SYNTHESIS OF OPTIMAL CONTROL LAW OF THE REORIENTATION OF THE NANOSATELLITE USING PROCEDURES FOR ANALYTIC CONSTRUCTION OF OPTIMAL REGULATORS

2020 ◽  
Author(s):  
L.I. Sinitsin ◽  
◽  
A.V. Kramlikh ◽  
Keyword(s):  
Optimal Control ◽  
Control Law ◽  
Analytic Construction

scholarly journals Adaptive Optimal Robust Control for Uncertain Nonlinear Systems Using Neural Network Approximation in Policy Iteration

2021 ◽  
Vol 11 (5) ◽  
pp. 2312
Author(s):  
Dengguo Xu ◽  
Qinglin Wang ◽  
Yuan Li
Keyword(s):  
Neural Network ◽  
Optimal Control ◽  
Robust Control ◽  
Nonlinear Systems ◽  
Policy Iteration ◽  
Control Law ◽  
Globally Asymptotically Stable ◽  
Control Approach ◽  
Input Uncertainties ◽  
Theoretical Results

In this study, based on the policy iteration (PI) in reinforcement learning (RL), an optimal adaptive control approach is established to solve robust control problems of nonlinear systems with internal and input uncertainties. First, the robust control is converted into solving an optimal control containing a nominal or auxiliary system with a predefined performance index. It is demonstrated that the optimal control law enables the considered system globally asymptotically stable for all admissible uncertainties. Second, based on the Bellman optimality principle, the online PI algorithms are proposed to calculate robust controllers for the matched and the mismatched uncertain systems. The approximate structure of the robust control law is obtained by approximating the optimal cost function with neural network in PI algorithms. Finally, in order to illustrate the availability of the proposed algorithm and theoretical results, some numerical examples are provided.

scholarly journals Optimal Control Based on the Polynomial Least Squares Method

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Constantin Bota ◽  
Bogdan Cǎruntu ◽  
Mǎdǎlina Sofia Pașca ◽  
Marioara Lǎpǎdat
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Variational Problem ◽  
Least Squares ◽  
Least Squares Method ◽  
Lagrange Equation ◽  
Control Law

In this paper an approach for computing an optimal control law based on the Polynomial Least Squares Method (PLSM) is presented. The initial optimal control problem is reformulated as a variational problem whose corresponding Euler-Lagrange equation is solved by using PLSM. A couple of examples emphasize the accuracy of the method.

Scheduling Strategy of Multiple Semi-Active Controllers With Information on the Disturbance and the Structural Response

2016 ◽  
Author(s):  
Kazuhiko Hiramoto ◽  
Taichi Matsuoka ◽  
Katsuaki Sunakoda
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Active Control ◽  
Structural Response ◽  
Design Parameters ◽  
Control Law ◽  
Control Performance ◽  
Multiple Control ◽  
Control Laws ◽  
Scheduling Strategy

A scheduling strategy of multiple semi-active control laws for various earthquake disturbances is proposed to maximize the control performance. Generally, the semi-active controller for a given structural system is designed as a single control law and the single control law is used for all the forthcoming earthquake disturbances. It means that the general semi-active control should be designed to achieve a certain degree of the control performance for all the assumed disturbances with various time and/or frequency characteristics. Such requirement on the performance robustness becomes a constraint to obtain the optimal control performance. We propose a scheduling strategy of multiple semi-active control laws. Each semi-active control law is designed to achieve the optimal performance for a single earthquake disturbance. Such optimal control laws are scheduled with the available data in the control system. As the scheduling mechanism of the multiple control laws, a command signal generator (CSG) is defined in the control system. An artificial neural network (ANN) is adopted as the CSG. The ANN-based CSG works as an interpolator of the multiple control laws. Design parameters in the CSG are optimized with the genetic algorithm (GA). Simulation study shows the effectiveness of the approach.

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