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This paper proposes the compensated Neuro-Fuzzy Control (NFC) incorporated with Support Vector Machine (SVM) learning algorithm for improving the dynamic response of a servo control of hydraulic system. The high steady state error and overshoot problems can occur when the servo system encounters a friction nonlinearity characteristic. This compensator neuro-fuzzy based on support vector machine combined...
Because of the friction nonlinearity characteristic in hydraulic system, high steady state error and overshoot have occurred in the position response as a typical imperfect implementation of associated control dynamic. In this situation, there is a necessity to be able to effectively utilizing the intelligent controller framework. The primary purpose of this research is to develop a control algorithm...
To enhance the controller performance for the master-slave manipulator system which using a position feedback framework, in this paper, a hybrid adaptive Neuro-Fuzzy Model Reference is proposed. By feeding back the slave's position, the movement at the master may appear ldquosluggishrdquo especially during no-contact operation. The Neuro-Fuzzy control is applied to in position-position and position-position/force...
A force-force bilateral scheme based on neuro-fuzzy control was designed for a six DOF tele-robotic system. An open architecture controller for the six DOF tele-robotic system has been successfully implemented. Increased system bandwidth system can be achieved with the new embedded PUMA 760 and PUMA 260 controllers. Both the slave and master robot controllers comprise a PC running a real-time operating...
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