• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.586-588
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• 2011

Adaptive feedforward control(AFC) is largely aimed for improving control performance of dynamic systems particularly involving periodic disturbance signals in engineering fields. This paper presents a novel hybrid AFC approach for specific systems with multiple disturbances in control input and state variables. The proposed AFC mechanism is hierarchically composed of the conventional AFC and a PID typed auxiliary control law in parallel. The former is generic to decrease periodic disturbance in control actuators and the latter is additionally constructed to overcome control deterioration due to time-varying uncertainty of given systems. We carry out numerical simulation to test reliability of the hybrid AFC system and compare its control performance with a well-known conventional AFC method in terms of time and frequency domains for proving of its superiority.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.219-223
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• 1995

This paper deals with the robust control system for parameter variations, fast responses and load torque variations. Frist, fuzzy-sliding adaptive control be used to. Fuzzy-sliding adaptive control is good at fast response. Second, there are many requests for selecting freely the moment of inertia, even though moment of inertia is determined with the materials, structure, shape, and size of the motors. Therefore we developed an inertia-lowering control system that uses torque observer to reduce the moment of inertia. Finally, using torque observer, torque control is done so as to compensate load torque. Consequently, the proposed system verified the superiority through the simulations using MATLAB.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.60-63
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• 1997

A new approach to the position sensor elimination of PM synchronous motor drives is presented in this study. Using the position sensing characteristics of PMSM itself, the actual rotor position as well as the machine speed can be estimated by adaptive flux observer and used as the feedback signal for the vector controlled PMSM drive. The adaptive speed estimation is achieved by model reference adaptive technique. The adaptive laws are derived by the Popov's hyperstability theory and the positivity concept. In order to verify the effectiveness of the proposed scheme, computer simulations are carried out for the actual parameters of a PM synchronous motor and the results well demonstrate that the proposed scheme provides a good estimation value of the rotor speed without mechanical sensor. It is also shown that the actual rotor position as well as the machine speed can be achieved under the variation of the magnet flux linkage. Since the flux linkages are estimated by the adaptive flux observer and used for the identification of the rotor speed, robust estimation of the rotor speed can be performed.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.591-595
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• 1989

The application of Variable Structure System (VSS) to the position control of a Permanent Magnet Synchronus Motor is discussed. VSS is expected to be a powerful and potential tool to construct new control strategy for ac machines, since the resulting system shows robust performance to parametic variations and disturbances. An adaptive VSS which can make corrections or adjustments in the parameters of the control device of the VSS in accordance with the current values of the plant parameters and the constraints on the control is preposed. Various simulation results are reported to show the validity of the proposed control method.

• Structural Engineering and Mechanics
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• v.88 no.6
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• pp.535-549
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• 2023

Deep extreme learning machine (DELM) and multi-verse optimization algorithms (MVO) are hybridized for designing an optimal and adaptive control framework for uncertain buildings. In this approach, first, a robust model predictive control (RMPC) scheme is developed to handle the problem uncertainty. The optimality and adaptivity of the proposed controller are provided by the optimal determination of the tunning weights of the linear programming (LP) cost function for clustered external loads using the MVO. The final control policy is achieved by collecting the clustered data and training them by DELM. The efficiency of the introduced control scheme is demonstrated by the numerical simulation of a ten-story benchmark building subjected to earthquake excitations. The results represent the capability of the proposed framework compared to robust MPC (RMPC), conventional MPC (CMPC), and conventional DELM algorithms in structural motion control.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.3 s.246
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• pp.295-301
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• 2006

The wheel slip control systems are able to control the braking force more accurately and can be adapted to different vehicles more easily than conventional ABS systems. In order to achieve the superior braking performance through the wheel-slip control, real-time information such as the tire braking force at each wheel is required. In addition, the optimal target slip values need to be determined depending on the braking objectives such as minimum braking distance, stability enhancement, etc. In this paper, a robust wheel slip controller is developed based on the adaptive sliding mode control method and an optimal target slip assignment algorithm. An adaptive law is formulated to estimate the longitudinal braking force in real-time. The wheel slip controller is designed using the Lyapunov stability theory and considering the error bounds in estimating the braking force and the brake disk-pad friction coefficient. The target slip assignment algorithm is developed for the maximum braking force and searches the optimal target slip value based on the estimated braking force. The performance of the proposed wheel-slip control system is verified In simulations and demonstrates the effectiveness of the wheel slip control in various road conditions.

• International Journal of Automotive Technology
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• v.8 no.2
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• pp.211-217
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• 2007

The wheel slip control systems are able to control the braking force more accurately and can be adapted to different vehicles more easily than conventional ABS (Anti-lock Brake System) systems. In realizing the wheel slip control systems, real-time information such as the tire braking force at each wheel is required. In addition, the optimal target slip values need to be determined depending on the braking objectives such as minimum braking distance and stability enhancement. In this paper, a robust wheel slip controller is developed based on the adaptive sliding mode control method and an optimal target slip assignment algorithm is proposed for maximizing the braking force. An adaptive law is formulated to estimate the braking force in real-time. The wheel slip controller is designed based on the Lyapunov stability theory considering the error bounds in estimating the braking force and the brake disk-pad friction coefficient. The target slip assignment algorithm searches for the optimal target slip value based on the estimated braking force. The performance of the proposed wheel slip control system is verified in HILS (Hardware-In-the-Loop Simulator) experiments and demonstrates the effectiveness of the wheel slip control in various road conditions.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.908-925
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• 2014

Induction Motor (IM) has several desirable features for high performance adjustablespeed operation. This paper presents the design of a robust controller for vector control induction motor drive performances improvement. Proposed predictive speed controller, which is aimed to guarantee the stability of the closed loop, is based on the Poisson-Laguerre (PL) models for the association vector control drive and the induction motor; without necessity of any mechanical parameter, and requires only two control parameters to ensure implicitly the integrator effect on the steady state error, load torque disturbances rejection and anti-windup effect. In order to improve robustness, insensitivity against external disturbances and preserve desired performance, adaptive control is added with the aim to ensure an online identification of controller parameters through an online PL models identification. The proposed control is compared with the conventional approach using PI controller. Simulation with MATLAB/SIMULINK software and experimental results for a 1kW induction motor using a dSPACE system with DS1104 controller board are carried out to show the improvement performance.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.3
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• pp.171-177
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• 2016

Noise problem that occurs in living environment is a big trouble in the economic, social and environmental aspects. In this paper, the filtered-X LMS algorithms, the adjoint LMS algorithms, and the robust adjoint LMS algorithms will be introduced for applications in active noise control(ANC). The filtered-X LMS algorithms is currently the most popular method for adapting a filter when the filter exits a transfer function in the error path. The adjoint LMS algorithms, that prefilter the error signals instead of divided reference signals in frequency band, is also used for adaptive filter algorithms to reduce the computational burden of multi-channel ANC systems such as the 3D space. To improve performance of the adjoint LMS ANC system, an off-line measured transfer function is connected parallel to the LMS filter. This parallel-fixed filter acts as a noise controller only when the LMS filter is abnormal condition. The superior performance of the proposed system was compared through simulation with the adjoint LMS ANC system when the adaptive filter is in normal and abnormal condition.