A finite-time-convergent fault-tolerant control and its experimental verification for DTS200 three-tank system

Abstract

This paper presents a fault-tolerant continuous super-twisting control algorithm for systems of dimension more than one, subject to Lipshitzian and non-Lipshitzian bounded disturbances. The conditions of finite-time convergence of the entire system state to the origin are obtained. An experimental verification of the designed fault-tolerant algorithm is conducted for a DTS200 three-tank system through varying fault sources, disturbances, input conditions, and inter-tank connections. I. INTRODUCTIONIt is well known that the classical discontinuous sliding mode control provides finite-time convergence for a scalar system state [1]. A finite-time stabilizing control for a system of dimension two is realized using the twisting algorithm [2], where the second order sliding mode control is also discontinuous. Both algorithms are robust with respect to bounded disturbances. On the other hand, using a continuous second-order sliding mode super-twisting algorithm [3], a scalar system state can be stabilized along with its first derivative. The super-twisting algorithm is robust with respect to unbounded disturbances satisfying a Lipschitz condition. A recent paper [4] has presented a modified super-twisting algorithm for systems of dimension more than one, which is however robust only against disturbances satisfying a Lipschitz condition.This paper corrects the indicated flaw and presents a faulttolerant homogeneous continuous super-twisting control algorithm for systems of dimension more than one, subject to Lipshitzian and non-Lipshitzian bounded disturbances. The conditions of finite-time convergence of the entire system state to the origin are obtained. First, the case of dimension two is addressed. Similar results are then obtained for systems of dimension more than two.The paper concludes with an experimental verification of the designed fault-tolerant algorithm, which is conducted for a DTS200 three-tank system through varying fault sources, disturbances, input conditions, and inter-tank connections. This three-tank system is a widely recognized testbed for applying performance tests and validating new control strategies [5]. Making use of its built-in fault scenarios (sensor fault, actuator

Passive Approach for Fault Tolerant Controller Using Hybrid Controller Structure for Effective Level Control of Conical Tank System

“…To take advantages of human/operator knowledge FTC framework proposed and applied on interactive and non-interactive system using artificial intelligence (neural network) under two fault and process disturbances (Patel and Shah, 2018d). In (Basin et al, 2015) author has proposed finite-time convergent fault-tolerant algorithm and an experimental validation of FTC is conducted for a DTS200 three-tank system through changing fault sources, process disturbances, input conditions and disturbances through inter-tank connections. Distributed FTC and a flatness based approach of FTC designed and implemented in (Torres et al, 2013;Capiluppi and Paoli, 2005) for threetank and two-tank level control system respectively, subsequently in (Altinisik and Yildirim, 2012) author designed FTC using data mining approach for three-tank level control system with fault.…”

Performance Comparison of Passive Fault Tolerant Control Strategy with PI and Fuzzy Control of Single-Tank Level Process with Sensor and System Fault

“…Artificial intelligence technique (fuzzy Logic) is combined with Model Predictive Control (MPC) for designing fault tolerant control scheme of three-tank nonlinear system with two fault constraintt (Mendonca et al, 2008). For DTS200 threetank system a finite-time convergent fault tolerant control was apply for varying fault sources, process disturbances, through inter-tank connections in (Basin et al, 2015). Parikh et al (2017) proposed and implemented Linear Quadratic Gaussian Control (LQG) with the Non-linear Model Predictive Control (NMPC) for three-tank interacting system and compared the performance for the servo plus disturbance rejection and regulatory control, process disturbance is adding through the interacting flow control valve.…”