Adaptive velocity synchronization compound control of electro-hydraulic load simulator

“…improve the torque tracking performance of the ELS under external disturbance caused by the actuator's active motion has been a topic of great interest in both academia and industry. Many results have been proposed to improve the torque tracking performance of ELS in the past several decades [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18]. Wang and Jiao [3] developed a compound control scheme, which consists of a synchronization controller and a torque PI controller to suppress the actuator's motion disturbance problem.…”

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confidence: 99%

“…Researchers of ELS have paid more attention to the actuator's motion disturbance in the load simulator, while the friction torque is always neglected in system modeling, which really does exist in practical systems [3,4,10]. Moreover, the actuator motion is only considered an external disturbance, and some algorithms are designed to eliminate the disturbance [3,5,[7][8][9]. In some cases, the actuator's motion does not always hinder the ELS from achieving torque tracking.…”

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confidence: 99%

Torque tracking control of electric load simulator with active motion disturbance and nonlinearity based on T‐S fuzzy model

Pan

Wang

2018

Asian Journal of Control

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This paper develops a high performance nonlinear control method for an electric load simulator (ELS). The tracking performance of the ELS is mainly affected by the actuator's active motion disturbance and friction nonlinearity. First, a nonlinear model of ELS is developed, and then the Takagi-Sugeno fuzzy model is used to represent the friction nonlinearity ofthe ELS. A state observer is constructed to estimate the speed of the load system. For converting the tracking control into a stabilization problem, a new control design called virtual desired state synthesis is proposed to define the internal desired states. External disturbances are attenuated based on an H ∞ criterion and the stability of the entire closed-loop model is investigated using the well-known quadratic Lyapunov function. Meanwhile, the feedback gains and the observer gains are obtained separately by solving a set of linear matrix inequalities (LMIs). Both a simulation and experiment were performed to validate the effectiveness of the developed algorithm. KEYWORDS T-S fuzzy modelH ∞ criterionelectric load simulator (ELS), linear matrix inequalities (LMIs), torque tracking control

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“…4,5 Therefore, how to improve the ELS torque tracking performance has become a research hotspot recently. The ordinary methods adopt the feed-forward compensation using the actuator's position and velocity signals, 6,7 or the dual-loop scheme, 8 but the constructed model cannot wholly describe the friction and backlash nonlinearities, especially the approximation precision shows worse in the practical working conditions, so intelligent controllers with nonlinear characteristics and high precisions have been proposed to substitute the mechanism model. The feed-forward neural networks (NN) with amazing learning ability, parallel computation, and remarkable generalization ability are widely applied to approximate the nonlinear and uncertain system, but they also have the drawbacks of the local minimum and low convergence rate.…”

Section: Introductionmentioning

confidence: 99%

Adaptive complementary fuzzy self-recurrent wavelet neural network controller for the electric load simulator system

Wang

Gao

Hou

et al. 2016

Advances in Mechanical Engineering

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Due to the complexities existing in the electric load simulator, this article develops a high-performance nonlinear adaptive controller to improve the torque tracking performance of the electric load simulator, which mainly consists of an adaptive fuzzy self-recurrent wavelet neural network controller with variable structure (VSFSWC) and a complementary controller. The VSFSWC is clearly and easily used for real-time systems and greatly improves the convergence rate and control precision. The complementary controller is designed to eliminate the effect of the approximation error between the proposed neural network controller and the ideal feedback controller without chattering phenomena. Moreover, adaptive learning laws are derived to guarantee the system stability in the sense of the Lyapunov theory. Finally, the hardware-in-the-loop simulations are carried out to verify the feasibility and effectiveness of the proposed algorithms in different working styles.

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Adaptive velocity synchronization compound control of electro-hydraulic load simulator

Cited by 55 publications

References 17 publications

Adaptive decoupling synchronous control of dissimilar redundant actuation system for large civil aircraft

Adaptive decoupling synchronous control of dissimilar redundant actuation system for large civil aircraft

Torque tracking control of electric load simulator with active motion disturbance and nonlinearity based on T‐S fuzzy model

Adaptive complementary fuzzy self-recurrent wavelet neural network controller for the electric load simulator system

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