Smooth Switching LPV Dynamic Output-feedback Control

He, Tianyi; Zhu, Guoming; Swei, Sean Shan‐Min

doi:10.1007/s12555-019-0088-3

Cited by 6 publications

(4 citation statements)

References 20 publications

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“…Apart from the YK concept, there has been a wide range of research to develop an LPV switching controller (see for instance 20,34 ). Recent extensions have mainly aimed to decrease the design complexity and conservatism, 35 and to provide smooth switching. 36 However, the LPV switching studies are still conservative due to the re-design of the local LPV controllers by proposed LMIs, in addition to some limitations that restrict the switching signals (e.g., hysteresis switching, switching with average dwell-time, etc.).…”

Section: Motivation and Contributionmentioning

confidence: 99%

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Multi‐variable and multi‐objective gain‐scheduled control based on Youla‐Kucera parameterization: Application to autonomous vehicles

Atoui,

Sename,

Milanes

et al. 2024

Intl J Robust & Nonlinear

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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.

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Section: Motivation and Contributionmentioning

confidence: 99%

“…) −1 (35) Since the input-output performance of Q and Q is similar (according to the state transformation concept), Reference 28,(35) can be written as…”

Section: Application To Autonomous Vehiclesmentioning

confidence: 99%

Multi‐variable and multi‐objective gain‐scheduled control based on Youla‐Kucera parameterization: Application to autonomous vehicles

Atoui,

Sename,

Milanes

et al. 2024

Intl J Robust & Nonlinear

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show abstract

“…Apart from the YK concept, there has been a wide range of research to develop an LPV switching controller (see for instance 13 , 26 ). Recent extensions have mainly aimed to decrease the design complexity and conservatism 27 , and to provide smooth switching 28 . However, the LPV switching studies are still conservative due to the re-design of the local LPV controllers by proposed LMIs, in addition to some limitations that restrict the switching signals (e.g.…”

Section: Motivation and Contributionmentioning

confidence: 99%

Multi-Variable and Multi-Objective Gain-Scheduled Control Based on Youla-Kucera Parameterization: Application to Autonomous Vehicles

Atoui

Sename

Milanés³

et al. 2023

Preprint

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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.

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“…Qu Shen [21] designed switched gain-scheduling LPV controllers with hysteresis switching logic using the Linear Matrix Inequality (LMI) convex optimization approach based on a switched LPV model. Tianyi He [22] proposed an innovative design of smooth-switching LPV Dynamic Output-Feedback (DOF) controllers and designed a family of LPV controllers on each subregion, as well as switching smoothness among adjacent subregions. Luca Cavanini [23] designed an MPC to drive a UAV based on the LPV model using a subspace identification technique.…”

Section: Introductionmentioning

confidence: 99%

Gain-Scheduled Model Predictive Control for a Commercial Vehicle Air Brake System

Deng

2021

Processes

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This paper presents a control-oriented Linear Parameter-Varying (LPV) model for commercial vehicle air brake systems with the electro-pneumatic proportional valve based on the nonlinear mathematical model, a set of discrete-time linearized models at different target pressures with the q-Markov Cover system identification method. The scheduled parameters for the LPV model were the brake chamber pressure, which was controlled by the electro-pneumatic proportional valve. On the basis of the LPV model, a family of Model Predictive Control (MPC) controllers with a Kalman filter was designed at each operation point. Then, the gain-scheduled MPC was designed over the entire operating range with the switched strategy, which was validated by experimental data. Furthermore, compared with the PID controller, the performance of the system was improved with a gain-scheduled MPC controller.

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Smooth Switching LPV Dynamic Output-feedback Control

Cited by 6 publications

References 20 publications

Multi‐variable and multi‐objective gain‐scheduled control based on Youla‐Kucera parameterization: Application to autonomous vehicles

Multi‐variable and multi‐objective gain‐scheduled control based on Youla‐Kucera parameterization: Application to autonomous vehicles

Multi-Variable and Multi-Objective Gain-Scheduled Control Based on Youla-Kucera Parameterization: Application to Autonomous Vehicles

Gain-Scheduled Model Predictive Control for a Commercial Vehicle Air Brake System

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