• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.3
• /
• pp.261-269
• /
• 2014

This paper provides an overview of the basics and recent studies of Lyapunov-based nonlinear adaptive control, the aim of which is to improve or maintain the performance and stability of the closed-loop system by cancelling out the presumable uncertainties in the nonlinear system dynamics. The design principles are essentially based on Lyapunov's direct method. In this survey, we provide a comprehensive overview of Lyapunov-based nonlinear adaptive control techniques with simplified effective design examples, which are to be elaborated as related recent results are gradually shown. The scope of the survey contains research on singularity problems in adaptive control, the techniques to deal with linearly and nonlinearly parameterized uncertainties, robust neuro-adaptive control, and adaptive control methodologies combined with various nonlinear control techniques such as sliding-mode control, back-stepping, dynamic surface control, and optimal/$H_{\infty}$ control.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.10
• /
• pp.17-24
• /
• 1999

본 논문에서는 새로운 적응 퍼지 슬라이딩 모드제어 방법을 제시하였다. 제어기는 정확한 수확적인 모델이 없이도 점근적으로 시스템을 안정화시킬 수 있으며 적분항을 포함시킴으로서 정상상태에서의 오차를 좀 더 줄일 수가 있다. 직접구동모터는 감쇄기어가 없어서 부하나 외란 토크의 변화에도 모터 역학에 직접적으로 많은 영향을 줄 수가 있다. 제어기의 실제성능을 확인하기 위하여 불확실한 부하나 변소를 갖는 직접구동모터의 위치제어에 적용하였다.

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

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.4 no.3
• /
• pp.603-610
• /
• 2000

In this paper, the direct and indirect adaptive controller are combined based on the Lyapunov synthesis approach. The Proposed controller is constructed from RBF Neural Network and weighting parameters are adjusted on-line according to some adaptation law. In this scheme, fuzzy IF-THEN rules are used to decide the combined weighting factor. In the results, proposed controller has the main advantages of both the direct adaptive controller and the indirect adaptive controller. The effectiveness of the proposed control scheme is demonstrated through simulation results of control for one-link rigid robotics manipulator.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.12
• /
• pp.2708-2715
• /
• 2012

This paper proposes a new sensorless speed control scheme of induction motor using Model Reference Adaptive Control and Direct Torque Control System. The Model Reference Adaptive Control System is based on the comparison between the outputs of Reference Model and Adjustable Model. The error between the estimated quantities obtained by the two models is used to drive a suitable adaptation mechanism which generates the estimated rotor speed for the Adjustable Model. And the Direct Torque Control scheme controls torque and flux by restricting the flux and torque errors within respective hysteresis bands, and motor torque and flux are controlled by the stator voltage space vector using optimum inverter switching table. The simulation results of proposed method indicate good speed responses from the low speed range to the high, and also show favorable characteristics of load operation.

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

• Journal of Power Electronics
• /
• v.9 no.4
• /
• pp.582-592
• /
• 2009

This paper proposes a new speed sensorless direct torque and flux controlled interior permanent magnet synchronous motor (IPMSM) drive. Closed-loop control of both the torque and stator flux linkage are achieved by using two proportional-integral (PI) controllers. The reference voltage vectors are generated by a SVM unit. The drive uses an adaptive sliding mode observer for joint stator flux and rotor speed estimation. Global asymptotic stability of the observer is achieved via Lyapunov analysis. At low speeds, the observer is combined with the high frequency signal injection technique for stable operation down to standstill. Hence, the sensorless drive is capable of exhibiting high dynamic and steady-state performances over a wide speed range. The operating range of the direct torque and flux controlled (DTFC) drive is extended into the high speed region by incorporating field weakening. Experimental results confirm the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10a
• /
• pp.870-875
• /
• 1987

The payload variation and modeling error can lye parameterized in such a way that known nonlinear functions are multiplied linearly by parameter errors. An adaptive control algorithm is derived for a perturbed linear system with such parameterization. Hence, in this approach no linear approximation of robot system is needed for the application of an adaptive law. The stability of the adaptive control algorithm is established and also supported by a computer simulation result.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.5
• /
• pp.25-32
• /
• 1996

This paper will propose the direct adaptive learning control scheme based on adaptive control technique and intelligent control theory for a nonlinear system. Using the proposed learning control scheme, we will apply to on-line control an uncertain but for model perfect matching, it's structure condition is known. The effectiveness of the proposed control schem will be illustrated by simulations of a robot manipulator.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1179-1181
• /
• 1996

In this paper, method for direct adaptive control of discrete nonlinear systems using neural network is presented. Also, the stability problems are investigated in sense of the Lyapunov stability conditions. Through extensive simulation, the SOON is shown to be effective for indirect adaptive control of nonlinear dynamic systems.