多变量周期系统的多模型二阶段自适应控制

Multiple models second level adaptive control of multivariable periodic systems

中文关键词  多变量  周期系统  多模型  二阶段自适应

英文关键词  multivariate  periodic system  multiple models  second level adaptive

中文摘要

      对于一类参数未知的多变量周期系统, 传统自适应控制方法存在参数收敛慢的问题, 导致系统暂态响应 差、控制效果不理想. 因此, 本文针对多变量周期系统设计了多模型二阶段自适应控制器. 首先根据先验知识, 确定 不确定区域范围, 并在不确定区域内建立多个自适应模型. 然后根据李雅普诺夫理论得到第一阶段辨识方程; 在第 二阶段中, 充分考虑辨识误差并确定了权值自适应律, 以此获取虚拟模型以提高参数的收敛速度. 接着, 利用得到的 虚拟模型参数设计了二阶段自适应控制器, 在保证了系统稳定性的基础上, 提高了系统的暂态性能. 最后, 给出的仿 真结果表明多模型二阶段自适应控制器提高了参数的收敛速度, 改善了系统的暂态性能.

英文摘要

      For a class of multivariable periodic systems with unknown parameters, the traditional adaptive control method has the problem of slow parameter convergence, which leads to poor transient response of the system and unsatisfactory control effect. Therefore, a multiple models second level adaptive controller is designed for multivariable periodic systems. Firstly, according to the prior knowledge, the range of the uncertain region is determined, and multiple adaptive models are built in the uncertain region. Secondly, the first level identification equation is obtained according to Lyapunov theory. In the second level, the identification error is fully considered and the weight adaptive law is determined to obtain the virtual model for improving the convergence rate of parameters. Then, a second level adaptive controller is designed by using the parameters of virtual model, which improves the transient performance of the system on the basis of ensuring the stability of the system. Finally, the simulation results show that the multiple model second level adaptive controller improves the convergence rate of parameters and the transient performance of the system.