Iterative Learning Control Temperature Control system of Room using MATLAB

Introduction

MATLABSolutions demonstrate In this task we are going to design In this project Iterative Learning Control (ILC) is a control approach for systems that do repetitive tasks. Robot arm manipulators, chemical batch operations, and reliability testing rigs are examples of systems that work in a repeated manner. Each of these jobs requires the system to repeat the same operation with great accuracy over and over again. The goal of this operation is to correctly monitor a given reference signal r(t) across a finite time interval. The basic principle behind iterative learning control is to take advantage of the fact that the controlled system will repeat the same operation multiple times. It will therefore be able to gradually enhance the control system's performance by selecting the input signal for the next operation based on the outcomes of the previous operation.

The control of industrial robots is the major application for ILC, and many types of actual or simulated robots are utilized as test cases in a vast number of papers. Convergence, or the repeated updating of the input signal converges to a signal with high performance, is a key concern when using ILC. These requirements, however, were too limiting, and a lot of time and effort was put into establishing more realistic circumstances.

This report represents the design of the iterative learning control algorithm for the temperature control of room, since room is subjected to repeating pattern of disturbance, ILC algorithm significantly improve performance. We first model the thermal model for the room then design ILC approach that converge in iterative domain.

Theory

Repetition helps the system to increase tracking accuracy by learning the essential input needed to track the reference precisely from repetition to repetition. The learning process leverages information from past repeats to enhance the control signal, allowing for repeated discovery of an appropriate control action. Although the internal model concept produces circumstances that allow for flawless tracking, the control algorithm's architecture still permits numerous options to be made to fit the application.