Switching LPV controller design under uncertain scheduling parameters

Zhao, Pan; Nagamune, Ryozo

doi:10.1016/j.automatica.2016.10.026

Cited by 54 publications

(47 citation statements)

References 21 publications

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“…For an illustration, see fig. 1 in the work of Zhao et al, 44 in which S (j,k) 1 denote the switching surfaces specifying the one-directional move of scheduling parameter in 1 direction from subset Θ (j) to Θ (k) . We define two regions Θ (j) and Θ (k) to be adjacent in l direction if the following conditions are satisfied:…”

Section: Problem Definitionmentioning

confidence: 99%

“…By introducing two independent families of parameter-dependent Lyapunov matrices and a family of auxiliary variables, less conservative results are obtained in comparison with some available methods. 44 A family of quadratic Lyapunov functions is utilized without the requirement for having the time-derivatives of the measurement errors. The merit of the proposed method lies in its considerably less conservativeness in comparison with the available methods.…”

Section: Introductionmentioning

confidence: 99%

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Improved multiobjective switching gain‐scheduled controller synthesis exploiting inexact scheduling parameters

Yavari

Sadeghzadeh

Shamaghdari

2020

Intl J Robust & Nonlinear

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In this article, the design problem of switching gain-scheduled output-feedback (SGSOF) controller with mixed  2 ∕ ∞ performance exploiting inexact scheduling parameters for continuous-time linear parameter-varying (LPV) systems is tackled. The absolute and proportional uncertainties on the scheduling parameters are considered. All the system matrices of the LPV plant are supposed to have polynomial dependency of arbitrary degree on the scheduling parameters. By exploiting hysteresis switching law and utilizing two independent families of parameter-dependent Lyapunov matrices and a family of slack variables, introducing additional degrees of freedom, performance improvement is achieved. A design approach, involving a two-step algorithm, is proposed in terms of solutions to a set of parameter-dependent linear matrix inequalities (LMIs) including parameter searches for two scalar values. The merit of the proposed method lies in its less conservativeness in comparison with the available approaches in the literature. Numerical studies are carried out to demonstrate the effectiveness of the presented method.

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Section: Problem Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved multiobjective switching gain‐scheduled controller synthesis exploiting inexact scheduling parameters

Yavari

Sadeghzadeh

Shamaghdari

2020

Intl J Robust & Nonlinear

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“…In the traditional approach, the worst-case L 2 -gain bound of the closed-loop system for all the subsets is used as the cost function. 6,7,8,10 With the existence conditions stated in Lemma 1, the traditional SLPV synthesis approach can be summarized as follows.…”

Section: Design Of Slpv Controllers With Improved Local Performancementioning

confidence: 99%

“…6,7 The SLPV control using inexact measurement of scheduling parameters was also investigated. 8 The advantages of SLPV control have been demonstrated through various applications. [9][10][11][12] The performance of an LPV control system is usually characterized by the upper bound of the L 2 -gain of the closed-loop system.…”

Section: Introductionmentioning

confidence: 99%

Switching linear parameter‐varying control with improved local performance and optimized switching surfaces

Zhao

Nagamune

2018

Intl J Robust & Nonlinear

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This paper presents a novel approach to designing switching linear parametervarying (SLPV) controllers with improved local performance and an algorithm for optimizing switching surfaces to further improve the performance of the SLPV controllers. The design approach utilizes the weighted average of the local L 2 -gain bounds (representing the local performance) as the cost function to be minimized, whereas the maximum of the local L 2 -gain bounds (representing the worst-case performance over all subsets) is bounded with a tuning parameter. The tuning parameter is useful for taking the trade-off between the local performance and the worst-case performance. An algorithm based on the particle swarm optimization is introduced to optimize the switching surfaces of an SLPV controller. The efficacy of the proposed SLPV controller design approach and switching surface optimization algorithm is demonstrated on both a numerical example and a physical example of air-fuel ratio control of an automotive engine.

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“…For this reason, Lyapunov-based approaches were developed, allowing taking into account constraints on the rate of variation of the varying parameters (Gahinet et al, 1996). A high number of related results published in the last few years shows that the development of efficient approaches to the design of gain-scheduled controllers for LPV systems (Zhao and Nagamune, 2017;Nguyen et al, 2018;Chitraganti et al, 2017) and for fault diagnosis (López-Estrada et al, 2015;Zhou et al, 2018) is still a hot research topic.…”

Section: Introductionmentioning

confidence: 99%

An Lmi–Based Heuristic Algorithm for Vertex Reduction in LPV Systems

Sanjuan

Rotondo

Nejjari

et al. 2019

International Journal of Applied Mathematics and Computer Science

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The linear parameter varying (LPV) approach has proved to be suitable for controlling many non-linear systems. However, for those which are highly non-linear and complex, the number of scheduling variables increases rapidly. This fact makes the LPV controller implementation not feasible for many real systems due to memory constraints and computational burden. This paper considers the problem of reducing the total number of LPV controller gains by determining a heuristic methodology that combines two vertices of a polytopic LPV model such that the same gain can be used in both vertices. The proposed algorithm, based on the use of the Gershgorin circles, provides a combinability ranking for the different vertex pairs, which helps in solving the reduction problem in fewer attempts. Simulation examples are provided in order to illustrate the main characteristics of the proposed approach.

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Switching LPV controller design under uncertain scheduling parameters

Cited by 54 publications

References 21 publications

Improved multiobjective switching gain‐scheduled controller synthesis exploiting inexact scheduling parameters

Improved multiobjective switching gain‐scheduled controller synthesis exploiting inexact scheduling parameters

Switching linear parameter‐varying control with improved local performance and optimized switching surfaces

An Lmi–Based Heuristic Algorithm for Vertex Reduction in LPV Systems

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