We compare the performance of proportional-integral-derivative (PID) control, linear model predictive control (LMPC), and nonlinear model predictive control (NMPC) for a physical setup of the quadruple tank system (QTS).

A multivariable laboratory process that consists of four interconnected water tanks is presented. The linearized dynamics of the system have a multivariable zero that is possible to move along the real axis by changing a valve.

The quadruple tank (QT) system consists of four interacting tanks and can switch between the minimum and non-minimum phase behavior with changes in the positions of pump valves and is considered a benchmark control problem.

In this article, the design of an advanced MPC controller and a PID control have been proposed and implemented in a programmable logic controller (PLC) for a quadruple process of tanks, developing a comparison between the 2 controllers.

Jan 1, 2014 · The objective of the work is to design and implement a different form of PID controller structure and robust control analysis for a multivariable four tank level control process. The designs are demonstrated on a quadruple tank …

This research compared three reinforcement learning (RL) algorithms (SAC, PPO, DDPG) to traditional PID control for water level control in single-tank and quadruple-tank systems. The RL algorithms were trained using MATLAB's Reinforcement Learning Toolbox and tested in a Simulink simulation.

Abstract: The objective of this paper is to implement different control strategies on a quadruple tank system and discuss about its interacting nature. The system in consideration is a quadruple tank system where input flow rates of two tanks are considered as manipulated variables and liquid level in the tanks are considered as controlled ...

Dec 9, 2022 · We compare the performance of proportional-integral-derivative (PID) control, linear model predictive control (LMPC), and nonlinear model predictive control (NMPC) for a physical setup of the quadruple tank system (QTS).

Control design for a quadruple-tank system with JuliaSim Control. In this example, we will implement several different controllers of increasing complexity for a nonlinear MIMO process, starting with a PID controller and culminating with a nonlinear MPC controller with …

This code simulates a system of four interconnected tanks (as shown in the image above) and generates data representing the measurements available from the sensors placed in each tank. Here's a brief description of the system and data generation process: