• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.239-243
• /
• 1989

This paper represents the control software development for Direct Drive Arm Robot with the WHILE language composed the 68000 assembly language and high level language modula-2. Direct Drive Ann Robot needs the control program which is fast step and exactly position moving because Direct Drive Arm Robt depends on accuracy. We found that the self-tuning algorithm for this robot control is very good for the real time control and the floating point operation using the 32 bit CPU(MC 68020) controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.64.2-64
• /
• 2002

Contents 1. Introduction $\textbullet$ Contents 2. System description $\textbullet$ Contents 3. Desired feedback control and function approximation $\textbullet$ Contents 4. Robust adaptive controller design $\textbullet$ Contents 5. Simulation study $\textbullet$ Contents 6. Conclusion

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.317-321
• /
• 1990

This paper proposes a performance improvement to a control system with optimal state feedback control. In this paper, a simple and direct design procedure is proposed to design the model following controller. The scheme is implemented in a 16 bit micromputer with math corprocessor. Tests on a DC machine have been conducted.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.3
• /
• pp.221-226
• /
• 2006

In this paper, we study an approach to design a Fuzzy PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of traditional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. In order to solve the above problems, we adapt Fuzzy PI controller for the fire angle control of rectifier. The performance of the Fuzzy PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain factors of the Fuzzy PI controller by Genetic Algorithms. A comparative study has been performed between Fuzzy PI controller and traditional PI controller, to prove the superiority of the proposed scheme.

• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2006.06a
• /
• pp.77-78
• /
• 2006

A mixed method between $H_2\;and\;H_{\infty}$ control are widely applied to systems which has parameter perturbation and uncertain model to obtain an optimal robust controller. Brushless Direct Current (BLDC) motors are widely used for high performance control applications. Conventional PID controller only provides satisfactory performance for set-point regulation. However, with the presence of nonlinearities, uncertainties and perturbations in the system, conventional PID is not sufficient to achieve an optimal robust controller. This paper presents an approach to ease designing a Mixed $H_2/H_{\infty}$ PID controller for controlling speed of Brushless DC motors and the genetic algorithm is used to solve the optimized problems. Numerical results are shown to prove that the performance in the proposed controller is better than that in the optimal PID controller using LQR approach.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.40 no.4
• /
• pp.264-274
• /
• 2003

This paper presents a direct generalized minimum-variance self tuning controller with a PID structure using neural network which adapts to the changing parameters of the nonlinear system with nonminimum phase behavior, noises and time delays. The self-tuning controller with a PID structure is a combination of the simple structure of a PID controller and the characteristics of a self-tuning controller that can adapt to changes in the environment. The self-tuning control effect is achieved through the RLS (recursive least square) algorithm at the parameter estimation stage as well as through the Robbins-Monro algorithm at the stage of optimizing the design parameter of the controller. The neural network control effect which compensates for nonlinear factor is obtained from the learning algorithm which the learning error between the filtered reference and the auxiliary output of plant becomes zero. Computer simulation has shown that the proposed method works effectively on the nonlinear nonminimum phase system with time delays and changed system parameter.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.4
• /
• pp.552-563
• /
• 2005

In this paper, we propose a wavelet based fuzzy neural network (WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges the advantages of the neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of the wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of a mobile robot via the gradient descent (GD) method. In addition, an approach that uses adaptive learning rates for training of the WFNN controller is driven via a Lyapunov stability analysis to guarantee fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control results of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.8
• /
• pp.899-905
• /
• 2014

In this paper, we propose a method that can be used to back-stepping controller design for speed control of Brushless Direct Current (BLDC) motor. First, back-stepping controller is designed with load torque estimator. The estimator is included to adapt to the variation of load torque in real time. Finally, the proposed controller is tested through experiment with a 120W BLDC motor for the angular velocity reference tracking performance and load torque volatility estimation. The simulation result verifies the performance of the proposed controller.

• Journal of Advanced Marine Engineering and Technology
• /
• v.35 no.6
• /
• pp.835-841
• /
• 2011

Wave power generation systems operated in the ocean, has been developed as large power and grid power connection systems in general. However, small wave power generation systems offer operational efficiency for the lighted (navigation aids) buoy. They simply adopts a full-wave rectification for charging battery (direct connection method). In this paper, a wave power controller based on a booster converter is developed by considering a characteristic of the wells turbine. Both direct connection and booster converter power controller is designed and tested to compare the characteristics. Experiments demonstrate that the output of the proposed controller has improved the characteristic of output power, when generator output voltage is low.

• Journal of Power Electronics
• /
• v.14 no.2
• /
• pp.369-382
• /
• 2014

A growing dynamic electrical demand has created an increasing interest in utilizing nonconventional energy sources like Photovoltaic (PV), wind power, etc. In this context, this paper focuses on the design and development of a composite power controller (CPC) in the decoupled double synchronous reference frame (DDSRF) combining the advantages of direct power control (DPC) and voltage oriented control (VOC) for a PV sourced grid connected inverter. In addition, a controller with the inherent active filter configuration is tested with nonlinear and unbalanced loads at the point of common coupling in both grid connected and autonomous modes of operation. Furthermore, the loss and reactive power compensation due to a non-fundamental component is also incorporated in the design, and the developed DDSRF model subsequently allows independent active and reactive power control. The proposed developed model of the controller is also implemented using MATLAB-Simulink-ISE and a Xilinx system generator which evaluate both the simulated and experimental setups. The simulation and experimental results confirm the validity of the developed model. Further, simulation results for the DPC are also presented and compared with the proposed CPC to further bring out the salient features of the proposed work.