• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.6
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• pp.612-619
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• 2004

Servo motor systems with ball-screw and timing-belt are widely used in NC, robot, FA and industrial applications. However, the nonlinear friction torque and damping effect in machine elements reduce the control performance. Especially tracking errors in trajectory control and very low velocity control range are serious due to the break-away friction and Stribeck effects. In this paper, a new double speed controller is proposed for compensation of the nonlinear friction torque. The proposed double speed controller has outer speed controller and inner friction torque compensator. The proposed friction torque compensator compensates the nonlinear friction torque with actual speed and speed error information. Due to the actual information for friction torque compensator without parameters and mathematical model of motor, proposed compensator is very simple structure and the stability is very high. The proposed compensator is verified by simulation and experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.494-499
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• 2013

Based on the state-feedback adaptive neuro-control algorithm for a SISO nonaffine pure-feedback nonlinear system proposed in [15], an output-feedback controller is proposed in this paper. The output-feedback adaptive neural-net controller for the considered nonlinear system has not been previously proposed in any other literatures yet. The proposed output-feedback controller inherits all the advantages of [15] such that it does not adopt backstepping and this results in relatively simple control and adapting laws. Only one neural network is required for the proposed adaptive controller. The proposed neural-net control scheme expands the applicable class of nonlinear systems.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.203-208
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• 1998

This paper presents an adaptive fuzzy controller using an neural network and adaptation algorithm. Reference-model following neuro-fuzzy controller(RMFNFC) is invesgated in order to overcome the difficulty of rule selecting and defects of the membership function in the general fuzzy logic controller(FLC). RMFNFC is developed to tune various parameter of the fuzzy controller which is used for the discrete nonlinear system control. RMFNFC is trained with the identification information and control closed loop error. A closed loop error is used for design criteria of a fuzzy controller which characterizes and quantize the control performance required in the overall control system. A control system is trained up the controller with the variation of the system obtained from the identifier and closed loop error. Numerical examples are presented to control of the discrete nonlinear system. Simulation results show the effectiveness of the proposed controller.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.125-126
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• 2008

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.881-889
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• 2013

In this paper, a nonlinear and adaptive back-stepping control technique is proposed for a speed control of IPMSM(Interior Permanent Magnet Synchronous Motor). The gain of back-stepping controller(including integral value of the states error) is designed for stability of the system. In order to adapting fast in variation of load torque, the controller is including load torque estimator. The simulation is completed by using PSIM software. The simulation results show that the designed back-stepping controller make the system stable in the constant torque region, and has better tracking performance than a controller without the integral gain.

• Journal of IKEEE
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• v.14 no.3
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• pp.182-189
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• 2010

A new Adaptive neural state-feedback controller for the fully nonaffine pure-feedback nonlinear system are presented in this paper. By reformulating the original pure-feedback system to a standard normal form with respect to newly defined state variables, the proposed controller requires no backstepping design procedure. Avoiding backstepping makes the controller structure and stability analysis considerably simple. The proposed controller employs only one neural network to approximate unknown ideal controllers, which highlights the simplicity of the proposed neural controller. Simulation examples demonstrate the efficiency and performance of the proposed approach.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.662-669
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• 2016

In this work, nonlinear control of a three-phase shunt active power filter (SAPF) has been studied and compared to classical control based on proportional integral regulator. The control strategy is based on the direct current method using sliding mode control (SMC), where the aim is to regulate the average voltage across the dc bus of the inverter. Details are given for the control algorithm; the controller is comprised of a current loop which utilizes a hysteresis controller to generate the gating signals for the switching devices, and a nonlinear controller based on SMC law which is different from classical laws based on error between reference and measured output voltage of the inverter. Sliding surface applied in this work contains the whole of state variables, in order to ensure full control of the system behavior in the presence of disturbances that affect the supply source, the load parameters or the reference value. The designed controller offers advantage that it can gives the improvement of dynamic and static performances in cases of large disturbances. A comparison of the effects of PI control and SMC on the APF response in steady stat, under line variations, load variations, and different component variations is performed.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.1
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• pp.18-25
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• 2013

In this paper, a nonlinear controller based on adaptive back-stepping method is proposed for high performance operation of Interior Permanent Magnet Synchronous Motor (IPMSM). First, in order to improve the performance of speed tracking, a nonlinear back-stepping controller is designed. In addition, since it is difficult to achieve the high quality control performance without considering parameter variation, a parameter estimator is included to adapt to the variation of load torque in real time. Finally, for the efficiency of power consumption of the motor, controller is designed to operate motor with the minimum current for the required maximum torque. The proposed controller is tested through experiment with a 1-hp Interior Permanent Magnet Synchronous Motor (IPMSM) for the angular velocity reference tracking performance and load torque volatility estimation, and to test the Maximum Torque per Ampere (MTPA) operation. The result verifies the efficacy of the proposed controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.605-614
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• 1999

This paper addresses analysis and design of a class of complex single-input single-output fuzzy control systems. In the proposed method, the fuzzy model, which represents the local dynamic behavior of the given nonlinear system, is utilized to construct the controller. The overall controller consists of the local compensators which compensate the local dynamic linear model and the feed-forward controller which is designed via sliding mode control theory. Therefore, the globally stable fuzzy controller is designed without finding a common Lyapunov matrix. and shows improved perfonnance and tracking results by taking the advantages of fuzzy-model-based control theory and sliding mode control theory. Furthennore, stability analysis is conducted not Ibr the fuzzy model but for the real underlying nonlinear system. Two numerical examples are included to show the effcctiveness and feasibility of the proposed fuzzy control method.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.423-429
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• 2011

This paper deals with the observer-based decentralized fuzzy controller design for nonlinear interconnected system for PEMFC. The nonlinear interconnected system is represented by a Takagi-Sugeno (T-S) fuzzy model. Based on T-S fuzzy interconnected system, the fuzzy observer and the decentralized fuzzy controller are designed. The stability condition of the closed-loop system with the proposed controller is represented to the linear matrix inequality (LMI) form, and the observer and control gain s are obtained by LMI. An example is given to show the verification discussed throughout the paper.