Performance assessment of cascade control loops with non-Gaussian disturbances using entropy information

• Published in: Chemical engineering research & design Vol. 104; pp. 68 - 80
• Main Authors: Zhang, Jianhua, Zhang, Luyao, Chen, Junghui, Xu, Jinliang, Li, Kang
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2015
• Subjects: Cascade control; Control performance assessment; Design analysis; Design engineering; Disturbances; Entropy (Information theory); Minimum entropy; Model identification; Non-Gaussian; Performance assessment; Performance indices; Cascade control; Non-Gaussian; Minimum entropy; Control performance assessment; Model identification
• ISSN: 0263-8762; 1744-3563
• DOI: 10.1016/j.cherd.2015.07.011

•An entropy based performance assessment (EPA) tool for cascade control is developed.•EPA for cascade control can cope with non-Gaussian disturbances.•Non-Gaussian disturbances can be estimated using the minimum entropy based filter.•The proposed method has been successfully used in a real industrial plant. Cascade control is one of the routinely used control strategies in industrial processes because it can dramatically improve the performance of single-loop control, reducing both the maximum deviation and the integral error of the disturbance response. Currently, many control performance assessment methods of cascade control loops are developed based on the assumption that all the disturbances are subject to Gaussian distribution. However, in the practical condition, several disturbance sources occur in the manipulated variable or the upstream exhibits nonlinear behaviors. In this paper, a general and effective index of the performance assessment of the cascade control system subjected to the unknown disturbance distribution is proposed. Like the minimum variance control (MVC) design, the output variances of the primary and the secondary loops are decomposed into a cascade-invariant and a cascade-dependent term, but the estimated ARMA model for the cascade control loop based on the minimum entropy, instead of the minimum mean squares error, is developed for non-Gaussian disturbances. Unlike the MVC index, an innovative control performance index is given based on the information theory and the minimum entropy criterion. The index is informative and in agreement with the expected control knowledge. To elucidate wide applicability and effectiveness of the minimum entropy cascade control index, a simulation problem and a cascade control case of an oil refinery are applied. The comparison with MVC based cascade control is also included.