• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.48.2-48
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• 2001

This paper deals with robust integral tracking control problem based on Lyapunov method via FL(Feedback Linearization) in order to solve a reference tracking problem of nonlinear system with parameter uncertainties. To overcome a restrictive matching condition the uncertainties is characterized in a suitable form. The design procedure which combine FL and LMIs(Linear Matrix Inequalities) based on Lyapunov method to achieve the robust performance and stability is developed. Finally, the performance of proposed controller is demonstrated via simulation of a linear reference tracking problem in the MLS(Magnetic levitating System).

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.271-274
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• 1995

This paper is concerned with the problem of robust stabilization of uncertain single-input and single-output nonlinear systems. Based on the input/output linearization approach for nonlinear state feedback synthesis in conjunction with Lyapunov methods, a stabilizing state feedback controller is proposed. Compared with the controllers reported in the control literature, instead of uniform ultimate boudedness, the controller proposed in this paper can guarantee uniform asymptotic stability of nonlinear systems in the presence of uncertainties. The required information about uncertain dynamics in the system is only that the uncertainties are bounded in Euclidean norm by known functions of the system state.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1650-1651
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• 2007

This paper presents a novel nonlinear speed control strategy for induction motor utilizing exact feedback linearization with states feedback. The speed and flux control loops utilize nonlinear feedback which eliminates the need for tuning, while ordinary proportional-integral controllers are used to control the stator current of d-axis the speed. The control scheme is derived in rotor field coordinates and employs an appropriate estimator for estimation of the rotor flux angle, flux magnitude.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.582-589
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• 2003

This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included Un the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.405-412
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• 1992

The problem we consider in this paper is more demanding than the problem of input-output linearization with state equivalence recently solved by Cheng, Isidori, Respondek, and Tarn. We request that the MIMO nonlinear system, for which the problem of input-output linearization with state-equivalence is solvable, can be decoupled. In exchange for further requirement like this, our problem produces more usable and informative results than the problem of input-output linearization with state-equivalence. We present the necessary and sufficient conditions for our problem to be solvable. We characterize each of the nonlinear systems satisfying these conditions by a set of parameters which are invariant under the group action of state feedback and transformation. Using this set of parameters, we can determine directly the unique one, among the canonical forms of decouplable and controllable linear systems, to which a nonlinear system can be transformed via appropriate state feedback and transformation. Finally, we present the necessary and sufficient conditions for our problem to be solvable with internal stability, that is, for stable decoupling.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2116-2124
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• 2018

Magnetic levitation system with the advantages of non-contact, no friction and no wear can satisfy the requirement of high precision and high speed positioning. In this paper, magnetic levitation positioning stage which mainly consists of planar coil and HALBACH permanent magnet array and its control and driving system are designed. Magnetic levitation system is a highly nonlinear and strongly coupled complex system and its control performance can be influenced by the uncertainty and external disturbance. So exact feedback linearization method is used to realize exact linearization and decoupling, and a strategy of sliding mode control based on disturbance observer is proposed to compensate the uncertainty and external disturbance. Detailed proofs of observer's convergence property and system stability are derived. Both the simulation and experiment results verify the effectiveness of sliding mode control algorithm based on disturbance observer.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.12
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• pp.19-26
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• 1991

In this paper, we give a structure algorithm for the synthesis problems of the nonlinear system via dynamic feedback. Using our algorithm, sufficient conditions for the input-output synthesis problems are discussed. The problems we consider in this paper include dynamic input-output decoupling input-output linearization, and immersion into a linear system.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.7
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• pp.690-695
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• 1991

The ability to linearize a nonlinear system by feedback and coordinate change reduces to finding an integrating factor for a one-form which is determined from the system dynamics. Utilizing Taylor series expansion of this one-form, we characterize approximate linearizabilitu. A constructive method is derived for approximate linearization up to order 2.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.410-415
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• 2013

This paper proposes a bidirectional platoon control law using a coupled distance error based on the backstepping-like feedback linearization control method for an interconnected mobile agent system with a string structure. Unlike the previous results where the single agent was controlled using the only own information without other agents, the proposed control law cannot show the only distance error convergence of each agent, but also the string stability of the whole system. Also, the control performances are improved by the proposed control law in spite of low performance of bidirectional control strategy in the previous results. The proposed bidirectional platoon control algorithm is based on the backstepping-like feedback linearization control method. The position errors between each agent and the preceding and the behind agents are coupled by weighted summation. By the proposed control law, the distance error of each agent can converge to zero while the string stability is guaranteed when the coupled errors can converge to zero. To this end, the back-stepping control method is employed. The pseudo velocity input is determined considering the kinematic relationship between agents and the string stability. Then, the actual dynamic control input is determined to make the actual velocity converge to the pseudo velocity input. The stability analysis and the simulation results of the proposed method are included in order to demonstrate the practical application of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.1
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• pp.30-39
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• 2000

In order to linearize the nonlinear systems, two different methods(i.e. state coordinate change and feedback) are usually used. In this paper, we consider the multi-input discrete-time nonlinear systems and obtain the necessary and sufficient conditions for both the linearization problem by state-coordinate change and the feedback linearization problem. The way of finding state coordinate change and state feedback which linearize the given system is also given in the proof.