Novel non-linear PID based multiple-controller incorporating a neural network learning sub-model

Zayed, A.S.; Hussain, A.

Abstract

The paper proposes a new non-linear adaptive PID based multiple-controller incorporating a neural network learning sub-model. The unknown non-linear plant is represented by an equivalent model consisting of a linear time-varying sub-model plus a non-linear neural-networks based learning sub-model. The proposed multiple-controller methodology provides the designer with a choice of using either a conventional PID self-tuning controller, a PID based pole-placement controller, or a newly proposed PID based pole-zero placement controller through the flick of a switch. Simulation results using a non-linear plant model demonstrate the effectiveness of the proposed multiple-controller, with respect to tracking set-point changes with the desired speed of response, penalising excessive control action, and its application to non-minimum phase and unstable systems.

Citation

Zayed, A., & Hussain, A. (2003, December). Novel non-linear PID based multiple-controller incorporating a neural network learning sub-model. Presented at 7th International Multi Topic Conference, 2003. INMIC 2003., Islamabad, Pakistan

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 7th International Multi Topic Conference, 2003. INMIC 2003.
• Start Date: Dec 8, 2003
• End Date: Dec 9, 2003
• Online Publication Date: Apr 11, 2005
• Publication Date: 2003
• Deposit Date: Oct 17, 2019
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 283-289
• Book Title: 7th International Multi Topic Conference, 2003. INMIC 2003.
• ISBN: 0-7803-8183-1
• DOI: https://doi.org/10.1109/INMIC.2003.1416729
• Keywords: three-term control, nonlinear control systems, neural nets, learning (artificial intelligence), adaptive control, time-varying systems, pole assignment, zero assignment, stability, neurocontrollers
• Public URL: http://researchrepository.napier.ac.uk/Output/1793736