PI Controller Design for a Coupled Tank System Using LMI Approach: An Experimental Study

Abstract

This paper presents a Linear Matrix Inequality (LMI) tuned PI controller for real-time control of a coupled-tank liquid level system. The proposed approach is based on the transformation of the PI controller design problem to a state feedback controller design problem, which is further solved using convex optimization approach. The model of the coupled tank system has been developed based on system identification technique that employs least square error method (LS) for parameter estimation. The proposed controller algorithm has been applied on the identified model. The performance of the proposed control algorithm has been compared with that of a Ziegler-Nichols tuned PI controller. From both the simulation as well as the experimental results, it is observed that the performance of the proposed PI control is more efficient than the widely used Ziegler-Nichols approach.

Design of 3×3 Multi Input Multi Output (MIMO) Decoupling on Coupled Tank System with PID Controller

“…Closedloop simulation requires a controller on a 3x3 MIMO model system circuit. The controller used in this research is Proportional Integral Derivative (PID) with the Ziegler-Nichols method (Ranjan et al, 2015). Table 2 is the result of tuning the controller parameters in each pairing.…”

A model-based tracking control scheme for nonlinear industrial processes involving joint unscented Kalman filter

“….. , N m } with N i > 0represents a set of multiplying factors used online for performance improvement in a perturbed/disturbed operating condition. The upper and lower limits u max and u min of the saturation blocks included in the scheme (Figure 2) are decided based on the physical strength of the actuators (Skogestad & Postlethwaite, 1996). Note here that the JUKF algorithm is executed on a discrete-time basis since both in simulation and real-time implementation, all input and output data are generated or measured at discrete time steps.…”

“…Apart from that, Joint EKF (JEKF) and Dual EKF (DEKF) are used for joint or sequential estimation of both states and parameters (Haykin, 2001). For recent of applications MPC, SMPC and other model-based control techniques, the articles Ma, Matusko, and Borrelli (2015), Bhadra, Panda, Bhowmick, Goswami, and Panda (2019), Wang, Chen, Ren, and Zhao (2018), Yuan, Dai, Wei, andMing (2020), Soumya Ranjan, Bidyadhar, andSubhojit (2017), Velarde, Maestre Ishii, and Negenborn (2018), Ringbeck, Garbade, and Sauer (2020), Liu and Guo (2021), Guo and Zhao (2022), Liu (2022), andGao et al (2020) can be referred.…”

Model Identification and Level Control of Coupled Tanks System

“…So, several control algorithms have been proposed, implemented and adopted over the past few decades and the quest for new development of CT control still continues. Smart controller based on reinforcement learning algorithm in [1], linear machine inequality (LMI) tuned PI controller in [4], neural network based predictive controller in conjunction with PID controller in [5] which is further extended with simplified additive autoregressive exogenous models in [6], LabVIEW based PID controller in [7], Simulink-PLC based level control in [8], tuned PID controller in [9]. In In the work of [2] the performance of model predictive, MPC,PI and PI-plusfeedforward controllers are compared and the performance of MPC are more acceptable in terms of disturbance handling and time response criteria.…”