Model-free chaos control based on AHGSA for a vibro-impact system

Wei, Xiaolin; Li, Ningzhou; Ding, Wangcai; Zhang, Cao-hui

doi:10.1007/s11071-018-4397-5

Cited by 11 publications

(7 citation statements)

References 9 publications

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“…However, most researches on chaos synchronization of HPSs don't consider this constraint. In this paper, to make the developed chaos synchronization technique more practical, the control input is considered to satisfy the following box constraint u j j � u max (5) where the variable u max > 0 represents the upper bound of the input. We aim to find a suitable controller such that…”

Section: Formulation Of the Input-constrained Chaos Synchronization Of Hpssmentioning

confidence: 99%

“…Many mechanical systems in engineering have been found able to exhibit chaotic motion in the last two decades, such as electro-mechanical gyrostat system, 1,2 atomic force microscope, 3,4 vibro-impact system with clearance, 5 centrifugal flywheel governors 6 and horizontal platform system (HPS), [7][8][9][10][11][12][13][14][15][16][17][18] etc. For a mechanical system, if it continuously operates in a state of chaotic motion, the resulted large broad-band dynamic response is prone to increase the likelihood of fatigue failure and thus shorten the structure lifetime.…”

Section: Introductionmentioning

confidence: 99%

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Input-constrained chaos synchronization of horizontal platform systems via a model predictive controller

Wang

Liu

Peng

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part C:

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Horizontal platform systems are mechanical systems that can exhibit both periodic and chaotic behaviour. Various control techniques have been developed to solve their chaos synchronization. However, the avoidance of control saturation is rarely considered in existing control techniques. In this paper, a model predictive controller is developed to address the input-constrained chaos synchronization of horizontal platform systems. To meet the requirements of computational efficiency, the highly efficient symplectic pseudospectral method is taken as the core solver of the model predictive controller. Two methods to impose the terminal boundary condition are considered. And two indices, i.e., the approximate synchronization time and the synchronization-consumed energy, are proposed to evaluate the synchronization performance. Numerical simulations demonstrate that the developed model predictive controller can achieve faster synchronization while owns better robustness under various kinds of external disturbances when compared to several feedback controllers.

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Section: Formulation Of the Input-constrained Chaos Synchronization Of Hpssmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Input-constrained chaos synchronization of horizontal platform systems via a model predictive controller

Wang

Liu

Peng

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

show abstract

“…Lee et al (2006) proposed a strategy based on the idea of feedback control, thus realizing the control of a class of collision oscillator positions. Wei et al (2018aWei et al ( , 2018b proposed a model-free chaos control method based on AHGSA for the chaotic motion control of a singledegree-of-freedom rigid vibro-impact system with clearance. Shen et al (2018) studied the control problem of grazing induced chaos in single-degree-of-freedom impact oscillator, and used a real-time discrete-time feedback control strategy to control them as periodic motions.…”

Section: Introductionmentioning

confidence: 99%

“…Souza et al (2007) investigated a damping control method for the chaotic motion of a class of single-degree-of-freedom vibro-impact system by varying the damping coefficients of the system to achieve the control of its chaotic motion. Wei, Li, Ding, and Zhang (2018a, 2018b) used a ridge-wave neural network optimized by a dynamic multi-subgroup gravitational search algorithm to achieve chaotic motion control. Lee et al (2006) proposed a strategy based on the idea of feedback control, thus realizing the control of a class of collision oscillator positions.…”

Section: Introductionmentioning

confidence: 99%

Two-parameter cooperative intelligent optimal control of chaotic motion for a vibro-impact system with soft constraint

Wei

ZHOU

et al. 2022

Journal of Vibration and Control

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For the chaotic motion control of a single-degree-of-freedom vibro-impact system with soft constraint, two-parameter cooperative intelligent optimal control method based on LRS-QPSO (i.e., Local Rotational Search Quantum Particle Swarm Optimization) algorithm optimization SVM (i.e., Support Vector Machines) was proposed. Firstly, in the parameter plane ( ω,ζ), the motion distribution of the system and the change of the maximum Lyapunov exponent is obtained by numerical simulation, and the correlation between parameters change and the transition from chaotic motion to periodic motion is analyzed. Secondly, by introducing ω and ζ into the construction of the input variables of the SVM controller, a chaotic motion two-parameter cooperative intelligent optimal control strategy is proposed to meet the requirements of expected control objectives. Therefore, by the virtue of nonlinear mapping characteristics of SVM, the combined effects of ω and ζ on the dynamic state transition of the system can be reflected in the output variables of the controller. Finally, with single parameter ω and single parameter ζ as the research object, the bifurcation diagram, Lyapunov exponential spectrum, and controlled periodic motion orbit diagram are analyzed, and the advantages of two-parameter cooperative intelligent optimal control are compared and analyzed.

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“…Li et al (2009) used the damping coefficient feedback control strategy proposed by De Souza and others as the reference to realize the chaotic motion control of two-degree-of-freedom vibro-impact system. A model-free chaos control method based on the AHGSA algorithm was proposed (Wei et al, 2018), and the chaotic motion of a single-degree-of-freedom rigid vibro-impact system with clearance was controlled to the desired trajectory.…”

Section: Introductionmentioning

confidence: 99%

Chaotic motion control of a vibro-impact system based on data-driven control method

Wei

Ding

2021

Journal of Vibration and Control

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For the chaotic motion control of a vibro-impact system with clearance, the parameter feedback chaos control strategy based on the data-driven control method is presented in this article. The pseudo-partial-derivative is estimated on-line by using the input/output data of the controlled system so that the compact form dynamic linearization (CFDL) data model of the controlled system can be established. And then, the chaos controller is designed based on the CFDL data model of the controlled system. And the distance between two adjacent points on the Poincaré section is used as the judgment basis to guide the controller to output a small perturbation to adjust the damping coefficient of the controlled system, so the chaotic motion can be controlled to a periodic motion by dynamically and slightly adjusting the damping coefficient of the controlled system. In this method, the design of the controller is independent of the order of the controlled system and the structure of the mathematical model. Only the input/output data of the controlled system can be used to complete the design of the controller. In the simulation experiment, the effectiveness and feasibility of the proposed control method in this article are verified by simulation results.

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Model-free chaos control based on AHGSA for a vibro-impact system

Cited by 11 publications

References 9 publications

Input-constrained chaos synchronization of horizontal platform systems via a model predictive controller

Input-constrained chaos synchronization of horizontal platform systems via a model predictive controller

Two-parameter cooperative intelligent optimal control of chaotic motion for a vibro-impact system with soft constraint

Chaotic motion control of a vibro-impact system based on data-driven control method

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