针对一类非最小相位系统,设计一种多模型自适应控制器.该控制器由固定控制器模型、常规自适应模型和可重新赋值自适应模型构成.固定控制器模型采用分层递阶结构用来减少模型集的数目,根据切换指标选出的上一层最优控制器,动态设计本层固定控制器模型实现对其参数变化范围的覆盖.该控制器采用直接自适应算法,通过加权多项式的选取,消除了稳态误差.文末对系统的覆盖性、模型数目等进行了分析.仿真结果表明当采用相同数目的模型时,其控制效果明显优于常规多模型控制器.
A novel Hierarchical multiple models Adaptive Controller (HMMAC) is presented for a multivariable nonminimum phase process, which includes hierarchical fixed optimal controllers, one free-running adaptive controller and one re-initialized adaptive controller. The hierarchical structure is adopted to reduce the number of the fixed controllers. In each level, the fixed controllers are designed dynamically to cover the high-level-optimal-fixed-controller. Based on to the switching index the selected controller is designed using the direct adaptive algorithm and the steady state error is eliminated by the choice of the weighting matrixes. At last, the covering analysis and the analysis of the number of hierarchical fixed controllers' are given. In the simulation example, if the same number of the fixed models is used, system transient response is improved greatly.