• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.111-114
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• 1996

This paper proposes a robust control method using Universal Learning Network(U.L.N.) and second order derivatives of U.L.N.. Robust control considered here is defined as follows. Even if external input (equal to reference input in this paper) to the system at control stage changes awfully from that at learning stage, the system can be controlled so as to maintain a good performance. In order to realize such a robust control, a new term concerning the perturbation is added to a usual criterion function. And parameter variables are adjusted so as to minimize the above mentioned criterion function using the second order derivative of the criterion function with respect to the parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1147-1154
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• 2001

In this paper, a new iterative learning control scheme for discrete time nonlinear systems is proposed based on an objective function consisting of the output error and input energy. The relationships between the proposed ILC and the optimal control are described. A new input update law is proposed and its convergence is proved under certain conditions. In this proposed update law, the inputs in the whole control horizon are updated at once considered as one large vector. Some illustrative examples are given to show the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1608-1611
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• 2004

Anti-lock brake systems (ABS) are being increasingly used in a wide range of applications due to safety. This paper deals with a high performance optimal sliding mode controller for slip-ratio control in the ABS. In this approach a sliding surface square is considered as an appropriate cost function. The optimum brake torque as a system input is determined by minimizing the cost function and used in the controller. Simulation results reveal the effectiveness of the proposed sliding mode controller.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.482-484
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• 1994

In this paper, to realize high speed position control of LDM (Linear DC Motor), the minimum time control method is applied. But, In this control method, calculation of non-linear function is required Therefore, in order to avoid this complex calculation, optimum switching of the Bang-Bang control is done on parabola type switching function established in the plane of phase. But, the sliding mode is occurred due to the modeling error of LDM and the variation of parameters. Thereby, the optimum 'control is not realized. In order to realize optimum control, the algorithm to modify switching function is proposed

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.428-437
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• 2006

Many physical systems are hybrid in the sense that they have continuous behaviors and discrete phenomena. In control system with multiple models, switching strategy and stability of the closed-loop system under switching are very important issues. In this paper, a novel adaptive control scheme based on multiple parameter models is proposed to cope with a change in Parameters. Switching strategy guarantees the non-increase in the global control Lyapunov function if the estimation of Lyapunov function value converges. Least-square estimation is used to find the estimated value of the Lyapunov function. Switching and adaptation law guarantees the stability of closed-loop system in the sense of Lyapunov. Simulation results on anti-lock brake system are shown to verify the effectiveness of the proposed controller in view of a large change in system parameters.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.4
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• pp.748-755
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• 2001

This paper concerns rotor vibration reduction using magnetic damper system. The fuzzy control logic is utilized to fulfill desired motion. The fuzzy system structure and membership function were first determined by simulation results. The researched control logic contains two fuzzy controller : reference position variation according to the rotor whirling status and error compensation algorithm to minimize the rotor vibration due to unbalance and unstable fluid film force. The Sugeno type output membership function was utilized by several trials and optimized membership function constants were selected from experiments. The experimental results show that the proposed method effectively control and reduce the rotor vibration with fluid film bearings.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.142-147
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• 1999

This paper presents a new approach to the dynamic control technique for track vehicle system using neural network-fuzzy control method. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle.

• Journal of the Korean Mathematical Society
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• v.34 no.3
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• pp.581-598
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• 1997

This paper is concerned with the impulsive control problem $$ \dot{x}(t) = f(t, x) + g(t, x)\dot{u}(t), t \in [0, T], x(0) = \overline{x}, $$ where u is a possibly discontinuous control function of bounded variation, $f : R \times R^n \mapsto R^n$ is a bounded and Lipschitz continuous function, and $g : R \times R^n \mapsto R^n$ is continuously differentiable w.r.t. the variable x and satisfies $\mid$g(t,\cdot) - g(s,\cdot)$\mid$ \leq \phi(t) - \phi(s)$, for some increasing function $\phi$ and every s < t. We show that the map $u \mapsto x_u$ is Lipschitz continuous when u ranges in the set of step functions whose total variations are uniformly bounded, where $x_u$ is the solution of the impulsive control system corresponding to u. We also define the generalized solution of the impulsive control system corresponding to a measurable control functin of bounded variation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.262-262
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• 2000

This paper presents a new torque sharing function method that extends the definition region of the conventional TSF to both the positive and negative torque production regions. By using this definition, all kinds of the control inputs that consider switching on/off angle control as well as the current profiling can be described. A parametrized representation of the current profiles is proposed by using a series of B-spline functions, which reduces memory requirement and enables additional controllers. Optimal determination of the TSFs are also investigated for various control objectives. Moreover, the comparison study of each objective is presented. Since this method generalizes all of the possible control input, the current and torque profiles obtained from the optimization are the most suitable control input that satisfy the objectives.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.6
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• pp.548-553
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• 2008

In this paper, we propose a new swing-up control strategy for rotary inverted pendulums with restricted rotation range. The control law is derived from a Lyapunov function. The Lyapunov function is defined as the square of the sum of the absolute value of the total mechanical energy and weighted squares of the arm's angular displacement and velocity. By adjusting the weighting parameters in the Lyapunov function, we can affect the swing-up strategy such that the restriction on rotation range can be satisfied. Finally, we verify the performance of the proposed control law through simulation and experiments.