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This paper gives stability analysis of the nonlinear predictive control strategy based on the off-line identified RBF-ARX model which is a pseudo-linear time-varying ARX model with system working-point dependent Gaussian RBF neural network style coefficients. The predictive controller doesn't require on-line parameter estimation; it may be applied to a(More)
SUMMARY This paper presents experimental results, analytical findings, and simulation evaluations pertaining to the longitudinal dynamics and headway performance of strings of vehicles with and without adaptive cruise control (ACC) systems. It focuses on the amplification of speed disturbances along a string of vehicles, i.e., the stability of string(More)
In this paper, we propose a systematic scheme of wavelength assignment for multi-cast in WDM network with sparse wavelength conversion nodes. The proposed scheme considers the generalized network environment when comparing to the literature [8], which assumed that all network nodes have no wavelength conversion capability. By using the concept of(More)
A smooth nonlinear system identification method without resorting to on-line parameter estimation is presented. Based on the radial basis function, a signal-dependent ARX (RBF-ARX) model is established to describe the nonlinear system dynamics. Especially, a new structured nonlinear parameter optimization algorithm based on the Levenberg-Marquardt algorithm(More)
This paper considers modeling and control problems of the non-stationary nonlinear processes whose dynamics depends on the working point. A hybrid RBF-ARX model-based predictive control (MPC) strategy without resorting to on-line parameter estimation for this kind of processes is presented. The RBF-ARX model is composed of the RBF networks and a rather(More)
For nonlinear thermal power plants whose dynamics vary with load demand, a load-dependent exponential ARX (Exp-ARX) model which can exactly describes the nonlinear properties of the plants is presented. The Exp-ARX model requires only off-line identification. Based on the model, a constrained multivariable generalized predictive control (CMGPC) strategy is(More)
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