Design of Interval Type 2 Fuzzy Fault-Tolerant Controller for a Non-Minimum Phase System: Application to quadruple conical tank system

Abstract

Quadruple Conical Tank System (QCTS) is benchmark a laboratory setup for testing of various linear and nonlinear control algorithms for the multivariate control system. The multiple process configuration for multivariate input-output can be obtained from quadruple conical tank system. This article is concerned with designing a novel Fault-Tolerant Control (FTC) using Interval Type 2 Fuzzy Control (IT2FLC) subject to actuator and system component (Leak) faults. Additionally, paper explores the pen loop response with given operating points of quadruple conical tank system linearized model for non-minimum phase configuration obtained from MATLAB. The proposed control design method is simulated on prototype model of quadruple conical tank process for onminimum phase configuration. The performance of the proposed controller is studied through extensive simulations with regulatory and servo responses. Through comparative studies of proposed controller with other model based H ∞ , LQR, 2 DoF Decentralized PI Controller and model free Type 1 Fuzzy Logic controller (T1FLC) responses in MATLAB simulation environment, the effect of interaction, coupling, time variations and change in dynamic behaviour of QCTS confirmed.

Fuzzy-based metaheuristic algorithm for optimization of fuzzy controller: fault-tolerant control application

“…Furthermore, the author used a two-input, two-output fuzzy inference system for dynamic parameter adaptation in all three suggested algorithms. In Cuevas et al (2021b), the authors describe the application of a variant of the shark smell optimization (VSSO) biological inspired algorithm in the optimal design of a type-2 fuzzy controller, and thereafter optimized controller is tested with the navigation of an AMR in an unknown and changing environment, in Cuevas et al (2021a), the prime objective of the research work is to outline the design and implementation of tracking and position control with a new approach to intelligent navigation in omnidirectional mobile robots (OMR) using type-2 fuzzy systems to control their response actions, due to distinct advantages such as handling of modeling and parameter uncertainties of the interval type-2 fuzzy sets and adding the experience of a human expert in the formation of a fuzzy knowledge IJICC 15,4 base that allows us to describe the relationship between input and output of the system (Patel and Shah, 2019b). Fault-tolerant control application is presented for nonlinear level control process using fractional-order fuzzy TID controller with metaheuristic GA in Patel et al (2021), Patel and Shah (2022) with simulation and statistical results.…”

Type-2 fuzzy logic applications designed for active parameter adaptation in metaheuristic algorithm for fuzzy fault-tolerant controller

“…Today, the use of interval type 2 fuzzy systems is becoming more common in the literature, and we will briefly mention some of these recent works in various disciplines below. For example, an interval set-based method and its application to complex control group decision making was proposed in Patel and Shah (2019c), a more comprehensible perspective for interval type-2 fuzzy sets used for fractional order TID controller for level control applications subject to uncertainties was put forward in Patel and Shah (2021). The works in Du et al (2019a, b, 2020) and Qu et al (2009) describe the use of type-2 fuzzy systems to achieve excellent results in a variety of control problems.…”