Hierarchical adaptive control of self-stabilizing electromechanical systems using artificial-immune self-tuning mechanism for state weighting-factors

2021 ◽  
Vol 35 (3) ◽  
pp. 1235-1250
Author(s):  
Omer Saleem ◽  
Khalid Mahmood-ul-Hasan
Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 77 ◽  
Author(s):  
Haibo Zhao ◽  
Xiaoxiang Wei ◽  
Yiming Zhong ◽  
Peihong Wang

Most work from the last decade on the piezoelectric vibration energy harvester (PVEHs) focuses on how to increase its frequency bandwidth but ignores the effect of vibration direction on the output performance of the harvester. However, both the frequency and the direction of the vibration in a real environment are time-variant. Therefore, improving the capability of PVEH to harvest multi-directional vibration energy is also important. This work presents a direction self-tuning two-dimensional (2D) PVEH, which consists of a spring-mass system and a direction self-tuning structure. The spring-mass system is sensitive to external vibration, and the direction self-tuning structure can automatically adjust its plane perpendicular to the direction of the external excitation driven by an external torque. The direction self-tuning mechanism is first theoretically analyzed. The experimental results show that this direction self-tuning PVEH can efficiently scavenge vibration energy in the 2D plane, and its output performance is unaffected by vibration direction and is very stable. Meanwhile, the effect of the initial deflection angle and the vibration acceleration on the direction self-tuning time of the PVEH is investigated. The direction self-tuning mechanism can also be used in other PVEHs with different energy conversion methods for harvesting multi-direction vibration energy.


Automatica ◽  
1978 ◽  
Vol 14 (6) ◽  
pp. 525-532 ◽  
Author(s):  
László Keviczky ◽  
Jenö Hetthéssy ◽  
Miklós Hilger ◽  
János Kolostori

1984 ◽  
Vol 106 (2) ◽  
pp. 134-142 ◽  
Author(s):  
C. S. G. Lee ◽  
B. H. Lee

This paper presents the development of a resolved motion adaptive control which adopts the ideas of “resolved motion rate control” [8] and “resolved motion acceleration control” [10] to control a manipulator in Cartesian coordinates for various loading conditions. The proposed adaptive control is performed at the hand level and is based on the linearized perturbation system along a desired hand trajectory. The controlled system is characterized by feedforward and feedback components which can be computed separately and simultaneously. The feedforward component resolves the specified positions, velocities, and accelerations of the hand into a set of values of joint positions, velocities, and accelerations from which the nominal joint torques are computed using the Newton-Euler equations of motion to compensate all the interaction forces among the various joints. The feedback component consisting of recursive least square identification scheme and an optimal adaptive self-tuning controller for the linearized system computes the perturbation torques which reduce the manipulator hand position and velocity errors along the nominal hand trajectory. The feasibility of implementing the proposed adaptive control using present day low-cost microprocessors is explored.


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