• 전자공학회논문지 IE
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• v.46 no.4
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• pp.49-56
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• 2009

In this paper, stabilization inverse optimal control for nonlinear systems with structural uncertainty is considered. Based on the control Lyapunov function, a theorem for the globally asymptotic stability is presented. From this a less conservative condition for the inverse optimal control is derived. The result is used to design an inverse optimal controller for a class of nonlinear systems, that improves and extends the existing results. The class of nonlinear system considered is also enlarger. The simulation results show the effectiveness of the method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.610-615
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• 2003

This paper proposes a nonlinear virtual coupling fur haptic interface, which offers better performance while maintaining stability of the system. The nonlinear virtual coupling is designed based on a human response model. This human response model exploits delay between the human Intention and the actual change of arm impedance. The proposed approach provides with less conservative constraints for the design of stable haptic interface, compared with the traditional passivity condition. This allows increased performance that is verified through experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.7
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• pp.523-528
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• 2000

In this short note the characteristics of a nonlinear system of which the state trajectories are oscillating in the phase plane are overviewed. The physical concept of stuck and sliding patch phenomena are also introduced by adding some switching functions and their stability on the sliding patches are analyzed by using the Lyapunov stability theory and Frobenius theorem.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.578-583
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• 2002

This paper presents a method for designing fuzzy $H_2/H_{\infty}$ controllers of nonlinear systems with time varying delay. Takagi-Sugeno fuzzy model is employed to represent nonlinear systems with time varying delay. Using a single quadratic Lyapunov function, the globally exponential stability and $H_2/H_{\infty}$ performance problem are discussed. A sufficient condition for the existence of fuzzy $H_2/H_{\infty}$ controllers is then presented in terms of linear matrix inequalities(LMls). The proposed fuzzy $H_2/H_{\infty}$ controllers minimizes the upper bound on the linear quadratic performance measure.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.165-171
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• 2006

This paper proposes a data fusion algorithm of nonlinear multi sensor dynamic systems of synchronous sampling based on filtering step by step. Firstly, the object state variable at the next time index can be predicted by the previous global information with the systems, then the predicted estimation can be updated in turn by use of the extended Kalman filter when all of the observations aiming at the target state variable arrive. Finally a fusion estimation of the object state variable is obtained based on the system global information. Synchronously, we formulate the new algorithm and compare its performances with those of the traditional nonlinear centralized and distributed data fusion algorithms by the indexes that include the computational complexity, data communicational burden, time delay and estimation accuracy, etc.. These compared results indicate that the performance from the new algorithm is superior to the performances from the two traditional nonlinear data fusion algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1669-1674
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• 2004

In this paper, a nonlinear information filter (IF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, a nonlinear IF is used in place of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.42-47
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• 1993

Importance of separation of a nonlinear dynamical system into nonlinear static part and linear dynamical part was insisted in designing a controller for the nonlinear system. We further proposed compensation techniques for oscillation of controlled variables caused by system time delay and compensation of steady state errors caused by modelling errors of the systems. The proposed principle of designing procedure and the compensation methods were discussed by applying them for temperature and level control of an actual tanked water system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.133-136
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• 2003

This paper presents a fuzzy control scheme for backing up control of Truck-Trailer, which is nonlinear and unstable by using TSK(Takagi-Sugeno-kang) fuzzy system. The nonlinear system of Truck-Trailer was expressed by using TSK fuzzy model, and the TSK fuzzy controller was designed from TSK fuzzy model. The usefulness of the proposed algorithm for backing up truck-trailer is certificated by the computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.9
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• pp.719-727
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• 2002

We proposed a decoupled adaptive fuzzy sliding-mode control scheme for a class of fourth-order nonlinear systems. The system is decoupled into two second-order systems such that each subsystem has a separate control target expressed in terms of sliding surface. For these sliding surfaces, we define main and sub target conditions. and, we made intermediate variables which are interconnected both surface conditions from the sub target sliding surface. Then, Two sets of fuzzy rule bases are utilized to represent the equivalent control input with unknown system functions of the main target sliding surface including intermediate variables. The membership functions of the THEN-part, which is used to construct a suitable equivalent control of sliding-mode control, are changed according to the adaptive law. With such a design scheme, we not only maintain the distribution of membership functions over state space but also reduce the computing time considerably. We apply the decoupled adaptive sliding-mode control to a nonlinear Cart-Pole system and confirms the validity of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.4
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• pp.329-339
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• 2003

A neural network based adaptive controller design method is proposed for reconfigurable flight control systems in the presence of variations in aerodynamic coefficients or control effectiveness decrease caused by control surface damage. The neural network based adaptive nonlinear controller is developed by making use of the backstepping technique for command following of the angle of attack, sideslip angle, and bank angle. On-line teaming neural networks are implemented to guarantee reconfigurability and robustness to the uncertainties caused by aerodynamic coefficients variations. The main feature of the proposed controller is that the adaptive controller is designed with assumption that not any of the nonlinear functions of the system is known accurately, whereas most of the previous works assume that only some of the nonlinear functions are unknown. Neural networks loam through the weight update rules that are derived from the Lyapunov control theory. The closed-loop stability of the error states is also investigated according to the Lyapunov theory. A nonlinear dynamic model of an F-16 aircraft is used to demonstrate the effectiveness of the proposed control law.