• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.53 no.12
• /
• pp.691-699
• /
• 2004

SRM(Switched Reluctance Motor) drives require the accurate position information of the rotor. These informations are generally provided by a tacho generator or digital shaft-position encoder These speed sensors lower the system reliability and require special attention to noise. This paper describes a new approach to estimating SRM speed from measured terminal voltages and currents for speed sensorless control. The described method is based on the sliding mode observer. The rotor speed and position observers are estimated by the adaptation law using the real and estimated currents. However, the conventional adaptive sliding mode observer based on the variable structure control theory has some disadvantages that the estimated values including the high-frequency chattering and the steady state error generated due to the infinite feedback gain chosen and the discontinuous control input. To reduce the chattering and steady state error, an integrator is also inserted in the sliding mode observer strategy. The described adaptive sliding mode observer decreases the vibration to the switching hyper-plane of the sliding mode by adding integrator. The described methodology incorporates the Lyapunov algorithm to drive the rotor speed and the stator resistance such that it can overcome the problem of sensitivity in the face of SRM parameter variation. Also, without any mechanical information. The rotor speed of SRM is obtained form adaptive scheme. The described method is verified through the simulation and experiment.

• Proceedings of the KIEE Conference
• /
• 2003.11b
• /
• pp.255-258
• /
• 2003

It is hard to centrol the wheeled mobile robot because of uncertainty of modeling, non-holonomic constraint and so on. To solve the problems, we design the controller of wheeled mobile robot based on fuzzy-neural network algorithm. In this paper, we should research the problem of classical controller for path-tracking algorithm and design of Fuzzy-Neural Network algorithm controller. Classical controller acquired different control value according to change of initial position and direction. In this control value having very difficult and having acquired a lot of trial and error Fuzzy is implemented to adaptive adjust control value by error and change of error and neural network is implemented to adaptive adjust the control gain during the optimization. The computer simulation shows that the proposed fuzzy-neural network controller is effective.

• Proceedings of the KIEE Conference
• /
• 2000.07b
• /
• pp.1046-1049
• /
• 2000

A direct torque control(DTC) based sensorless speed control system which employs a new closed loop flux observer is proposed. The flux observer is an adaptive gain scheduling observer where motor speed is used as the scheduling variable. Adaptive nature comes from the fact that the estimates of stator resistance and speed are included as observer parameters. Simulation results show that the proposed flux observer gives better control and estimation results than conventional flux estimator specially in low speed region.

• Journal of Advanced Marine Engineering and Technology
• /
• v.32 no.4
• /
• pp.618-623
• /
• 2008

This paper presents a design method of the Interpolation-based adaptive LQ controller that is accomplished by getting the final controller interpolated with each gain of sub-LQ controllers. The Lagrange interpolation method is used in the scheme. The proposed controller is useful to control nonlinear systems which are especially changed the system parameters. The design method is illustrated by an application to the stabilization and tracking problems of an inverted pole system on a cart. Several cases of simulations are carried out in order to validate the control effectiveness and robustness. The simulation results are compared with those of LQ controller and prove the better control performance than LQ controller.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.33 no.3
• /
• pp.39-46
• /
• 2005

In this paper, adaptive higher harmonic control technique using Neural Networks (NN) is proposed. First, linear transfer function is estimated to relate the input harmonics and output harmonics, then NN which has the universal function approximation property is applied to expand application range of the transfer function. Optimal control gain matrix computed from the transfer function is used to train NN weights. Online weight adaptation laws are derived from Lyapunov's direct method to guarantee internal stability. Results of the simulation of 6-input 2-output nonlinear system show that adaptive HHC is applicable to the system with uncertain transfer function.

• Journal of KSNVE
• /
• v.8 no.3
• /
• pp.441-449
• /
• 1998

A self-tuning control scheme, incorporated with the simplified 1st-order ARMAX(Auto-Regressive Moving Average eXogenous) model, for single rod hydraulic cylinder which has varying dynamic characteristics is presented here. An adaptive controller is developed for the system that uses feedforward and optimal feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the self-tuning controller with a fixed gain proportional controller clearly shows its superior ability in handling load changes in quiescent states.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.726-728
• /
• 2004

In this paper, the gain of the observer is properly set up using the fuzzy control and Fuzzy-Sliding observer(FSQ) that have a superior transient characteristic and is easy to implement compared to the existing method is designed. It estimate the differentiation of the armature current directly using the armature current measured in the AC motor. It estimate the speed of the rotor using the differentiation. It is proposed speed sensorless control method using the estimated speed. Optimal gain of speed observer(Luenberger observer) was set up using the fuzzy control and adapted speed control of AC servo motor. To verify the performance of designed Fuzzy-Sliding observer, simulation compared with fixed speed observer gain of G.B Wang and S.S Peng's sliding observer is performed. Also, it was proved the excellence and feasibility of the proposed observer from the comparison test with a speed sensor and without a speed sensor which used a highly efficient drive and 400W AC servo motor starting system.

• Proceedings of the KIEE Conference
• /
• 1999.11c
• /
• pp.530-532
• /
• 1999

In adaptive fuzzy control, system designer develops an adaptive law for the output of the unknown plant to track a given signal. The adaptation gains of the adaptive law are critical elements in the overall system, however, they were used to be selected by the designer's experience or intuition. In this paper, genetic algorithm is used to search an optimal adaptation gain and simulation results will be presented to show the improved tracking responses.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.60 no.2
• /
• pp.63-67
• /
• 2011

This paper presents the mobile robot control based on vision system. The proposed vision based controller consist of the camera tracking controller and the formation controller. Th e camera controller has the adaptive gain based on IBVS. The formation controller which is designed in the sense of the Lyapunov stability follows the leader. Simluation results show that the proposed vision based mobile robot control is validated for indoor mobile robot applications.

• Proceedings of the KIEE Conference
• /
• 1981.07a
• /
• pp.146-153
• /
• 1981

A practical and robust control scheme is suggested for MIMO discrete time processes with real simple poles. This type of control scheme, having the advantages of both the adaptiveness and optimality, may be successfully applicable to structured dynamic controllers for plants whose parameters are slowly time-varying. The identification of the process parameters is under-taken in ARMA form and the optimization of the feedback gain matrix is performed in the state space representation with regard to a standard quadratic criterion.