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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, the CARMA model is used to establish a multivariable long-range predictive controller. The state space method is used to analyze the stability of the closed-loop system. This controller replaces the minimum variance with the multi-step rolling optimization in long-range prediction and the one-step prediction optimization in the generalized minimum variance controller, and introduces the concept of controlling the time domain, which can be applied to non-minimum phase and open-loop unstable systems. Adaptation algorithm, less knowledge of the pre-test model, do not need to know the system interaction matrix, a small amount of computation. The numerical simulation results confirm the above characteristics of the control algorithm.