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Multi-Variable and Multi-Objective Gain-Scheduled Control Based on Youla-Kucera Parameterization: Application to Autonomous Vehicles
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This paper presents a Youla-Kucera based interpolation between a set of
Linear Parameter-Varying (LPV) controllers, each one being a
gain-scheduled of Linear Time-Invariant (LTI) controllers designed
separately for different operating points. The gain-scheduling is
achieved based on Youla-Kucera (YK) parameterization. A generalized
LPV-YK control structure is designed to interpolate between various LPV
controllers. The closed-loop system is proved to guarantee the quadratic
stability for any continuous/discontinuous interpolating signals in
terms of a set of Linear Matrix Inequalities (LMIs). The proposed method
can help multi-variable and multi-objective systems to achieve high
performances at different operating conditions and different critical
situations regardless of the interpolation rate. A numerical example is
simulated to show the importance of the proposed method to achieve
different objectives for lateral control of autonomous vehicles. In
addition, the approach has been tested on a real Renault ZOE vehicle to
validate its real performance, and compare it with a standard polytopic
LPV controller.
Title: Multi-Variable and Multi-Objective Gain-Scheduled Control Based on Youla-Kucera Parameterization: Application to Autonomous Vehicles
Description:
This paper presents a Youla-Kucera based interpolation between a set of
Linear Parameter-Varying (LPV) controllers, each one being a
gain-scheduled of Linear Time-Invariant (LTI) controllers designed
separately for different operating points.
The gain-scheduling is
achieved based on Youla-Kucera (YK) parameterization.
A generalized
LPV-YK control structure is designed to interpolate between various LPV
controllers.
The closed-loop system is proved to guarantee the quadratic
stability for any continuous/discontinuous interpolating signals in
terms of a set of Linear Matrix Inequalities (LMIs).
The proposed method
can help multi-variable and multi-objective systems to achieve high
performances at different operating conditions and different critical
situations regardless of the interpolation rate.
A numerical example is
simulated to show the importance of the proposed method to achieve
different objectives for lateral control of autonomous vehicles.
In
addition, the approach has been tested on a real Renault ZOE vehicle to
validate its real performance, and compare it with a standard polytopic
LPV controller.
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