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In this paper, a novel robust adaptive control algorithm is proposed for a class of ship course autopilot with parameter uncertainty and input saturation. With the help of Lyapunov stability theory and adaptive backstepping technique, one controller is constructed by considering parameter uncertainty and actuator saturation constraints, and the stability analysis subject to the effect of input saturation...
In this paper, by incorporating the dynamic surface control technique into a neural network based adaptive control design framework, we have developed a backstepping based control design for a class of nonlinear systems in pure-feedback form with arbitrary uncertainty. Our development is able to eliminate the problem of ??explosion of complexity?? inherent in the existing method. In addition, the...
Using clonal selection model identification, an adaptive PD control algorithm is proposed for uncertain dynamical systems. The practical industrial processes are dynamically identified as second-order linear model; then,a certainty equivalence principle is applied to tune the PD controller. The combination of previous elitist reservation and stochastic initialization for the initial population in...
A simple adaptive fuzzy control (SAFC) is proposed for a class of strict-feedback uncertain nonlinear systems with both unknown system nonlinearities and unknown virtual control gain nonlinearities. Combining the dynamic surface control (DSC) technique with minimal-learning-parameters (MLP) algorithm, a systematic procedure for synthesis of SAFC is developed base on the universal approximation of...
A robust adaptive fuzzy tracking control problem is discussed for a class of uncertain MIMO nonlinear systems with strongly coupled interconnections. T-S fuzzy systems are used to approximate the unknown system uncertainties. Combining ldquodynamic surface control(DSC)rdquoapproach with ldquominimal learning parameters(MLP)rdquo algorithm, a systematic procedure for controller design is developed...
An adaptive neural network control (ANNC) is proposed for a class of strict-feedback uncertain nonlinear systems with unknown system nonlinearities and unknown virtual control gain nonlinearities. Combining the dynamic surface control (DSC) technique with minimal-learning-parameters (MLP) algorithm, a systematic procedure for synthesis of ANNC is developed based on the universal approximation of neural...
The path following problem is concerned for conventional surface ships with second order nonholonomic constraints. A nonlinear feedback algorithm is presented using decoupling control method. The cross track error and heading error are stabilized by means of the rudder alone and the thruster is left to adjust the forward speed. The underactuated following control objective is achieved without a reference...
An adaptive tracking problem is discussed for a class of strict-feedback uncertain systems. Combined "dynamic surface control" technique with "minimal learning parameters" algorithm, a robust adaptive fuzzy tracking controller is developed by use of Takagi-Sugeno (T-S) fuzzy systems as approximators. The proposed algorithms can solve both problems of "dimension curse"...
A robust adaptive tracking control problem is discussed for a class of strict-feedback uncertain nonlinear systems. Takagi-Sugeno type fuzzy logic systems are used to approximate the uncertainties. A unified and systematic procedure is developed to derive a novel robust adaptive tracking controller by use of the input-to-state stability (ISS) and by combining the dynamic surface control (DSC)-based...
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