Tracking control via switching and learning for a class of uncertain flexible joint robots with variable stiffness actuators

2021 ◽  
Author(s):  
Jian Li ◽  
KaiFa Ma ◽  
ZhaoJing Wu
2020 ◽  
Vol 17 (2) ◽  
pp. 172988142091177
Author(s):  
Jishu Guo ◽  
Junmei Guo ◽  
Zhongjun Xiao

In this article, a novel robust tracking control scheme based on linear extended state observer with estimation error compensation is proposed for the tracking control of the antagonistic variable stiffness actuator based on equivalent nonlinear torsion spring and the serial variable stiffness actuator based on lever mechanism. For the dynamic models of these two classes of variable stiffness actuators, considering the parametric uncertainties, the unknown friction torques acting on the driving units, the unknown external disturbances acting on the output links and the input saturation constraints, an integral chain pseudo-linear system with input saturation constraints and matched lumped disturbances is established by coordinate transformation. Subsequently, the matched lumped disturbances in the pseudo-linear system are extended to the new system states, and we obtain an extended integral chain pseudo-linear system. Then, we design the linear extended state observer to estimate the unknown states of the extended pseudo-linear system. Considering the input saturation constraints in the extended pseudo-linear system and the estimation errors of the linear extended state observer with fixed preset observation gains, the adaptive input saturation compensation laws and the novel estimation error compensators are designed. Finally, a robust tracking controller based on linear extended state observer, sliding mode control, adaptive input saturation compensation laws, and estimating error compensators is designed to achieve simultaneous position and stiffness tracking control of these two classes of variable stiffness actuators. Under the action of the designed controller, the semi-global uniformly ultimately bounded stability of the closed-loop system is proved by the stability analysis of the candidate Lyapunov function. The simulation results show the effectiveness, robustness, and adaptability of the designed controller in the tracking control of these two classes of variable stiffness actuators. Furthermore, the simulation comparisons show the effectiveness of the proposed estimation error compensation measures in reducing the tracking errors and improving the disturbance rejection performance of the controller.


2015 ◽  
Vol 23 (9) ◽  
pp. 1535-1547 ◽  
Author(s):  
Majid Moradi Zirkohi ◽  
Mohammad Mehdi Fateh

This paper presents a novel decentralized tracking control system of electrically driven flexible-joint robots by adaptive type-2 fuzzy estimation and compensation of uncertainties. Owing to using voltage control strategy, the proposed control approach has important advantages over the torque control approaches in terms of being free from manipulator dynamics, computationally simple and decoupled. The design includes two interior loops: the inner loop controls the motor position while the outer loop controls the joint angle of the robot. An adaptive proportional–integral–derivative controller governs the outer loop, whereas a robust nonlinear controller supported by estimation of uncertainty is employed for the inner loop. More specifically, the main contribution of the paper arises from this fact that the proposed control method uses the interval Type-2 Fuzzy Logic systems for estimation of uncertainty. This is the main difference between this paper and those published in literature. One advantage of the proposed approach is that it uses available feedbacks as an important advantage from a practical point of view. The method is verified by stability analysis and its effectiveness is demonstrated by simulations. The direct method of Lyapunov is utilized for stability analysis of the proposed approach. The case of study is the tracking control of a three-joint articulated flexible-joint robot driven by permanent magnet DC motors. Simulation results show the superior robustness of the type-2 fuzzy system to Type-1 fuzzy system.


Author(s):  
Jorge Montoya‐Cháirez ◽  
Javier Moreno‐Valenzuela ◽  
Víctor Santibáñez ◽  
Ricardo Carelli ◽  
Fracisco G. Rossomando ◽  
...  

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