Discrete-time optimal adaptive RBFNN control for robot manipulators with uncertain dynamics
نویسندگان
چکیده
منابع مشابه
Optimal discrete-time control of robot manipulators in repetitive tasks
Optimal discrete-time control of linear systems has been presented already. There are some difficulties to design an optimal discrete-time control of robot manipulator since the robot manipulator is highly nonlinear and uncertain. This paper presents a novel robust optimal discrete-time control of electrically driven robot manipulators for performing repetitive tasks. The robot performs repetit...
متن کاملoptimal discrete-time control of robot manipulators in repetitive tasks
optimal discrete-time control of linear systems has been presented already. there are some difficulties to design an optimal discrete-time control of robot manipulator since the robot manipulator is highly nonlinear and uncertain. this paper presents a novel robust optimal discrete-time control of electrically driven robot manipulators for performing repetitive tasks. the robot performs repetit...
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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...
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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...
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This paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. A novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances and discretization error. Parameters of the fuzzy estimator are adapted to minimize the estimat...
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ژورنال
عنوان ژورنال: Neurocomputing
سال: 2017
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2016.12.048