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Modern mechatronic machining centers belong to complex technical systems. Existing mathematical models are not capable to describe the fullness and complexity of the processes of dynamic interaction of mechatronic machine elements: “control system - machine - attachment - tool - work material”, that affect quality and efficiency of machining. With continuous monitoring all these factors by information-measuring...
In this brief, it presents the implementation of control of an inverted pendulum system by using the Adaptive Neural- Fuzzy. The inverted pendulum system has been built in the educational kit whose purpose is to educate control engineers in the college students. The inverted pendulum system is known as a nonlinear system whose goal is to maintain the balance of the pendulum while tracking a desired...
In this paper, a neural network controller is applied to control (suppress) chaotic behavior in a theoretical model of a third order phase locked loop (PLL). It is demonstrated that the neural network controller can successfully cause the phase error to behave in a desired way. The performance of the neural network control method is compared to that of previously used LTI filters showing hence, the...
Taking the multi-variable of synchronization system of the AC induction motors as study object, focusing on the system of induction motors powered by current-tract SPWM transducers, the mathematical model of the system of two motors is established. Combining decoupling technology of adaptive neuron decoupling compensator, RBF neural network adaptive PID controller is adopted to design the neural network...
Turbine supercharged set is used to supply high pressure combustion-supporting air. But the control for combustion-supporting air flux is a control with the characteristics of time-varying and nonlinearity and complex coupling. It is difficult to get the good performance through the traditional control mode. Evaluating of the characteristics of fuzzy control with quick dynamic response, good robustness...
The paper discusses the designing of neural network controller for a twin rotor MIMO (multi-input multi-output) system. The controller is designed such that change in one degree should have minimum effect on other and overall the system should remain stable. For this system commonly known as the helicopter problem, many traditional controllers exist. RBF (radial basis function) neural network and...
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