Design and Application of Enhanced Composite Nonlinear Feedback Control Based on Genetic Algorithm

Ma, Jiawei; Chen, Hui; Sun, Weijie; Yeow, John T. W.

doi:10.23919/chicc.2018.8483940

Cited by 5 publications

(2 citation statements)

References 18 publications

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“…GA [38] is a random, global searching, and populationbased optimization method. After decades of research and development, GA is known as a kind of effective and robust optimization method which can be employed to solve a variety of optimization problems [39][40][41], including problems in which the objective function is discontinuous, nondifferentiable, stochastic, or highly nonlinear. In this study, GA is used to optimize Λ and σ in the FE algorithm.…”

Section: Parameter Optimizationmentioning

confidence: 99%

Actuator Fault Estimation for Vehicle Active Suspensions Based on Adaptive Observer and Genetic Algorithm

Jin

Xue

2019

Shock and Vibration

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This paper is concerned with the problem of actuator fault estimation (FE) for vehicle active suspension systems. First, the fast FE approach, which combines the output error term with its derivative term in the FE algorithm, is extended to the active suspension system with actuator fault and external disturbance input. Then, considering three typical kinds of actuator faults, i.e., constant gain change fault, drift fault, and stuck fault, genetic algorithm (GA) is employed to optimize the adjustable parameters in the FE algorithm, which are usually determined by trials. Finally, simulation results of FE and fault-tolerant control (FTC) are presented to illustrate the effectiveness and applicability of the proposed FE method.

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Section: Parameter Optimizationmentioning

confidence: 99%

Actuator Fault Estimation for Vehicle Active Suspensions Based on Adaptive Observer and Genetic Algorithm

Jin

Xue

2019

Shock and Vibration

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“…Likewise, more studies have addressed such a problem as selecting parameters, not the tuning one; for instance, the trial and error methods [6,23] or poles placement [2,10,29,30]. Besides, in distinct investigations from others [31][32][33], the CNF controller have been tuned by a minimization such as Hooke-Jeeves algorithm (HJA), genetic algorithm (GA), and LMI-based minimization to improve the transient performance. Despite their popularity, the HJA and GA are traditional approaches.…”

Section: Introductionmentioning

confidence: 99%

An innovative algorithm for tuning of composite nonlinear feedback control in continuous‐time systems

Vazani

Ghaffari

2022

Asian Journal of Control

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The transient response improvement is the most crucial feature of the composite nonlinear feedback (CNF) controllers. This study proposes a novel CNF tuning method for systems subject to saturation. To achieve the goals, the linear part is optimally obtained via a performance index and the linear matrix inequality (LMI). Then, employing the passivity property, a heuristic way is suggested to adjust the nonlinear term. Thus, the automatic and online features would be the key novelties of this algorithm compared with the offline, trial and error, or nonautomatic ones. Some systems are simulated to evaluate the technique and compare with the existing methods. The outcomes confirm that the proposed tuning yields outstanding improvement concerning the aforementioned systems.

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LMI-Based Composite Nonlinear Feedback Tracker for Uncertain Nonlinear Systems With Time Delay and Input Saturation

et al. 2022

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This study proposes a composite nonlinear feedback approach for the robust tracking control problem of uncertain nonlinear systems with input saturation, Lipschitz nonlinear functions, multivariable time-delays, and disturbances. The composite nonlinear feedback technique includes two components: a linear feedback portion constructed in such a way that it changes the damping ratio so as to speed up the system's response. A nonlinear feedback controller is designed to further increment the damping ratio in a way that it ensures the tracking whilst reducing the overshoot created by the linear portion. By creating a suitable Lyapunov functional and by using the linear matrix inequality (LMI) approach, the LMI conditions are determined to guarantee system stability and obtain the required design parameters. The performance of the proposed approach is assessed using a simulation study of a two-dimensional system along with a Chua's circuit system. The advantages of the proposed approach are its less-restrictive assumptions, improved transient performance, and steady-state precision.INDEX TERMS Composite nonlinear feedback; input saturation; linear matrix inequality; robust tracking; time delay.

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Design and Application of Enhanced Composite Nonlinear Feedback Control Based on Genetic Algorithm

Cited by 5 publications

References 18 publications

Actuator Fault Estimation for Vehicle Active Suspensions Based on Adaptive Observer and Genetic Algorithm

Actuator Fault Estimation for Vehicle Active Suspensions Based on Adaptive Observer and Genetic Algorithm

An innovative algorithm for tuning of composite nonlinear feedback control in continuous‐time systems

LMI-Based Composite Nonlinear Feedback Tracker for Uncertain Nonlinear Systems With Time Delay and Input Saturation

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