Neural net backlash compensation with Hebbian tuning using dynamic inversion

Šelmić, Rastko R.; Lewis, Frank L.

doi:10.1016/s0005-1098(01)00066-8

Cited by 59 publications

(32 citation statements)

References 17 publications

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“…On the other hand, the control methods of system with backlash are being frequently developing, such as adaptive inverse method [7,8], robust adaptive control [9 -11], fuzzy logic control [12,13], neural network control [14,15] and so on. In recent years, backlash nonlinearity compensation strategies have also been studied by many scholars.…”

Section: Introductionmentioning

confidence: 99%

Improved Backstepping Adaptive Control of Dual-motor Driving Servo System with Backlash Based on Fuzzy Parameter Approximation

Zhao¹,

Wang²

2016

Open Cyber

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Aiming at the control problem of dual-motor driving servo system with backlash nonlinearity, a model for the system is introduced. Two adaptive fuzzy systems were used to approximate the nonlinear part and unknown parameters in system online, to avoid the complex calculation in deducing the adaptive law of each unknown parameter. By using improved backstepping approach and recursively selecting the Lyapunov function, introducing the virtual control quantity and the integration of position tracking error, an adaptive fuzzy controller with state feedback was designed, and its stability was analyzed. System response analysis and system robustness analysis were considered in simulation test for comparing the improved backstepping control with conventional backstepping control. Simulation results show that the improved backstepping control has better position tracking performance and robustness than conventional backstepping control. Finally, experimental analysis also validates the effectiveness and efficiency of the proposed control strategy.

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Section: Introductionmentioning

confidence: 99%

Improved Backstepping Adaptive Control of Dual-motor Driving Servo System with Backlash Based on Fuzzy Parameter Approximation

Zhao¹,

Wang²

2016

Open Cyber

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“…It is well known that this kind of nonlinearity may often cause delays, oscillations and inaccuracy which severely limit the performance of control systems [2,16,24,[31][32][33]. Therefore, compensation of backlash has attracted research effort by several decades [25,27].…”

Section: Introductionmentioning

confidence: 99%

Identification of Nonlinear Cascade Systems with Time-Varying Backlash

Vörös¹

2011

Journal of Electrical Engineering

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Recursive identification of cascade systems with time-varying input backlash and linear dynamic system is presented. A new analytic form of backlash characteristic description is used, hence all the parameters in the cascade model equation are separated and their estimation is solved as a quasi-linear problem using the recursive least squares method with internal variable estimation. Simulation studies are included.K e y w o r d s: nonlinear systems, backlash, cascade systems, recursive identification, time-varying systems

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“…Since most methods to compensate for the effect of backlash are model based (Chandler et al, 2000;Selmic and Lewis, 2001;Toyozawa et al, 2004;Campos et al, 2000;Nordin and Gutman, 2002), the accuracy of the model to describe the behavior of systems with output backlash is very important for the performance of the compensation. In many cases, the operation environment may be changed with time due to the wear and tear of the components of the system.…”

Section: Introductionmentioning

confidence: 99%

Recursive identification algorithm for dynamic systems with output backlash and its convergence

Dong

Tan

2009

International Journal of Applied Mathematics and Computer Science

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This paper proposes a recursive identification method for systems with output backlash that can be described by a pseudoWiener model. In this method, a novel description of the nonlinear part of the system, i.e., backlash, is developed. In this case, the nonlinear system is decomposed into a piecewise linearized model. Then, a modified recursive general identification algorithm (MRGIA) is employed to estimate the parameters of the proposed model. Furthermore, the convergence of the MRGIA for the pseudo-Wiener system with backlash is analysed. Finally, a numerical example is presented.

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Neural net backlash compensation with Hebbian tuning using dynamic inversion

Cited by 59 publications

References 17 publications

Improved Backstepping Adaptive Control of Dual-motor Driving Servo System with Backlash Based on Fuzzy Parameter Approximation

Improved Backstepping Adaptive Control of Dual-motor Driving Servo System with Backlash Based on Fuzzy Parameter Approximation

Identification of Nonlinear Cascade Systems with Time-Varying Backlash

Recursive identification algorithm for dynamic systems with output backlash and its convergence

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