• Title/Summary/Keyword: bounded parameters and signals

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On the robust adaptive linearizing control for unknown and analytic relay nonlinearity

  • Lee, Jae-Kwan;Abe, Ken-ichi
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10a
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    • pp.177-180
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    • 1996
  • The purpose of this paper is to design a robust adaptive control algorithm for a class of systems having continuous relay nonlinearity. This continuous relay nonlinearity can be defined as an analytic nonlinear function having unknown parameters and bounded unmodeling part. By this mathematical modeling, the whole system can be considered as a nonlinear system having unknown parameters and bounded perturbation. The control algorithm of this paper, RALC, can be constructed by robust adaptive law, feedback linearization, and indirect robust adaptive control. By this RALC, we can obtain that the output of given system can follow that of a stable reference linear model made by designer and the boundedness of all signals in closed-loop system can be maintained. Therefore, we can confirm a robust adaptive control for a class of systems having continuous relay nonlinearity.

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A nonlinear controller based on saturation functions with variable parameters to stabilize an AUV

  • Campos, E.;Monroy, J.;Abundis, H.;Chemori, A.;Creuze, V.;Torres, J.
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.11 no.1
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    • pp.211-224
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    • 2019
  • This paper deals with a nonlinear controller based on saturation functions with variable parameters for set-point regulation and trajectory tracking control of an Autonomous Underwater Vehicle (AUV). In many cases, saturation functions with constant parameters are used to limit the input signals generated by a classical PD (Proportional-Derivative) controller to avoid damaging the actuators; however this abrupt bounded harms the performance of the controller. We, therefore, propose to replace the conventional saturation function, with constant parameters, by a saturation function with variable parameters to limit the signals of a PD controller, which is the base of the nonlinear PD with gravitational/buoyancy compensation and the nonlinear PD + controllers that we propose in this paper. Consequently, the mathematical model is obtained, considering the featuring operation of the underwater vehicle LIRMIA 2, to do the stability analysis of the closed-loop system with the proposed nonlinear controllers using the Lyapunov arguments. The experimental results show the performance of an AUV (LIRMIA 2) for the depth control problems in the case of set-point regulation and trajectory tracking control.

Adaptive Formation Control of Nonholonomic Multiple Mobile Robots Considering Unknown Slippage (미지의 미끄러짐을 고려한 비홀로노믹 다개체 이동 로봇의 적응 군집 제어)

  • Choi, Yoon-Ho;Yoo, Sung-Jin
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.1
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    • pp.5-11
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    • 2010
  • An adaptive formation control approach is proposed for nonhonolomic multiple mobile robots considering unknown slipping and skidding. It is assumed that unknown slipping and skidding effects are bounded by unknown constants. Under this assumption, the adaptive technique is employed to estimate the bounds of unknown slipping and skidding effects of each mobile robot. To deal with the skidding effect included in kinematics, the dynamic surface design approach is applied to design a local controller for each mobile robot. Using Lyapunov stability theorem, the adaptation laws for tuning bounds of slipping and skidding are induced and it is proved that all signals of the closed-loop system are bounded and the tracking errors and the synchronization errors of the path parameters converge to an adjustable neighborhood of the origin. Finally, simulation results are provided to verify the effectiveness of the proposed approach.

DNN-Based Adaptive Optimal Learning Controller for Uncertain Robot Systems (동적 신경망에 기초한 불확실한 로봇 시스템의 적응 최적 학습제어기)

  • 정재욱;국태용;이택종
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.6
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    • pp.1-10
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    • 1997
  • This paper presents an adaptive optimal learning controller for uncertian robot systems which makes use fo simple DNN(dynamic neural network) units to estimate uncertain parameters and learn the unknown desired optimal input. With the aid of a lyapunov function, it is shown that all that error signals in the system are bounded and the robot trajectory converges to the desired one globally exponentially. The effectiveness of the proposed controller is hsown by applying the controller to a 2-DOF robot manipulator.

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Adaptive control of flexible joint manipulators based on the singular perturbation theory (특이 섭동 이론에 의한 유연성 관절 매니퓰레이터의 적응제어)

  • 김응석;양해원
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.7-11
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    • 1991
  • The adaptive control of flexible joint manipulator is the focus of this paper. The full order flexible joint manipulator dynamic system does not allow the determination of a feedback linearization control as for rigid manipulators. This drawback is overcome by a model order reduction based on a singular perturbation strategy. The full order flexible joint manipulator dynamic model is adopted for derivation of the adaptive control law to damp out the elastic oscillations at the joints. It is shown that the joint position error will converge to zero asymptotically and that other signals remain bounded without precise knowledge of parameters of the manipulator and its joint flexibility.

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A model reference adaptive fuzzy control for MIMO Takagi-Sugeno fuzzy model (MIMO Takagi-Sugeno 퍼지 모델을 위한 모델참조 적응 퍼지 제어기의 설계)

  • Cho, Young-Wan
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.1
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    • pp.130-135
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    • 2007
  • In this paper, a direct model reference adaptive fuzzy control (MRAFC) scheme is developed for the plant model whose structure is represented by the MIMO Takagi-Sugeno fuzzy model. The MRAFC scheme is proposed to provide asymptotic tracking of a reference signal lot the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee that all signals in the closed-loop system are bounded. In addition, the plant state tracks the state of the reference model asymptotically with time tot any bounded reference input signal.

Design of Single-input Direct Adaptive Fuzzy Logic Controller Based on Stable Error Dynamics

  • Park, Byung-Jae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.1 no.1
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    • pp.44-49
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    • 2001
  • For minimum phase systems, the conventional fuzzy logic controllers (FLCs) use the error and the change-of-error as fuzzy input variables. Then the control rule table is a skew symmetric type, that is, it has UNLP (Upper Negative and Lower Positive) or UPLN property. This property allowed to design a single-input FLC (SFLC) that has many advantages. But its control parameters are not automatically adjusted to the situation of the controlled plant. That is, the adaptability is still deficient. We here design a single-input direct adaptive FLC (SDAFLC). In the AFLC, some parameters of the membership functions characterizing the linguistic terms of the fuzzy rules are adjusted by an adaptive law. The SDAFLC is designed by a stable error dynamics. We prove that its closed-loop system is globally stable in the sense that all signals involved are bounded and its tracking error converges to zero asymptotically. We perform computer simulations using a nonlinear plant and compare the control performance between the SFLC and the SDAFLC.

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A Design of Stable Adaptive Composite Control Systems (안정한 적응 이중 제어시스템의 설계)

  • Zhang, Jeong-Il;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • 1994.11a
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    • pp.370-372
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    • 1994
  • In this paper, a stable adaptive composite control system consisting of a PID and a fuzzy controllers is designed to control nonlinear systems. In the fuzzy controller, parameters of membership functions characterizing the linguistic terms change according to some adaptive law. Also, parameters of PID controller change according to some adaptive law. These adaptive laws are based on the Lyapunov synthesis approach. Then, it is proved that the closed-loop system using such an adaptive composite control system is globally stable in the sense that all signals involved are bounded and the tracking error converges to zero. We apply this adaptive composite control system to control a nonlinear system.

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Synchronization of Network Interfaces in System Area Networks (시스템 에어리어 네트?에서의 동기화 기법)

  • Song, Hyo-Jung
    • Journal of KIISE:Computer Systems and Theory
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    • v.32 no.5
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    • pp.219-231
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    • 2005
  • Many applications in cluster computing require QoS (Quality of Service) services. Since performance predictability is essential to provide QoS service, underlying systems must provide predictable performance guarantees. One way to ensure such guarantees from network subsystems is to generate global schedules from applications'network requests and to execute the local portion of the schedules at each network interface. To ensure accurate execution of the schedules, it is essential that a global time base must be maintained by local clocks at each network interface. The task of providing a single time base is called a synchronization problem and this paper addresses the problem for system area networks. To solve the synchronization problem, FM-QoS (1) proposed a simple synchronization mechanism called FBS(Feedback-Based Synchronization) which uses built-in How control signals. This paper extends the basic notion of FM-QoS to a theoretical framework and generalizes it: 1) to identify a set of built-in network flow control signals for synchrony and to formalize it as a synchronizing schedule, and 2) to analyze the synchronization precision of FBS in terms of flow control parameters. Based on generalization, two application classes are studied for a single switch network and a multiple switch network. For each class, a synchroniring schedule is proposed and its bounded skew is analyzed. Unlike FM-QoS, the synchronizing schedule is proven to minimize the bounded skew value for a single switch network. To understand the analysis results in practical networks, skew values are obtained with flow control parameters of Myrinet-1280/SAN. We observed that the maximum bounded skew of FBS is 9.2 Usec or less over all our experiments. Based on this result, we came to a conclusion that FBS was a feasible synchronization mechanism in system area networks.

Design of an Adaptive Fuzzy Controller and Its Application to Controlling Uncertain Chaotic Systems

  • Rark, Chang-woo;Lee, Chang-Hoon;Kim, Jung-Hwan;Kim, Seungho;Park, Mignon
    • Transactions on Control, Automation and Systems Engineering
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    • v.3 no.2
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    • pp.95-105
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    • 2001
  • In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the chaotic state tracks the state of the stable reference model(SRM) asymptotically with time for any bounded reference input signal. The suggested AFC design technique is applied for the control of an uncertain Lorenz system based on T-S fuzzy model such as stabilization, synchronization and chaotic model following control(CMFC).

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