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Taking advantage of neural network back propagation algorithm and Takagi-Sugeno fuzzy inference system, a kind of pilot model is developed based on adaptive neural fuzzy inference system. A longitudinal man machine systems in air-refueling condition is simulated. The simulation results show that the model presented by our scheme is reasonable and can be used to illustrate the handling behavior of...
The composition and control process of the ball and beam system are introduced in the paper, a mathematical model of ball and beam system based on Lagrange equations is set up with the application of the energy balance principle concerning dynamics, and on the base of analysis on such model, the design of a controller is worked out by utilizing the techniques of adaptive neural network. A reference...
This paper studies the applications of Adaptive Neuro-Fuzzy Inference Systems(ANFIS) in the Autonomous Underwater Vehicle(AUV) height control system. A control method of ANFIS is mentioned after absorbing the advantages of fuzzy logic and neural network. According to the data fedback by sensors, this method can get the needed fuzzy membership functions and fuzzy rules by self-study, which composes...
In this paper, the Multi-ADAptive LINear Element (MADA LINE) neural network was generalized for On-line System identification of linear time-invariant (LTI) Multi-Input Multi-Output (MIMO) systems. Based on the input output polynomial model which can be easily transformed into the row canonical state space model, Tapped delay line are introduced, so the MADALINE becomes recurrent in nature and thus...
Linear system theory has made significant contribute to the developments of the classical control's area in the past three decades. The motivation of this paper emerges from the need to develop novel control strategies that can be applied to nonlinear dynamic systems. Furthermore, the need for an adaptive scheme emerges for dealing with time varying systems. Paper presents model reference based neural...
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