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Nonlinear motion model of HEV electronic throttle is built. Aiming at the problem that is difficult to set the nonlinear control system optimum parameters for the traditional PID control, and based on the advantages of the fast convergence and strong universal approximation ability of the neural network, the method neural network setting PID control electronic throttle based on the Radial Basis Function...
Since the start process for control system of electric forklift has the characters of nonlinearity and fast time-variety, and routine PID method is difficult to satisfy the nonlinear and variable request. So this paper applied a control strategy based on radial basis function neural network, RBFNN PID, to control the motor through closed-loop control, in order to compensate the perturbation, nonlinearity...
It is more and more popular to use electromagnetism clutch on mini-cars, for its unique structure and simple controlling. But the drive of the electromagnetism clutch has some nonlinearity, and there is interference around it, so the traditional PID control strategy couldn't work at its best. The single neuron self-adaptive PID controller using on-line identification of radial basis function Neural...
The real time adaptive control of urban traffic, as a complex large system, usually needs to know the traffic of every intersection in advance. So traffic flow forecasting is a key problem in the real time adaptive control of urban traffic. This paper's research object is two typical adjacent intersections of city road. A double RBF NN model with classifying coefficient is presented. The space of...
In this paper, a strategy of failure detection, identification and reconfigurable scheme for a dynamic system is proposed. The proposed scheme provides detection and identification of sensor, actuator and/or system component failures, dynamic system state estimation and system performance recovery. Fault detection and identification is carried out using radial basis function (RBF) neural network and...
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