• Proceedings of the KIPE Conference
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• 1999.07a
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• pp.382-385
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• 1999

In this paper, by means of Lyapunov second method, the stability of IPD control servo systems is analyzed in the time domain for the first time. Based on the results of the stability analysis, the design rule to select the gain of IPD control is suggested such that the maximum error of output to the nominal system is guaranteed for all uncertainty and load variations. An example of a position control of a brushless dc motor is given to prove the unusefulness of the gain design rule.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2763-2765
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• 2003

Generally, we made use of PID control for torque control, speed control and stability, Hence, dynamic characteristic of DC motor has been studied for stable drive and accurate speed control by many engineers. But, in this paper, we applied genetic algorithm to current control for robust control and stability In conclusion, we prove that current control of genetic algorithm can be high efficiency.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.574-578
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• 2001

The stability analysis for the fuzzy logic controller (FLC) has widely been reported. Furthermore many research in the FLC has been introduced to decrease the number of parameters representing the antecedent part of the fuzzy control rule. In this paper we briefly explain a single-input fuzzy logic controller (SFLC) or simple-structured FLC which uses only a single input variable. And then we analyze that it is absolutely stale based on the sector bounded condition. We also show the feasibility of the proposed stability analysis through a numerical example of a mass-damper-spring system.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.53.6-53
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• 2002

$\textbullet$ Present a new stability analysis method of NCSs $\textbullet$ Propose the stability condition of NCSs with dynamic controller $\textbullet$ Find the stability region where NCSs for power system are guaranteed to be stable $\textbullet$ Determine a proper sampling period of NCSs that preserves desired stability performance $\textbullet$ Experiment : NCSs for power system using CAN.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.189-195
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• 2000

The mathematical solutions of the stability convergence are important problems in system control. In this paper such problems are analyzed and resolved for system control using multilayer neural networks. We describe an algorithm to control an unknown nonlinear system with a disturbance, using a multilayer neural network. We include a disturbance among the modeling error, and the weight update rules of multilayer neural network are derived to satisfy Lyapunov stability. The overall control system is based upon the feedback linearization method. The weights of the neural network used to approximate a nonlinear function are updated by rules derived in this paper . The proposed control algorithm is verified through computer simulation. That is as the weights of neural network are updated at every sampling time, we show that the output error become finite within a relatively short time.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.3
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• pp.164-169
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• 2001

This paper considers the problem of robust stabilization and disturbance attenuation for a class of uncertain singularly perturbed systems with norm-bounded nonlinear uncertainties. It is shown that the state feedback gain matrices can be determined to guarantee the stability of the closed-loop system for all $\varepsilon$$\in$(0, $\infty$). Based on this key result and some standard Riccati inequality approaches for robust control of singularly perturbed systems, a constructive design procedure is developed.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.545-558
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• 2006

In this paper, PD-like visual servoing is modified in two ways: a sliding-mode observer is applied to estimate the joint velocities, and a RBF neural network is used to compensate the unknown gravity and friction. Based on Lyapunov method and input--to-state stability theory, we prove that PD-like visual servoing with the sliding mode observer and the neuro compensator is robust stable when the gain of the PD controller is bigger than the upper bounds of the uncertainties. Several simulations are presented to support the theory results.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.147-153
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• 2002

In the preceding research, the active balancing device, which is an electro-magnetic type, has been developed and active balancing method using influence coefficient method is also proposed. The stability of active balancing control is studied in this paper. A stable condition for active balancing control is derived by estimating errors of influence coefficients. A gain scheduling control using influence coefficients of the reference model is proposed when dynamic characteristic of rotor system is changed. The stability of the balancing method is verified by experiments.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.12-14
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• 1998

Sensorless PMSM is much studied for the industrial applications and home appliances because a mechanical sensor reduces reliability and increases cost. This paper studies the stability of sensorless speed control of PMSM using state observer. Sensorless control scheme using state observer is known as a scheme having a comparatively good performance. Several papers have studied the stability of state observer control scheme, but have not considered parameter variation which is important to sensorless control. This paper studies the stability through computer simulation in case of parameter variation.

• Journal of applied mathematics & informatics
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• v.8 no.3
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• pp.829-840
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• 2001

Generally it is not easy task whether the stable systems governed by nonlinear ordinary differential equations are asymptotically stable or not. This problem often appears in studying a collision and avoidance control problem based on the stability theory. In this paper we devoted to finding conditions that the stable system obtained from the collision and avoidance control problem is asymptotically stable.