• Journal of Power Electronics
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• v.16 no.2
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• pp.564-571
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• 2016

This study proposes an adaptive neuro-fuzzy inference system (ANFIS)-based rotor position controller for brushless direct current (BLDC) motors to improve the control performance of the drive under transient and steady-state conditions. The dynamic response of a BLDC motor to the proposed ANFIS controller is considered as standard reference input. The effectiveness of the proposed controller is compared with that of the proportional integral derivative (PID) controller and fuzzy PID controller. The proposed controller solves the problem of nonlinearities and uncertainties caused by the reference input changes of BLDC motors and guarantees a fast and accurate dynamic response with an outstanding steady-state performance. Furthermore, the ANFIS controller provides low torque ripples and high starting torque. The detailed study includes a MATLAB-based simulation and an experimental prototype to illustrate the feasibility of the proposed topology.

• Smart Structures and Systems
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• v.20 no.1
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• pp.85-97
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• 2017

The aim of this research is to develop a new method to use magnetorheological (MR) damper for vibration control. It is a new way to achieve the MR damper response without the need to have detailed constant parameters estimations. The methodology adopted in designing the control structure in this work is based on the experimental results. In order to investigate and understand the behaviour of an MR damper, an experiment is first conducted. Force-displacement and force-velocity responses with varying current have been established to model the MR damper. The force for upward and downward motions of the damper piston is found to be increasing with current and velocity. In cyclic motion, which is the combination of upward and downward motions of the piston, the force with hysteresis behaviour is seen to be increasing with current. In addition, the energy dissipated is also found to be linear with current. A proportional-integral-derivative (PID) controller, based on the established characteristics for a quarter car suspension model, has been adapted in this study. A fuzzy rule based PID controller (F-PID) is opted to achieve better response for a varying frequency input. The outcome of this study can be used in the modelling of MR damper and applied to control engineering. Moreover, the identified behaviour can help in further development of the MR damper technology.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.85.6-85
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• 2001

This paper describes a 3-DOF attitude control of a small model helicopter in hover through explicit decoupling and adaptive control scheme. A model helicopter mounted on gimbal-stand is considered as a system that has 3 independent SISO systems representing motions about roll, pitch and yaw axis and these subsystems are identified from the test flight data. In this consideration, the contribution of others to yaw channel is neglected since it is relatively small. Two PID controllers based on Ziegler-Nichols method are designed for roll pitch channels independently. Also, adaptive fuzzy tuner is designed and applied to those PID controllers to cope with coupling effects between each channel and system uncertainties due to variation of engine RPM. The experimental results show that the attitude control ...

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.691-695
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• 1998

Most of systems has nonlinearity . And also accurate modelings of these uncertain nonlinear systems are very difficult. In this paper, a fuzzy modeling technique for the stabilization control of an IP(inverted pendulum) system with nonlinearity was proposed. The fuzzy modeling was acquired on the basis of ANFIS(Adaptive Neuro Fuzzy Infernce System) which could learn using a series of input-output data pairs. Simulation results showed its superiority to the PID controller. We believe that its applicability can be extended to the other nonlinear systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.246-254
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• 2002

In this paper auto-tuning scheme of PID controller based on the reference model has been studied for a Process control system by immune algorithm. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. Also, a number of approaches have been proposed to implement mixed control structures that combine a PID controller with fuzzy logic. However, in the actual plant, they are manually tuned through a trial and error procedure, and the derivative action is switched off. Therefore, it is difficult to tune. Since the immune system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (Parallel Distributed Processing) network to complete patterns against the environmental situation. Simulation results reveal that reference model basd tuning by immune network suggested in this paper is an effective approach to search for optimal or near optimal process control.

• 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 Power Electronics
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• v.11 no.4
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• pp.393-400
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• 2011

The main objective of this paper is to control the speed of Nonlinear Hybrid Electric Vehicle (HEV) by controlling the throttle position. Various control techniques such as well known Proportional-Integral-Derivative (PID) controller in conjunction with state feedback controller (SFC) such as Pole Placement Technique (PPT), Observer Based Controller (OBC) and Linear Quadratic Regulator (LQR) Controller are designed. Some Intelligent control techniques e.g. fuzzy logic PD, Fuzzy logic PI along with Adaptive Controller such as Self Organizing Controller (SOC) is also designed. The design objective in this research paper is to provide smooth throttle movement, zero steady-state speed error, and to maintain a Selected Vehicle (SV) speed. A comparative study is carried out in order to identify the superiority of optimal control technique so as to get improved fuel economy, reduced pollution, improved driving safety and reduced manufacturing costs.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.586-589
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• 2005

Recently, the applications of unmanned system are steadily increasing. Unmanned automatic system is suitable for routine mission such as reconnaissance, environment monitoring, resource conservation and investigation. Especially, for the ocean environmental probe mission, many ocean engineers had scoped with the routine and even risky works. The unmanned surface vessel designed for sea probes can replace the periodic and routine missions such as water sampling, temperature and salinity measuring, etc. In this paper, an unmanned surface vessel was designed for ocean environmental probe missions. A classical and an adaptive fuzzy control system were designed and tested for the unmanned surface vessel. The design methodologies and performance of the surface vessel and fuzzy control algorithm were illustrated and verified with this unmanned vessel system designed for sea probes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.49-53
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• 2011

Path following of the mobile robot is one research hot for the mobile robot navigation. For the control system of the wheeled mobile robot(WMR) being in nonhonolomic system and the complex relations among the control parameters, it is difficult to solve the problem based on traditional mathematics model. In this paper, we presents a simple and effective way of implementing an adaptive following controller based on the PID for mobile robot path following. The method uses a non-linear model of mobile robot kinematics and thus allows an accurate prediction of the future trajectories. The proposed controller has a parallel structure that consists of PID controller with a fixed gain. The control law is constructed on the basis of Lyapunov stability theory. Computer simulation for a differentially driven nonholonomic mobile robot is carried out in the velocity and orientation tracking control of the nonholonomic WMR. The simulation results of wheel type mobile robot platform are given to show the effectiveness of the proposed algorithm.