Soft computing-based fuzzy integral sliding mode control: a real-time investigation on a conical tank process

In this work, a fuzzy integral sliding mode controller (FISMC) for level control in a conical tank process is demonstrated in real time. In traditional sliding mode controller (SMC) algorithm, the robustness with respect to parameter variations and external disturbances can be achieved only after the reach of sliding phase. However, robustness is not guaranteed during the reaching phase. But integral sliding mode controller (ISMC) hunts to eliminate the reaching phase by imposing sliding mode throughout the system response. ISMC also mitigates chattering caused by discontinuity of controller. Hence, integral of error term is used in the sliding surface. A modified power rate reaching law is proposed to describe the dynamics of the switching function. The fuzzy logic system is integrated to approximate the sliding variable, and control law is formulated so as to alleviate the chattering effect of the control signal. In this paper, Takagi and Sugeno fuzzy logic is integrated with ISMC to achieve smoother sliding surface. Genetic algorithm (GA) is used to tune the membership functions of fuzzy logic and the parameters of the control law. GA-tuned FISMC integrates the features of fuzzy logic control, SMC and soft computing techniques. The effectiveness of algorithm is demonstrated in an experimental setup. The reported results confirm the superiority of GAFISMC compared with proportional integral controller and ISMC algorithm. The real-time implementation ensures the robustness of GAFISMC in terms of operating-level variations, parameter variations and disturbance rejection.