基于CARMA模型的多变量远程预测自适应控制器

Multivariable Adaptive Long-Range Predictive Controller Bascd on CARMA Model

本文采用CARMA模型,建立多变量远程预测控制器,并采用状态空间法分析其闭环系统的稳定性。这种控制器以远程预测多步滚动优化取代最小方差和广义最小方差控制器中的一步预测优化,并引入控制时域的概念,从而可应用于非最小相位和开环不稳定系统;在自适应算法中,对模型验前知识要求少,不需要知道系统的交互矩阵,计算量小。数字仿真结果证实了控制算法的以上特性。

In this paper, a multivariable adaptive long-range predictive controller based on CARMA model is developed. It seems better than Refs.[4] and [8] in that it is suitable for systems that are unstable and / or in non-minimun phase. It seems better than Refs. [8] [9] [10] in that it requries less prior knowlege of the interactor matrix of the system. It seems better than Ref. [3] in that it requires less amount of computations. Using the state space approach, the authors succeed in analyzing the robust stability of long-range predictive control systems, including the proposed control system. It is believed that the authors are the first to succcced in such an analysis. In developing the above proposed controller, the authors take two effective measures. First,thc authors use long-range predictor and multi-stage cost-function minimization schemes instead of single-step predictor and single-stage cost-function minimization schemes used by Borison [8] and Koivo [9], Secondly the authors introduce a control horizon. Simulation results appear to confirm that the proposed adaptive controller is better than previous ones.