Adaptive Inverse Optimal Control of Stochastic Nonlinear Systems with Uncertain Wiener Noises
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摘要: 针对一类具有不确定Wiener噪声扰动和未知定常参数的随机非线性系统,采用随 机微分方程描述系统,基于Backstepping算法,利用随机控制Lyapunov函数,研究了自适 应逆最优控制问题的可解定理,系统地给出了全局依概率渐近稳定和自适应逆最优控制策略 的设计方法.这种方法可同时获得控制律和自适应律,仿真结果表明该控制算法的有效性.
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关键词:
- 不确定Wiener噪声 /
- Backstepping算法 /
- 逆最优 /
- 依概率渐近稳定
Abstract: The solvable theorem of adaptive inverse optimal control problems for a class of stochastic nonlinear systems with uncertain Wiener noises and constant unknown parameters is studied. The systems are depicted by stochastic differential equations. By using backstepping algorithms and stochastic control Lyapunov functions, a designing procedure of control laws of global asymptotic stability in probability and adaptive inverse optimal stabilization in probability are presented systematically. Adaptive control laws and update laws can be obtained at the same time by this design scheme. Results of simulation show the effectiveness of the control algorithms. -
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