• 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.

• Journal of Aerospace System Engineering
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• v.15 no.3
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• pp.1-10
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• 2021

The electro-hydrostatic actuators (EHA) are widely used in various industrial fields since they can independently execute the function of the hydraulic power source and have high efficiency. Particularly, in the aviation field, the EHA is mainly designed as dual redundant asymmetric tandem actuator to mitigate failure and minimize installation space. However, aviation EHAs designed in the form of dual redundant asymmetric tandem actuator have the disadvantage of decreased durability performance due to the occurrence of force fighting. In this paper, the controller is designed based on backstepping technique to improve control performance and reduce force fighting for aviation EHA. The augmented state observer is proposed to estimate the states required for control. Through simulation, it was verified that the proposed controller had superior control performance and significantly reduces the force fighting compared to the general PI controller.