Locomotion control of a hydraulically actuated hexapod robot by robust adaptive fuzzy control and dead-zone compensation

Robotica ◽  
2006 ◽  
Vol 25 (3) ◽  
pp. 269-281 ◽  
Author(s):  
Ranjit Kumar Barai ◽  
Kenzo Nonami

SUMMARYThis investigation presents locomotion control of a hydraulically actuated six-legged humanitarian demining robot by robust adaptive fuzzy control in conjunction with the dead zone compensation technique within independent joint control framework. For proper locomotion of the demining robot, accurate tracking of the desired joint trajectory is very important. However, high degree of nonlinearity, the uncertainties due to changing hydraulic properties, and delay due to the flow of oil and dead zone of the proportional electromagnetic control valve results into an inaccurate plant model for the hydraulically actuated robotic joints. Consequently, model-based classical control techniques result into a large tracking error. Therefore, adaptive fuzzy control technique, being a model independent control paradigm for complex and uncertain systems, is a good choice for such systems. In this work, a hydraulic dead zone compensated robust adaptive fuzzy control law has been proposed for locomotion control of hydraulically actuated hexapod demining robot. The experimental results exhibit a fairly accurate trajectory tracking of the leg joints and, consequently, very stable locomotion of the walking robot.

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Chang-Qi Zhu ◽  
Lei Liu

This paper concentrates on the adaptive fuzzy control problem for stochastic nonlinear large-scale systems with constraints and unknown dead zones. By introducing the state-dependent function, the constrained closed-loop system is transformed into a brand-new system without constraints, which can realize the same control objective. Then, fuzzy logic systems (FLSs) are used to identify the unknown nonlinear functions, the dead zone inverse technique is utilized to compensate for the dead zone effect, and a robust adaptive fuzzy control scheme is developed under the backstepping frame. Based on the Lyapunov stability theory, it is proved ultimately that all signals in the closed-loop system are bounded and the tracking errors converge to a small neighborhood of the origin. Finally, an example based on an actual system is given to verify the effectiveness of the proposed control scheme.


2020 ◽  
Vol 42 (13) ◽  
pp. 2519-2532
Author(s):  
Aissa Rebai ◽  
Kamel Guesmi

This paper deals with the problem of adaptive fuzzy control for a class of nonlinear uncertain systems with hysteresis input. Fuzzy logic systems are employed to approximate the unknown nonlinear behaviors, and the sliding mode technique is used to synthesize an adaptive fuzzy controller. A proportional integral control term is adopted to reduce the chattering phenomenon engendered by both sliding mode control technique and hysteretic characteristic of the system. The proposed control scheme ensures the boundedness of all closed-loop signals, and forces the tracking error to converge to zero. The main contribution of this work is the development of a control strategy for a class of nonlinear hysteretic systems subject to external disturbances and uncertainties. Two case studies are given to illustrate and to prove the effectiveness of the presented approach.


Author(s):  
Shuzhen Diao ◽  
Wei Sun ◽  
Le Wang ◽  
Jing Wu

AbstractThis study considers the tracking control problem of the nonstrict-feedback nonlinear system with unknown backlash-like hysteresis, and a finite-time adaptive fuzzy control scheme is developed to address this problem. More precisely, the fuzzy systems are employed to approximate the unknown nonlinearities, and the design difficulties caused by the nonlower triangular structure are also overcome by using the property of fuzzy systems. Besides, the effect of unknown hysteresis input is compensated by approximating an intermediate variable. With the aid of finite-time stability theory, the proposed control algorithm could guarantee that the tracking error converges to a smaller region. Finally, a simulation example is provided to further verify the above theoretical results.


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