This paper aims at developing a robust gain-scheduled proportional-integral-derivative (PID) control design method for a linear-parameter-varying (LPV) system. It is recognized in the literature that robust fixed-order controller design can be formulated as a feasibility problem of a bilinear matrix inequality (BMI) constraint. Unfortunately, the search for a feasible solution of a BMI constraint is a NP hard problem in general. A common way to solve this dilemma is to apply a linearization method, such as variable change method or congruence transformation, to transform the BMI into LMI. The applicability of the linearization method depends on the specific structure of the problem at hand and cannot be generalized. This paper formulates the gain-scheduled PID controller design as a feasibility problem of a quadratic matrix inequality (QMI) constraint, which covers the BMI constraint as a special case. An augmentation of the newly developed sequential LMI optimization method is proposed to search for a feasible solution of a QMI constraint iteratively. In the application part, a vehicle lateral control problem is presented to demonstrate the applicability of the proposed algorithm to a real-world output feedback control design.
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ASME 2017 Dynamic Systems and Control Conference
October 11–13, 2017
Tysons, Virginia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5828-8
PROCEEDINGS PAPER
A Sequential LMI Approach for Design of a Gain-Scheduled PID Controller for LPV Systems
Yan Wang,
Yan Wang
University of Minnesota, Minneapolis, MN
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Rajesh Rajamani
Rajesh Rajamani
University of Minnesota, Minneapolis, MN
Search for other works by this author on:
Yan Wang
University of Minnesota, Minneapolis, MN
Rajesh Rajamani
University of Minnesota, Minneapolis, MN
Paper No:
DSCC2017-5199, V002T05A002; 10 pages
Published Online:
November 14, 2017
Citation
Wang, Y, & Rajamani, R. "A Sequential LMI Approach for Design of a Gain-Scheduled PID Controller for LPV Systems." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications. Tysons, Virginia, USA. October 11–13, 2017. V002T05A002. ASME. https://doi.org/10.1115/DSCC2017-5199
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