Nonlinear control for a class of hydraulic servo system

Yu, Hong; Feng, Zhengjin; Wang, Xuyong

doi:10.1631/jzus.2004.1413

Cited by 33 publications

(17 citation statements)

References 10 publications

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“…A robust state-feedback controller is designed by employing backstepping design technique such that the system output tracks a given signal and all signals in the closedloop system remain bounded [9]. The backstepping design strategy also used to develop a Lyapunov-based nonlinear controller for a hydraulic servo system which incorporates load, hydraulic, and valve dynamics in the design process [10].…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System

Rozali

Rahmat

Husain

2014

Journal of Applied Mathematics

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This paper presents backstepping controller design for tracking purpose of nonlinear system. Since the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA) and particle swarm optimization (PSO) techniques are used to optimise these parameters in order to achieve a predefined system performance. The performance is evaluated based on the tracking error between reference input given to the system and the system output. Then, the efficacy of the backstepping controller is verified in simulation environment under various system setup including both the system subjected to external disturbance and without disturbance. The simulation results show that backstepping with particle swarm optimization technique performs better than the similar controller with gravitational search algorithm technique in terms of output response and tracking error.

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Section: Introductionmentioning

confidence: 99%

Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System

Rozali

Rahmat

Husain

2014

Journal of Applied Mathematics

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“…It can make the actuator to complete the appropriate actions in accordance with the requirements by controlling the pressure, flow rate and flow direction of working fluid. Hong has summarized the characteristics of the various electro-hydraulic servo systems, and indicated that it can realize complex program control and remote control by using electrical signals as well as has higher control precision by using feedback [1]. At the same time, Li and Ding have studied the position servo control of the electro-hydraulic proportional system.…”

Section: Introductionmentioning

confidence: 99%

BP-PID Control for Electro-hydraulic Proportional Position Servo System

Zheng¹,

Min²,

Yang³

et al. 2013

Int. J. Onl. Eng.

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Abstract-The electro-hydraulic proportional position servo system is a kind of highly non-linear and time-varying system as well as parameter uncertainties. It is often difficult to achieve satisfactory control results with the traditional control methods. Considering that the adaptive neural network PID control method has the characteristics of online learning and adjustment PID control parameters adaptively, this paper puts forward to adopt BP-PID control method for the position servo control of electro-hydraulic proportional system. An online adaptive BP-PID controller is designed. The simulation model of the system is established based on Simulink platform. The step response and Sinusoidal tracking characteristics are researched through simulations and experiments. The results show that BP-PID has a strong ability of online learning and self-tuning PID parameters. Compared with the traditional PID control method, the BP-PID control has strong self-adaptability and robustness, and can significantly improve the step response speed and tracking control precision.

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“…For instance, FitzSimons and Palazzolo [8] used linear control theory and Vossoughi and Donath [9] utilized feedback linearization in their respective hydraulic control problems. Recently, quantitative feedback theory, in Pachter et al [2] and Niksefat and Sepehri [10], and backstepping design technique (Yu et al, [11]) have been used to create robust controllers. However, it is in Alleyne and Hedrick [3] where nonlinear adaptive control is applied in the presence of parametric uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Parameter Identification for Electrohydraulic Valvetrain Systems

Gray¹,

Krstić

Chaturvedi

2011

Journal of Dynamic Systems, Measurement, and Control

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We consider an electrohydraulic valve system (EHVS) model with uncertain parameters that may possibly vary with time. This is a nonlinear third order system consisting of two clearly separated subsystems, one for the piston position and the other for the chamber pressure. The nonlinearities involved are flow-pressure characteristics of the solenoid valves, the pressure dynamics of the chamber due to varying volume, and a variable damping nonlinearity. We develop a parametric model that is linear in the unknown parameters of the system using filtering. We deal with a nonlinear parameterization in the variable damping term using the Taylor approximation. We design a parameter identifier, which employs a continuous-time unnormalized least-squares update law with a forgetting factor. This update law exponentially converges to the true parameters under a persistence of excitation condition, which is satisfied due to the periodic regime of operation of EHVS. We present simulation results that show good following of unknown parameters even with the presence of sensor noise.

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Nonlinear control for a class of hydraulic servo system

Cited by 33 publications

References 10 publications

Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System

Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System

BP-PID Control for Electro-hydraulic Proportional Position Servo System

Parameter Identification for Electrohydraulic Valvetrain Systems

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