Model predictive control of nonlinear parameter varying systems via receding horizon control Lyapunov functions
Model predictive control of nonlinear parameter varying systems via receding horizon control Lyapunov functions
复制标题
通过后退地平线控制 Lyapunov 函数的非线性参数变化系统的模型预测控制
DOI：
10.1049/pbce061e_ch4
复制
发表时间：
2001
期刊：
影响因子：
--
通讯作者：
J. Cloutier
中科院分区：
文献类型：
--
作者：
M. Sznaier;J. Cloutier
The problem of rendering the origin an asymptotically stable equilibrium point of a nonlinear system while, at the same time, optimising some measure of performance has been the object of much attention in the past few years. In contrast to the case of linear systems where several optimal synthesis techniques (such as H∞, H2 and l1) are well established, their nonlinear counterparts are just starting to emerge. Moreover, in most cases these tools lead to partial differential equations that are difficult to solve. In this chapter we propose a suboptimal regulator for nonlinear parameter varying, control affine systems based upon the combination of model predictive and control Lyapunov function techniques. The main result of the chapter shows that this controller is nearly optimal provided that a certain finite horizon problem can be solved online. Additional results include: (a) sufficient conditions guaranteeing closed-loop stability even in cases where there is not enough computational power available to solve this optimisation online; and (b) an analysis of the suboptimality level of the proposed method.
