• Transactions of The Korea Fluid Power Systems Society
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• v.8 no.2
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• pp.23-28
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• 2011

This paper investigates the motion control of a hydraulic motor-load system using the Simple Adaptive Control (SAC) method. The plant transfer function has been modelled mathematically. The open-loop responses have been obtained experimentally in order to identify the design parameters of transfer function. The hydraulic motor-load system has been modelled using the 3D CAD and imbedded in the hydraulic circuit simulation program to verify the overall performance. The experimental results confirm that the SAC method gives a good tracking performance compared to the PID control.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.12
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• pp.894-902
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• 1988

In this paper, a method for the design of robust adaptive controller using the heuristic rules of industrial engineers is presented. This scheme works on the basis of heuristic rules and includes a supervisor, a system identifier and a detuner. The supervisor detects onsetting instability based on the analysis of the amplitude and the trend of error signal, also selects running controllers. Upon detecting instability, the controller is switched to a PID algorithm and run recursively until stability is restored. Simultaneously, new input / output data is gathered and the system identifier runs to get critical sensitivity (kc) and critical period(tc). Based on the new values(kc, tc), a GPC controller is redesigned and normal GPC is finally run. The algorithm described in this paper belongs to the supervised adaptive control category with a limited use of heuristic rules. Finally, we show the robust of this scheme by simulated example.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.236-236
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• 2000

Control of Industrial processes is very difficult due to nonlinear dynamics, effect of disturbances and modeling errors. M.Morari proposed Internal Model Control(IMC) system that can be effectively applied to the systems with model uncertainties and time delays. The advantage of IMC systems is their robustness with respect to a model mismatch and disturbances. But it was difficult to apply for nonlinear systems. Adaptive Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to identify a nonlinear dynamical systems. In this paper, we propose new IMC design method using adaptive neuro-fuzzy inference system for nonlinear plant. Numerical simulation results show that proposed IMC design method has good performance than classical PID controller.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.526-533
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• 2008

We propose a wavelet neural network (WNN) control method for active queue management (AQM) in an end-to-end TCP network, which is trained by adaptive learning rates (ALRs). In the TCP network, AQM is important to regulate the queue length by passing or dropping the packets at the intermediate routers. RED, PI, and PID algorithms have been used for AQM. But these algorithms show weaknesses in the detection and control of congestion under dynamically changing network situations. In our method, the WNN controller using ALRs is designed to overcome these problems. It adaptively controls the dropping probability of the packets and is trained by gradient-descent algorithm. We apply Lyapunov theorem to verify the stability of the WNN controller using ALRs. Simulations are carried out to demonstrate the effectiveness of the proposed method.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.6
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• pp.633-641
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• 2015

Several complex processes that are employed in industries, such as shipping, power plants, and the petrochemical industry, involve time-varying behavior as well as strong nonlinear behavior during operation. The fixed-parameter proportional-integral-derivative (PID) controllers have difficulty in dealing with control problems that occur in such processes. In this paper, we propose a method of designing a nonlinear PID controller for industrial processes that exhibit a large number of nonlinearities and time-varying behavior. The gains of the nonlinear PID controller are characterized by a simple nonlinear function of the error and/or error rate depending on the process set-point and output. We tune the user-defined parameters using a genetic algorithm by minimizing the integral of time absolute error (ITAE) index. We verify the effectiveness of the proposed method by performing a comparison of the proposed method and two other nonlinear and adaptive methods that are employed for reference tracking, disturbance-rejection performances, and robustness to parameter changes on a continuously stirred tank reactor.

• International Journal of Aeronautical and Space Sciences
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• v.6 no.2
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• pp.1-16
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• 2005

Adaptive control methods are studied for the Satellite to isolate vibration in spite of the nonlinear system dynamics and parameter uncertainties of disturbance. First, a centralized control scheme is developed based on the particle swarm optimization(PSO) algorithm and feedback theory to automatically tune controller gains. A simulation study of a 3 degree-of-freedom device was conducted to evaluate the performance of the proposed control scheme. Next, since a centralized control scheme is hard to construct model dynamics and not goad at performance when controller and systems environment are easily changed, a decentralized control scheme is presented to avoid these defects of the centralized control scheme from the point of view of production and maintenance. It is based on the adaptive control methodologies to find PID controller parameters. Experiment studies were conducted to apply the adaptive control scheme and evaluate the performance of the proposed control scheme with those of the conventional control schemes.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2522-2534
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• 2020

It is well known that the model of nuclear reactors features natural nonlinearity, and variable parameters during power tracking operation. In this paper, a disturbance observer-based adaptive sliding mode control (DOB-ASMC) strategy is proposed for power tracking of the pressurized-water reactor (PWR) in the presence of lumped disturbances. The nuclear reactor model is firstly established based on point-reactor kinetics equations with six delayed neutron groups. Then, a new sliding mode disturbance observer is designed to estimate the lumped disturbance, and its stability is discussed. On the basis of the developed DOB, an adaptive sliding mode control scheme is proposed, which is a combination of backstepping technique and integral sliding mode control approach. In addition, an adaptive law is introduced to enhance the robustness of a PWR with disturbances. The asymptotic stability of the overall control system is verified by Lyapunov stability theory. Simulation results are provided to demonstrate that the proposed DOB-ASMC strategy has better power tracking performance than conventional sliding mode controller and PID control method as well as conventional backstepping controller.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1644-1651
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• 2022

This paper focuses on the power-level control of nuclear power plants (NPPs) in the presence of lumped disturbances. An adaptive second-order nonsingular terminal sliding mode control (ASONTSMC) scheme is proposed by resorting to the second-order nonsingular terminal sliding mode. The pre-existing mathematical model of the nuclear reactor system is firstly described based on point-reactor kinetics equations with six delayed neutron groups. Then, a second-order sliding mode control approach is proposed by integrating a proportional-derivative sliding mode (PDSM) manifold with a nonsingular terminal sliding mode (NTSM) manifold. An adaptive mechanism is designed to estimate the unknown upper bound of a lumped uncertain term that is composed of lumped disturbances and system states real-timely. The estimated values are then added to the controller, resulting in the control system capable of compensating the adverse effects of the lumped disturbances efficiently. Since the sign function is contained in the first time derivative of the real control law, the continuous input signal is obtained after integration so that the chattering effects of the conventional sliding mode control are suppressed. The robust stability of the overall control system is demonstrated through Lyapunov stability theory. Finally, the proposed control scheme is validated through simulations and comparisons with a proportional-integral-derivative (PID) controller, a super twisting sliding mode controller (STSMC), and a disturbance observer-based adaptive sliding mode controller (DO-ASMC).

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.822-828
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• 2018

AC-DC conversion is a necessary for the systems that require DC source. This conversion has been done via rectifiers based on controlled or uncontrolled semiconductor switches. Advances in the power electronics and microprocessor technologies allowed the use of Pulse Width Modulation (PWM) rectifiers. In this paper, dq-axis current and DC link voltage of three-phase PWM rectifier are controlled by using type-2 fuzzy neural network (T2FNN) controller. For this aim, a simulation model is built by MATLAB/Simulink software. The model is tested under three different operating conditions. The parameters of T2FNN is updated online by using back-propagation algorithm. The results obtained from both T2FNN and Proportional + Integral + Derivate (PID) controller are given for three operating conditions. The results show that three-phase PWM rectifier using T2FNN provides a superior performance under all operating conditions when compared with PID controller.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.925-931
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• 2016

The BLDC motor is used widely in industry due to its controllability and freedom from maintenance because there is no mechanical brush in the BLDC motor. Furthermore, it is suitable for high-speed applications, such as compressors and air blowers. For instance, for a compressor with a small impeller due to miniaturizing, the BLDC motor has to rotate at a very high speed to maintain the compression ratio of the compressor. Typically, to reach an ultra-high speed, airfoil bearings must be used in place of ball bearings because of their friction. Unfortunately, the characteristics of airfoil bearings change drastically depending on the revolution speed. In this paper, a BLDC motor with airfoil bearings is controlled with a PID controller. To analyze and determine the PID coefficients, the relay-feedback method is used. Additionally, for adaptive control, a fuzzy logic controller is used. Furthermore, the auto-tuning and self-tuning techniques are combined to control the BLDC motor. The proposed method is able to control the airfoil-bearing BLDC motor efficiently.