This paper presents a method to control both the dc boost and the ac output voltage of Z-source inverter using neural network controllers. The capacitor voltage of Z-source network has been controlled linearly in order to improve the transient response of the dc boost control of the Z-source inverter. The peak value of the line to line ac output voltage is used to control and keep the ac output...

Being difficult to attain the precise mathematical models, traditional control methods such as proportional integral (PI) and proportional integral differentiation (PID) cannot meet the demands for real time and robustness when applied in some nonlinear systems.The neural network controller is a good replacement to overcome these shortcomings. However, the performance of neural network controll...

The wing rock motion is mathematically described by a nonlinear differential equation with coefficients varying with angle of attack. In this paper, a neural-network-based adaptive control system is developed for the wing rock motion control. The adaptive controller comprises a neural network controller and a compensation controller. The neural network controller using a recurrent neural networ...

Navigation of multiple mobile robots using neuro-fuzzy controller has been discussed in this paper. In neuro-fuzzy controller the output from the neural network is fed as an input to fuzzy controller and the final outputs from the fuzzy controller are used for motion control of robots. The inputs to the neural network are obtained from the robot sensors (such as left, front, right obstacle dist...

As traditional PID controller has mature technique, it is applied widely. But the design of it depends on mathematical model of the controlled object. But the parameters of PID controller use engineering tuning method, it requires much time and effort and the parameters are only effect in a specific range. It is not suitable for complicated nonlinear and time-variable system. In recent year, pe...

This paper presents an approach for acquisition and transfer of an experienced driver’s skills to an automatic parking controller. The controller processes visual input information from a video sensor and generates the corresponding steering commands. Two neural control architectures are considered. In the direct neural control architecture the controller is a single artificial neural network. ...

typical production objectives in distillation process require the delivery of products whose compositions meet certain specifications. the distillation control system, therefore, must hold product compositions as near the set points as possible in faces of upset. in this project, inferential model predictive control, that utilizes an artificial neural network estimator and model predictive cont...

In this paper, the use of a proposed recurrent neural network control system to control a four-legged walking robot is investigated. The control system consists of a neural controller, standard PD controller and the walking robot. The robot is a planar four-legged walking robot. The proposed Neural Network (NN) is employed as an inverse controller of the robot. The NN has three layers, which ar...

In this paper, a neural network controller for constrained robot manipulators is presented. A feedforward neural network is used to adaptively compensate for the uncertainties in the robot dynamics. Training signals are proposed for the feed-forward neural network controller. The neural network weights are tuned on-line, with no off-line learning phase required. It is shown that the controller ...