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

Citation

Zayed AS & Hussain A (2003) Novel non-linear PID based multiple-controller incorporating a neural network learning sub-model. In: 7th International Multi Topic Conference, 2003. INMIC 2003. 7th International Multi Topic Conference, 2003. INMIC 2003, Islamabad, Pakistan, 08.12.2003-09.12.2003. Piscataway, NJ: IEEE, pp. 283-289. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1416729&refinements%3D4281509371%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A30640%29; https://doi.org/10.1109/INMIC.2003.1416729

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.