Design of Stable Model Reference Adaptive System via Lyapunov Rule for Control of a Chemical Reactor

Abstract

In this paper, two model reference adaptive control strategy including MIT rule and Lyapunov rule are used to design iterative learning controllers for a chemical-reactor system with uncertain parameters, initial output resetting error and input disturbance. The learning controller compensates for the unknown parameters, uncertainties, and non-linearity using adaptation law which updates control parameters. It is shown that the internal signals remain bounded if we use a Lyapunov base algorithm, but the algorithm via MIT rule can!t guarantee the stability of system in all conditions. The output tracking error will converge to a profile which can be tuned by design parameters and the convergence speed is improved if the adaptation gain is large. The proposed control algorithm was simulated using MATLAB / Simulink software package to validate the performance of designed algorithm.

We are known for integrity, innovation, and our commitment to delivering the best for our clients. Everything we do is about empowering you to achieve your goals through value-added services, products and collaboration. Our solutions are tailored to your needs, integrated and agile so that they grow and adapt with you. We partner with our clients to create pioneering solutions that power possibilities for a better tomorrow.

Jafar Saleh

Sr. Automation & Control Engineer

My research interests include Industrial automation, Artificial intelligence and Robotics.