Adaptive Control of Robotic Manipulators With Unified Motion Constraints
نویسندگان
چکیده
منابع مشابه
Discrete-time repetitive optimal control: Robotic manipulators
This paper proposes a discrete-time repetitive optimal control of electrically driven robotic manipulators using an uncertainty estimator. The proposed control method can be used for performing repetitive motion, which covers many industrial applications of robotic manipulators. This kind of control law is in the class of torque-based control in which the joint torques are generated by permanen...
متن کاملNonlinear Adaptive H∞ Control for Robotic Manipulators
A new class of adaptive nonlinear H∞ control for robotic manipulators is proposed in this manuscript. Those control strategies are derived as solutions of particular nonlinear H∞ control problems, where both disturbances and estimation errors of unknown system parameters are regarded as exogenous disturbances to the processes, and the 2 gains from those uncertainties to generalized outputs are ...
متن کاملAdaptive Nonlinear Control Algorithms for Robotic Manipulators
In this paper some adaptive nonlinear multivariable techniques used in the control of robotic manipulators are presented. The nonlinear control law and state feedback are used in achieving a linear inputoutput behavior for the controlled system. For the design of the adaptive nonlinear control, the exact feedback input-output linearization and the method of gradient are used. The nonlinear cont...
متن کاملAdaptive Neural Network Motion Control of Manipulators with Experimental Evaluations
A nonlinear proportional-derivative controller plus adaptive neuronal network compensation is proposed. With the aim of estimating the desired torque, a two-layer neural network is used. Then, adaptation laws for the neural network weights are derived. Asymptotic convergence of the position and velocity tracking errors is proven, while the neural network weights are shown to be uniformly bounde...
متن کاملAdaptive RBF network control for robot manipulators
TThe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. This paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. As a novelty, the proposed controller employs a simple Gaussian Radial-Basis-Function Network as an uncertainty estimator. The proposed netw...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Systems, Man, and Cybernetics: Systems
سال: 2017
ISSN: 2168-2216,2168-2232
DOI: 10.1109/tsmc.2016.2608969