• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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• pp.305-311
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• 2003

We propose a new technique of adaptive-neuro controller design to implement real-time control of robot manipulator, Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of loaming a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real time control of robot system using DSPs(TMS320C50)

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 전문대학교육위원
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• pp.128-131
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• 2005

In this paper a robust controller using adaptive backstepping technique is proposed to control the speed of a wind turbine system. To make wind power generation truly cost effective and reliable, advanced and robust control algorithms are derived to on-line adjust the excitation winding voltage of the generator based on both mechanical and electrical dynamics. This method is shown to be able to achieve smooth and asymptotic rotor position tracking, as justified by analysis.

• 대한전기학회논문지
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• 제37권4호
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• pp.220-225
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• 1988

A class of adaptive controllers with integral action is proposed, which may riject the offset due to any load disturbance on the plant. Effective integral action and robust identification against the offset can be achieved via the zero-gain predictor. The system is improved, in this paper, to be of more generalized structure, and the detuning control weight which can cope with nonminimum-phase systems is tuned on-line. Discrete-time versions of the improved system are developed, which may be more flexible for the choice of the design parameters. The resulting control systems may also be shown to be robust to the unmodelled dynamics.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1227-1229
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• 2007

In this paper a robust controller using adaptive backstepping technique is proposed to control the position of wind power generation system. To make wind power generation truly cost effective and reliable, advanced and robust control algorithms are derived to on-line adjust the excitation winding voltage of the generator based on both mechanical and electrical dynamics. This method is shown to be able to achieve smooth and asymptotic rotor speed tracking, as justified by analysis and computer simulation.

• Journal of Power Electronics
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• 제10권5호
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• pp.505-517
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• 2010

In this paper, an intelligent sliding-mode speed controller for achieving favorable decoupling control and high precision speed tracking performance of permanent-magnet synchronous motor (PMSM) drives is proposed. The intelligent controller consists of a sliding-mode controller (SMC) in the speed feed-back loop in addition to an on-line trained wavelet-neural-network controller (WNNC) connected in parallel with the SMC to construct a robust wavelet-neural-network controller (RWNNC). The RWNNC combines the merits of a SMC with the robust characteristics and a WNNC, which combines artificial neural networks for their online learning ability and wavelet decomposition for its identification ability. Theoretical analyses of both SMC and WNNC speed controllers are developed. The WNN is utilized to predict the uncertain system dynamics to relax the requirement of uncertainty bound in the design of a SMC. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding mode speed controller. An experimental system is established to verify the effectiveness of the proposed control system. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulated and experimental results confirm that the proposed RWNNC grants robust performance and precise response regardless of load disturbances and PMSM parameter uncertainties.

• 로봇학회논문지
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• 제19권2호
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• pp.139-148
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• 2024

In this paper, we propose a two-degree-of-freedom snake robot head system and an I-PID (Intelligent Proportional-Integral-Derivative)-based controller utilizing RBF (Radial Basis Function) neural network and adaptive robust terms as a control strategy to reduce rotation occurring in the snake robot head. This study proposes a two-degree-of-freedom snake robot head system to avoid complex snake robot dynamics. This system has a control system independent of the snake robot. Subsequently, it utilizes an I-PID controller to implement a control system that can effectively manage rotation at the snake robot head, the robot's nonlinearity, and disturbances. To compensate for the time delay estimation errors occurring in the I-PID control system, an RBF neural network is integrated. Additionally, an adaptive robust term is designed and integrated into the control system to enhance robustness and generate control inputs responsive to signal changes. The proposed controller satisfies stability according to Lyapunov's theory. The proposed control strategy was tested using a 9-degreeof-freedom snake robot. It demonstrates the capability to reduce rotation in Lateral undulation, Rectilinear, and Sidewinding locomotion.

• Journal of Power Electronics
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• 제19권2호
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• pp.549-559
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• 2019

This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권3호
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• pp.173-181
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• 2004

In normal robot control systems without any actuator failures, it is assumed that actuator torque coefficients applied at each joint have normally 1's all the time. However, it is more practical that actuator torque coefficients applied at each joint are nonlinear time-varying. In other words, it has to be considered that actuators equipped at joints may fail due to hardware or software faults. In this work, actuator torque coefficients are assumed to have non-zero values at all joints. In the case of an actuator torque coefficient which has a zero value at a joint, it means the complete loss of torque on the joint. This paper doesn't deal with the case. As factors of performance degradation of robots, both actuator failures and uncertainties are considered in this paper at the same time. This paper proposes a robust adaptive fault-tolerant control scheme to maintain the required performance and achieve task completion for robot manipulators with performance degradation due to actuator failures and uncertainties. Simulation results are shown to verify the fault tolerance and robustness of the Proposed control scheme.

• 전력전자학회:학술대회논문집
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• 전력전자학회 1996년도 창립기념 전력전자학술발표회 논문집
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• pp.1-4
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• 1996

The purpose of this treatise is to estimate speed of an induction motor and realize a robust speed control system with estimated speed in field-weakening region. A speed estimation is based on Model Reference Adaptive System(MRAS) technique and two flux estimator are designed to be robust against parameter variation. The MRAS-based overall control scheme has been implemented on 7.5kW Spindle induction motor control system. And it is verified that the proposed control scheme is very stable and robust in field-weakening region.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.426-426
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• 2000

When real robot manipulators arc mathematically modeled, uncertainties are not avoidable. The uncertainties are often nonlinear and time varying, The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance and etc. We proposed a class of robust hybrid position/force control of manipulators and provided the stability analysis in the previous work. In the work, we propose a class of adaptive robust hybrid position/force control of manipulators with bound estimation and the stability based on Lyapunov function is presented. Especially, this controller does not need the information of uncertainty bound. The simulation results are provided to show the effectiveness of the algorithm.