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Due to the technical difficulties related to the practical application of Lyapunov's 2nd or “direct” method in the adaptive control of nonlinear systems as an alternative approach the use of “Robust Fixed Point Transformations (RFPT)” were suggested on the basis of recent researches. Various application possibilities were revealed for the new controller and design for imprecisely and partially modeled...
Working robots may encounter and interact with various objects, whose dynamical characteristics are unknown; linear or nonlinear and their strength of stiffness. The interaction includes such processes as collision of arm with environments, hand gripping of objects, holding human body in medical case etc. These processes consist of free motion before touching the objects, and constrained motion after...
Integrating repetitive control and RBF neural network PID control , a novel control scheme for DC servo system is proposed for the high accuracy of Oscillating Mirrorsystem . The repetitive control is used to improve the steady-state characteristi of the control serosystem and enhance its ability to withstand the disturbance with same frequency; the RBF neural network PID control is used to enhance...
The studying history and present situation of chaos optimization algorithm is summarized and the basic steps of this method are introduced. A new, feasible chaos optimization is presented to nonlinear constrained programming problems. Computing results in an instance show that this algorithm is reliable and applicable to almost all of the problems in multidimensional, nonlinear, complex constrained...
In this paper the operation of a recently introduced novel version of the popular “Model Reference Adaptive Controller (MRAC)” is compared with that of a simple version of its possible traditional implementations. The “traditional implementations” normally use Lyapunov's 2nd (“direct”) method for adaptive tuning of the controllers' parameters. This method yields global asymptotic stability but its...
In order to deal with the control difficulties of the dredger's dynamic positioning system under large disturbances caused by dredging operation, a disturbances compensating dynamic surface control method is proposed to be used in the dredger's dynamic positioning system. Disturbances can be measured and compensated by the adding forces sensors. The proposed robust controller guarantees the semi-globally...
After this text carries on deep research to the fuzzy controller of routine and PID controller, we know that it is a kind of non-linear controller changed. It has a lot of similarity to PID controller, and then we design a fuzzy PID controller. Fuzzy PID controller is the exactly making of each parameter of the fuzzy controller in the key of comprehensive application that puts in the working range...
Adaptive control technique is adopted to synchronize two identical non-autonomous systems with unknown parameters in finite time. A virtual unknown parameter is introduced in order to avoid the unknown parameters from appearing in the controllers and parameters update laws. The Duffing equation and a gyrostat system are chosen as the numerical examples to show the validity of the present method.
Scalar feedback control in a chaotic discrete prey predator system is investigated. The existence of the fixed points and the local stability of the positive fixed point are discussed. By using center manifold theorem, it is proved rigorously that the system undergoes the flip bifurcation near the unique positive fixed point. To eliminate the undesirable chaos induced by the flip bifurcation and stabilize...
In this paper, active sliding mode controllers are designed to realize the control and synchronization of fractional-order hyper chaotic systems. Based on stability theorems of fractional calculus, the stability analysis of the proposed method is performed. Finally, three numerical simulations are presented to show the effectiveness of the obtained results. The simulations are all implemented using...
In this paper, the sliding-mode lag synchronization control scheme is proposed based on the neural network to synchronize two different delayed chaotic systems. An integral delayed sliding surface is presented to design the sliding mode control. The lag synchronization controller is achieved by combining the RBF (radial basis function) neural network with sliding-mode control. Numerical simulations...
The proportional plus-derivative control of chaotic system is concerned. Controller is firstly designed and then the controlled stochastic forced brusselator is transformed into its equivalent deterministic one by the Chebyshev polynomial approximation. Finally, the chaotic motions of forced brusselator can be successfully converted to the stable lower periodic orbits by proportional plus-derivative...
This paper presents the stability analysis of a class of nonlinear time-varying delay systems with parameter uncertainty, through extended Takagi-Sugeno fuzzy modeling. The delay-dependent stability and robust stability criterions are presented using delay decomposition approach, in terms of linear matrix inequalities (LMIs). The time-varying delay is assumed to be bounded and continuous need not...
In this paper, a multifractal approach to the classification of unknown self affine signals is presented as an improvement over traditional traffic signal. The fundamental advantages of using multifractal measures include normalization and a very high compression ratio of a signature of the traffic, thereby leading to faster implementations, and the abiliiy to add new traffic classes without redesigning...
Tuning of a pH process is a challenging problem due to the strong on-line non-linearity and extreme sensitivity to disturbances of the process. Hence, a nonlinear control strategy based on sliding mode, which is a standard approach to tackle the parametric and modeling uncertainties of a nonlinear system, is chosen for tuning a pH process. Fuzzy Sliding Mode Control (FSMC) as a robust and intelligent...
In this paper a feedback linearization is presented that addresses the coupling effects between two groups of electromagnetic trains. The module, based on some reasonable assumptions of nonlinear mathematical model, is modeled as a double-electromagnet system. The proposed algorithm in tracking has a satisfying performance in presence of unknown changes in the mass. It also shows robustness against...
The paper presents a neural network based predictive control (NPC) strategy to control nonlinear chemical process or system. Multilayer perceptron neural network (MLP) is chosen to represent a Nonlinear autoregressive with exogenous signal (NARX) model of a nonlinear process. Based on the identified neural model, a generalized predictive control (GPC) algorithm is implemented to control the composition...
Inverted Pendulum is a nonlinear, coupling, variable and naturally unsteady system. In order to control the system, the mathematic model through lag range equation was set up and the LQR Controller was designed in this paper. Last, the author analyzes the control results and obtains superior parameters through simulation. The experimental results show that LQR control is more effective and robust.
This report presents a technique of chaotification based on the optimal time-delay feedback that can make a system chaotic with large chaotic parameters range. The bifurcation analysis is done to determine the stability of the time-delay system. An implicit performance index and an optimization strategy are proposed for the time-delay control scheme that can be effectively carried out to obtain the...
This paper introduces a new chaotic system. Some basic dynamical properties are studied, such as the equilibria, the Lyapunov exponents and the fractal dimension. Based on these properties, effective feedback controllers are proposed for stabilizing chaos to unstable equilibria. In addition, based on Lyapunov stability theory, sufficient condition for the synchronization has been analyzed theoretically...
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