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Researching on gas discharging system on heading laneway in coal mine is extremely urgent since gas exploring accident takes loss immeasurable. In order to satisfy normal ventilation function and exceeding limited gas discharging function, a double model fuzzy control model using MATLAB language in the Simulink dynamic simulation tools is established. Each includes four-input and single-output. In...
A fuzzy sliding mode controller based on radial basis function neural network (RBFNN) for permanent magnet synchronous machine (PMSM) is investigated in this paper, in which direct torque control (DTC) concept, variable structure control and space vector modulation (SVM) are integrated to achieve high performance. Fuzzy logic is used to adjust the gain of the corrective control of the sliding mode...
This paper investigates an intelligence realization of direct torque control(DTC) in permanent magnet synchronous motor(PMSM) drives. The scheme is based on fuzzy logic control(FLC) and probabilistic neural networks(PNN). The torque error and flux linkage error were all properly fuzzified into several subsets to select a middle state variable accurately, which is the linear function of flux linkage...
It is difficult to realize dynamic control for some complex nonlinear processes which are operated in different environments and when operation conditions are changed frequently. In this paper we propose an identifier-based control method in dynamic tracking neuro-fuzzy control system. The dynamic tracking neuro-fuzzy control (DTNFC) system is comprised of two neural networks and a system identification...
On the basis of distributed traffic control framework, fuzzy theory, and artificial neural networks technique, the road network traffic intelligent coordination control technique with bus priority was proposed. The whole road network was regarded as a large-scale system, and the subsystems were the intersections. Multiphase intelligent signal controller that controlled its own traffic and cooperated...
To compensate voltage difference between the reference and the actual output voltages caused by dead-time effects, a novel compensation method for permanent magnet synchronous motor (PMSM) drive based on neuro-fuzzy observer is proposed. This method presents the implementation of a voltage distortion observer based on the artificial neural network (ANN), using the output of the fuzzy controller (FC),...
To compensate voltage difference between the reference and the actual output voltages caused by dead-time effects, a novel compensation method for permanent magnet synchronous motor (PMSM) direct torque controlled (DTC) drive based on neuro-fuzzy observer is proposed. This method presents the implementation of a voltage distortion observer based on the artificial neural network (ANN). Using the output...
Principle of a new adaptive neuro-fuzzy inference system (ANFIS) with supervisory learning algorithm is introduced and is used to regulate the speed of a four-switch, three-phase inverter (FSTPI) brushless DC (BLDC) drive. The proposed algorithm has advantages of neural and fuzzy networks. To enhance of drive's performance, instead of well-known back propagation learning method, a fuzzy based supervisory...
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