• Journal of the Korean Society for Precision Engineering
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• v.25 no.6
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• pp.62-70
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• 2008

An adaptive fuzzy backstepping controller is proposed for the motion control for a single-link flexible-joint robot in the presence of parametric uncertainties. Fuzzy logic system is used to approximate the uncertainties of functions and a backstepping technique is employed to deal with the mismatched problem. A compensation controller is also employed to estimates the bound of approximation error so that the shattering effect of the control effort can be reduced. Thus the asymptotic stability of the closed loop control system can be obtained based on a Lyapunov synthesis approach. Numerical simulation results for a single-link flexible-joint robot are included to show the effectiveness of proposed controller.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.175-184
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• 1996

In this paper the newly developed discrete-time adaptive sliding mode control method is proposed and applied to the power system stabilization problem. In contrast to the conventional continuous-time sliding mode controller, the proposed method is developed in the discrete-time domain and based on the input/output measurements instead of the continuous-time and the full-states feedback, respectively. Because the proposed control method has the adaptivity property in addition to the natural robustness property of the sliding mode control, it is possible to design the power system stabilizer which can overcome both the minor variations of the parameters of the power system and the diverse operating conditions and faults of the power system. Mathematical proof and the various computer simulations are done to verify the performance and stability of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.128-137
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• 2007

A robust adaptive controller design for a class of Markovian jump parametric -strict-feedback systems is given. The disturbances considered herein include both uncertain nonlinearities and Wiener noises of unknown covariance. And they satisfy some bound-conditions. By using stochastic Lyapunov method in Markovian jump systems, a switching robust adaptive controller was obtained that guarantees global uniform ultimate boundedness of the closed-loop jump system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.9
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• pp.423-429
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• 2001

This paper proposes adaptive impedance control algorithm using fuzzy inference when robot contacts with its environments. The characteristics of the adaptive impedance controller is to adapt with parametric uncertainty and nonlinear conditions. The control algorithm is to join impedance controller with fuzzy inference engine. The proposed control method overcomes the problem of impedance controller using gain-tuning algorithm of fuzzy inference engine. We implemented an experimental set-up consisting of environment-generated one-link robot system and DSP system for controller development. We apply the adaptive fuzzy impedance controller to one-link root system, and it shows the good performance on regulating the interactive force in case of contacting with arbitrary environment.

• Journal of Drive and Control
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• v.19 no.1
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• pp.51-61
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• 2022

This paper presents a model-free system based on a framework of a backstepping sliding mode control (BSMC) with a radial basis function neural network (RBFNN) and adaptive mechanism for electro-hydraulic systems (EHSs). First, an EHS mathematical model was dedicatedly derived to understand the system behavior. Based on the system structure, BSMC was employed to satisfy the output performance. Due to the highly nonlinear characteristics and the presence of parametric uncertainties, a model-free approximator based on an RBFNN was developed to compensate for the EHS dynamics, thus addressing the difficulty in the requirement of system information. Adaptive laws based on the actor-critic neural network (ACNN) were implemented to suppress the existing error in the approximation and satisfy system qualification. The stability of the closed-loop system was theoretically proven by the Lyapunov function. To evaluate the effectiveness of the proposed algorithm, proportional-integrated-derivative (PID) and improved PID with ACNN (ACPID), which are considered two complete model-free methods, and adaptive backstepping sliding mode control, considered an ideal model-based method with the same adaptive laws, were used as two benchmark control strategies in a comparative simulation. The simulated results validated the superiority of the proposed algorithm in achieving nearly the same performance as the ideal adaptive BSMC.

• Journal of Korean Association for Spatial Structures
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• v.18 no.4
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• pp.97-104
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• 2018

A connected control method for the adjacent buildings has been studied to reduce dynamic responses. In these studies, seismic loads were generally used as an excitation. Recently, multi-hazards loads including earthquake and strong wind loads are employed to investigate control performance of various control systems. Accordingly, strong wind load as well as earthquake load was adopted to evaluate control performance of adaptive smart coupling control system against multi-hazard. To this end, an artificial seismic load in the region of strong seismicity and an artificial wind load in the region of strong winds were generated for control performance evaluation of the coupling control system. Artificial seismic and wind excitations were made by SIMQKE and Kaimal spectrum based on ASCE 7-10. As example buildings, two 20-story and 12-story adjacent buildings were used. An MR (magnetorheological) damper was used as an adaptive smart control device to connect adjacent two buildings. In oder to present nonlinear dynamic behavior of MR damper, Bouc-Wen model was employed in this study. After parametric studies on MR damper capacity, optimal command voltages for MR damper on each seismic and wind loads were investigated. Based on numerical analyses, it was shown that the adaptive smart coupling control system proposed in this study can provide very good control performance for Multi-hazards.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.111-114
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• 1996

Hydroponics is to grow plants, not in soil but in water which the quantity of necessary chemical food can be controlled. In this paper, this is designed in the automatic system. The closed culture reduces cost of production and produces a many kinds of agricultural products in a confined place. An adaptive fuzzy control in the best method to solve and to overcome parametric uncertainties and non-linearity of the controlled system. A hydroponics automation system which is able to overcome these control problems. It is used in implementation of the hydroponics automation system. The performance is analyzed through an experiment in which the new adaptive fuzzy control method is applied to the automatic control of tomato hydroponics.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.165-168
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• 1996

In this paper, we propose a design method of PID adaptive controller based on frequency domain analysis. The method is based on the estimation of a nonparametric process model in the frequency domain and the determination of the PID controller parameters by achieving partial model matching so as to minimize a performance function concerning to relative model error between the loop transfer function of the control system and the desired system. In the design method the process is represented only by a discrete set of points on the Nyquist curve of the process. Therefore it is not necessary to estimate a full order parameterized process model.

• International Journal of Ocean System Engineering
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• v.3 no.2
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• pp.50-60
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• 2013

This paper presents a novel approach to the design of an adaptive fuzzy sliding mode controller for depth control of an autonomous underwater vehicle (AUV). So far, AUV's dynamics are highly nonlinear and the hydrodynamic coefficients of the vehicles are difficult to estimate, because of the variations of these coefficients with different operating conditions. These kinds of difficulties cause modeling inaccuracies of AUV's dynamics. Hence, we propose an adaptive fuzzy sliding mode control with novel fuzzy adaptation technique for regulating vertical positioning in presence of parametric uncertainty and disturbances. In this approach, two fuzzy approximator are employed in such a way that slope of the linear sliding surface is updated by first fuzzy approximator, to shape tracking error dynamics in the sliding regime, while second fuzzy approximator change the supports of the output fuzzy membership function in the defuzzification inference module of fuzzy sliding mode control (FSMC) algorithm. Simulation results shows that, the reaching time and tracking error in the approaching phase can be significantly reduced with chattering problem can also be eliminated. The effectiveness of proposed control strategy and its advantages are indicated in comparison with conventional sliding mode control FSMC technique.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.73-82
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• 1995

The paper demonstrates that an adaptive fuzzy controller can be used effectively for the control of the temperature and density of the Tokarnak fusion recator which is nonlinear and has dynamic uncertainties. The dynamic uncertainties are non-parametric but state dependent. Thus the conventional adaptive nonlinear control methods have difficulties to cope with the problem. The proposed adaptive fuzzy controller can be used as a solution and performs well in a predetermined local space. Simulation result verifies the effectiveness of the scheme.