Algorithm Design and Convergence Analysis of Iterative Adaptive Dynamic Programming

2013 ◽  
Vol 336-338 ◽  
pp. 852-855
Author(s):  
Bao Sheng Yang ◽  
Bao Sheng Yang ◽  
Li Li Chen
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Iterative Algorithm ◽  
System Performance ◽  
Time Delays ◽  
Adaptive Dynamic Programming ◽  
System Stability ◽  
Delay Systems ◽  
Control Law ◽  
Adaptive Dynamic

Time delays are tremendous difficulties to system stability analysis and controller design, and often cause system instability or even lead to the deterioration of the system performance. The optimal control law is solved for a class of nonlinear discrete affine systems with multiple time delays. The systems HJB equation of optimal control is solved by adaptive dynamic iterative algorithm and minimized system performance index function, given the convergence proof of the algorithm. Neural networks are adopted to realize iterative algorithm for optimal control law of time delay systems. The simulation results show that the adaptive dynamic programming can solve for the optimal control of delay nonlinear systems, make the system to achieve stability.

scholarly journals Adaptive Dynamic Programming based Control Scheme for Uncertain Two-Wheel Robots

2021 ◽  
Author(s):  
Linh Nguyen
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Adaptive Dynamic Programming ◽  
Control Law ◽  
Parameter Uncertainties ◽  
Adaptive Dynamic ◽  
Uncertain Dynamics ◽  
Control Scheme ◽  
State Controller ◽  
Optimal Control Scheme

<div>The paper addresses the problem of effectively controlling a two-wheel robot given its inherent non-linearity and parameter uncertainties. In order to deal with the unknown</div><div>and uncertain dynamics of the robot, it is proposed to employ the adaptive dynamic programming, a reinforcement learning based technique, to develop an optimal control law. It is interesting that the proposed algorithm does not require kinematic parameters while finding the optimal state controller is guaranteed. Moreover, convergence of the optimal control scheme is theoretically proved. The proposed approach was implemented in a synthetic</div><div>two-wheel robot where the obtained results demonstrate its</div><div>effectiveness.</div>

scholarly journals Adaptive Dynamic Programming based Control Scheme for Uncertain Two-Wheel Robots

2021 ◽  
Author(s):  
Linh Nguyen
Keyword(s):  
Optimal Control ◽  
Dynamic Programming ◽  
Adaptive Dynamic Programming ◽  
Control Law ◽  
Parameter Uncertainties ◽  
Adaptive Dynamic ◽  
Uncertain Dynamics ◽  
Control Scheme ◽  
State Controller ◽  
Optimal Control Scheme

<div>The paper addresses the problem of effectively controlling a two-wheel robot given its inherent non-linearity and parameter uncertainties. In order to deal with the unknown</div><div>and uncertain dynamics of the robot, it is proposed to employ the adaptive dynamic programming, a reinforcement learning based technique, to develop an optimal control law. It is interesting that the proposed algorithm does not require kinematic parameters while finding the optimal state controller is guaranteed. Moreover, convergence of the optimal control scheme is theoretically proved. The proposed approach was implemented in a synthetic</div><div>two-wheel robot where the obtained results demonstrate its</div><div>effectiveness.</div>

Time Delay System Tracking Control Based on ADP Iterative Algorithm

2013 ◽  
Vol 765-767 ◽  
pp. 1984-1987
Author(s):  
Chang Qing Cui ◽  
Yi Qiang Wang ◽  
Chun Yan Yang ◽  
Bao Sheng Yang
Keyword(s):  
Dynamic Programming ◽  
Iterative Algorithm ◽  
Tracking Control ◽  
Delay System ◽  
Adaptive Dynamic Programming ◽  
Delay Systems ◽  
Tracking Problem ◽  
Adaptive Dynamic ◽  
Affine System ◽  
Output Trajectory

Tracking control is to select a control strategy, so that the actual output of the system to be able to track the desired output trajectory, and makes minimal prescribed performance index function. Actually adjustment problem is also a special tracking problem, namely zero output trajectory tracking problem. Adaptive dynamic programming for solving delay systems tracking control aspects of the article is very small. The proposed delay systems tracking control features include two aspects: First, the research object containing the delay nonlinear discrete affine system, the second is the research method is adaptive dynamic programming iterative algorithm.

Heuristic Dynamic Programming Iterative Algorithm Design Based on BP Neural Network

2013 ◽  
Vol 850-851 ◽  
pp. 893-896
Author(s):  
Yu Zhao ◽  
Ji Ye Yang
Keyword(s):  
Neural Network ◽  
Optimal Control ◽  
Dynamic Programming ◽  
Time Delay ◽  
Iterative Algorithm ◽  
System Analysis ◽  
Adaptive Dynamic Programming ◽  
Dynamic Programming Method ◽  
Adaptive Dynamic ◽  
Delay Phenomenon

The time-delay delay phenomenon is a kind of widespread physical and biological phenomenon. The existence of time-delay not only give the stability of system analysis and controller design brings great difficulties but also usually make the systems unstable and even cause the system performance deteriorated. We use the adaptive dynamic iterative algorithm to solve this equation. By using the neural network to achieve the iterative algorithm, get the optimal control law of the systems with time delay. The simulation results show that the adaptive dynamic programming method to solve the optimal control of the nonlinear system is effective.

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