• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.394-400
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• 2008

A known nonlinear compensator design approach is adapted to allow design of nonlinear lead and/or lag compensators, and a number of MATLAB functions are developed that automate the compensator design procedure. With this design tool, control engineers would be able to rapidly design nonlinear lead and/or lag compensators. An example of a tutorial nature is presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.966-972
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• 2007

This paper presents position control of nonlinear three-dimensional crane systems using neural network approach. Such crane system generally includes very complicated characteristic dynamics and mechanical framework such that its mathematical model is expressed by strong nonlinearity. This leads difficulty in control design for the systems. We linearize the nonlinear system model to construct PID control applying well-known linear control theory and then neural network is utilized to compensate system perturbation due to linearization. Thus, control input of the crane system is composed of nominal PID and neural output signals respectively. Our method illustrates simple design procedure, but system perturbation and modelling error are overcome through a neural compensator. As well. adaptive neural control is constructed from online learning. Computer simulation demonstrates our control approach is superior to the classic control systems.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2863-2866
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• 2003

In nonlinear control fields, for irregular nonlinear systems, control form which consists of approximate tracking control law and exact tracking control law and which switches between two laws has been proposed recently. In this thesis, we design new switching control law which connect approximate linearization control law and exact linearization control law by fuzzy rules for irregular nonlinear system, ball and beam system. Fuzzy switching controller designed by fuzzy concept is proved that designed scheme overcomes singularities of irregular system, improves unstability problem of switching procedure, and has more efficient control value through simulation. Stability of fuzzy control system proved by Lyapunov's stability theorems.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.1031-1035
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• 2001

In this paper, a robust recursive control approach for nonlinear system, which is based on Lyapunov stability, is proposed. The proposed method can apply to extended systems including cascaded systems and the stability is guaranteed in the sense of Lyapunov. The recursive design procedure so called “robust recursive control approach” is used to find a stabilizing robust controller and simultaneously estimate the uncertainty parameters. First, a nonlinear model with uncertainties whose bounds are unknown is derived. Then, unknown bounds of uncertainties are estimated. By using these estimates, the stabilizing robust controller is updated at each step. This approach is applied to the pitch autopilot design of a nonlinear missile system and simulation results indicate good performance.

• East Asian mathematical journal
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• v.16 no.2
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• pp.317-330
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• 2000

In this paper we consider the optimal control problem of both operators and parameters for nonlinear hyperbolic systems. For the identification problem, we show that for every value of the parameter and operators, the optimal control problem has a solution. Moreover we obtain the necessary conditions of optimality for the optimal control problem on the system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.218-218
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• 2000

Advanced Vehicle Control Systems(AVCS) is one of the key elements in Intelligent Transportation Systems(ITS). This paper considers the problem of longitudinal control in vehicle platoon on a straight lane of a highway. In a very simplified situation, longitudinal vehicle dynamics contains many nonlinear elements. The nonlinear characteristics are mainly composed of an engine, a torque converter, and a drag force. In this paper, sliding control, one of nonlinear control methods, is applied to longitudinal automated vehicle control for platooning. Output feedback linearization is also simulated for comparison with the sliding control. Simulations for comparative study for the adopted controllers such as sliding control and output feedback linearization are peformed under the same conditions. This Paper aims at clarifying the characteristics of sliding control and output feedback linearization.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.994-998
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• 2005

A new control method, called a simple model matching, has been recently developed by the author. This is very simple and be applied for linear and nonlinear discrete time systems with/without time lag. Based on this formulation, identification is examined in this paper using an interconnected neural network with the EBP-EWLS learning algorithm. With this result, a control method is also presented for a nonlinear discrete time system.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.7
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• pp.575-582
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• 2004

The observer design problem is studied for a class of multi-output nonlinear systems that are not necessarily observable. Generalized nonlinear observer canonical form is introduced for multi-output nonlinear systems to design nonlinear observers. Sufficient conditions are given for a nonlinear system to be transformed by state-space change of coordinates into generalized nonlinear observer canonical form. Based on this canonical from, a sufficient condition is also given for the existence of nonlinear observers. An illustrative example is presented to show the design procedure of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.2
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• pp.76-82
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• 2009

A Heating, Ventilating and Air Conditioning (HVAC) system is a nonlinear multi-input multi-output (MIMO) system. This system is very difficult to control the temperature and the humidity ratio of a thermal space because of complex nonlinear characteristics. This paper proposes an adaptive fuzzy output feedback control based on observer for the nonlinear HVAC system. The nonlinear HVAC system is linearized through dynamic extension. State observers are designed for estimating state variables of the HVAC system. Fuzzy systems are employed to approximate uncertain nonlinear functions of the HVAC system with unavailable state variables. The obtained controller compares with an adaptive feedback controller. Simulation is given to demonstrate the effectiveness of our proposed adaptive fuzzy method.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.244-251
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• 2005

In this paper, we study the problem of stabilizing a general nonlinear control system by means of gradient descent control method which is a dynamic feedback control law. In this method, the general nonlinear control system can be considered as an affine nonlinear control systems. Then by using Sontag's formula we investigate the stability (asymptotic) of the general nonlinear control system.