Electrical-Discharge machining (EDM) stands for highly accurate and very sophisticated metal shaping. The physical process takes advantage of electric field effects between two electrodes, a tool and a workpiece. Material is removed by sequences of electrical discharges. The electrically efficient gap width, which is determined among other parameters by the electric conductivity of the gap and ...

This paper proposes an intelligent regenerative braking control of hybrid buses through a neuro-fuzzy controller (NFC) by combining the fuzzy logic algorithm and the artificial neural networks. The braking torque distribution between the integrating starting generator (ISG) and the friction disc brake is addressed through the proposed NFC. The results of simulation and validation show that the ...

Low Frequency Oscillations (LFO) occur in power systems because of lack of the damping torque in order to dominance to power system disturbances as an example of change in mechanical input power. In the recent past Power System Stabilizer (PSS) was used to damp LFO. FACTs devices, such as Unified Power Flow Controller (UPFC), can control power flow, reduce sub-synchronous resonance and increase...

This paper presents the development of a vision-based neuro-fuzzy controller for a two axes gimbal system mounted on a small Unmanned Aerial Vehicle (UAV). The controller uses vision-based object detection as input and generates pan and tilt motion and velocity commands for the gimbal in order to keep the interest object at the center of the image frame. A readial basis function based neuro-fuz...

The dynamic model of a force control system depends not only on the actuator but also on the manipulated object. Generally the object dynamics are unknown and frequently change, and it therefore is difficult to identify the actual dynamics of the system. Designing a nonadaptive controller to perform well under unknown and variant conditions is not feasible. To enhance the controller performance...

This paper considers the identification and fuzzy controller design for nonlinear uncertain systems in presence of unknown input time-delay. Firstly, a time-delay Takagi-Sugeno-Kang (TSK) type fuzzy neural system (TDFN) is proposed to identify a class of nonlinear input time-delay systems. The input-output signals of nonlinear systems are used to identify the system dynamics and unknown time-de...

Induction Motors are widely used in Industries, because of the low maintenance and robustness. Speed Control of Induction motor can be obtained by maximum torque and efficiency. Apart from other techniques Artificial Intelligence (AI) techniques, particularly the neural networks, improves the performance & operation of induction motor drives. This paper presents dynamic simulation of induction ...

Overview material for the Special Session (Tuning Fuzzy Controllers Using Adaptive Critic Based Approximate Dynamic Programming) is provided. The Dual Heuristic Programming (DHP) method of Approximate Dynamic Programming is described and used to the design a fuzzy control system. DHP and related techniques have been developed in the neurocontrol context but can be equally productive when used w...

This paper discusses the performance of various intelligent control schemes in extracting maximum wind power using doubly fed induction generator (DFIG). Intelligent control scheme such as fuzzy, neuro-fuzzy, and genetic algorithm based fuzzy controllers are applied for pitch control of DFIG based wind generation system. Wind generation system with eight numbers of identical 1.5MW wind generato...