Adaptive Controller Design for Teleoperation System with Actuator Saturation

Author(s):  
Changchun Hua ◽  
Yana Yang ◽  
Xian Yang ◽  
Xinping Guan

Author(s):  
Mohamad Anwar Baayoun ◽  
Naseem Daher ◽  
Matthias Liermann

This paper presents an adaptive control design of a pneumatic teleoperation system that could be useful for applications like MRI-guided surgery. The system under study is special because of its reduced number of components compared to other bilateral teleoperation systems, which reduces cost and complexity. The direct fluidic connection and the force feedback that is transferred to the human operator allow the operator to feel as if s/he were having physical contact with the environment without the need for a force sensor on the slave actuator. A simulation model that allows stability and transparency assessment is presented in detail. A linear controller is optimized for various operating remote environments via transparency assessment. The linear controller leads to good results for certain operating environments, but its tuning is dependent on the impedance characteristic of the environments both on the master and slave sides. Since the system must perform under parametric uncertainties on both sides of the teleoperator, an adaptive control scheme is developed. A self-tuning regulator is designed to allow the teleoperator to cope with a variable environment. The control design is validated in simulation and yielded satisfactory performance under multiple environment settings.



Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 823
Author(s):  
Wen-Jer Chang ◽  
Yu-Wei Lin ◽  
Yann-Horng Lin ◽  
Chin-Lin Pen ◽  
Ming-Hsuan Tsai

In many practical systems, stochastic behaviors usually occur and need to be considered in the controller design. To ensure the system performance under the effect of stochastic behaviors, the controller may become bigger even beyond the capacity of practical applications. Therefore, the actuator saturation problem also must be considered in the controller design. The type-2 Takagi-Sugeno (T-S) fuzzy model can describe the parameter uncertainties more completely than the type-1 T-S fuzzy model for a class of nonlinear systems. A fuzzy controller design method is proposed in this paper based on the Interval Type-2 (IT2) T-S fuzzy model for stochastic nonlinear systems subject to actuator saturation. The stability analysis and some corresponding sufficient conditions for the IT2 T-S fuzzy model are developed using Lyapunov theory. Via transferring the stability and control problem into Linear Matrix Inequality (LMI) problem, the proposed fuzzy control problem can be solved by the convex optimization algorithm. Finally, a nonlinear ship steering system is considered in the simulations to verify the feasibility and efficiency of the proposed fuzzy controller design method.



2013 ◽  
Vol 385-386 ◽  
pp. 977-980
Author(s):  
Bao Bin Liu

A nonlinear adaptive controller is proposed for the design of pulse width modulation voltage-source rectifier with disturbance signals of harmonics to achieve reference velocity tracking. The procedure of the robust controller design is developed via improved backstepping method. With the proposed controller, PWM voltage-source rectifiers can guarantee accuracy of output voltage tracking. Global asymptotic stability of the closed-loop system has been proved. The simulation results demonstrate effectiveness of the presented method.



Measurement ◽  
2021 ◽  
Vol 174 ◽  
pp. 109071
Author(s):  
S. Morteza Ghamari ◽  
Hasan Mollaee ◽  
Fatemeh Khavari


2013 ◽  
Vol 341-342 ◽  
pp. 945-948 ◽  
Author(s):  
Wei Zhou ◽  
Bao Bin Liu

In view of parameter uncertainty in the magnetic levitation system, the adaptive controller design problem is investigated for the system. Nonlinear adaptive controller based on backstepping is proposed for the design of the actual system with parameter uncertainty. The controller can estimate the uncertainty parameter online so as to improve control accuracy. Theoretical analysis shows that the closed-loop system is stable regardless of parameter uncertainty. Simulation results demonstrate the effectiveness of the presented method.



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