• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.76-81
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• 1998

This paper presents an on-line scheme for parameter estimation of continuous-time systems, based on the model adjustment technique and the genetic algorithm technique. To deal with the initialisation and unmeasurable signal problems in on-line parameter estimation of continuous-time systems, a discrete-time model is obtained for the linear differential equation model and approximations of unmeasurable states with the observable output and its time-delayed values are obtained for the nonlinear state space model. Noisy observations may affect these approximation processes and degrade the estimation performance. A digital prefilter is therefore incorporated to avoid direct approximations of system derivatives from possible noisy observations. The parameters of both the model and the designed filter are adjusted on-line by a genetic algorithm, A set of simulation works for linear and nonlinear systems is carried out to demonstrate the effectiveness of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.349-354
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• 2007

This paper considers the problem of designing static output feedback controllers for nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models. Based on linear matrix inequality technique, a new method is developed for designing fuzzy stabilizing controllers via static output feedback. Furthermore, the result is also extended to $H_{\infty}$ control. Examples are given to illustrate the effectiveness of the proposed methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.138-143
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• 2006

This paper presents intelligent digital redesign method for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an . example to guarantee the stability and effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.139-144
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• 2011

We consider the stabilization problem for a class of networked control systems with random delays in the discrete-time domain. The controller-to-actuator and sensor-to-controller time-delays are modeled as two Markov chains, and the resulting closed-loop systems are Markovian jump nonlinear systems with two modes. The T-S (Takagi-Sugeno) fuzzy model is employed to represent a nonlinear system with Markovian jump parameters. The aim is to design a fuzzy controller such that the closed-loop Markovian jump fuzzy system is stochastically stable. The necessary and sufficient conditions on the existence of stabilizing fuzzy controllers are established in terms of LMIs (Linear Matrix Inequalities). It is shown that fuzzy controller gains are mode-dependent. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method.

• Bulletin of the Korean Mathematical Society
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• v.35 no.1
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• pp.157-172
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• 1998

A numerical method is proposed for dynamical systems. We utilize the fact that special matrix exponentials can be exactly evaluated by the intrinsic library functions. Numerical examples are given, which show that the relative error s of the proposed method converge to a small constant and that the method faithfully approximates the dynamics of the nonlinear differential equations.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.12
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• pp.793-798
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• 2004

In this paper, the problem of adaptively identifying time-varying nonlinear systems is considered. For that purpose, the discrete time-varying Volterra series is employed as a system model, and the filtered weighted least squares (FWLS) algorithm, developed for adaptive identification of linear time-varying systems, is utilized for the adaptive identification of time-varying quadratic Volterra systems. To demonstrate the performance of the proposed approach, some simulation results are provided. Note that the FWLS algorithm, decomposing the conventional weighted basis function (WBF) algorithm into a cascade of two (i.e., estimation and filtering) procedures, leads to fast parameter tracking with low computational burden, and the proposed approach can be easily extended to the adaptive identification of time-varying higher-order Volterra systems.

• Journal of Power Electronics
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• v.19 no.3
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• pp.655-664
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• 2019

In order to analyze the nonlinear phenomena of the bifurcation and chaos caused by the switching of nonlinear switching devices in inductively coupled power transfer (ICPT) systems, a Jacobian matrix model, based on discrete mapping numerical modeling, is established to judge the system stability of the periodic closed orbit and to study the nonlinear behavior of Hopf bifurcation in a system under full resonance. The general flow of the parameter design, based on the stability principle for ICPT systems, is proposed to avoid the chaos and bifurcation phenomena caused by unreasonable parameter selection. Firstly, based on the state equation of SS-type compensation, a three-dimensional bifurcation diagram with the coupling coefficient as the bifurcation parameter is established with a numerical simulation to observe the nonlinear phenomena in the system. Then Filippov's method based on a Jacobian matrix model is adopted to deduce the boundary of stable operation and to judge the type of the bifurcation in the system. Then the general flow of the parameter design based on the stability principle for ICPT systems is proposed through the above analysis to realize stable operation under the conditions of weak coupling. Finally, an experimental platform is built to confirm the correctness of the numerical simulation and modeling.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.93-101
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• 1997

This paper describes the application of Genetic Algorithms(GAs) to nonlinear constrained mixed optimization problems. Genetic Algorithms are combinatorial in nature, and therefore are computationally suitable for treating discrete and integer design variables. But, several problems that conventional GAs are ill defined are application of penalty function that can be adapted to transform a constrained optimization problem into an unconstrained one and premature convergence of solution. Thus, we developed an improved GAs to solve this problems, and two examples are given to demonstrate the effectiveness of the methodology developed in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.267-270
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• 1994

To increase the robustness of tile feedforward tracking control system, a new discrete time sliding function has been defined and utilized for the formulation of control law, In adaptive case the robustness is achieved by using both a normalized gradient algorithm with deadzone and a sliding function-based nonlinear feedback, while in nonadaptive case by using only a sliding function-based nonlinear feedback.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.56-60
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• 1992

This paper addresses the problem of designing a neural network based controller for a discrete-time nonlinear dynamical system. Using two multi-layered neural networks we first design an indirect controller the weights of which are updated by the informations obtained from system identification. The weight update is executed by parameter optimization method under Lagrangian formulation. For the nonlinear dynamical system, we define several cost functions and by computer simulations analyze the control performances of them and the effects of penalty-weighting values.