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Continuous-Time Single Network Adaptive Critic Based Optimal Sliding Mode Control for Nonlinear Control Affine Systems.

机译:非线性控制仿射系统的连续单网络自适应批评基于最优滑模控制。

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Integrating the Sliding Mode Control (SMC) theory with Approximate Dynamic Programming (ADP), this paper presents a novel technique for designing robust optimal sliding mode control schemes for a class of nonlinear control affine systems with disturbances. The main motivation of the work is to merge the inherent robustness of conventional sliding mode control with optimal control theory. Towards this end, a dynamic sliding surface is first used and a control law is defined which guarantees stability in the sense of Lyapunov in the presence of the disturbances. Next, a continuous time single network adaptive critic is used to find an approximate solution to the Hamilton-Jacobi-Bellman (HJB) equation. Since the adaptive critic approximates the optimal cost-to-go function using a parametric positive semi-definite function, the stability of the system is studied during the evolution of weights by employing Lyapunov theory. The merits of the proposed algorithm are demonstrated through simulation examples.
机译:本文介绍了具有近似动态编程(ADP)的滑模控制(SMC)理论,提出了一种用于设计具有干扰的一类非线性控制仿射系统的强大的最佳滑动模式控制方案的新技术。该工作的主要动机是利用具有最优控制理论的传统滑模控制的固有稳健性。朝向此结束,首先使用动态滑动表面,并且定义了对照法,该控制定律在存在干扰情况下保证Lyapunov意义上的稳定性。接下来,使用连续时间单个网络自适应批评评论来查找汉密尔顿 - Jacobi-Bellman(HJB)方程的近似解。由于自适应评论估计使用参数正半定函数近似最佳成本效果,因此通过采用Lyapunov理论在权重的演变期间研究了系统的稳定性。通过模拟实施例证明了所提出的算法的优点。

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