Sliding mode optimal control for linear systems

Rodriguez‐Ramirez, Pablo; Ferrara, Antonella; Calderon-Alvarez, Dario

doi:10.1016/j.jfranklin.2011.05.010

Cited by 34 publications

(30 citation statements)

References 19 publications

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“…In this simulation, the original linear model used in [12] is adopted as a comparative model as follows:…”

Section: Example 1-comparative Controllermentioning

confidence: 99%

“…There was an optimal control law with a multiphase cost function and the inverse model [8], in which the recovery matrix theory was used to change the matrix in the cost function. On the other hand, the Bolza-Meyer criterion associated with the Hamiltonian function is frequently used to formulate advanced optimal control laws [9][10][11][12][13][14]. In these studies, the Hamiltonian function is used as a basis to formulate new optimal controllers.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, an optimal controller based on criteria such as the Meyer, Bolza-Meyer, HJB and HJI term needs to be improved since the value of definite symmetry matrices (gains) is 1 or less than 1. This value limits both control performances and robustness of the optimal controllers [9][10][11][12][13][14]. This problem becomes more serious when conventional models of optimal control laws are used.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Adaptive Gain of Optimal Sliding Mode Controller for Linear Time-Varying Systems

2019

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In this study, a new optimal control law associated with the sliding mode control is developed for the linear time-varying system based on the Bolza-Meyer criterion. The salient characteristic of the controller proposed in this work is to have adjustable gains in which the gain values can be larger than 1. This leads to the enhancement of control performances with the given cost function. It is noted here that conventional optimal control laws have a constant gain of 1 or less than 1, and hence, control performances such as the convergence speed are not satisfactory. After formulating the proposed optimal control law for linear time-varying systems, several illustrative examples are adopted and control performances were evaluated to show some benefits of the proposed controller. In particular, three crucial index values of control gain index, main input control index and the state index were investigated. Among illustrative examples, one is related to vibration control problem of the vehicle seat suspension system with magnetorheological (MR) damper. This example is specially treated to evaluate the practical applicability of the proposed optimal controller by considering the measured road profiles; two different random road excitations.

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“…In this simulation, the original linear model used in [12] is adopted as a comparative model as follows:…”

Section: Example 1-comparative Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Novel Adaptive Gain of Optimal Sliding Mode Controller for Linear Time-Varying Systems

2019

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“…Researchers applied sliding-mode control as the method with proper performance due to its fundamental property of robustness and invariance to plant model uncertainties and external disturbance which are unavoidable [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Optimal robust decoupled sliding mode control based on a Multi-objective Genetic Algorithm

2013

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Optimal design of the decoupled sliding mode control (SMC) is a great and worthwhile challenge by regarding appropriate design parameters and objective function. In the present study, Genetic Algorithm (GA) is employed as an effectual smart evolutionary algorithm to design optimally the control coefficients of an Inverted Pendulum (IP) and to eliminate tedious and repetitive trial-and-error process. When decoupled SMC is used to address the problem, there has to be a trade-off between the error of the position and the error of the angle. Hence, a Multi-objective Genetic algorithm is used to design optimally the Pareto front of the problem by regarding the errors as objective functions. Moreover, simulation has been done by considering the case with external disturbance and without external disturbance. Then, the results implemented in the MATLAB software environment are contrasted with the experimental results. Numerical results and comparison analysis elucidates the superiority of the optimal robust proposed controller over the traditional decoupled sliding mode controller in terms of attenuating the chattering and actuator variations.

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“…In this paper, having in mind vehicle dynamics control, the design of a new adaptive optimization-based second-order SMC algorithm is addressed. Optimization-based SMC is a topic that has already obtained the attention of researchers in the past years, starting from the seminal book 1 and arriving to more recent publications (see, for instance, other works [38][39][40][41][42][43][44] ). The present work deals with the design of an optimization-based control law combined with an adaption mechanism, giving rise to a new adaptive SMC algorithm.…”

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confidence: 99%

Optimization‐based adaptive sliding mode control with application to vehicle dynamics control

Ferrara

Incremona

Regolin

2018

Intl J Robust & Nonlinear

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Summary This paper presents the design of a new adaptive optimization‐based second‐order sliding mode control algorithm for uncertain nonlinear systems. It is designed on the basis of a second‐order sliding mode control with optimal reaching, with the aim of reducing the control effort while maintaining all the positive aspects in terms of finite‐time convergence and robustness in front of matched uncertainties. These features are beneficial to guarantee good performance in case of vehicle dynamics control, a crucial topic in the light of the increasing demand of semiautonomous and autonomous driving capabilities in commercial vehicles. The new proposal is theoretically analyzed, as well as verified relying on an extensive comparative study, carried out on a realistic simulator of a 4‐wheeled vehicle, in the case of a lateral stability control system.

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Sliding mode optimal control for linear systems

Cited by 34 publications

References 19 publications

A Novel Adaptive Gain of Optimal Sliding Mode Controller for Linear Time-Varying Systems

A Novel Adaptive Gain of Optimal Sliding Mode Controller for Linear Time-Varying Systems

Optimal robust decoupled sliding mode control based on a Multi-objective Genetic Algorithm

Optimization‐based adaptive sliding mode control with application to vehicle dynamics control

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