Robust Adaptive Control of a Quadruple Tank Process with Sliding Mode and Pole Placement Control Strategies

Abstract

Many industrial processes have challenging issues such as complex nonlinear nature, high sensitivity to disturbances and existence of parametric uncertainties. A Quadruple Tank Process (QTP) is used in the laboratory as a scaled representation of many industrial processes involving liquid level control problems. Conventional controllers are relatively slow in tracking the reference inputs and in reacting to disturbances, and they tend to lack the ability in dealing with parametric changes in the QTP. The aim of this paper is to design and test an Adaptive Pole Placement Controller (APPC) and a robust Adaptive Sliding Mode Controller (ASMC) with the purpose of high-efficacy control of a minimum phase QTP. The controllers are tested via simulations and performance indices resulting from the simulation of these controllers are compared with a PID controller in terms of the three cases of robustness to set point variations, rejection of disturbance inputs, and robustness to parametric uncertainties. Simulation results reveal that the proposed adaptive control configurations perform better than the PID controller with lower performance indices and faster settling times due to the paramater estimation method used in the design processes. ASMC outperforms APPC in different variations of inputs and in regulation performances due to the invariant nature of the Sliding Mode Control (SMC). The results show that a decentralized ASMC can be used to improve the rapidity and robustness of many multivariable industrial process control systems.