• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.93-99
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• 2003

One of the methods to simplify the design process for a fuzzy logic controller (FLC) is to reduce the number of variables representing the rule antecedent. This in turn decreases the number of control rules, membership functions, and scaling factors. For this purpose, we designed a single-input FLC that uses a sole fuzzy input variable. However, it is still deficient in the capability of adapting some varying operating conditions although it provides a simple method for the design of FLC's. We here design two simple-structured adaptive fuzzy logic controllers (SAFLC's) using the concept of the single-input FLC. Linguistic fuzzy control rules are directly incorporated into the controller by a fuzzy basis function. Thus some parameters of the membership functions characterizing the linguistic terms of the fuzzy control rules can be adjusted by an adaptive law. In our controllers, center values of fuzzy sets are directly adjusted by an adaptive law. Two SAFLC's are designed. One of them uses a Hurwitz error dynamics and the other a switching function of the sliding mode control (SMC). We also prove that 1） their closed-loop systems are globally stable in the sense that all signals involved are bounded and 2） their tracking errors converge to zero asymptotically. We perform computer simulations using a nonlinear plant.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2540-2545
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• 2003

We propose a new technique to the design and real-time implementation of an adaptive controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved direct Lyapunov method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot consisting of two 4-d.o.f. robots at the joint space and cartesian space.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.741-746
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• 2004

We propose a new technique to the design and real-time implementation of an adaptive controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved direct Lyapunov method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot consisting of two 4-d.o.f. robots at the joint space and cartesian space.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.26-30
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• 1995

In this study, the fuzzy approximator and sliding mode control (SMC) scheme are considered. An adaptive sliding mode control is proposed based on the SMC theory. This proposed control scheme is that a adaptive law is utilized to approximate the unknown function f by fuzzy logic system in designing the sliding mode controller for the nonlinear system. In order to reduce the approximation errors, the differences of nonlinear function and fuzzy approximator, an adaptive law is also intoduced and the stability of proposed control scheme are proven with simple adaptive law and roburst adaptive law. This proposed control scheme is applied to a single link robot arm.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.154-161
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• 1999

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.79-84
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manipulators to achieve trajectory tracking by the joint angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time-varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.4
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• pp.26-37
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C30) for robotic manipulators to achieve trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed control scheme adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller. feedback controller. and PID type time-varying auxiliary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Moreover, this scheme does not require a an accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the adaptive controller is illustrated by simulation and experimental results for a SCARA robot.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.11
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• pp.2862-2868
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• 1996

A sueueing model is developed and analyzed to evaluate the performance of a local and a remote destination of one multicast connection subject to a simple two-level(binary) feedback-based adaptive rate control scheme. The reate control scheme is a simple extension of the one for point-to-point case. Individual cell loss probabilities at the local and remote destinations are obtained to study the fairness of the adaptive rate control scheme. Numerical results show that this simple adaptive rate control scheme, which is fair when it is applied to a multicast connection consisting of destinations with equal propagation delays, bears bias against remote destination.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.139-145
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• 2006

A multi-variable Golden-Section adaptive controller is proposed for the tracking control of robotic manipulators with unknown dynamics. With a small sample time, the unknown dynamics of the robotic manipulator are denoted equivalently by a characteristic model of a 2-order multivariable time-varying difference equation. The coefficients of the characteristic model change slowly with time and some of their valuable characteristic relationships emerge. Based on the characteristic model, an adaptive algorithm with a simple form for the control of robotic manipulators is presented, which combines the multi-variable Golden-Section adaptive control law with the weighted least squares estimation method. Moreover, a compensation neural network law is incorporated into the designed controller to reduce the influence of the coefficients estimation error on the control performance. The results of the simulations indicate that the developed control scheme is effective in robotic manipulator control.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1142-1144
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• 2003

This Paper presents a speed controller based on the adaptive fuzzy tuning method for brushless DC(BLDC) motor drives under load variations. Generally, the speed tracking control systems use PI controller due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, PI controller of which the parameters are modified during operation by adaptive fuzzy tuning method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.