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In this paper, the reconstruction error between the real system to be controlled and its T-S fuzzy model is considered in the context of control system design. As a result, an H∞ approach to adaptive controller that consists of two parts: one is obtained by solving certain linear matrix inequalities (LMIs) (fixed part) and another one is acquired by the fuzzy approximator in which the related parameters...
In recent years the area of nonlinear control systems has been the subject of many studies. Computational developments have enabled more complex applications to provide solutions to nonlinear problems. The purpose of this paper is to use a combination of two techniques to control a nonlinear system: the Magnetic Levitation System. First, the exact linearization technique with state feedback is applied...
The signalized intersection system often exhibits severe nonlinear and time-varying characteristic due to the random fluctuation of traffic demand or some special event, therefore, it cannot be adequately controlled with some traditional ways. The traditional reinforcement learning was extended to the fuzzy pattern with defining the fuzzy reinforcement function by using the fuzzy state. A stochastic...
This paper quantifies performance bounds of L1 adaptive controllers for linear uncertain systems with input quantization. Two basic types of quantizers are considered: uniform quantizers and logarithmic quantizers. The performance bounds of the L1 adaptive controller in the presence of input quantization proved to have an additional term, dependent upon the quality of quantization. The signals of...
Using of the electric motor control system and the principle of rolling plastic deformation, this paper describes the stable state mathematical model of cold rolling process is established. The dynamic process of cold rolling is simulated by using the MATLAB/ Simulink. Cold rolling control system exists time-delay, time-varying, large inertia, nonlinear and other problems. Setting parameters of traditional...
In view of Chaos is such a complex nonlinear systems, we analyze the parameters of initial sensitivity and unpredictability, and use a universal adaptive controller based on adaptive control theory, combined with the stability of Lyaponov theory, making the system to eliminate chaos and asymptotic stability to the desired smooth orbit. Matlab simulation results have verified the efficiency of this...
This paper presents an adaptive disturbance rejection scheme which makes use of a neural model of the disturbance. Unknown disturbances may account for the reduction in the performance of a control system where precise tracking is required. These disturbances may be nonlinear and dynamic making the rejection problem difficult for traditional methods. Also the plant being controlled may be unknown,...
In this paper, the problem of adaptive control for nonlinear systems is considered. Employing the adaptive method based on the Lyapunov stability theorem, the corresponding controller is constructed. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the nonlinear systems in presence of noise and model uncertainties.
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...
In this paper, a system which includes two ties (AC and DC), interconnecting two large AC networks, is studied. The system includes DC control interacting with the conventional AC area controls. In this regard, optimal exploitation of classical controllers has been a controversial issue in reputable journals. In this article, the stability of the network in each of the areas is controlled by a new...
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