Switching Control With Learning for a Class of Systems

2003 ◽  
Vol 125 (3) ◽  
pp. 448-450
Author(s):  
X. Zhang ◽  
S. S. Nair
Keyword(s):  
Adaptive Learning ◽  
Control Strategy ◽  
Controller Design ◽  
Switching Control ◽  
Robust Adaptive Control ◽  
Control Effort ◽  
On Line ◽  
Robust Adaptive ◽  
Adaptive Control Strategy ◽  
Stable Learning

Analytical details are developed for a robust adaptive control strategy that combines switching control and on-line adaptive learning, for a class of nonlinear systems. The condition for stable learning is derived, guidelines for design parameter selection are provided, and the tradeoff between performance and chattering control effort is examined. The results of the study are summarized in the form of a constructive procedure for controller design for the class of systems.

Dynamics and Improved Robust Adaptive Control Strategy for the Finite Time Synchronization of Uncertain Nonlinear Systems

2017 ◽  
Vol 6 (4) ◽  
pp. 34-62 ◽  
Author(s):  
Kammogne Soup Tewa Alain ◽  
Kengne Romanic ◽  
Fotsin Hilaire Bertrand
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Finite Time ◽  
Time Synchronization ◽  
Robust Adaptive Control ◽  
Adaptive Robust Control ◽  
Stability And Convergence ◽  
Slave System ◽  
Robust Adaptive ◽  
Adaptive Control Strategy

This letter addresses a robust adaptive control for the synchronization method based on a modified polynomial observer (slave system) which tends to follow exponentially the chaotic Colpitts circuits brought back to a topology of the Chua oscillator (master system) with perturbations. The authors derive some less stringent conditions for the exponential and asymptotic stability of adaptive robust control systems at finite time. They provide a proof of stability and convergence (hence, that synchronization takes place) via Lyapunov stability method. That is, the observer (slave system) must synchronize albeit noisy measurements and reject the effect of perturbations on the system dynamics. To highlight their contribution, the authors also present some simulation results with the purpose to compare the proposed method to the classical polynomial observer. Finally, numerical results are used to show the robustness and effectiveness of the proposed control strategy.

Robust adaptive control of door opening by a mobile rescue manipulator based on unknown-force-related constraints estimation

Robotica ◽  
2017 ◽  
Vol 36 (1) ◽  
pp. 119-140 ◽  
Author(s):  
Liang Ding ◽  
Kerui Xia ◽  
Haibo Gao ◽  
Guangjun Liu ◽  
Zongquan Deng
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Robust Adaptive Control ◽  
Mobile Manipulator ◽  
Joint Position ◽  
Door Opening ◽  
Robust Adaptive ◽  
Adaptive Control Strategy ◽  
Mobile Base

SUMMARYThis study focuses on a door-opening mobile manipulator operating in four phases (reaching the door, grasping the door handle, turning the door handle, and pulling the door). We use force/torque feedback-based control, achieving compliance of the mobile base when it comes into contact with the handle. A method is proposed for estimating the unknown force-related constraints from manipulator joint position measurements. A robust adaptive control strategy is developed for tracking the planned trajectory to open the door. Finally, a mobile manipulator opens a real door with a locked latch and unknown force-related constraints, demonstrating the validity of the proposed approach.

Robust Adaptive Control for Vision-Based Stabilization of a Wheeled Humanoid Robot

2016 ◽  
Vol 13 (03) ◽  
pp. 1650010 ◽  
Author(s):  
Zhengcai Cao ◽  
Longjie Yin ◽  
Yili Fu ◽  
Jian S. Dai
Keyword(s):  
Adaptive Control ◽  
Humanoid Robot ◽  
Controller Design ◽  
Robust Adaptive Control ◽  
Lyapunov Theory ◽  
Control Technique ◽  
Robot Kinematics ◽  
Unknown Parameters ◽  
Actuator Dynamics ◽  
Robust Adaptive

A significant amount of work has been reported in the area of vision-based stabilization of wheeled robots during the last decade. However, almost all the contributions have not considered the actuator dynamics in the controller design. Considering the unknown parameters of the robot kinematics and dynamics incorporating the actuator dynamics, this paper presents a vision-based robust adaptive controller for the stabilization of a wheeled humanoid robot by using the adaptive backstepping approach. For the controller design, the idea of backstepping is used and the adaptive control technique is applied to treat all parametric uncertainties. Moreover, to attenuate the effect of the external disturbances on control performance, smooth robust compensators are employed. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, simulation results are given to verify the effectiveness of the proposed controller.

Neural Network Adaptive Control of Free Floating Space Robot with Actuator Saturation

2014 ◽  
Vol 590 ◽  
pp. 380-385 ◽  
Author(s):  
Guo Liang Zhang ◽  
Ting Lei ◽  
Fan Yang ◽  
Zhuang Cai
Keyword(s):  
Neural Network ◽  
Adaptive Learning ◽  
Control Strategy ◽  
Actuator Saturation ◽  
Space Robot ◽  
Global Approximation ◽  
Neural Network Approach ◽  
The Neural Network ◽  
On Line ◽  
The Stability

This paper proposes an adaptive neural network law for trajectory tracking of a class of free-floating space robot with actuator saturation. Using neural network with global approximation, the control strategy design an on-line real time adaptive learning law to approach the uncertain model and the actuator saturation nonlinearity. The neural network approach errors and outside disturbance can be eliminated by a robust controller.The control strategy need not depend on the model, and can be used under actuator saturation.The control strategy can guarantee the stability of system and the asymptotic convergence of tracking errors based on the Lyapunov’s theory. The simulation results indicate that the proposed strategy can effectively work with actuator saturation.

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