Sliding Mode Control of Coupled Tank Systems Using Conditional Integrators

作     者：Sankata Bhanjan Prusty Sridhar Seshagiri Umesh Chandra Pati Kamala Kanta Mahapatra Sankata Bhanjan Prusty;Sridhar Seshagiri;Umesh Chandra Pati;Kamala Kanta Mahapatra

作者机构：Department of Electronics and Communication EngineeringMadanapalle Institute of Technology and ScienceMadanapalleAndhra Pradesh 517325India Department of Electrical and Computer EngineeringSan Diego State UniversitySan DiegoCA 92182 USA Department of Electronics and Communication EngineeringNational Institute of TechnologyRourkelaOdisha 769008India 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2020年第7卷第1期

页      面：118-125页

核心收录：

学科分类：08[工学] 0826[工学-兵器科学与技术] 0835[工学-软件工程] 0802[工学-机械工程] 080201[工学-机械制造及其自动化] 

主　　题：Conditional integrator coupled tank system LabVIEW sliding mode control 

摘      要：For the problem of set point regulation of the liquid level in coupled tank systems, we present a continuous sliding mode control(SMC) with a conditional integrator, which only provides integral action inside the boundary layer. For a special choice of the controller parameters, our design can be viewed as a PID controller with anti-windup and achieves robust *** proposed controller recovers the transient response performance without control chattering. Both full-state feedback as well as output-feedback designs are presented in this work. Our output-feedback design uses a high-gain observer(HGO) which recovers the performance of a state-feedback design where plant parameters are assumed to be known. We consider both interacting as well as non-interacting tanks and analytical results for stability and transient performance are presented in both the cases. The proposed controller continuous SMC with conditional integrators(CSMCCI) provides superior results in terms of the performance measures as well as performance indices than ideal SMC, continuous SMC(CSMC) and continuous SMC with conventional integrator(CSMCI). Experimental results demonstrate good tracking performance in spite of unmodeled dynamics and disturbances.