• Journal of the Korean Society of Industry Convergence
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• v.21 no.2
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• pp.53-62
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• 2018

This study propose a new approach to control the optimal working path of vertical type articulated robot with translation joint for trimming working process automation in forging manufacturing process. The basic structure of the proposed robotic joints controller consists of a Proportional-Intergral controller and a Proportional-Derivative controller in parallel. The proposed control scheme takes advantage of the properties of the fuzzy PID controllers. The proposed method is suitable to control of the trajectory and path control in cartesian space for vertical type articulated robot manipulator. The results illustrates that the proposed fuzzy computed torque controller is more stable and robust than the conventional computed torque controller. The reliability is varified by simulation test for vertical type s articulated robot with seven joints including one trqanslation joint.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.9
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• pp.1065-1071
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• 2012

Wind energy is becoming one of the most preferable alternatives to conventional sources of electric power that rely on fossil fuels. For stable electric power generation, constant rotating speed control of a wind turbine is performed through pitch control and stall control of the turbine blades. Recently, variable pitch control has been implemented in modern wind turbines to harvest more energy at variable wind speeds that are even lower than the rated one. Although wind turbine pitch controllers are currently optimized using a step response via the Ziegler-Nichols auto-tuning process, this approach does not satisfy the requirements of variable pitch control. In this study, the variable pitch controller was optimized by a genetic algorithm using a neural network model that was constructed by the Latin Hypercube sampling method to improve the Ziegler-Nichols auto-tuning process. The optimized solution shows that the root mean square error, rise time, and settle time are respectively improved by more than 7.64%, 15.8%, and 15.3% compared with the corresponding initial solutions obtained by the Ziegler-Nichols auto-tuning process.

• 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.