scholarly journals Rate-dependent Asymmetric Hysteresis Modeling and Robust Adaptive Trajectory Tracking for Piezoelectric Micropositioning Stages

2021 ◽  
Author(s):  
Linlin Nie ◽  
Yiling Luo ◽  
Wei Gao ◽  
Miaolei Zhou
Keyword(s):  
Control Method ◽  
Excitation Frequency ◽  
Robust Adaptive Control ◽  
Adaptive Robust Control ◽  
Signal Frequency ◽  
Loop Control ◽  
Model Based ◽  
Rate Dependent ◽  
Robust Adaptive ◽  
Micropositioning Stages

Abstract Hysteresis is an inherent characteristic of piezoelectric materials that can be determined by not only the historical input but also the input signal frequency. Hysteresis severely degrades the positioning precision of piezoelectric micropositioning stages. In this study, the hysteresis characteristics and the excitation frequency effects on the hysteresis behaviors of the piezoelectric micropositioning stage are investigated. Accordingly, a rate-dependent asymmetric hysteresis Prandtl-Ishlinskii (RDAPI) model is developed by introducing a dynamic envelope function into the play operators of the Prandtl-Ishlinskii (PI) model. The RDAPI model uses a relatively simple analytical structure with fewer parameters then other modified PI model to characterize the rate-dependent and asymmetric hysteresis behavior in piezoelectric micropositioning stages. Considering practical situations with the uncertainties and external disturbances associated with the piezoelectric micropositioning stages, the system dynamics are described using a second-order differential equation. On this basis, a corresponding adaptive robust control method that does not involve the construction of a complex hysteretic inverse model is developed. The Lyapunov analysis method proves the stability of the entire closed-loop control system. Experiments confirm that the proposed RDAPI model achieves a significantly improved accuracy compared with the PI model. Furthermore, compared with the inverse RDAPI model-based feedforward compensation and the inverse RDAPI model-based proportional-integral-derivative control methods, the proposed robust adaptive control strategy exhibits improved tracking performance.

Robust adaptive tracking control for uncertain nonholonomic mobile manipulator

2021 ◽  
pp. 095965182110277
Author(s):  
Abdelkrim Brahmi ◽  
Maarouf Saad ◽  
Brahim Brahmi ◽  
Ibrahim El Bojairami ◽  
Guy Gauthier ◽  
...  
Keyword(s):  
Control Method ◽  
Sliding Mode ◽  
Robust Adaptive Control ◽  
Convergence Time ◽  
Adaptive Sliding Mode Control ◽  
Mobile Manipulator ◽  
Control Law ◽  
Adaptive Tracking Control ◽  
Robust Adaptive ◽  
Manipulator Robot

In the research put forth, a robust adaptive control method for a nonholonomic mobile manipulator robot, with unknown inertia parameters and disturbances, was proposed. First, the description of the robot’s dynamics model was developed. Thereafter, a novel adaptive sliding mode control was designed, to which all parameters describing involved uncertainties and disturbances were estimated by the adaptive update technique. The proposed control ensures a relatively good system tracking, with all errors converging to zero. Unlike conventional sliding mode controls, the suggested is able to achieve superb performance, without resulting in any chattering problems, along with an extremely fast system trajectories convergence time to equilibrium. The aforementioned characteristics were attainable upon using an innovative reaching law based on potential functions. Furthermore, the Lyapunov approach was used to design the control law and to conduct a global stability analysis. Finally, experimental results and comparative study collected via a 05-DoF mobile manipulator robot, to track a given trajectory, showing the superior efficiency of the proposed control law.

scholarly journals Robust Adaptive Control for Nonlinear Aircraft System with Uncertainties

2020 ◽  
Vol 10 (12) ◽  
pp. 4270
Author(s):  
Jiao Chen ◽  
Jiangyun Wang ◽  
Weihong Wang
Keyword(s):  
Adaptive Control ◽  
High Frequency ◽  
Control Method ◽  
Longitudinal Direction ◽  
Flight Simulation ◽  
Robust Adaptive Control ◽  
High Frequency Oscillation ◽  
Robust Adaptive ◽  
Aircraft System ◽  
Fast Adaptation

Model reference adaptive control (MRAC) schemes are known as an effective method to deal with system uncertainties. High adaptive gains are usually needed in order to achieve fast adaptation. However, this leads to high-frequency oscillation in the control signal and may even make the system unstable. A robust adaptive control architecture was designed in this paper for nonlinear aircraft dynamics facing the challenges of input uncertainty, matched uncertainty, and unmatched uncertainty. By introducing a robust compensator to the MRAC framework, the high-frequency components in the control response were eliminated. The proposed control method was applied to the longitudinal-direction motion control of a nonlinear aircraft system. Flight simulation results demonstrated that the proposed robust adaptive method was able to achieve fast adaptation without high-frequency oscillations, and guaranteed transient performance.

scholarly journals Model-based Robust Adaptive Control for Power-generating Systems in the Presence of Long Time Delay

2017 ◽  
Vol 50 (1) ◽  
pp. 3232-3237 ◽  
Author(s):  
Lei Pan ◽  
Jiong Shen ◽  
Xiao Wu ◽  
Li Sun ◽  
Kwang. Y. Lee ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Time Delay ◽  
Robust Adaptive Control ◽  
Model Based ◽  
Long Time ◽  
Robust Adaptive

scholarly journals Robust adaptive control for continuous wheel slip rate tracking of vehicle with state observer

2020 ◽  
Vol 53 (7-8) ◽  
pp. 1331-1341
Author(s):  
Jiaxu Zhang ◽  
Zhengtang Shi ◽  
Xiong Yang ◽  
Jian Zhao
Keyword(s):  
Tracking Control ◽  
Control Method ◽  
Slip Rate ◽  
State Observer ◽  
Robust Adaptive Control ◽  
Wheel Slip ◽  
Fuzzy Uncertainty ◽  
Tracking Differentiator ◽  
Adaptive Laws ◽  
Robust Adaptive

This article proposes a novel robust adaptive wheel slip rate tracking control method with state observer. First, a modified tracking differentiator is proposed based on a combination of tangent sigmoid function with terminal attraction factor and linear function to improve convergence speed and avoid chattering phenomenon, and then, the modified tracking differentiator is used as state observer to smooth and estimate the states of the system. Second, a robust adaptive wheel slip rate tracking control law with fuzzy uncertainty observer and modified adaptive laws is derived based on Lyapunov-based method. The fuzzy uncertainty observer is used for estimating and compensating the additive uncertainty, and the modified adaptive laws are used for estimating the unknown optimal weight vector of the fuzzy uncertainty observer and the multiplicative uncertainty. Finally, the performance of the robust adaptive wheel slip rate tracking control method is verified based on the model-in-the-loop simulation system.

Adaptive Robust Control for a Class of Nonlinear Uncertain System With Unknown Input Backlash

2009 ◽  
Author(s):  
Jian Guo ◽  
Bin Yao ◽  
Jun Jiang ◽  
Qingwei Chen
Keyword(s):  
Robust Control ◽  
Nonlinear Dynamic System ◽  
Uncertain System ◽  
Robust Adaptive Control ◽  
Adaptive Robust Control ◽  
Unknown Input ◽  
Uncertain Disturbances ◽  
On Line ◽  
Parameterized Model ◽  
Robust Adaptive

An adaptive robust control (ARC) algorithm is developed for a class of nonlinear dynamic system with unknown input backlash, parametric uncertainties and uncertain disturbances. Due to the non-smooth dynamic nonlinear nature of backlash, existing robust adaptive control methods mainly focus on using approximate inversion of backlash by on-line parameter adaptation. But experimental results show that a linear controller alone can perform better than a controller including the selected backlash inverter with a correctly estimated or overestimated backlash gap. Unlike many existing control schemes, the backlash inverse is not constructed in this paper. A new linearly parameterized model for backlash is presented. The backlash nonlinearity is linearly parameterized globally with bounded model error. The proposed adaptive robust control law ensure that all closed-loop signals are bounded and achieves the tracking within the desired precision. Simulations results illustrate the performance of the ARC.

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