Aimed at infinite horizon optimal control problems of discrete time-varying nonlinear systems,in this paper,a new iterative adaptive dynamic programming algorithm,which is the discrete-time time-varying policy iterati...Aimed at infinite horizon optimal control problems of discrete time-varying nonlinear systems,in this paper,a new iterative adaptive dynamic programming algorithm,which is the discrete-time time-varying policy iteration(DTTV)algorithm,is developed.The iterative control law is designed to update the iterative value function which approximates the index function of optimal performance.The admissibility of the iterative control law is analyzed.The results show that the iterative value function is non-increasingly convergent to the Bellman-equation optimal solution.To implement the algorithm,neural networks are employed and a new implementation structure is established,which avoids solving the generalized Bellman equation in each iteration.Finally,the optimal control laws for torsional pendulum and inverted pendulum systems are obtained by using the DTTV policy iteration algorithm,where the mass and pendulum bar length are permitted to be time-varying parameters.The effectiveness of the developed method is illustrated by numerical results and comparisons.展开更多
Building upon previous work (Lancaster, 2014) which defined and theoretically situated political monitoring as an analytical concept, this essay first reiterates the importance of political monitoring to the study o...Building upon previous work (Lancaster, 2014) which defined and theoretically situated political monitoring as an analytical concept, this essay first reiterates the importance of political monitoring to the study of institutions of governance and related policy design. The conceptualization of political monitoring builds upon the psychological notion that people change their behavior if they believe someone is watching them. Second, it discusses theoretically how and why policy design might incorporate political monitoring in order to produce specific outcomes. Third, it presents empirical evidence from several illustrative examples to demonstrate how the institutionalization of political monitoring affects policy outcomes.展开更多
基金supported in part by Fundamental Research Funds for the Central Universities(2022JBZX024)in part by the National Natural Science Foundation of China(61872037,61273167)。
文摘Aimed at infinite horizon optimal control problems of discrete time-varying nonlinear systems,in this paper,a new iterative adaptive dynamic programming algorithm,which is the discrete-time time-varying policy iteration(DTTV)algorithm,is developed.The iterative control law is designed to update the iterative value function which approximates the index function of optimal performance.The admissibility of the iterative control law is analyzed.The results show that the iterative value function is non-increasingly convergent to the Bellman-equation optimal solution.To implement the algorithm,neural networks are employed and a new implementation structure is established,which avoids solving the generalized Bellman equation in each iteration.Finally,the optimal control laws for torsional pendulum and inverted pendulum systems are obtained by using the DTTV policy iteration algorithm,where the mass and pendulum bar length are permitted to be time-varying parameters.The effectiveness of the developed method is illustrated by numerical results and comparisons.
文摘Building upon previous work (Lancaster, 2014) which defined and theoretically situated political monitoring as an analytical concept, this essay first reiterates the importance of political monitoring to the study of institutions of governance and related policy design. The conceptualization of political monitoring builds upon the psychological notion that people change their behavior if they believe someone is watching them. Second, it discusses theoretically how and why policy design might incorporate political monitoring in order to produce specific outcomes. Third, it presents empirical evidence from several illustrative examples to demonstrate how the institutionalization of political monitoring affects policy outcomes.