Toric patch is a kind of rational multisided patch,which is associated with a finite integer lattice points set A.A set of weights is defined which depend on a parameter according to regular decomposition of A.When al...Toric patch is a kind of rational multisided patch,which is associated with a finite integer lattice points set A.A set of weights is defined which depend on a parameter according to regular decomposition of A.When all weights of the patch tend to infinity,we obtain the limiting form of toric patch which is called its regular control surface.The diferent weights may induce the diferent regular control surfaces of the same toric patch.It prompts us to consider that how many regular control surfaces of a toric patch.In this paper,we study the regular decompositions of A by using integer programming method firstly,and then provide the relationship between all regular decompositions of A and corresponding state polytope.Moreover,we present that the number of regular control surfaces of a toric patch associated with A is equal to the number of regular decompositions of A.An algorithm to calculate the number of regular control surfaces of toric patch is provided.The algorithm also presents a method to construct all of the regular control surfaces of a toric patch.At last,the application of proposed result in shape deformation is demonstrated by several examples.展开更多
Background Both medication and non-medication therapies are effective approaches to control blood pressure (BP) in hypertension patients.However,the association of joint changes in antihypertensive medication use and ...Background Both medication and non-medication therapies are effective approaches to control blood pressure (BP) in hypertension patients.However,the association of joint changes in antihypertensive medication use and healthy lifestyle index (HLI)with BP control among hypertension patients is seldom reported,which needs to provide more evidence by prospective intervention studies.We examined the association of antihypertensive medication use and HLI with BP control among employees with hypertension in China based on a workplace-based multicomponent intervention program.Methods Between January 2013 and December 2014,a cluster randomized clinical trial of a workplace-based multicomponent intervention program was conducted in 60 workplaces across 20 urban areas in China.Workplaces were randomly divided into intervention (n=40) and control (n=20) groups.Basic information on employees at each workplace was collected by trained professionals,including sociodemographic characteristics,medical history,family history,lifestyle behaviors,medication status and physical measurements.After baseline,the intervention group received a 2-year intervention to achieve BP control,which included:(1) a workplace wellness program for all employees;(2) a guidelines-oriented hypertension management protocol.HLI including nonsmoking,nondrinking,adequate physical activity,weight within reference range and balanced diet,were coded on a 5-point scale (range:0-5,with higher score indicating a healthier lifestyle).Antihypertensive medication use was defined as taking drug within the last 2 weeks.Changes in HLI,antihypertensive medication use and BP control from baseline to 24 months were measured after the intervention.Results Overall,4655 employees were included (age:46.3±7.6 years,men:3547 (82.3%)).After 24 months of the intervention,there was a significant improvement in lifestyle[smoking (OR=0.65,95%CI:0.43-0.99;P=0.045),drinking (OR=0.52,95%CI:0.40-0.68;P<0.001),regular exercise (OR=3.10,95%CI:2.53-3.78;P<0.001),excessive intake of fatty food (OR=0.17,95%CI:0.06-0.52;P=0.002),restrictive use of salt (OR=0.26,95%CI:0.12-0.56;P=0.001)].Compare to employees with a deteriorating lifestyle after the intervention,those with an improved lifestyle had a higher BP control.In the intervention group,compared with employees not using antihypertensive medication,those who consistent used (OR=2.34;95%CI:1.16-4.72;P=0.017) or changed from not using to using antihypertensive medication (OR=2.24;95%CI:1.08-4.62;P=0.030) had higher BP control.Compared with those having lower HLI,participants with a same (OR=1.38;95%CI:0.99-1.93;P=0.056) or high (OR=1.79;95%CI:1.27~2.53;P<0.001) HLI had higher BP control.Those who used antihypertensive medication and had a high HLI had the highest BP control (OR=1.88;95%CI:1.32-2.67,P<0.001).Subgroup analysis also showed the consistent effect as the above.Conclusion These findings suggest that adherence to antihypertensive medication treatment and healthy lifestyle were associated with a significant improvement in BP control among employees with hypertension.展开更多
This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear systems.Unlike existing optimal state feedback control,the control input of the optimal parallel control is int...This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear systems.Unlike existing optimal state feedback control,the control input of the optimal parallel control is introduced into the feedback system.However,due to the introduction of control input into the feedback system,the optimal state feedback control methods can not be applied directly.To address this problem,an augmented system and an augmented performance index function are proposed firstly.Thus,the general nonlinear system is transformed into an affine nonlinear system.The difference between the optimal parallel control and the optimal state feedback control is analyzed theoretically.It is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index function.Moreover,an adaptive dynamic programming(ADP)technique is utilized to implement the optimal parallel tracking control using a critic neural network(NN)to approximate the value function online.The stability analysis of the closed-loop system is performed using the Lyapunov theory,and the tracking error and NN weights errors are uniformly ultimately bounded(UUB).Also,the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference signals.Finally,the effectiveness of the developed optimal parallel control method is verified in two cases.展开更多
Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and ...Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.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 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
In this paper,a novel adaptive Fault-Tolerant Control(FTC)strategy is proposed for non-minimum phase Hypersonic Vehicles(HSVs)that are affected by actuator faults and parameter uncertainties.The strategy is based on t...In this paper,a novel adaptive Fault-Tolerant Control(FTC)strategy is proposed for non-minimum phase Hypersonic Vehicles(HSVs)that are affected by actuator faults and parameter uncertainties.The strategy is based on the output redefinition method and Adaptive Dynamic Programming(ADP).The intelligent FTC scheme consists of two main parts:a basic fault-tolerant and stable controller and an ADP-based supplementary controller.In the basic FTC part,an output redefinition approach is designed to make zero-dynamics stable with respect to the new output.Then,Ideal Internal Dynamic(IID)is obtained using an optimal bounded inversion approach,and a tracking controller is designed for the new output to realize output tracking of the nonminimum phase HSV system.For the ADP-based compensation control part,an ActionDependent Heuristic Dynamic Programming(ADHDP)adopting an actor-critic learning structure is utilized to further optimize the tracking performance of the HSV control system.Finally,simulation results are provided to verify the effectiveness and efficiency of the proposed FTC algorithm.展开更多
Due to the nonlinearity and uncertainty, the precise control of underwater vehicles in some intelligent operations hasn’t been solved very well yet. A novel method of control based on desired state programming was pr...Due to the nonlinearity and uncertainty, the precise control of underwater vehicles in some intelligent operations hasn’t been solved very well yet. A novel method of control based on desired state programming was presented, which used the technique of fuzzy neural network. The structure of fuzzy neural network was constructed according to the moving characters and the back propagation algorithm was deduced. Simulation experiments were conducted on general detection remotely operated vehicle. The results show that there is a great improvement in response and precision over traditional control, and good robustness to the model’s uncertainty and external disturbance, which has theoretical and practical value.展开更多
In the three-wire welding system, a welding process consists of the operations of four devices, namely three welding machines and one bogie. The operations need to be synchronized by a numerical coordinate controller ...In the three-wire welding system, a welding process consists of the operations of four devices, namely three welding machines and one bogie. The operations need to be synchronized by a numerical coordinate controller （ NCC ）. In this paper, we will discuss a tnsk-job-procedure cubic program structure. Under this structure, the devices are synchronized and isolated at the same time. This cubic program structure can also be used as a reference for other multi-device or multi-unit manufacturing processes.展开更多
This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discretetime systems. First, a novel finite-horizon Policy Iteration (PI) method for linear time-vary...This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discretetime systems. First, a novel finite-horizon Policy Iteration (PI) method for linear time-varying discrete-time systems is presented. Its connections with existing in finite-horizon PI methods are discussed. Then, both data-drive n off-policy PI and Value Iteration (VI) algorithms are derived to find approximate optimal controllers when the system dynamics is completely unknown. Under mild conditions, the proposed data-driven off-policy algorithms converge to the optimal solution. Finally, the effectiveness and feasibility of the developed methods are validated by a practical example of spacecraft attitude control.展开更多
A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical an...A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical and electrical impli- cations of robots equipped with DC motor actuators.This model takes into account all non-linear aspects of the system.Then,we develop computational algorithms for optimal control based on dynamic programming.The robot's trajectory must be predefined,but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being studied.As an example,a manipulator arm with 3 degrees of freedom is analyzed.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
In this paper,a stochastic linear quadratic optimal tracking scheme is proposed for unknown linear discrete-time(DT)systems based on adaptive dynamic programming(ADP)algorithm.First,an augmented system composed of the...In this paper,a stochastic linear quadratic optimal tracking scheme is proposed for unknown linear discrete-time(DT)systems based on adaptive dynamic programming(ADP)algorithm.First,an augmented system composed of the original system and the command generator is constructed and then an augmented stochastic algebraic equation is derived based on the augmented system.Next,to obtain the optimal control strategy,the stochastic case is converted into the deterministic one by system transformation,and then an ADP algorithm is proposed with convergence analysis.For the purpose of realizing the ADP algorithm,three back propagation neural networks including model network,critic network and action network are devised to guarantee unknown system model,optimal value function and optimal control strategy,respectively.Finally,the obtained optimal control strategy is applied to the original stochastic system,and two simulations are provided to demonstrate the effectiveness of the proposed algorithm.展开更多
In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed sign...In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.展开更多
This work presents a new methodology based on Linear Programming (LP) to tune Proportional-Integral-Derivative (PID) control parameters. From a specification of a desired output time domain of the plant, a linear opti...This work presents a new methodology based on Linear Programming (LP) to tune Proportional-Integral-Derivative (PID) control parameters. From a specification of a desired output time domain of the plant, a linear optimization system is proposed to adjust the PID controller leading the output signal to stable operation condition with minimum oscillations. The constraint set used in the optimization process is defined by using numerical integration approach. The generated optimization problem is convex and easily solved using an interior point algorithm. Results obtained using familiar plants from literature have shown that the proposed linear programming problem is very effective for tuning PID controllers.展开更多
The field experiments were conducted at the experimental farm of Faculty of agricultural, southern Illinois University SIUC, USA. The project makes the irrigation automated. With the use of low cost sensors and the si...The field experiments were conducted at the experimental farm of Faculty of agricultural, southern Illinois University SIUC, USA. The project makes the irrigation automated. With the use of low cost sensors and the simple circuitry makes currently project a low cost product, which can be bought even by a poor farmer. This research work is best suited for places where water is scares and has to be used in limited quantity and this proposal is a model to modernize the agriculture industries at a mass scale with optimum expenditure. In the field of agricultural engineering, use of sensor method of irrigation operation is important and it is well known that closed circuits of Mini-sprinkler irrigation system are very economical and efficient. Closed circuits are considered one of the modifications of Mini-sprinkler irrigation system, and added advantages to Mini-sprinkler irrigation system because it can relieve low operating pressures problem at the end of the lateral lines. In the conventional closed circuits of Mini-sprinkler irrigation system, the farmer has to keep watch on irrigation timetable, which is different for different crops. Using this system, one can save manpower, water to improve production and ultimately profit. The data could be summarized in following: Irrigation methods under study when using lateral length 60 mcould be ranked in the following ascending order according the values of the predicted and measured head losses CM1M-SIS CM2M-SIS.The correlation (Corr.) coefficients were used to compare the predicted and measured head losses along the lateral lines of all the closed circuits designs. Generally, the values of correlation analysis were (>0.90) were obtained with 0% field slope60 mlength (experimental conditions) for all closed circuits.The interaction between irrigation methods: at the start there are significant differences between CM2M-SIS and CM1M-SIS.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
This paper introduces a self-learning control approach based on approximate dynamic programming. Dynamic programming was introduced by Bellman in the 1950's for solving optimal control problems of nonlinear dynami...This paper introduces a self-learning control approach based on approximate dynamic programming. Dynamic programming was introduced by Bellman in the 1950's for solving optimal control problems of nonlinear dynamical systems. Due to its high computational complexity, the applications of dynamic programming have been limited to simple and small problems. The key step in finding approximate solutions to dynamic programming is to estimate the performance index in dynamic programming. The optimal control signal can then be determined by minimizing (or maximizing) the performance index. Artificial neural networks are very efficient tools in representing the performance index in dynamic programming. This paper assumes the use of neural networks for estimating the performance index in dynamic programming and for generating optimal control signals, thus to achieve optimal control through self-learning.展开更多
The objective of this paper is to present a robust safety-critical control system based on the active disturbance rejection control approach, designed to guarantee safety even in the presence of model inaccuracies, un...The objective of this paper is to present a robust safety-critical control system based on the active disturbance rejection control approach, designed to guarantee safety even in the presence of model inaccuracies, unknown dynamics, and external disturbances. The proposed method combines control barrier functions and control Lyapunov functions with a nonlinear extended state observer to produce a robust and safe control strategy for dynamic systems subject to uncertainties and disturbances. This control strategy employs an optimization-based control, supported by the disturbance estimation from a nonlinear extended state observer. Using a quadratic programming algorithm, the controller computes an optimal, stable, and safe control action at each sampling instant. The effectiveness of the proposed approach is demonstrated through numerical simulations of a safety-critical interconnected adaptive cruise control system.展开更多
基金Supported by the National Natural Science Foundation of China(12001327,12071057)。
文摘Toric patch is a kind of rational multisided patch,which is associated with a finite integer lattice points set A.A set of weights is defined which depend on a parameter according to regular decomposition of A.When all weights of the patch tend to infinity,we obtain the limiting form of toric patch which is called its regular control surface.The diferent weights may induce the diferent regular control surfaces of the same toric patch.It prompts us to consider that how many regular control surfaces of a toric patch.In this paper,we study the regular decompositions of A by using integer programming method firstly,and then provide the relationship between all regular decompositions of A and corresponding state polytope.Moreover,we present that the number of regular control surfaces of a toric patch associated with A is equal to the number of regular decompositions of A.An algorithm to calculate the number of regular control surfaces of toric patch is provided.The algorithm also presents a method to construct all of the regular control surfaces of a toric patch.At last,the application of proposed result in shape deformation is demonstrated by several examples.
基金supported by grant 2011BAI11B01 from the Projects in the Chinese National Science and Technology Pillar Program during the 12th Five-year Plan Periodby grant 2017-I2M-1-004 from the Chinese Academy of Medical Science Innovation Fund for Medical Sciencesby the Major science and technology special plan project of Yunnan Province (202302AA310045)。
文摘Background Both medication and non-medication therapies are effective approaches to control blood pressure (BP) in hypertension patients.However,the association of joint changes in antihypertensive medication use and healthy lifestyle index (HLI)with BP control among hypertension patients is seldom reported,which needs to provide more evidence by prospective intervention studies.We examined the association of antihypertensive medication use and HLI with BP control among employees with hypertension in China based on a workplace-based multicomponent intervention program.Methods Between January 2013 and December 2014,a cluster randomized clinical trial of a workplace-based multicomponent intervention program was conducted in 60 workplaces across 20 urban areas in China.Workplaces were randomly divided into intervention (n=40) and control (n=20) groups.Basic information on employees at each workplace was collected by trained professionals,including sociodemographic characteristics,medical history,family history,lifestyle behaviors,medication status and physical measurements.After baseline,the intervention group received a 2-year intervention to achieve BP control,which included:(1) a workplace wellness program for all employees;(2) a guidelines-oriented hypertension management protocol.HLI including nonsmoking,nondrinking,adequate physical activity,weight within reference range and balanced diet,were coded on a 5-point scale (range:0-5,with higher score indicating a healthier lifestyle).Antihypertensive medication use was defined as taking drug within the last 2 weeks.Changes in HLI,antihypertensive medication use and BP control from baseline to 24 months were measured after the intervention.Results Overall,4655 employees were included (age:46.3±7.6 years,men:3547 (82.3%)).After 24 months of the intervention,there was a significant improvement in lifestyle[smoking (OR=0.65,95%CI:0.43-0.99;P=0.045),drinking (OR=0.52,95%CI:0.40-0.68;P<0.001),regular exercise (OR=3.10,95%CI:2.53-3.78;P<0.001),excessive intake of fatty food (OR=0.17,95%CI:0.06-0.52;P=0.002),restrictive use of salt (OR=0.26,95%CI:0.12-0.56;P=0.001)].Compare to employees with a deteriorating lifestyle after the intervention,those with an improved lifestyle had a higher BP control.In the intervention group,compared with employees not using antihypertensive medication,those who consistent used (OR=2.34;95%CI:1.16-4.72;P=0.017) or changed from not using to using antihypertensive medication (OR=2.24;95%CI:1.08-4.62;P=0.030) had higher BP control.Compared with those having lower HLI,participants with a same (OR=1.38;95%CI:0.99-1.93;P=0.056) or high (OR=1.79;95%CI:1.27~2.53;P<0.001) HLI had higher BP control.Those who used antihypertensive medication and had a high HLI had the highest BP control (OR=1.88;95%CI:1.32-2.67,P<0.001).Subgroup analysis also showed the consistent effect as the above.Conclusion These findings suggest that adherence to antihypertensive medication treatment and healthy lifestyle were associated with a significant improvement in BP control among employees with hypertension.
基金supported in part by the National Key Reseanch and Development Program of China(2018AAA0101502,2018YFB1702300)in part by the National Natural Science Foundation of China(61722312,61533019,U1811463,61533017)in part by the Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles。
文摘This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear systems.Unlike existing optimal state feedback control,the control input of the optimal parallel control is introduced into the feedback system.However,due to the introduction of control input into the feedback system,the optimal state feedback control methods can not be applied directly.To address this problem,an augmented system and an augmented performance index function are proposed firstly.Thus,the general nonlinear system is transformed into an affine nonlinear system.The difference between the optimal parallel control and the optimal state feedback control is analyzed theoretically.It is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index function.Moreover,an adaptive dynamic programming(ADP)technique is utilized to implement the optimal parallel tracking control using a critic neural network(NN)to approximate the value function online.The stability analysis of the closed-loop system is performed using the Lyapunov theory,and the tracking error and NN weights errors are uniformly ultimately bounded(UUB).Also,the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference signals.Finally,the effectiveness of the developed optimal parallel control method is verified in two cases.
基金supported in part by the National Natural Science Foundation of China(62222301, 62073085, 62073158, 61890930-5, 62021003)the National Key Research and Development Program of China (2021ZD0112302, 2021ZD0112301, 2018YFC1900800-5)Beijing Natural Science Foundation (JQ19013)。
文摘Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.
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.
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supported in part by the Science Center Program of National Natural Science Foundation of China(62373189,62188101,62020106003)the Research Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures,China。
文摘In this paper,a novel adaptive Fault-Tolerant Control(FTC)strategy is proposed for non-minimum phase Hypersonic Vehicles(HSVs)that are affected by actuator faults and parameter uncertainties.The strategy is based on the output redefinition method and Adaptive Dynamic Programming(ADP).The intelligent FTC scheme consists of two main parts:a basic fault-tolerant and stable controller and an ADP-based supplementary controller.In the basic FTC part,an output redefinition approach is designed to make zero-dynamics stable with respect to the new output.Then,Ideal Internal Dynamic(IID)is obtained using an optimal bounded inversion approach,and a tracking controller is designed for the new output to realize output tracking of the nonminimum phase HSV system.For the ADP-based compensation control part,an ActionDependent Heuristic Dynamic Programming(ADHDP)adopting an actor-critic learning structure is utilized to further optimize the tracking performance of the HSV control system.Finally,simulation results are provided to verify the effectiveness and efficiency of the proposed FTC algorithm.
基金Supported by the National High Technology and Development Program Foundation of China under Grant No. 2002AA420090.
文摘Due to the nonlinearity and uncertainty, the precise control of underwater vehicles in some intelligent operations hasn’t been solved very well yet. A novel method of control based on desired state programming was presented, which used the technique of fuzzy neural network. The structure of fuzzy neural network was constructed according to the moving characters and the back propagation algorithm was deduced. Simulation experiments were conducted on general detection remotely operated vehicle. The results show that there is a great improvement in response and precision over traditional control, and good robustness to the model’s uncertainty and external disturbance, which has theoretical and practical value.
基金This work was supported by the Natural Science Fund of China,grant number 50375054.
文摘In the three-wire welding system, a welding process consists of the operations of four devices, namely three welding machines and one bogie. The operations need to be synchronized by a numerical coordinate controller （ NCC ）. In this paper, we will discuss a tnsk-job-procedure cubic program structure. Under this structure, the devices are synchronized and isolated at the same time. This cubic program structure can also be used as a reference for other multi-device or multi-unit manufacturing processes.
基金The work of B. Pang and Z.-P. Jiang has been supported in part by the National Science Foundation (No. ECCS-1501044).
文摘This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discretetime systems. First, a novel finite-horizon Policy Iteration (PI) method for linear time-varying discrete-time systems is presented. Its connections with existing in finite-horizon PI methods are discussed. Then, both data-drive n off-policy PI and Value Iteration (VI) algorithms are derived to find approximate optimal controllers when the system dynamics is completely unknown. Under mild conditions, the proposed data-driven off-policy algorithms converge to the optimal solution. Finally, the effectiveness and feasibility of the developed methods are validated by a practical example of spacecraft attitude control.
文摘A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical and electrical impli- cations of robots equipped with DC motor actuators.This model takes into account all non-linear aspects of the system.Then,we develop computational algorithms for optimal control based on dynamic programming.The robot's trajectory must be predefined,but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being studied.As an example,a manipulator arm with 3 degrees of freedom is analyzed.
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.
基金This work was supported by the National Natural Science Foundation of China(No.61873248)the Hubei Provincial Natural Science Foundation of China(Nos.2017CFA030,2015CFA010)the 111 project(No.B17040).
文摘In this paper,a stochastic linear quadratic optimal tracking scheme is proposed for unknown linear discrete-time(DT)systems based on adaptive dynamic programming(ADP)algorithm.First,an augmented system composed of the original system and the command generator is constructed and then an augmented stochastic algebraic equation is derived based on the augmented system.Next,to obtain the optimal control strategy,the stochastic case is converted into the deterministic one by system transformation,and then an ADP algorithm is proposed with convergence analysis.For the purpose of realizing the ADP algorithm,three back propagation neural networks including model network,critic network and action network are devised to guarantee unknown system model,optimal value function and optimal control strategy,respectively.Finally,the obtained optimal control strategy is applied to the original stochastic system,and two simulations are provided to demonstrate the effectiveness of the proposed algorithm.
基金Project(2014BAG01B0403)supported by the High-Tech Research and Development Program of China
文摘In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.
文摘This work presents a new methodology based on Linear Programming (LP) to tune Proportional-Integral-Derivative (PID) control parameters. From a specification of a desired output time domain of the plant, a linear optimization system is proposed to adjust the PID controller leading the output signal to stable operation condition with minimum oscillations. The constraint set used in the optimization process is defined by using numerical integration approach. The generated optimization problem is convex and easily solved using an interior point algorithm. Results obtained using familiar plants from literature have shown that the proposed linear programming problem is very effective for tuning PID controllers.
文摘The field experiments were conducted at the experimental farm of Faculty of agricultural, southern Illinois University SIUC, USA. The project makes the irrigation automated. With the use of low cost sensors and the simple circuitry makes currently project a low cost product, which can be bought even by a poor farmer. This research work is best suited for places where water is scares and has to be used in limited quantity and this proposal is a model to modernize the agriculture industries at a mass scale with optimum expenditure. In the field of agricultural engineering, use of sensor method of irrigation operation is important and it is well known that closed circuits of Mini-sprinkler irrigation system are very economical and efficient. Closed circuits are considered one of the modifications of Mini-sprinkler irrigation system, and added advantages to Mini-sprinkler irrigation system because it can relieve low operating pressures problem at the end of the lateral lines. In the conventional closed circuits of Mini-sprinkler irrigation system, the farmer has to keep watch on irrigation timetable, which is different for different crops. Using this system, one can save manpower, water to improve production and ultimately profit. The data could be summarized in following: Irrigation methods under study when using lateral length 60 mcould be ranked in the following ascending order according the values of the predicted and measured head losses CM1M-SIS CM2M-SIS.The correlation (Corr.) coefficients were used to compare the predicted and measured head losses along the lateral lines of all the closed circuits designs. Generally, the values of correlation analysis were (>0.90) were obtained with 0% field slope60 mlength (experimental conditions) for all closed circuits.The interaction between irrigation methods: at the start there are significant differences between CM2M-SIS and CM1M-SIS.
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.
基金Supported by the National Science Foundation (U.S.A.) under Grant ECS-0355364
文摘This paper introduces a self-learning control approach based on approximate dynamic programming. Dynamic programming was introduced by Bellman in the 1950's for solving optimal control problems of nonlinear dynamical systems. Due to its high computational complexity, the applications of dynamic programming have been limited to simple and small problems. The key step in finding approximate solutions to dynamic programming is to estimate the performance index in dynamic programming. The optimal control signal can then be determined by minimizing (or maximizing) the performance index. Artificial neural networks are very efficient tools in representing the performance index in dynamic programming. This paper assumes the use of neural networks for estimating the performance index in dynamic programming and for generating optimal control signals, thus to achieve optimal control through self-learning.
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）
基金supported by the Fondo para el Primer Proyecto of the Comitépara el Desarrollo de la Investigación(CODI)at the Universidad de Antioquia(Grant Number PRV2024-78509)。
文摘The objective of this paper is to present a robust safety-critical control system based on the active disturbance rejection control approach, designed to guarantee safety even in the presence of model inaccuracies, unknown dynamics, and external disturbances. The proposed method combines control barrier functions and control Lyapunov functions with a nonlinear extended state observer to produce a robust and safe control strategy for dynamic systems subject to uncertainties and disturbances. This control strategy employs an optimization-based control, supported by the disturbance estimation from a nonlinear extended state observer. Using a quadratic programming algorithm, the controller computes an optimal, stable, and safe control action at each sampling instant. The effectiveness of the proposed approach is demonstrated through numerical simulations of a safety-critical interconnected adaptive cruise control system.
