18 results with keyword: 'pso based neuro fuzzy sliding control robot manipulator'
A neural network based sliding mode adaptive control (NNSMAC) which is a combination of sliding mode technique, neural network approximation and adaptive technique is designed
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The control law for proposed controller is as (4) form. K gain of the corrective control u c is adjusted with fuzzy logic and is the equivalent control u eq is computed by
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Inspired by the idea of basing the fuzzy logic inference procedure on a feedforward network structure, Jang [18] proposed a fuzzy neural network model - the Adaptive
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In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) based Computed Torque (PD) controller is applied to the dynamic model of puma 600 robot arm presented.. To validate
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Evolutionary Computing Neural Networks Fuzzy Systems Swarm Intelligence Neuro-Fuzzy Systems Neuro-Genetic Systems Neuro-Swarm Systems Fuzzy-PSO Systems Fuzzy-GA
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Trajectory planning on robot manipulator by using SOM neural network and Fuzzy logic control is able to guide robot manipulator to reach the target points.. The obtained results
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This paper presents a hybrid control strategy called Neuro-Fuzzy Sliding Mode Control (NFSMC) based on the Brushless Doubly fed Induction Generator (BDFIG).. This replaces
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Despite the fact that the centralized approaches have attained significant achievements to improve the tracking performance of robots, but when the degree of freedom (D.O.F) of
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Experi- mental results demonstrate that the adaptive RBFNN- based fuzzy sliding mode control is applicable control scheme for trajectory tracking applications of robotic
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In this paper, a control parameter selection algorithm is proposed by genetic algorithm to select the gain switching (k) and sliding surface constant parameter (s) so that
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Keywords: ANFLC (artificial neuro fuzzy logic controller); BF (bacterial foraging); Hybrid learning; PID control; PSO (particle swarm
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Figure 1.a shows the proposed coupled fuzzy controller and the rule base and the membership functions for the shoulder are shown in Figure 1.b and Table 1, and the elbow link rule
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We design three fuzzy controllers for each angle, the construction of the fuzzy controller consists in defining the linguistic variable and the fuzzy terms associated with the
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The mathematical model of two DOF robot manipulator is designed in the form of differential equations and then feedback linearization technique is applied to
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During the sliding mode phase, although the system is robust towards invariance, the discontinuous control action to correct the trajectory error supposedly switches
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The fuzzy logic controller is used to stabilise this robot with Particle Swarm Optimization algorithm for optimum performance of the system.. The result of the
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