不确定拟Hamilton系统的非线性随机最优控制的鲁棒性与其鲁棒控制
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摘要
本文由两部分组成,分别研究不确定拟Hamilton系统的非线性随机最优控制的鲁棒性与其鲁棒控制。在第一部分中,首先基于不确定参数和随机激励的独立性,应用随机平均法和随机动态规划原理得到具平均值参数名义拟Hamilton系统的非线性随机最优控制;然后,应用随机平均法和概率分析得到不确定拟Hamilton系统均方根响应、控制效果和控制效率的均值和标准差;最后,引进受控均方根响应、控制效果和控制效率的变差系数对不确定参数变差系数的敏感性作为鲁棒性评价指标,对非线性随机最优控制的鲁棒性进行分析。作为拟Hamilton系统非线性随机最优控制策略在实际工程中的应用,给出了Bouc-Wen及Preisach滞迟系统两个例子,并使用上述的鲁棒性分析方法对它们进行全面研究。数值结果显示了这一控制方法的卓越的鲁棒性能。
     在第二部分中,基于随机平均法和随机微分对策,提出了受有界的参数和外部扰动的拟Hamilton系统的极小极大最优控制策略。寻求最坏情况下最优控制的目标通过求解一个随机微分对策问题实现,而最坏情况扰动与相应的最优控制由Hamilton-Jacobi-Isaacs方程确定。作为上述方法的一个推广,详细阐述了其在反馈稳定化问题中的应用。通过求解一个具待定成本函数的随机微分对策问题确定系统的最坏情况扰动及相应的最优控制的形式,然后以最坏扰动下最优控制系统的最大Lyapunov指数最小为准则确定成本函数。
The present dissertation consists of two parts. In the first part, the robustness of the nonlinear stochastic optimal control for uncertain quasi Hamiltonian systems is studied. Based on the independence of uncertain parameters and stochastic excitations, the nonlinear stochastic optimal control for the nominal quasi Hamiltonian system with average-value parameters is firstly obtained by using the stochastic averaging method and stochastic dynamical programming principle. Then, the means and standard deviations of root-mean-square responses, control effectiveness and control efficiency for the uncertain quasi Hamiltonian system are calculated by using the stochastic averaging method and the probabilistic analysis. By introducing the sensitivities of the variation coefficients of controlled root-mean-square responses, control effectiveness and control efficiency to those of the uncertain parameters as measures, the robustness of the nonlinear stochastic optimal control is evaluated. As the application of the nonlinear stochastic optimal control strategy, controlled Bouc-Wen and Preisach hysteretic systems are studied and the robustness of the control strategy is also analyzed. Numerical results show the remarkable robustness of nonlinear stochastic optimal control.
     In the second part, the robust control of uncertain quasi Hamiltonian systems is studied. A minimax optimal control strategy for quasi Hamiltonian systems with bounded parametric and/or external disturbances is proposed based on the stochastic averaging method and stochastic differential game. The proposed strategy is searching for the optimal worst-case controller by solving a stochastic differential game problem, and the worst-case disturbances and the corresponding optimal controls are obtained by solving a Hamilton-Jacobi-Isaacs equation. The feedback stabilization of uncertain quasi Hamiltonian systems are investigated as a generalization of the above robust control strategy. The form of the worst-case disturbances and the optimal controls are firstly obtained by solving a stochastic differential game problem with undetermined cost function. The cost function is then determined by the requirement of minimizing the maximal Lyapunov exponent of the controlled system in worst case.
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