• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.11
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• pp.753-763
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• 2015

This paper proposes a decentralized robust adaptive neural network control scheme using multiple radial basis function neural networks for electrically driven robot manipulators with bounded input voltages in the presence of uncertainties. The proposed controller considers both robot link dynamics and actuator dynamics. Practically, the controller gain coefficients applied at each joint may be nonlinear time-varying and the input voltage at each joint is saturated. The proposed robot controller overcomes the various uncertainties and the input voltage saturation problem. The proposed controller does not require any robot and actuator parameters. The adaptation laws of the proposed controller are derived by using the Lyapunov stability analysis and the stability of the closed-loop control system is guaranteed. The validity and robustness of the proposed control scheme are verified through simulation results.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.10
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• pp.1066-1074
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• 1990

In this paper, we attempt to control induction motors with high power efficiency as well as high dynamic performance by utilizing the recently developed theories : singular perturbation technique and noninteracting feedback control. Our controller consists of three subcontrollers` a saturation current controller, a decoupling controller, and a well-known flux simulator. The decoupling controller decouples rotor speed (or motor torque) and rotor flux linearly. Our controller does not need the rotor resistance that varies widely with the machine temperature. To illuminate the practical significance of our results, we present simulation and experimental results as well as mathematical performance analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.411-418
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• 2006

There are mainly two types of bang-bang controllers for nominal linear time-invariant (LTI) system. Optimal bang-bang controller is designed based on optimal control theory and suboptimal bang-bang controller is obtained by using Lyapunov stability condition. In this paper, the suboptimal bang-bang control method is extended to LTI system involving both control input saturation and structured real parameter uncertainties by using Lyapunov robust stability condition. Two robust optimal bang-bang controllers are derived by minimizing the time derivative of Lyapunov function subjected to the limit of control input. The one is developed based on the classical quadratic stability(QS), and the other is developed based on the affine quadratic stability(AQS). And characteristics of the two controllers are compared. Especially, bounds of parameter uncertainties which theoretically guarantee robust stability of the two controllers are compared quantitatively for 1DOF vibrating system. Moreover, the validity of robust optimal bang-bang controller based on the AQS is shown through numerical simulations for this system.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.77-88
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• 2018

This paper proposes a RBFNN(Radial Basis Function Neural Network) based decentralized adaptive tracking control scheme using PSO(Particle Swarm Optimization) for an uncertain electrically driven robot system with input saturation. Practically, the magnitudes of input voltage and current signals are limited due to the saturation of actuators in robot systems. The proposed controller overcomes this input saturation and does not require any robot link and actuator model parameters. The fitness function used in the presented PSO scheme is expressed as a multi-objective function including the magnitudes of voltages and currents as well as the tracking errors. Using a PSO scheme, the control gains and the number of the RBFs are tuned automatically and thus the performance of the control system is improved. The stability of the total control system is guaranteed by the Lyapunov stability analysis. The validity and robustness of the proposed control scheme are verified through simulation results.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.3
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• pp.156-165
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• 1997

In the practical control systems, the dynamic range of actuatiors is limited(or saturated) when actuators are driven by sufficiently large signals. This gives rise to a nonlinearity as a result of actuator saturation. For example, the upper limit is imposed on productive capability by available factory space and capital equipment. Other examples of those kinds of actuator saturations are a maximum torque of the actua- ting motors and a throttle position in an aircraft speed control A saturating actuator may lead not only to a large overshoot during start-up and shut-down, but also to deterioration of the performance due to the uncertainties. That is, the speed of response is decreased and, possibly, the system output may not follow the lalrge reference inputs. The large-overshoot may be accompanied by rest wind-up(or called by integra- tor wind-up) which comes from controllers with integral action in saturation operation regions. Eventually, as the overshoot increases, the system has a limit cycle or becomes oscillatorily unstable. Due to these cir- cumstances, many studies are focused on the stability and robustness of the nonlinear systems with satu- rating actuator in the time-domain as well as in the frequency-domain.

• Journal of Power Electronics
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• v.9 no.3
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• pp.354-364
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• 2009

Rotor resistance variation due to changing rotor temperature is a significant issue in the design of induction motor controls. In this work, a new on-line rotor resistance estimator is proposed based on an alternate qd induction machine model which provides better mathematical representation of an induction machine than the classical qd model (which uses constant parameters). This is because the former simultaneously includes leakage saturation, magnetizing path saturation, and distributed circuit effects in the rotor conductors. The comparisons via computer simulation studies show the ability of the proposed estimator to accurately track rotor resistance variation. For the experimental studies, due to the difficulty in measuring the actual rotor resistance, comparison of the controller performance using the proposed estimator, the classical qd model based estimator, and no estimator is made.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.697-702
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• 2004

In this paper, we proposed that the problem of controlling induction motor with magnetic saturation, is studied from an input-output feedback linearization with adaptive algorithm. is considered. An adaptive input-output feedback linearizing controller is considered under the assumption of known motor parameters and unknown load torque. In order to achieve the speed regulation with the consideration of improving power efficiency, rotor angular speed and flux amplitude tracking objectives are formulated. Simulation results are provided for illustration.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.166-173
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• 1999

Reference models are used in many control algorithms for improvement of transient response characteristics. They provide desired trajectories that the plant should follow Most control systems have bounded control inputs to avoid saturation of the plant. If we design the reference models that do not account for limits of the control inputs, control performance of the system may be deteriorated. In this paper a new approach of avoiding saturation by varying the reference model for TDC(time delay control) based systems subject to step changes in the reference input. In this scheme, the variable reference model is determined based on the information on control inputs and the size of the step changes in the reference inputs. This scheme was verified by application to the BLDC motor position control system in simulations and experiments. The responses of the TDC with the variable reference model showed better tracking performance than that with the fixed reference model.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.325-328
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• 2002

In this paper, we proposed that the problem of controlling induction motor with magnetic saturation is studied from an input-output feedback linearization with adaptive algorithm. The $\pi$-model of induction motor is considered. An adaptive input-output feedback linearizing controller is considered under the assumption of known motor parameters and unknown load torque. Simulation results are provided for illustration.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.4
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• pp.34-40
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• 2013

Attitude command response type required for enhanced handling qualities of helicopter can be implemented by mechanical automatic flight control system with SAS actuators which have limited authorities. However, the early saturation of SAS actuator hinders the helicopter from following the attitude command for large stick command. Auto-trim controller can delay SAS actuator's saturation by utilizing trim actuators and allows the attitude command response type for larger stick command. This paper describes the control law for limited authority system of helicopter with auto-trim. Limited authority system is applied to BO-105 linear dynamic model and simulation is performed along with handling quality analysis.