• Title/Summary/Keyword: Lyapunov direct method

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A study on Real-Time Implementation of Robust Control for Horizontal Articulated Arm with Eight Axis

  • Nguyen, Hoo-Cong;Kim, Jun-Hong;Lee, Hee-Seop
    • Journal of the Korean Society of Industry Convergence
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    • v.18 no.3
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    • pp.139-149
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    • 2015
  • In this paper, we describe a new approach to perform real-time implementation of an robust controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs 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 robot manipulator consisting of dual arm with eight degrees of freedom at the joint space and cartesian space.

Development of an Adaptive Feedback based Actuator Fault Detection and Tolerant Control Algorithms for Longitudinal Autonomous Driving (적응형 되먹임 기반 종방향 자율주행 구동기 고장 탐지 및 허용 제어 알고리즘 개발)

  • Oh, Kwangseok;Lee, Jongmin;Song, Taejun;Oh, Sechan;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.12 no.4
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    • pp.13-22
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    • 2020
  • This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

A study on simulation and performance improvement of industrial robot manipulator controller using adaptive model following control method (적응모델추종제어기법에 의한 산업용 로봇 매니퓰레이터 제어기의 성능개선 및 시뮬레이션에 관한 연구)

  • 허남수;한성현;이만형
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.15 no.2
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    • pp.463-477
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    • 1991
  • This study proposed a new method to design a robot manipulator control system capable of tracking the trajectories of joint angles in a reasonable accuracy to cover with actual situation of varying payload, uncertain parameters, and time delay. The direct adaptive model following control method has been used to improve existing industrial robot manipulator control system design. The proposed robot manipulator controller is operated by adjusting its gains based on the response of the manipulator in such a way that the manipulator closely matches the reference model trajectories predefined by the designer. The manipulator control system studied has two loops: they are an inner loop on adaptive model following controller to compensate nonlinearity in the manipulator dynamic equation and to decouple the coupling terms and an outer loop of state feedback controller with integral action to guarantee the stability of the adaptive scheme. This adaptation algorithm is based on the hyperstability approach with an improved Lyapunov function. The coupling among joints and the nonlinearity in the dynamic equation are explicitly considered. The designed manipulator controller shows good tracking performance in various cases, load variation, parameter uncertainties. and time delay. Since the proposed adaptive control method requires only a small number of parameters to be estimated, the controller has a relatively simple structure compared to the other adaptive manipulator controllers. Therefore, the method used is expected to be well suited for a high performance robot controller under practical operation environments.

Design of Path Tracking Controller for Underactuated Autonomous Underwater Vehicle Using Approach Angle Concept (접근 각도 개념을 이용한 과소 작동기 무인 잠수정의 경로 추적 제어기 설계)

  • Kim, Kyoung-Joo;Choi, Yoon-Ho;Park, Jin-Bae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.2
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    • pp.225-231
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    • 2012
  • In this paper, we propose a method for designing the path tracking controller using an approach angle concept for an underactuated autonomous underwater vehicle (AUV). The AUV is controlled by the surge speed and yaw rate: there is no side thruster. To solve this underactuated AUV problem in the path tracking, we introduce an approach angle concept which makes the AUV converge to the reference path. And we design the path tracking controller using the proposed approach angle. To design the path tracking controller, we obtain the new vehicle's error dynamics in the body-fixed frame, and then design the path tracking controller based on Lypunov direct method. Finally, some simulation results demonstrate the effectiveness of the proposed controller.

Adaptive Feedback Linearization Control Based on Airgap Flux Model for Induction Motors

  • Jeon Seok-Ho;Baang Dane;Choi Jin-Young
    • International Journal of Control, Automation, and Systems
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    • v.4 no.4
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    • pp.414-427
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    • 2006
  • This paper presents an adaptive feedback linearization control scheme for induction motors with simultaneous variation of rotor and stator resistances. Two typical modeling techniques, rotor flux model and stator flux model, have been developed and successfully applied to the controller design and adaptive observer design, respectively. By using stator fluxes as states, over-parametrization in adaptive control can be prevented and control strategy can be developed without the need of nonlinear transformation. It also decrease the relative degree for the flux modulus by one, thereby, yielding, a simple control algorithm. However, when this method is used for flux observer, it cannot guarantee the convergence of flux. Similarly, the rotor flux model may be appropriate for observers, but it is not so for adaptive controllers. In addition, if these two existing methods are merged into overall adaptive control system, it brings about structural complexies. In this paper, we did not use these two modeling methods, and opted for the airgap flux model which takes on only the positive aspects of the existing rotor flux model and stator flux model and prevents structural complexity from occuring. Through theoretical analysis by using Lyapunov's direct method, simulations, and actual experiments, it is shown that stator and rotor resistances converge to their actual values, flux is well estimated, and torque and flux are controlled independently with the measurements of rotor speed, stator currents, and stator voltages. These results were achieved under the persistent excitation condition, which is shown to hold in the simulation.