执行阀黏滞过程的控制性能评估

控制性能评估是衡量工业过程控制回路性能和质量的重要技术,常见性能评估方法一般针对线性过程,而忽视了执行阀黏滞等造成的非线性特征.为此研究了一类存在执行阀黏滞现象的非线性系统,并提出了一种基于改进的径向基函数神经网络时间序列建模的控制性能基准估计方法.将Hinich检验算法引入网络评价函数,利用改进的网络评价指标训练径向基网络,以去除过程输出的非线性,进而采用时序分析技术准确估计出系统的控制性能基准.通过仿真分析,验证了方法的有效性.

Control Performance Assessment in the Presence of Valve Stiction Nonlinearities

Control performance assessment (CPA) is an important strategy to establish the quality of industrial control loops. However, most CPA methods are mainly restricted to linear systems, ignoring common process nonlinearities such as valve stiction. To tackle this problem, a control performance assessment method based on the improved radial basis function (RBF) nonlinear time series model in the presence of valve stiction nonlinearities was proposed in this paper. By applying the Hinich test method into the RBF learning, which guarantees the removing of the nonlinear part of the output, the performance benchmark was estimated using standard time series identification techniques. The simulation of an integral process verifies the validity of the proposed method.