• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2007년도 추계학술대회 논문집
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• pp.313-318
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• 2007

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive fuzzy neural network controller and artificial neural network(ANN). This control method is applicable over the entire speed range which considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using Adaptive-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper reposes speed control of IPMSM using Adaptive-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is a lied to IPMSM drive system controlled Adaptive-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the Adaptive-FNN and ANN controller.

• 유공압시스템학회논문집
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• 제4권1호
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• pp.13-17
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• 2007

The brake gain adaptive wheel slip controller for a vehicle is designed in this paper. The brake gain from braking pressure to braking torque defined by friction coefficient, friction area and effective friction radius is estimated by the adaptive law based on the wheel slip dynamics. And the wheel slip controller is designed based on the estimated brake gain. The robustness of the designed controller is analyzed using Lyapunov function and the convergence of brake gain is verified. Proposed wheel slip controller is verified via CarSim simulation with two kinds of desired wheel slip ratio.

• Journal of Advanced Marine Engineering and Technology
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• 제27권5호
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• pp.609-616
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• 2003

The purpose of this study is to design the adaptive speed control system of a marine diesel engine by combining the Model Matching Method and the Nominal Model Tracking Method. The authors proposed already a new method to determine efficiently the PID control Parameters by the Model Matching Method. typically taking a marine diesel engine as a non-oscillatory second-order system. But. actually it is very difficult to find out the exact model of a diesel engine. Therefore, when diesel engine model and actual diesel engine are unmatched as an another approach to promote the speed control characteristics of a marine diesel engine, this paper Proposes a Model Reference Adaptive Speed Control system of a diesel engine, in which PID control system for the model of a diesel engine is adopted as the nominal model and Fuzzy controller and derivative operator are adopted as the adaptive controller.

• 제어로봇시스템학회논문지
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• 제8권7호
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• pp.533-538
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• 2002

We propose a direct adaptive controller for a class of nonlinearly parametrized systems. A normalized output error is added to the previous control law to construct the proposed adaptive controller. The transient performance of the resulting closed-loop system can be guaranteed by suitably choosing a novel kind of Lyapunov function while the tracking performance of the adaptive control system is improved using the proposed algorithm. Finally, the effectiveness of the proposed algorithm is illustrated with computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1292-1295
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• 1996

This paper proposes an adaptive control technique for the autopilot design of STT missile. Dynamics of the missile is highly nonlinear and the equilibrium point is vulnerable to change due to fast maneuvering. Therefore nonlinear control techniques are desirable for the autopilot design of the missile. The nonlinear controller requires the exact model to obtain satisfactory performance. Generally a look-up table is used for the dynamic coefficients of a missile, so there must be coefficients error during actual flight, and the performance of the nonlinear controller using these data can be degraded. The proposed adaptive control technique compensates the nonlinear controller with modeling error resulting from the error of aerodynamic data and disturbance. To investigate the usefulness, the proposed method is applied to autopilot design of STT missile through simulations.

• 제어로봇시스템학회논문지
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• 제22권5호
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• pp.315-319
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• 2016

This paper proposes a simple adaptive sliding mode control algorithm for controlling a permanent magnet synchronous generator (PMSG) of a MW-class direct-driven wind turbine system. The proposed adaptive sliding mode controller does not require accurate knowledge of the PMSG parameter or turbine torque values. The proposed controller can accurately track the reference angular speed computed by the maximum power point tracking(MPPT) algorithm. Finally, this paper gives Matlab/Simulink simulation results to verify the practicality and effectiveness of the proposed adaptive sliding mode controller.

• Journal of Mechanical Science and Technology
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• 제15권12호
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• pp.1664-1675
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• 2001

In this paper, the development of a new group controller for high-speed elevators is described utilizing the approach of adaptive dual fuzzy logic. Some goals of the control are to minimize the waiting time, mean-waiting time and long-waiting time in a building. When a new hall call is generated, all adaptive dual fuzzy controller evaluates the traffic patterns and changes the membership function of a fuzzy rule base appropriately. A control algorithm is essential to control the cooperation of multiple elevators in a group and the most critical control function in the group controller is an effective and proper hall call assignment of the elevators. The group elevator system utilizing adaptive dual fuzzy control clearly performs more effectively than previous group controllers.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.51-55
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• 1995

An adaptive unified predictive control (UPC) algorithm is applied to a batch polymerization reactor for poly(methyl methancrylate) (PMMA) and the effects of controller parameters are investigated. Computational studies are performed for a batch polymerization system model developed in this study. A transfer function in parametric form is estimated by recursive least squares (RLS) method, and the UPC algorithm is implemented to control the reactor temperature on the basis of this transfer function. The adaptive unified predictive controller shows a better performance than the PID controller for tracking set point changes, especially in the latter part of reaction course when gel effect becomes significant. Various performance can be acquired by selecting adequate values for parameters of the adaptive unified predictive controller; in other words, the optimal set of parameters exists for a given set of reaction conditions and control objective.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 B
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• pp.1114-1116
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• 2000

A direct model reference adaptive control (DMRAC) is applied to the speed control of brushless do(BLDC) motor. The main objective is to achieve precise speed control in the face of varying motor parameters and load. The control is described as an outer loop speed control and an inner current loop control which has raster dynamics than the speed loop. The adaptive control is applied to the outer speed control loop. DMRAC is compared to an indirect adaptive controller(IMRAC) and a PI controller. Simulation results show that the two adaptive controllers give similar respose and are superior to the PI controller. However, the DMRAC algorithm is simpler to implement.

• 전기학회논문지
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• 제58권9호
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• pp.1821-1826
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• 2009

An adaptive neural controller for perturbed strict-feedback nonlinear system is proposed. All the previous adaptive neural (or fuzzy) controllers are based on the backstepping scheme where the universal approximators are employed in every design steps. These schemes involve virtual controls and their time derivatives that make the stability analysis and implementation of the controller very complex. This fact is called 'explosion of complexty ' since the complexity grows exponentially as the system dynamic order increases. The proposed adaptive neural control scheme adopt the backstepping design procedure only for determining ideal control law and employ only one neural network to approximate the finally selected ideal controller, which makes the controller design procedure and stability analysis considerably simple compared to the previously proposed controllers. It is shown that all the time-varing signals containing tracking error are stable in the Lyapunov viewpoint.