• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2684-2686
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• 2005

This paper presents design of nonlinear controller based on genetic-fuzzy algorithm. Motor system that is included at a humanoid robot has many nonlinear parameters such as saturation, backlash and so on. So, it is hard to control a humanoid robot because of these nonlinearities. Also, tracking following ability is also reduced by these nonlinearities. In this paper, fuzzy PID controller is proposed for reducing efficiency by saturation. At that time, genetic algorithm is supplied at making fuzzy rule in order to make optimal fuzzy PID controller. Also, disturbance observer is used to reduce the efficiency of backlash. All these processes are verified by simulation and experiment in the real humanoid robot.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1405-1411
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• 2007

In this paper, a new speed sensorless control based on a fuzzy compensator are proposed for the interior permanent magnet synchronous motor (IPMSM) drives. The conventional proportional plus integrate(PI) control are very sensitive to step change of the command speed, parameter variations and load disturbance. To cope with these problems of the PI control, the estimated speeds are compensated by using the fuzzy logic controller (FLC). In the FLC used by the speed compensator of the IPMSM, the system control parameters are adjusted by the fuzzy rule based system, which is a logical model of the human behavior for process control. The effectiveness of algorithm is confirmed by the experiments.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1505-1506
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• 2008

In this paper, a robust adaptive backstepping control is developed for efficiency optimization of induction motors with uncertainties. The proposed control scheme consists of efficiency flux control(EFC) using a sliding mode adaptive flux observer and robust speed control(RSC) using a function approximation for mechanical uncertainties. In EFC, it is important to find the flux reference to minimize power losses of induction motors. Therefore, we proposed the optimal flux reference using the electrical power loss function. The sliding mode flux observer is designed to estimate rotor fluxes and variation of inverse rotor time constant. In RSC, the unknown function approximation technique employs nonlinear disturbance observer(NDO) using fuzzy neural networks(FNNs). The proposed controller guarantees both speed tracking and flux tracking. Simulation results are presented to illustrate the effectiveness of the approaches proposed.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.2
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• pp.118-123
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• 2002

A torque transmission system, which is composed of serveral gears and couplings, is flexible. Therefore, the torsion vibration occurs when the motor speed abruptly changes. Consequently, for accuracy characteristic response of motor, we must suppressed vibration. Therefore, vibration suppression is very important motor control. In order to suppress the vibration, various control method have been proposed. Specially, one method of vibration suppression is used disturbance observer and filter. The disturbance observer is used to suppress the vibration in this method. By feedback of the estimated torsion torque, the vibration can be suppressed. The coefficient diagram method is used to design the filter and proportional controller. But using coefficient diagram method, not adapted controller parameter in disturbance. In order to solve this problem. we used fuzzy controller for auto tuning controller parameter $K_P$. We proved of this approach is confirmed by simulation. 

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2423-2425
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• 2004

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and the floor decreases suddenly, the robot has slip state. First of all, this paper models adhesion characteristics and slip in wheeled robot. Secondly, the paper proposes estimation method of adhesion force coefficient(AFC) according to slip velocity. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. The paper proposes an anti-slip control system based on an ordinary disturbance observer, that is, the re-adhesion control is achieved by reducing the driving torque enough to give maximum adhesion force coefficient. fuzzy logic controller(FLC) is petty useful with slip through that compare fuzzy with PI control for the controller performance. These procedure is implemented using a Pioneer 2-DXE parameter.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.13-18
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• 2005

Over the last few years, the control of bipedal robot has been considered a promising but difficult research field in the community of robotics. In this paper, a new robust output control method for a bipedal robot is proposed using the adaptive fuzzy logic. The adaptive fuzzy logic is used as an system approximator to cancel the unknown uncertainty. First, a model for a bipedal robot including switching leg influence, uncertainty and disturbance is presented. Second, a controller is designed in which the joint velocity measurement is not required. Fuzzy approximation error estimator is inserted in the system for tuning the fuzzy logic. Finally, the result of the computer simulation is presented to show the validity of the suggested control method.

• Steel and Composite Structures
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• v.46 no.1
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• pp.107-114
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• 2023

A new intelligent adaptive control scheme was proposed that combines observer disturbance-based adaptive control and fuzzy adaptive control for a composite structure with a mass-adjustable damper. The most important advantage is that the control structures do not need to know the uncertainty limits and the interference effect is eliminated. Three adjustable parameters in LMI are used to control the gain of the 2D fuzzy control. Binary performance indices with weighted matrices are constructed to separately evaluate validation and training performance using the revalidation learning function. Determining the appropriate weight matrix balances control and learning efficiency and prevents large gains in control. It is proved that the stability of the control system can be ensured by a linear matrix theory of equality based on Lyapunov's theory. Simulation results show that the multilevel simulation approach combines accuracy with high computational efficiency. The M-TMD system, by slightly reducing critical joint load amplitudes, can significantly improve the overall response of an uncontrolled structure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.506-510
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• 2004

A torque transmission system composed of several gears and couplings is flexible. In order to get an exact response of motor, the torsional vibration due to an unexpected change of motor speed must be suppressed. Therefore, it is very important that motor control suppress vibration. Various methods to control it including dual inertia system are proposed. Specially, the method of vibration suppression is that vibration can be suppressed to fee㏈ack the estimated torsion torque via the disturbance observer filter being of normal filter. The suitable Proportional controller and coefficient parameter can be designed using CDM and the torsional vibration also be suppressed, but it has a low degree of adaptability to disturbance. The PID controller can be designed easily, but makes the excessive overshoot and oscillation for system response in the early period. To resolve these problems, simple and practical PID controller with two degree of freedom is proposed recently that it ran improve performance of obeying the reference unconcerned in any disturbance by changing the proportional gain by two degree of freedom parameter. But it has also the defect that parameter a must be changed to obtain the ideal Proportional parameter. On this paper, we design the controller which automatically adjusts parameter u using fuzzy Algorithm to overcome such defects. Also, we compare the proposed method with established one and evaluate them to confirm performance of the designed controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.215-221
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• 2006

This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems such as the structural instability, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control were fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system by employing only single algorithm since the system usually includes multiple nonlinearities. In this paper, a switching Pill is considered for a control of saturation and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between the results of simulation and experiment, and then the switching Pill gains are determined using genetic algorithm with some heuristic approach. The performance of the switching Pill controller for saturation and the dual feedback for backlash control is investigated through the simulation. Finally, it is shown that the implemented control system has good results and can be applied to the real humanoid robot system ISHURO.