A high-performance control scheme for reluctance type bearingless motors

2017 ◽  
Vol 53 (3) ◽  
pp. 537-549 ◽  
Author(s):  
Xiaodong Sun ◽  
Bokai Su ◽  
Long Chen ◽  
Zebin Yang ◽  
Yifei Yang ◽  
...  
Solar Energy ◽  
2018 ◽  
Vol 159 ◽  
pp. 353-368 ◽  
Author(s):  
Billel Talbi ◽  
Fateh Krim ◽  
Toufik Rekioua ◽  
Saad Mekhilef ◽  
Abdelbaset Laib ◽  
...  

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3516 ◽  
Author(s):  
Abdelbasset Krama ◽  
Laid Zellouma ◽  
Boualaga Rabhi ◽  
Shady Refaat ◽  
Mansour Bouzidi

This paper proposes a high performance control scheme for a double function grid-tied double-stage PV system. It is based on model predictive power control with space vector modulation. This strategy uses a discrete model of the system based on the time domain to generate the average voltage vector at each sampling period, with the aim of canceling the errors between the estimated active and reactive power values and their references. Also, it imposes a sinusoidal waveform of the current at the grid side, which allows active power filtering without a harmonic currents identification phase. The latter attempts to reduce the size and cost of the system as well as providing better performance. In addition, it can be implemented in a low-cost control platform due to its simplicity. A double-stage PV system is selected due to its flexibility in control, unlike single-stage strategies. Sliding mode control-based particle swarm optimization (PSO) is used to track the maximum power of the PV system. It offers high accuracy and good robustness. Concerning DC bus voltage of the inverter, the anti-windup PI controller is tuned offline using the particle swarm optimization algorithm to deliver optimal performance in DC bus voltage regulation. The overall system has been designed and validated in an experimental prototype; the obtained results in different phases demonstrate the higher performance and the better efficiency of the proposed system in terms of power quality enhancement and PV power injection.


Robotica ◽  
2020 ◽  
pp. 1-26
Author(s):  
Tao Xue ◽  
ZiWei Wang ◽  
Tao Zhang ◽  
Ou Bai ◽  
Meng Zhang ◽  
...  

SUMMARY Accurate torque control is a critical issue in the compliant human–robot interaction scenario, which is, however, challenging due to the ever-changing human intentions, input delay, and various disturbances. Even worse, the performances of existing control strategies are limited on account of the compromise between precision and stability. To this end, this paper presents a novel high-performance torque control scheme without compromise. In this scheme, a new nonlinear disturbance observer incorporated with equivalent control concept is proposed, where the faster convergence and stronger anti-noise capability can be obtained simultaneously. Meanwhile, a continuous fractional power control law is designed with an iteration method to address the matched/unmatched disturbance rejection and global finite-time convergence. Moreover, the finite-time stability proof and prescribed control performance are guaranteed using constructed Lyapunov function with adding power integrator technique. Both the simulation and experiments demonstrate enhanced control accuracy, faster convergence rate, perfect disturbance rejection capability, and stronger robustness of the proposed control scheme. Furthermore, the evaluated assistance effects present improved gait patterns and reduced muscle efforts during walking and upstair activity.


2020 ◽  
Vol 90 ◽  
pp. 106133 ◽  
Author(s):  
Laura Micheli ◽  
Jonathan Hong ◽  
Simon Laflamme ◽  
Alice Alipour

Micromachines ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 597
Author(s):  
Brahim Brahmi ◽  
Ibrahim El Bojairami ◽  
Tanvir Ahmed ◽  
Asif Al Zubayer Swapnil ◽  
Mohammad AssadUzZaman ◽  
...  

The research presents a novel controller designed for robotic systems subject to nonlinear uncertain dynamics and external disturbances. The control scheme is based on the modified super-twisting method, input/output feedback linearization, and time delay approach. In addition, to minimize the chattering phenomenon and ensure fast convergence to the selected sliding surface, a new reaching law has been integrated with the control law. The control scheme aims to provide high performance and enhanced accuracy via limiting the effects brought by the presence of uncertain dynamics. Stability analysis of the closed-loop system was conducted using a powerful Lyapunov function, showing finite time convergence of the system’s errors. Lastly, experiments shaping rehabilitation tasks, as performed by healthy subjects, demonstrated the controller’s efficiency given its uncertain nonlinear dynamics and the external disturbances involved.


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