基于多模型切换的阶梯式广义预测控制器

摘要

To deal with a system with jumping parameters,a stair-like generalized predictive control algorithm based on multiple models switching is adopted.Multiple fixed models and two adaptive models are established to identify the dynamic characteristic of the system in paralle1.Multiple fixed models are used to improve the transient performance,while the re-initialized adaptive model can eliminate the steady-state error,the conventional adaptive model ensure the stability of the system at the same time.At each sampling time,the stair-like generalized predictive controller is designed based on the best model which is selected according to the switching index.Then,the global control is achieved. Finally,the stability and convergence analysis are also given.Compared with the convenient single model generalized predictive controller,control effect of the proposed method above is better.%　　针对一类模型参数跳变系统，提出一种基于多模型切换的阶梯式广义预测控制算法。该算法采用多个固定模型和两个自适应模型并行辨识系统的动态特性。多个固定模型用以提高系统的暂态性能，可重新赋初值的自适应模型用以消除系统的稳态误差，常规自适应模型用以保证系统的稳定性。在每个采样时刻基于切换性能指标得到最优的局部模型，实现系统的全局控制。最后给出了全局稳定性证明及收敛性分析。仿真结果表明：控制效果明显优于单一模型的广义预测控制器。