To control complex system's safety effectively,safety control program was supported based on the principles of behavioral science that shapes organizational be- havior,and organizational behavior produced individu...To control complex system's safety effectively,safety control program was supported based on the principles of behavioral science that shapes organizational be- havior,and organizational behavior produced individual behavior.The program can be structured into a model that consists of three modules including individual behavior rectifi- cation,organization behavior diagnosis and model of safety culture.The research result not only reveals the deep cause of complex system accidents but also provides structural descriptions with the accidents cause.展开更多
This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method...This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method, controllers for solving the singular systems optimal control problem are designed. The proposed algorithm can work well when the system model is not exactly known but the input and output data can be measured. The policy iteration of each controller only uses their own states and input information for learning,and do not need to know the whole system dynamics. Simulation results on the New England 10-machine 39-bus test system show the effectiveness of the designed controller.展开更多
In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPS...In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPSO) is implemented to optimize the fuzzy controller parameters in order to decrease the distance error of the cart and summation of the angle errors of the pendulums, simultaneously. The feasibility and efficiency of the proposed Pareto front is assessed in comparison with results reported in literature and obtained from other algorithms.Finally, the Java programming with applets is utilized to simulate the stability of the nonlinear system and explain the internetbased control.展开更多
Dynamic Programming (DP) algorithm is used to find the optimal trajectories under Beijing cycle for the power management of synergic electric system (SES) which is composed of battery and super capacitor. Feasible rul...Dynamic Programming (DP) algorithm is used to find the optimal trajectories under Beijing cycle for the power management of synergic electric system (SES) which is composed of battery and super capacitor. Feasible rules are derived from analyzing the optimal trajectories, and it has the highest contribution to Hybrid Electric Vehicle (HEV). The methods of how to get the best performance is also educed. Using the new Rule-based power management strat-egy adopted from the optimal results, it is easy to demonstrate the effectiveness of the new strategy in further improvement of the fuel economy by the synergic hybrid system.展开更多
In the machining process of large-scale complex curved surface,workers will encounter problems such as empty stroke of tool,collision interference,and overcut or undercut of the workpieces.This paper presents a method...In the machining process of large-scale complex curved surface,workers will encounter problems such as empty stroke of tool,collision interference,and overcut or undercut of the workpieces.This paper presents a method for generating the optimized tool path,compiling and checking the numerical control(NC)program.Taking the bogie frame as an example,the tool paths of all machining surface are optimized by the dynamic programming algorithm,Creo software is utilized to compile the optimized computerized numerical control(CNC)machining program,and VERICUT software is employed to simulate the machining process,optimize the amount of cutting and inspect the machining quality.The method saves the machining time,guarantees the correctness of NC program,and the overall machining efficiency is improved.The method lays a good theoretical and practical foundation for integration of the similar platform.展开更多
With the enlarging scale and intensifying production of livestock and poultry breeding, the environment pollution becomes increasingly prominent in the Dianchi Lake Basin since 1990s. According to the survey of ＂The ...With the enlarging scale and intensifying production of livestock and poultry breeding, the environment pollution becomes increasingly prominent in the Dianchi Lake Basin since 1990s. According to the survey of ＂The First National Census of Pollution Sources＂, occurrence and discharge of pollutants in large-scale livestock and poultry farms in this region were first understood. The pollution characteristics of large-scale live- stock and poultry breeding were also analyzed deeply. On this basis, the significance of pollution control programs for environment protection was investigated from aspects of pollution control policy, technology management and publicity.展开更多
The dynamic research of aircraft environmental control system (ECS) is an important step in the advanced ECS design process. Based on the thermodynamics theory, mathematical models for the dynamic performance simulati...The dynamic research of aircraft environmental control system (ECS) is an important step in the advanced ECS design process. Based on the thermodynamics theory, mathematical models for the dynamic performance simulating of aircraft ECS were set up and an ECS simulation toolbox (ECS_1.0) was created with MATLAB language. It consists of main component modules (ducts, valves, heat exchangers, compressor, turbine, etc.). An aircraft environmental control system computer model was developed to assist engineers with the design and development of ECS dynamic optimization. An example simulating an existing ECS was given which shows the satisfactory effects.展开更多
This paper proposes a Genetic Programming based algorithm that can be used to design optimal controllers. The proposed algorithm will be named a Multiple Basis Function Genetic Programming (MBFGP). Herein, the main id...This paper proposes a Genetic Programming based algorithm that can be used to design optimal controllers. The proposed algorithm will be named a Multiple Basis Function Genetic Programming (MBFGP). Herein, the main ideas concerning the initial population, the tree structure, genetic operations, and other proposed non-genetic operations are discussed in details. An optimization algorithm called numeric constant mutation is embedded to strengthen the search for the optimal solutions. The results of solving the optimal control for linear as well as nonlinear systems show the feasibility and effectiveness of the proposed MBFGP as compared to the optimal solutions which are based on numerical methods. Furthermore, this algorithm enriches the set of suboptimal state feedback controllers to include controllers that have product time-state terms.展开更多
This paper estimates an off-policy integral reinforcement learning（IRL） algorithm to obtain the optimal tracking control of unknown chaotic systems. Off-policy IRL can learn the solution of the HJB equation from the...This paper estimates an off-policy integral reinforcement learning（IRL） algorithm to obtain the optimal tracking control of unknown chaotic systems. Off-policy IRL can learn the solution of the HJB equation from the system data generated by an arbitrary control. Moreover, off-policy IRL can be regarded as a direct learning method, which avoids the identification of system dynamics. In this paper, the performance index function is first given based on the system tracking error and control error. For solving the Hamilton–Jacobi–Bellman（HJB） equation, an off-policy IRL algorithm is proposed.It is proven that the iterative control makes the tracking error system asymptotically stable, and the iterative performance index function is convergent. Simulation study demonstrates the effectiveness of the developed tracking control method.展开更多
In this paper two different control strategies designed to alleviate the response of quasi partially integrable Hamiltonian systems subjected to stochastic excitation are proposed. First, by using the stochastic avera...In this paper two different control strategies designed to alleviate the response of quasi partially integrable Hamiltonian systems subjected to stochastic excitation are proposed. First, by using the stochastic averaging method for quasi partially integrable Hamiltonian systems, an n-DOF controlled quasi partially integrable Hamiltonian system with stochastic excitation is converted into a set of partially averaged It^↑o stochastic differential equations. Then, the dynamical programming equation associated with the partially averaged It^↑o equations is formulated by applying the stochastic dynamical programming principle. In the first control strategy, the optimal control law is derived from the dynamical programming equation and the control constraints without solving the dynamical programming equation. In the second control strategy, the optimal control law is obtained by solving the dynamical programming equation. Finally, both the responses of controlled and uncontrolled systems are predicted through solving the Fokker-Plank-Kolmogorov equation associated with fully averaged It^↑o equations. An example is worked out to illustrate the application and effectiveness of the two proposed control strategies.展开更多
Approximate dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain and nonconvex environments over time.
A strategy is proposed based on the stochastic averaging method for quasi non- integrable Hamiltonian systems and the stochastic dynamical programming principle.The pro- posed strategy can be used to design nonlinear ...A strategy is proposed based on the stochastic averaging method for quasi non- integrable Hamiltonian systems and the stochastic dynamical programming principle.The pro- posed strategy can be used to design nonlinear stochastic optimal control to minimize the response of quasi non-integrable Hamiltonian systems subject to Gaussian white noise excitation.By using the stochastic averaging method for quasi non-integrable Hamiltonian systems the equations of motion of a controlled quasi non-integrable Hamiltonian system is reduced to a one-dimensional av- eraged It stochastic differential equation.By using the stochastic dynamical programming princi- ple the dynamical programming equation for minimizing the response of the system is formulated. The optimal control law is derived from the dynamical programming equation and the bounded control constraints.The response of optimally controlled systems is predicted through solving the FPK equation associated with It stochastic differential equation.An example is worked out in detail to illustrate the application of the control strategy proposed.展开更多
The optimal bounded control of stochastic-excited systems with Duhem hysteretic components for maximizing system reliability is investigated. The Duhem hysteretic force is transformed to energy-depending damping and s...The optimal bounded control of stochastic-excited systems with Duhem hysteretic components for maximizing system reliability is investigated. The Duhem hysteretic force is transformed to energy-depending damping and stiffness by the energy dissipation balance technique. The controlled system is transformed to the equivalent non- hysteretic system. Stochastic averaging is then implemented to obtain the It5 stochastic equation associated with the total energy of the vibrating system, appropriate for eval- uating system responses. Dynamical programming equations for maximizing system re- liability are formulated by the dynamical programming principle. The optimal bounded control is derived from the maximization condition in the dynamical programming equation. Finally, the conditional reliability function and mean time of first-passage failure of the optimal Duhem systems are numerically solved from the Kolmogorov equations. The proposed procedure is illustrated with a representative example.展开更多
The design of a wireless water level control system is introduced and discussed in detail. In this system, the wireless Proportional Integral (PI) controller is developed using the LabVIEW graphical user programming l...The design of a wireless water level control system is introduced and discussed in detail. In this system, the wireless Proportional Integral (PI) controller is developed using the LabVIEW graphical user programming language. Zigbee wireless technology is chosen for the wireless data transfer system. The experimental testbed was built and the system software and hardware were implemented. In order to compare the performance of the wired and wireless system, a corresponding wired water level control system was built. Experimental results show that under the same PI parameters, the settling time of the wired system is 3.3 times faster than the wireless system. However, the percent overshoot using the wireless controller is 4% smaller.展开更多
In this paper, an optimal tracking control scheme is proposed for a class of discrete-time chaotic systems using the approximation-error-based adaptive dynamic programming （ADP） algorithm. Via the system transformat...In this paper, an optimal tracking control scheme is proposed for a class of discrete-time chaotic systems using the approximation-error-based adaptive dynamic programming （ADP） algorithm. Via the system transformation, the optimal tracking problem is transformed into an optimal regulation problem, and then the novel optimal tracking control method is proposed. It is shown that for the iterative ADP algorithm with finite approximation error, the iterative performance index functions can converge to a finite neighborhood of the greatest lower bound of all performance index functions under some convergence conditions. Two examples are given to demonstrate the validity of the proposed optimal tracking control scheme for chaotic systems.展开更多
The control system of HLS (Hefei Light Source) is based on EPICS.The control data is held in a distributed dittabase, which resides in several IOCs. An EPICS tool, AR, is used to archive the control data. A data manag...The control system of HLS (Hefei Light Source) is based on EPICS.The control data is held in a distributed dittabase, which resides in several IOCs. An EPICS tool, AR, is used to archive the control data. A data management system isdeveloped to managc the archiv ed data. A number of CGI prograrns make it easy to access the data via WWW, and the programs also provide several functions foranalyzing the data. The results can be displayed in various modes.展开更多
基金Supported by National High Technology Research and Development Program of China （863 Program） （2006AA04Z183）, National Nat- ural Science Foundation of China （60621001, 60534010, 60572070, 60774048, 60728307）, and the Program for Changjiang Scholars and Innovative Research Groups of China （60728307, 4031002）
文摘To control complex system's safety effectively,safety control program was supported based on the principles of behavioral science that shapes organizational be- havior,and organizational behavior produced individual behavior.The program can be structured into a model that consists of three modules including individual behavior rectifi- cation,organization behavior diagnosis and model of safety culture.The research result not only reveals the deep cause of complex system accidents but also provides structural descriptions with the accidents cause.
基金supported in part by the National Natural Science Foundation of China(61473070,61433004,61627809)SAPI Fundamental Research Funds(2018ZCX22)
文摘This paper presents a new design approach to achieve decentralized optimal control of high-dimension complex singular systems with dynamic uncertainties. Based on robust adaptive dynamic programming(robust ADP) method, controllers for solving the singular systems optimal control problem are designed. The proposed algorithm can work well when the system model is not exactly known but the input and output data can be measured. The policy iteration of each controller only uses their own states and input information for learning,and do not need to know the whole system dynamics. Simulation results on the New England 10-machine 39-bus test system show the effectiveness of the designed controller.
文摘In this paper, at first, the single input rule modules(SIRMs) dynamically connected fuzzy inference model is used to stabilize a double inverted pendulum system. Then, a multiobjective particle swarm optimization(MOPSO) is implemented to optimize the fuzzy controller parameters in order to decrease the distance error of the cart and summation of the angle errors of the pendulums, simultaneously. The feasibility and efficiency of the proposed Pareto front is assessed in comparison with results reported in literature and obtained from other algorithms.Finally, the Java programming with applets is utilized to simulate the stability of the nonlinear system and explain the internetbased control.
文摘Dynamic Programming (DP) algorithm is used to find the optimal trajectories under Beijing cycle for the power management of synergic electric system (SES) which is composed of battery and super capacitor. Feasible rules are derived from analyzing the optimal trajectories, and it has the highest contribution to Hybrid Electric Vehicle (HEV). The methods of how to get the best performance is also educed. Using the new Rule-based power management strat-egy adopted from the optimal results, it is easy to demonstrate the effectiveness of the new strategy in further improvement of the fuel economy by the synergic hybrid system.
基金supported by the Collaborative Innovation Center of Ma jor Machine Manufacturing in Liaoning
文摘In the machining process of large-scale complex curved surface,workers will encounter problems such as empty stroke of tool,collision interference,and overcut or undercut of the workpieces.This paper presents a method for generating the optimized tool path,compiling and checking the numerical control(NC)program.Taking the bogie frame as an example,the tool paths of all machining surface are optimized by the dynamic programming algorithm,Creo software is utilized to compile the optimized computerized numerical control(CNC)machining program,and VERICUT software is employed to simulate the machining process,optimize the amount of cutting and inspect the machining quality.The method saves the machining time,guarantees the correctness of NC program,and the overall machining efficiency is improved.The method lays a good theoretical and practical foundation for integration of the similar platform.
基金funded by the National Water Pollution Control and Management Technology Major Projects (2008ZX07102)
文摘With the enlarging scale and intensifying production of livestock and poultry breeding, the environment pollution becomes increasingly prominent in the Dianchi Lake Basin since 1990s. According to the survey of ＂The First National Census of Pollution Sources＂, occurrence and discharge of pollutants in large-scale livestock and poultry farms in this region were first understood. The pollution characteristics of large-scale live- stock and poultry breeding were also analyzed deeply. On this basis, the significance of pollution control programs for environment protection was investigated from aspects of pollution control policy, technology management and publicity.
文摘The dynamic research of aircraft environmental control system (ECS) is an important step in the advanced ECS design process. Based on the thermodynamics theory, mathematical models for the dynamic performance simulating of aircraft ECS were set up and an ECS simulation toolbox (ECS_1.0) was created with MATLAB language. It consists of main component modules (ducts, valves, heat exchangers, compressor, turbine, etc.). An aircraft environmental control system computer model was developed to assist engineers with the design and development of ECS dynamic optimization. An example simulating an existing ECS was given which shows the satisfactory effects.
文摘This paper proposes a Genetic Programming based algorithm that can be used to design optimal controllers. The proposed algorithm will be named a Multiple Basis Function Genetic Programming (MBFGP). Herein, the main ideas concerning the initial population, the tree structure, genetic operations, and other proposed non-genetic operations are discussed in details. An optimization algorithm called numeric constant mutation is embedded to strengthen the search for the optimal solutions. The results of solving the optimal control for linear as well as nonlinear systems show the feasibility and effectiveness of the proposed MBFGP as compared to the optimal solutions which are based on numerical methods. Furthermore, this algorithm enriches the set of suboptimal state feedback controllers to include controllers that have product time-state terms.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61304079 and 61374105)the Beijing Natural Science Foundation,China(Grant Nos.4132078 and 4143065)+2 种基金the China Postdoctoral Science Foundation(Grant No.2013M530527)the Fundamental Research Funds for the Central Universities,China(Grant No.FRF-TP-14-119A2)the Open Research Project from State Key Laboratory of Management and Control for Complex Systems,China(Grant No.20150104)
文摘This paper estimates an off-policy integral reinforcement learning（IRL） algorithm to obtain the optimal tracking control of unknown chaotic systems. Off-policy IRL can learn the solution of the HJB equation from the system data generated by an arbitrary control. Moreover, off-policy IRL can be regarded as a direct learning method, which avoids the identification of system dynamics. In this paper, the performance index function is first given based on the system tracking error and control error. For solving the Hamilton–Jacobi–Bellman（HJB） equation, an off-policy IRL algorithm is proposed.It is proven that the iterative control makes the tracking error system asymptotically stable, and the iterative performance index function is convergent. Simulation study demonstrates the effectiveness of the developed tracking control method.
基金The project supported by the National Natural Science Foundation of China (10332030)Research Fund for Doctoral Program of Higher Education of China(20060335125)
文摘In this paper two different control strategies designed to alleviate the response of quasi partially integrable Hamiltonian systems subjected to stochastic excitation are proposed. First, by using the stochastic averaging method for quasi partially integrable Hamiltonian systems, an n-DOF controlled quasi partially integrable Hamiltonian system with stochastic excitation is converted into a set of partially averaged It^↑o stochastic differential equations. Then, the dynamical programming equation associated with the partially averaged It^↑o equations is formulated by applying the stochastic dynamical programming principle. In the first control strategy, the optimal control law is derived from the dynamical programming equation and the control constraints without solving the dynamical programming equation. In the second control strategy, the optimal control law is obtained by solving the dynamical programming equation. Finally, both the responses of controlled and uncontrolled systems are predicted through solving the Fokker-Plank-Kolmogorov equation associated with fully averaged It^↑o equations. An example is worked out to illustrate the application and effectiveness of the two proposed control strategies.
文摘Approximate dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain and nonconvex environments over time.
基金Project supported by the National Natural Science Foundation of China(No.19972059).
文摘A strategy is proposed based on the stochastic averaging method for quasi non- integrable Hamiltonian systems and the stochastic dynamical programming principle.The pro- posed strategy can be used to design nonlinear stochastic optimal control to minimize the response of quasi non-integrable Hamiltonian systems subject to Gaussian white noise excitation.By using the stochastic averaging method for quasi non-integrable Hamiltonian systems the equations of motion of a controlled quasi non-integrable Hamiltonian system is reduced to a one-dimensional av- eraged It stochastic differential equation.By using the stochastic dynamical programming princi- ple the dynamical programming equation for minimizing the response of the system is formulated. The optimal control law is derived from the dynamical programming equation and the bounded control constraints.The response of optimally controlled systems is predicted through solving the FPK equation associated with It stochastic differential equation.An example is worked out in detail to illustrate the application of the control strategy proposed.
基金supported by the National Natural Science Foundation of China(Nos.11202181 and11402258)the Special Fund for the Doctoral Program of Higher Education of China(No.20120101120171)
文摘The optimal bounded control of stochastic-excited systems with Duhem hysteretic components for maximizing system reliability is investigated. The Duhem hysteretic force is transformed to energy-depending damping and stiffness by the energy dissipation balance technique. The controlled system is transformed to the equivalent non- hysteretic system. Stochastic averaging is then implemented to obtain the It5 stochastic equation associated with the total energy of the vibrating system, appropriate for eval- uating system responses. Dynamical programming equations for maximizing system re- liability are formulated by the dynamical programming principle. The optimal bounded control is derived from the maximization condition in the dynamical programming equation. Finally, the conditional reliability function and mean time of first-passage failure of the optimal Duhem systems are numerically solved from the Kolmogorov equations. The proposed procedure is illustrated with a representative example.
文摘The design of a wireless water level control system is introduced and discussed in detail. In this system, the wireless Proportional Integral (PI) controller is developed using the LabVIEW graphical user programming language. Zigbee wireless technology is chosen for the wireless data transfer system. The experimental testbed was built and the system software and hardware were implemented. In order to compare the performance of the wired and wireless system, a corresponding wired water level control system was built. Experimental results show that under the same PI parameters, the settling time of the wired system is 3.3 times faster than the wireless system. However, the percent overshoot using the wireless controller is 4% smaller.
基金supported by the Open Research Project from SKLMCCS (Grant No. 20120106)the Fundamental Research Funds for the Central Universities of China (Grant No. FRF-TP-13-018A)+1 种基金the Postdoctoral Science Foundation of China (Grant No. 2013M530527)the National Natural Science Foundation of China (Grant Nos. 61304079, 61125306, and 61034002)
文摘In this paper, an optimal tracking control scheme is proposed for a class of discrete-time chaotic systems using the approximation-error-based adaptive dynamic programming （ADP） algorithm. Via the system transformation, the optimal tracking problem is transformed into an optimal regulation problem, and then the novel optimal tracking control method is proposed. It is shown that for the iterative ADP algorithm with finite approximation error, the iterative performance index functions can converge to a finite neighborhood of the greatest lower bound of all performance index functions under some convergence conditions. Two examples are given to demonstrate the validity of the proposed optimal tracking control scheme for chaotic systems.
文摘The control system of HLS (Hefei Light Source) is based on EPICS.The control data is held in a distributed dittabase, which resides in several IOCs. An EPICS tool, AR, is used to archive the control data. A data management system isdeveloped to managc the archiv ed data. A number of CGI prograrns make it easy to access the data via WWW, and the programs also provide several functions foranalyzing the data. The results can be displayed in various modes.
