• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.88-93
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• 1995

This paper presents a study using neural networks in the design of the tracking controller of robotic systems. Our strategy is to put to use the available knowledge about the robot manipulator, such as estimation models, in the contoller design via the computed torque method, and then to add the neural network to control the remaining uncertainty. The neural network used here learns to provide the inverse dynamics of the plant uncertainty, and acts as an inverse controller. In the simulation study, we verify that the proposed neural network controller is robust not only to structured uncertainties, but also to unstructured uncertainties such as friction models.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.424-428
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• 2016

A simple new sufficient condition for asymptotic stability of the positive linear time-varying discrete-time systems, with unstructured time-varying uncertainty in delayed states, is established in this paper Compared with previous results that cannot be applied to time-varying systems; the time-varying system and delay time are considered simultaneously in this paper. The proposed conditions are compared with suitable conditions for the typical discrete-time systems. The considerations are illustrated by numerical examples of previous work.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.463-465
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• 1998

In this paper, we consider the problem of robust stability of large-scale uncertain linear systems with time-varying delays. The considered uncertainties are both unstructured uncertainty which is only known its norm bound and structured uncertainty which is known its structure. Based on Lyapunov stability theorem and $H_{\infty}$ theory. we present uncertainty upper bound that guarantee the robust stability of systems. Especially, robustness bound are obtained directly without solving the Lyapunov equation. Finally, we show the usefulness of our results by numerical example.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.615-621
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• 1999

In this paper, we consider the robust stability of uncertain linear systems with time-delay in the time domain. The considered uncertainties are both the unstructured uncertainty which is only Known its norm bound and the structured uncertainty which is known its structured. Based on Lyapunov stability theorem and{{{{ { H}_{$\infty$ } }}}} theory known as Strictly Bounded Real Lemma (SBRL), we present new conditions that guarantee the robust stability of system. Also, we extend this to multiple time-varying delays systems and large-scale systems, respectively. Finally, we show the usefulness of our results by numerical examples.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.6 s.171
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• pp.90-97
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• 2005

Magnetic flywheel system utilizes a magnetic bearing, which is able to support the shaft without mechanical contacts, and also it is able to control rotational vibration. Magnetic flywheel system is composed of position sensors, a digital controller, actuating amplifiers, an electromagnet and a flywheel. This work applies the neuro-fuzzy control algorithm to control the vibration of a magnetic flywheel system. It proposes the design skill of an optimal controller when the system has structured uncertainty and unstructured uncertainty, i.e. it has a difficulty in extracting the exact mathematical model. Inhibitory action of vibration was verified at the specified rotating speed. Unbalance response, a serious problem in rotating machinery, is improved by using a magnetic bearing with neuro-fuzzy algorithm.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.10 s.103
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• pp.1148-1159
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• 2005

In this paper, the various uncertainties generated in an optical disk drive (ODD) and the robust servo designs considering the uncertainties are studied. First, the brief introduction an ODD and the servo error tolerance of it are discussed. Then, the classifications of uncertainty and the concept of relative stability are introduced. Considering the uncertainty of an ODD, two robust control approaches are applied: (i) mixed sensitivity approach in H$\infty$ control theory for unstructured uncertainty, (ii) QFT for structured uncertainty Finally, the designed controllers are realized by DSP, and these controllers are applied to a commercial DVD-ROM drive. From these experiments, we prove that the designed robust controllers have more good disturbance rejection performance and robustness when it is compared to the conventional lead-lag controller.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.52-54
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• 1991

In this paper, the robust stability, and the quadratic performance of linear uncertain systems are studied. A quadratic Lyapunov function candidate with time-varying matrix is derived to provide robust stability bounds. Also upper bounds of a quadratic performance is given under the assumption that the uncertain system is stable. Both the robust stability bounds and the upper bounds of a quadratic performance are obtained as solutions of a class of modified Lyapunov equations.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.1982-1984
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• 1997

In this paper, adaptive variable structure control is proposed for Electromagnetic Suspension(EMS). Although variable structure control shows excellent robustness to unstructured modelling uncertainty, such as flux leakage and saturation, it has several drawbacks that severely limit practical applicability such as high control activity and control chattering. To minimize these effects, the mass of the electromagnet and efficiency of levitation force are estimated on-line to reduce the range of system uncertainty. The effectiveness of the proposed control scheme is verified by experimental results using a 1.5kg electromagnet and DSP (TMS320C31).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.432-437
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• 1998

Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently fuzzy controllers have become quite popular for robust control due to its capability of dealing with unstructured uncertainty. Thus in this paper we design an adaptive fuzzy controller using an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Simulation results show that satisfactory performance is achieved by the proposed controller.