This paper presents the design and implementation of advanced control algorithms for a nonlinear coupled Multi-Input Multi-Output (MIMO) system, focusing on the hardware structure of Quadruple Conical Tank System (QCTS). Nonlinear MIMO systems, characterized by complex interactions between multiple inputs and outputs, pose significant challenges for control engineering. The QCTS, with its four interconnected conical tanks, serves as an exemplary testbed for evaluating advanced control strategies. The paper elaborates on the theoretical and practical implementation of Proportional-Integral-Derivative (PID) control, Fuzzy Logic Control (FLC), and Model Predictive Control (MPC), emphasizing their capabilities in managing multi-variable systems with constraints. Additionally, a comparative analysis of MPC with traditional control methods such as PID and FLC is presented. The practical implementation is demonstrated through hardware experiments. The hardware experimental results highlight the strengths and limitations of each control strategy, providing insights into their applicability for complex nonlinear MIMO systems. The findings underscore the superior performance of MPC in handling multi-variable interactions and constraints, making it a robust choice for advanced control applications in industrial processes.
Patel et al. (Wed,) studied this question.
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