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This paper describes predictive control of pneumatic actuator. Pneumatic cylinder is a complex nonlinear object because of friction and compressibility of the air. A precision and fast control such an object using traditional methods of control is very difficult. Predictive control with neural networks model of the plant is one of the modern approaches to control complex nonlinear objects.
This paper is concerned with H∞ control problems for a class of uncertain nonlinear systems. In the procedure, neural networks (NNs) are used to model the nonlinear functions, H∞ tracking controller is derived based on Lyapunov function and the notion of dissipativeness. The controller can not only guarantee the stability of the overall control system, but also attenuate the effect of both the external...
A recurrent wavelet neural network (RWNN) controller is proposed in this study to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive to track periodic reference trajectories. First, the dynamic model of the PMLSM drive system is derived. Next, an RWNN controller is proposed to control the PMLSM. Moreover, the connective weights, translations and dilations of the RWNN...
A kind of fractional-order PIalpha controller is considered. Controller structure with two modes is presented, active status of two modes and mode switching are described. The Tustin operator is used for digital realization of the fractional-order PIalpha controller. Different approximation order is discussed to get a tradeoff between approximation precision and complexity of discretization expression...
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