الفهرس 
Chapter 1: Introduction And ReviewOnly 14 pages are availabe for public view
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Abstract
Liquid level control is employed in for various industrial applications, e.g., filtration, boilers, industrial chemical processing, pharmaceutical industrial, and several other applications. The control quality directly effects the quality of the products and the safety of equipment’s. However, the liquid level control system of water tanks with large lag, nonlinear complex dynamics, time varying behavior and sensitivity to disturbances, make its control is a real challenge. The liquid level control has been an active area of research in process control over the last decades and various control approaches have been proposed.
This thesis presents a successful experimental application of parameter identification and nonlinear control for a state-coupled two-tank liquid level control. The considered system here is nonlinear system with a coupled tank state. It is desired to achieve a precise and economical liquid level control of the lower tank. The genetic algorithm (GA) and the trust-region reflective newton (TRNN) method of nonlinear least-square algorithm are proposed in this work to estimate the physical parameter values of the nonlinear model of the system. The model validation using the best fit rate demonstrates a satisfactory results.
The feedback linearization control strategy is proposed to control the level of the lower tank of the state-coupled two-tank system. To deal with the system uncertainty, the sliding mode control is implemented for the system. In order to estimate the system states free of measurement noise the considered controllers are combined with a model-based nonlinear high gain observer. These control techniques have been implemented in simulation and experimentally. The achieved results demonstrates good estimation of the states of the system and satisfactory tracking of the liquid level to a given reference in comparison with a conventional PI controller.