Fault-Tolerant Tracking Control for a Biological Process: Multiple Lyapunov Functions Approach

Abstract

This paper addresses trajectory tracking and active Fault Tolerant Control (FTC) of a nonlinear biological process affected by actuators faults. The nonlinear biological process transformed to a fuzzy Takagi-Sugeno (T-S) model, then a nominal control based on the optimal Linear Quadratic Integral (LQI) is synthesized for ensuring the trajectory tracking. To build the active fault tolerant control, a Proportional Integral Observer (PIO) is proposed to estimate simultaneously the actuators faults and states, the estimated faults used to reconfigure the nominal control. the new conditions of convergence to increase the fault compensation speed are proposed, which based on multiple Lyapunov functions. The proposed method is applied to the bacterial growth process and their efficiency is demonstrated via simulations.