• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.235-243
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• 2000

The probabilistic data association filter(PDAF) is known to provide better tracking performance than the standard Kalman filter(KF) in a cluttered environment. In this paper, the stability of the PDAF of Fortmann et al[7], in the presence of uncertainties with regard to the origin of measurement, is investigated. The modified Riccati equation derived by approximating two random terms with their expectations is used to prove the stability of the PDAF. A new Lyapunov function based approach, which is different from the quantitative evaluation of Li and Bar-Shalom[7], is pursued. With the assumption that the system and observation noises are bounded, specific tracking error bounds are established.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.17-22
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• 1997

The stability robustness problem of linear discrete-time systems with time-varying perturbations is considered. By using Lyapunov direct method, the perturbation bounds for guaranteeing the quadratic stability of the uncertain systems are derived. In the previous results, the perturbation bounds are derived by the quadratic equation stemmed from Lyapunov method. In this paper, the bounds are obtained by a numerical optimization technique. Linear matrix inequalities are proposed to compute the perturbation bounds. It is demonstrated that the suggested bound is less conservative for the uncertain systems with unstructured perturbations and seems to be maximal in many examples. Furthermore, the suggested bound is shown to be maximal for the special classes of structured perturbations.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.237-242
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• 2015

This paper presents a method to enhance tracking performance of an input-constrained bilinear system using MPC (Model Predictive Control) when a feasible tracking control is known. Since the error dynamics induced by the known tracking control is asymptotically stable, there exists a Lyapunov function for the stable error dynamics. By defining a cost function including the Lyapunov function and describing tracking performance, an MPC law is derived. In simulation, the performance of the proposed MPC law is demonstrated by applying it to a converter model.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.42-47
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• 2014

This paper investigates an adaptive approximation design problem for the tracking control of output-constrained non-affine pure-feedback systems. To satisfy the desired performance without constraint violation, we employ a barrier Lyapunov function which grows to infinity whenever its argument approaches some limits. The main difficulty in dealing with pure-feedback systems considering output constraints is that the system has a non-affine appearance of the constrained variable to be used as a virtual control. To overcome this difficulty, the implicit function theorem and mean value theorem are exploited to assert the existence of the desired virtual and actual controls. The function approximation technique based on adaptive neural networks is used to estimate the desired control inputs. It is shown that all signals in the closed-loop system are uniformly ultimately bounded.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.3
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• pp.157-166
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• 2015

In this paper, we proposed a new robust control scheme to implement stable control of robot manipulators including nonlinear perameters The proposed robust controller is composed of a nonlinear controller and linear compemsation controller. It shows a good robust performance in reaching mode which does not possess invariance property. Thus, the proposed nonlinear controller showed a good robust performance in the whole region, It was illustrated that the proposed control showed a good transient response and trajectory tracking performance for robot manipulator with four joint by experiments.

• Journal of KSNVE
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• v.8 no.3
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• pp.408-419
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• 1998

Dynamic characteristics are investigated when a nonlinear system showing periodic and chaotic responses under harmonic excitation is exposed to random perturbation. Approach for both qulitative and quantitative analysis of the noise effect in a nonlinear system under harmonic excitation is presented. For the qualitative analysis, Lyapunov exponents are calculated and Poincar map is illustrated. For the quatitative analysis. Fokker-Planck equatin is solved numerical by means of a Path-integral solution procedure. Eigenvalue problem obtained from the numerical caculation is solved and the relation of eigenvalue, eigenvector and chaotic motion is investigated.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.10-14
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• 2004

We present a predictive control algorithm combined with the robust robot control that is constructed on the Lyapunov min-max approach. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about the model, it is an important trend to design a robust control law that guarantees the desired properties of the manipulator under uncertain elements. In the preceding robust control work, we need to tune several control parameters in the admissible set where the desired stability can be achieved. By introducing an optimal predictive control technique in robust control we can find out much more deterministic controller for both the stability and the performance of manipulators. A new class of robust control combined with an optimal predictive control is constructed. We apply it to a simple type of 2-link robot manipulator and show that a desired performance can be achieved through the computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.67-71
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• 2009

This paper presents a rank-constrained linear matrix inequality (LMI) approach to the design of a multi-objective controller such as $H_2/H_{\infty}$ control. Multi-objective control is formulated as an LMI optimization problem with a nonconvex rank condition, which is imposed on the controller gain matirx not Lyapunov matrices. With this rank-constrained formulation, we can expect to reduce conservatism because we can use separate Lyapunov matrices for different control objectives. An iterative penalty method is applied to solve this rank-constrained LMI optimization problem. Numerical experiments are performed to illustrate the proposed method.

• The Journal of the Korea institute of electronic communication sciences
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• v.1 no.1
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• pp.49-55
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• 2006

Applied by periodic Stimulating Currents in Bonhoeffer -Van der Pol(BVP) model, chaotic and periodic phenomena occured at specific conditions. The conditions of the chaotic motion in BVP comprised 0.7182< $A_1$ <0.792 and 1.09< $A_1$ <1.302 proved by the analysis of phase plane, bifurcation diagram, and lyapunov exponent. To control the chaotic motion, two methods were suggested by the first used the amplitude parameter A1, $A1={\varepsilon}((x-x_s)-(y-y_s))$ and the second used the temperature parameterc, $c=c(1+{\eta}cos{\Omega}t)$ which the values of ${\eta},{\Omega}$ varied respectlvly, and $x_s$, $y_s$ are the periodic signal. As a result of simulating these methods, the chaotic phenomena was controlled with the periodic motion of periodisity. The feasibilities of the chaotic and the periodic phenomena were analysed by phase plane Poincare map and lyapunov exponent.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.210-212
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• 1995

Its is proposed that a stable adaptive control system composed of a fuzzy and a compensating controller, is designed to control nonlinear systems. In fuzzy and proposed compensating controller, parameters of membership functions characterizing the linguistic terms change according to some adaptive law. The adaptive law are based on the Lyapunov systhesis approach. the closed-loop system using the adaptive control structure proposed in this paper is globally stable in the sense that the Lyapunov function decreases as time goes. the following simulation shows the results.