The hybrid system consists of wind generator (WG, diesel generator (DG, and flywheel energy storage system (FESS. These subsystems are based on permanent magnet synchronous machines (PMSM which are controlled by sliding mode control. A supervisor control is designed to determine the energy transfer type of flywheel energy storage system (charging / discharging / no transfer energy, to take decision on diesel generators ON/OFF status, and to determine the reference powers for these two subsystems. The supervisor inputs are the power requested by AC grid, the power generated by wind generator, and the energy stored in flywheel. The objectives of the control and supervision for hybrid renewable energy system are to satisfy the power requested by AC grid, to manage the energy transfer between hybrid system and AC grid, to optimize the use of wind energy, and to reduce fuel of diesel generator. The system is simulated with Matlab – Simulink software and it gave good results.
Optimally Controlled Flexible Fuel Powertrain System
Energy Technology Data Exchange (ETDEWEB)
Hakan Yilmaz; Mark Christie; Anna Stefanopoulou
2010-12-31
The primary objective of this project was to develop a true Flex Fuel Vehicle capable of running on any blend of ethanol from 0 to 85% with reduced penalty in usable vehicle range. A research and development program, targeting 10% improvement in fuel economy using a direct injection (DI) turbocharged spark ignition engine was conducted. In this project a gasoline-optimized high-technology engine was considered and the hardware and configuration modifications were defined for the engine, fueling system, and air path. Combined with a novel engine control strategy, control software, and calibration this resulted in a highly efficient and clean FFV concept. It was also intended to develop robust detection schemes of the ethanol content in the fuel integrated with adaptive control algorithms for optimized turbocharged direct injection engine combustion. The approach relies heavily on software-based adaptation and optimization striving for minimal modifications to the gasoline-optimized engine hardware system. Our ultimate objective was to develop a compact control methodology that takes advantage of any ethanol-based fuel mixture and not compromise the engine performance under gasoline operation.
An asymptotically optimal nonparametric adaptive controller
Institute of Scientific and Technical Information of China (English)
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.
On Optimal Control of a Brownian Motion.
1982-06-01
barriers. Puterman [9] uses diffusion processes to model production and inventory processes. In both cases they assume the existence of a stationary... Puterman , A diffusion model for a storage system, Logistic, M. Geisler ed., North-Holland 197S. [101 J. Rath, The optimal policy for a controlled
Optimizing discrete control systems with phase limitations
Energy Technology Data Exchange (ETDEWEB)
Shakhverdian, S.B.; Abramian, A.K.
1981-01-01
A new method is proposed for solving discrete problems of optimizing control systems with limitations on the phase coordinates. Results are given from experimental research which demonstrate the need to introduce tangential limitations independent of the method of accounting for the phase limitations.
Efficient evolutionary algorithms for optimal control
López Cruz, I.L.
2002-01-01
If optimal control problems are solved by means of gradient based local search methods, convergence to local solutions is likely. Recently, there has been an increasing interest in the use
Determination of optimal gains for constrained controllers
Energy Technology Data Exchange (ETDEWEB)
Kwan, C.M.; Mestha, L.K.
1993-08-01
In this report, we consider the determination of optimal gains, with respect to a certain performance index, for state feedback controllers where some elements in the gain matrix are constrained to be zero. Two iterative schemes for systematically finding the constrained gain matrix are presented. An example is included to demonstrate the procedures.
Optimization-based controller design for rotorcraft
Tsing, N.-K.; Fan, M. K. H.; Barlow, J.; Tits, A. L.; Tischler, M. B.
1993-01-01
An optimization-based methodology for linear control system design is outlined by considering the design of a controller for a UH-60 rotorcraft in hover. A wide range of design specifications is taken into account: internal stability, decoupling between longitudinal and lateral motions, handling qualities, and rejection of windgusts. These specifications are investigated while taking into account physical limitations in the swashplate displacements and rates of displacement. The methodology crucially relies on user-machine interaction for tradeoff exploration.
Doubly Optimal Secure Multicasting: Hierarchical Hybrid Communication Network : Disaster Relief
Garimella, Rama Murthy; Singhal, Deepti
2011-01-01
Recently, the world has witnessed the increasing occurrence of disasters, some of natural origin and others caused by man. The intensity of the phenomenon that cause such disasters, the frequency in which they occur, the number of people affected and the material damage caused by them have been growing substantially. Disasters are defined as natural, technological, and human-initiated events that disrupt the normal functioning of the economy and society on a large scale. Areas where disasters have occurred bring many dangers to rescue teams and the communication network infrastructure is usually destroyed. To manage these hazards, different wireless technologies can be launched in the area of disaster. This paper discusses the innovative wireless technologies for Disaster Management. Specifically, issues related to the design of Hierarchical Hybrid Communication Network (arising in the communication network for disaster relief) are discussed.