• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.4
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• pp.78-83
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• 1984

A method is proposed for the adaptive control of linear time varying discrete systems. The stability problem of the model reference adaptive control systems is considered by means of the properties of hypergtability, The hyperstability approach also allows for solutions to the adaptation mechanism. Employing the principles of the continuous time case with output feedback renders it to the discrete case which simplified the system design. The system response is obtained by applying the ramp and step input as a reference signal to the system respectively. With checking the adaptation time for ramp and step input the validity of proposed algorithm was confirmed by the computer simulation.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.327-329
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• 2006

A controller is proposed for the robust adaptive backstepping control of a class of uncertain nonlinear systems using nonlinear disturbance observer (NDO). The NDO is applied to estimate the time-varying lumped disturbance in each step, but a disturbance observer error does not converge to zero since the derivative of lumped disturbance is not zero. Then the fuzzy neural network (FNN) is presented to estimate the disturbance observer error such that the outputs of the system are proved to converge to a small neighborhood of the desired trajectory. The proposed control scheme guarantees that all the signals in the closed-loop are semiglobally uniformly ultimately bounded on the basis of the Lyapunov theorem. Simulation results are presented to illustrate the effectiveness and the applicability of the approaches proposed.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1037-1041
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• 1996

Input-output linearization technique in nonlinear control does not guarantee the robustness in the presence of parameter uncertainty or unmodeled dynamics, etc. However, it has been used as an important preliminary step in achieving additional control objectives, for instance, robustness to parameter uncertainty and disturbance attenuation. An indirect adaptive control scheme based on input-output linearization is proposed in this paper. The scheme consists of a Hopfield network for process parameter identification and an adaptive sliding mode controller based on input-output linearization, which steers the system response into a desired configuration. A numerical example is presented for the trajectory tracking of uncertain nonlinear dynamic systems with slowly time-varying parameters.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.6
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• pp.889-897
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• 1986

The purpose of this study is to describe the strategy of machining process suitable for developing adaptive control with constraint of NC-machine tool. The algorithm that controls machining process parameters of every sampling time is established for the constraint of torque in machinig center. To prove this AC algorithm, manual AC-unit control test is used for simulating the on-line AC strategy control. Also machining tests are carried out on a CNC-machining center fitted with the ACC system and compared with the simulated results. The practical effectiveness of the ACC systems so discussed and the reduction of machining time are demonstrated with reference to typical models of cutting workpieces. As a typical model, taper and step geometry model are selected. The computer simulation results have a good agreement with the experimental observation and make it possible to develope a NC-machine tool with an on-line ACC system.

• Journal of Power Electronics
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• v.16 no.6
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• pp.2212-2220
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• 2016

Based on the conventional PID algorithm and the adaptive PID (AD-PID) algorithm, a separate sampling adaptive PID (SSA-PID) algorithm is proposed to improve the transient response of digitally controlled DC-DC converters. The SSA-PID algorithm, which can be divided into an oversampled adaptive P (AD-P) control and an adaptive ID (AD-ID) control, adopts a higher sampling frequency for AD-P control and a conventional sampling frequency for AD-ID control. In addition, it can also adaptively adjust the PID parameters (i.e. $K_p$, $K_i$ and $K_d$) based on the system state. Simulation results show that the proposed algorithm has better line transient and load transient responses than the conventional PID and AD-PID algorithms. Compared with the conventional PID and AD-PID algorithms, the experimental results based on a FPGA indicate that the recovery time of the SSA-PID algorithm is reduced by 80% and 67% separately, and that overshoot is decreased by 33% and 12% for a 700mA load step. Moreover, the SSA-PID algorithm can achieve zero overshoot during startup.

• Smart Structures and Systems
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• v.25 no.5
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• pp.559-567
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• 2020

Vibration at the tip of various flexible manipulators may affect their operation accuracy and work efficiency. To suppress such vibrations, the feasibility of using MFC actuators and sensors is investigated in this paper. Considering the convergence of the famous filtered-x least mean square (FXLMS) algorithm could not be guaranteed while it is employed for vibration suppression of plants with varying secondary path, this paper proposes a new multiple model switching adaptive control algorithm to implement the real time active vibration suppression tests with a new multiple switching strategy. The new switching strategy is based on a cost function with reconstructed error signal and disturbance signal instead of the error signal from the error sensor. And from a robustness perspective, a new variable step-size sign algorithm (VSSA) based FXLMS algorithm is proposed to improve the convergence rate. A cantilever beam with varying tip mass is employed as flexible manipulator model. MFC layers are attached on both sides of it as sensors and actuators. A co-simulation platform was built using ADAMS and MATLAB to test the feasibility of the proposed algorithms. And an experimental platform was constructed to verify the effectiveness of MFC actuators and sensors and the real-time vibration control performance. Simulation and experiment results show that the proposed FXLMS algorithm based multiple model adaptive control approach has good convergence performance under varying load conditions for the flexible cantilever beam, and the proposed FX-VSSA-LMS algorithm based multiple model adaptive control algorithm has the best vibration suppression performance.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.831-836
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• 1990

Real-time implementations of active noise controller are proposed and tested. For compensation of time delay of feed-back path, the n-step ahead prediction is applied. And predicting source noise and reflection noise respectively, reflection noise can be cancelled. For real-time processing, the DSP56001(Digital Signal Processor) is used. Experimental results show that the proposed controller is stable and of good performance.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.4
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• pp.428-434
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• 2012

Missiles suffer from flight instability problems at high angles of attack, since vortex flow over a fuselage cause lateral force to the body. To overcome this problem at a high angle of attack, the development of a real time vortex controller is needed. In this paper, Proper Orthogonal Decomposition (POD) and feedback controllers are developed for real time vortex control. The POD method is one of the most well known techniques for modeling low order models that represent the original full-order model. An adaptive control algorithm is used for real time control.

• Journal of Advanced Navigation Technology
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• v.12 no.1
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• pp.22-27
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• 2008

This paper presents adaptive-MMOSPRED method for prediction of resource demands requested by multimedia calls, and shows the performance of the call admission control based on proposed resource prediction method in multimedia wireless networks. The proposed method determines (I-CDP) random variables of the standard normal distribution by using LMS algorithm that minimize errors of prediction in resource demands, while parameters in an existing method are constant all through the prediction time. Our simulation results show that prediction error in adaptive-MMOSPRED method is much smaller than in fixed-MMOSPRED method. Also we can see via simulation the CAC performance based on the proposed method improves the new call blocking performance compared with the existing method under the desired handoff dropping probability.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.211-217
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the teaming control field was teaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.