By differentiating four different types of output, the paperargues that their roles are also different. And learners of differ-ent language proficiency levels should be guided to produce dif-ferent types of output. Th...By differentiating four different types of output, the paperargues that their roles are also different. And learners of differ-ent language proficiency levels should be guided to produce dif-ferent types of output. Thus the paper introduces a new concept,namely "optimal output". Blindly making the learner produceoutput which is far beyond his current English level will only doharm to his interlanguage development, making it fossilize at anearly stage.展开更多
This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the sl...This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the slow and fast characteristics among system states,the interconnected SPS is decomposed into the slow time-scale dynamics and the fast timescale dynamics through singular perturbation theory.For the fast time-scale dynamics with interconnections,we devise a decentralized optimal control strategy by selecting appropriate weight matrices in the cost function.For the slow time-scale dynamics with unknown system parameters,an off-policy RL algorithm with convergence guarantee is given to learn the optimal control strategy in terms of measurement data.By combining the slow and fast controllers,we establish the composite decentralized adaptive optimal output regulator,and rigorously analyze the stability and optimality of the closed-loop system.The proposed decomposition design not only bypasses the numerical stiffness but also alleviates the high-dimensionality.The efficacy of the proposed methodology is validated by a load-frequency control application of a two-area power system.展开更多
This paper reviews recent developments in learning-based adaptive optimal output regulation that aims to solve the problem of adaptive and optimal asymptotic tracking with disturbance rejection.The proposed framework ...This paper reviews recent developments in learning-based adaptive optimal output regulation that aims to solve the problem of adaptive and optimal asymptotic tracking with disturbance rejection.The proposed framework aims to bring together two separate topics—output regulation and adaptive dynamic programming—that have been under extensive investigation due to their broad applications in modern control engineering.Under this framework,one can solve optimal output regulation problems of linear,partially linear,nonlinear,and multi-agent systems in a data-driven manner.We will also review some practical applications based on this framework,such as semi-autonomous vehicles,connected and autonomous vehicles,and nonlinear oscillators.展开更多
Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scal...Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.展开更多
The solvability of quadratic optimal control via output feedback is studied. It has been concluded that every optimal output feedback is a derivative solution to the corresponding optimal-state feedback, and the linea...The solvability of quadratic optimal control via output feedback is studied. It has been concluded that every optimal output feedback is a derivative solution to the corresponding optimal-state feedback, and the linear matrix equation that determines the existence of the optimal output feedback is generally unsolvable. The output matrix C with some parameters is discussed, and the necessary condition for the existence of the optimal output feedback is given. Moreover, for the single-input system, the condition is proved almost sufficient.展开更多
A robust optimal output tracking control method for a midwater trawl system is investigated based on T-S fuzzy nonlinear model. A simplified nonlinear mathematical model is first employed to represent a midwater trawl...A robust optimal output tracking control method for a midwater trawl system is investigated based on T-S fuzzy nonlinear model. A simplified nonlinear mathematical model is first employed to represent a midwater trawl system, and then a T-S fuzzy model is adopted to approximate the nonlinear system. Since the strong nonlinearities and the external disturbance of the trawling system, a mixed H2/H∞ fuzzy output tracking control strategy via T-S fuzzy system is proposed to regulate the trawl depth to follow a desired trajectory. The trawl depth can be regulated by adjusting the winch velocity automatically and the tracking error can be minimized according to the robust optimal criterion. In order to validate the proposed control method, a computer simulation is conducted. The simulation results indicate that the proposed fuzzy robust optimal controller make the trawl net rapidly follow the desired trajectory under the model uncertainties and the extemal disturbance caused by wave and current.展开更多
This paper has deduced a non-parameter analysis framework that can estimate the sources of economic growth based on provincial data as samples. Result of the estimate indicates that between 1978 and 2010, TFP, labor a...This paper has deduced a non-parameter analysis framework that can estimate the sources of economic growth based on provincial data as samples. Result of the estimate indicates that between 1978 and 2010, TFP, labor and capital contributed to China＇s economic growth by 10.9%, 3.7% and 85.4% respectively. If the impact of global financial crisis is not taken into account, these figures should be 20.70/0, 3.3% and 76.0%. Contribution of labor to economic growth is the smallest, below 8%for most of the years. Share of TFP contribution increased before the 1990s despite wild swings, exceeding 50% in 1992, followed by continuous decline until well below 10% after 2005. Share of capital contribution decreased before 1990s with wild swings and maintained an upward trend after 1992, approaching 90% after 2005.展开更多
文摘By differentiating four different types of output, the paperargues that their roles are also different. And learners of differ-ent language proficiency levels should be guided to produce dif-ferent types of output. Thus the paper introduces a new concept,namely "optimal output". Blindly making the learner produceoutput which is far beyond his current English level will only doharm to his interlanguage development, making it fossilize at anearly stage.
基金supported by the National Natural Science Foundation of China (62073327,62273350)the Natural Science Foundation of Jiangsu Province (BK20221112)。
文摘This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the slow and fast characteristics among system states,the interconnected SPS is decomposed into the slow time-scale dynamics and the fast timescale dynamics through singular perturbation theory.For the fast time-scale dynamics with interconnections,we devise a decentralized optimal control strategy by selecting appropriate weight matrices in the cost function.For the slow time-scale dynamics with unknown system parameters,an off-policy RL algorithm with convergence guarantee is given to learn the optimal control strategy in terms of measurement data.By combining the slow and fast controllers,we establish the composite decentralized adaptive optimal output regulator,and rigorously analyze the stability and optimality of the closed-loop system.The proposed decomposition design not only bypasses the numerical stiffness but also alleviates the high-dimensionality.The efficacy of the proposed methodology is validated by a load-frequency control application of a two-area power system.
文摘This paper reviews recent developments in learning-based adaptive optimal output regulation that aims to solve the problem of adaptive and optimal asymptotic tracking with disturbance rejection.The proposed framework aims to bring together two separate topics—output regulation and adaptive dynamic programming—that have been under extensive investigation due to their broad applications in modern control engineering.Under this framework,one can solve optimal output regulation problems of linear,partially linear,nonlinear,and multi-agent systems in a data-driven manner.We will also review some practical applications based on this framework,such as semi-autonomous vehicles,connected and autonomous vehicles,and nonlinear oscillators.
基金Project(50275150) supported by the National Natural Science Foundation of ChinaProject(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject(05JJ40128) supported by the Natural Science Foundation of Hunan Province, China
文摘Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.
基金Project supported by the National Natural Science Fundation of China.
文摘The solvability of quadratic optimal control via output feedback is studied. It has been concluded that every optimal output feedback is a derivative solution to the corresponding optimal-state feedback, and the linear matrix equation that determines the existence of the optimal output feedback is generally unsolvable. The output matrix C with some parameters is discussed, and the necessary condition for the existence of the optimal output feedback is given. Moreover, for the single-input system, the condition is proved almost sufficient.
基金supported by the National High-Technology Research and Development Program of China (863 Program,Grant No. 2008AA042703)
文摘A robust optimal output tracking control method for a midwater trawl system is investigated based on T-S fuzzy nonlinear model. A simplified nonlinear mathematical model is first employed to represent a midwater trawl system, and then a T-S fuzzy model is adopted to approximate the nonlinear system. Since the strong nonlinearities and the external disturbance of the trawling system, a mixed H2/H∞ fuzzy output tracking control strategy via T-S fuzzy system is proposed to regulate the trawl depth to follow a desired trajectory. The trawl depth can be regulated by adjusting the winch velocity automatically and the tracking error can be minimized according to the robust optimal criterion. In order to validate the proposed control method, a computer simulation is conducted. The simulation results indicate that the proposed fuzzy robust optimal controller make the trawl net rapidly follow the desired trajectory under the model uncertainties and the extemal disturbance caused by wave and current.
文摘This paper has deduced a non-parameter analysis framework that can estimate the sources of economic growth based on provincial data as samples. Result of the estimate indicates that between 1978 and 2010, TFP, labor and capital contributed to China＇s economic growth by 10.9%, 3.7% and 85.4% respectively. If the impact of global financial crisis is not taken into account, these figures should be 20.70/0, 3.3% and 76.0%. Contribution of labor to economic growth is the smallest, below 8%for most of the years. Share of TFP contribution increased before the 1990s despite wild swings, exceeding 50% in 1992, followed by continuous decline until well below 10% after 2005. Share of capital contribution decreased before 1990s with wild swings and maintained an upward trend after 1992, approaching 90% after 2005.
