基于ANOVA-like 方差分解的非线性系统控制性能评估

针对实际控制回路大多包含非线性特征,导致评估结果存在偏差的问题,以一类非线性系统为对象,首先分析其最小方差性能下限的存在性,并推导出其与系统干扰项的关系式;然后用正交最小二乘方法辨识系统闭环模型,进而使用ANOVA-like方差分解公式估计超前干扰项对输出方差的贡献,由此获得非线性系统的控制性能;最后,将所提出的方法与传统方法通过仿真实例进行比较.仿真结果表明,所提出的方法是可行且有效的.

Control performance assessment based on ANOVA-like variance decomposition for nonlinear systems

In practice, many industrial control loops inevitably include nonlinearites, so the estimates of the control performance may not be correct. Firstly, the existence of the minimum variance performance lower bound(MVPLB) for a class of nonlinear systems is analyzed and the relation between the MVPLM and disturbance terms is determined. Then, the model of closed-loop system is identified by using orthogonal least square algorithm. Based on the achieved model, the contribution to the output variance due to the uncertainties in most recent ahead disturbance terms is calculated according to ANOVA-like decomposition formula, so that the control performance of the nonlinear system is obtained. Finally, simulation results show the effectiveness and feasibility of the proposed algorithm.