Hybrid Control Scheme of a Hydraulically Actuated Lower Extremity Exoskeleton for Load-Carrying

2017 ◽  
Vol 91 (3-4) ◽  
pp. 493-500 ◽  
Author(s):  
Yi Long ◽  
Zhi-jiang Du ◽  
Chao-feng Chen ◽  
Wei-dong Wang ◽  
Long He ◽  
...  
Author(s):  
Lihua Huang ◽  
Ryan Ryan Steger ◽  
H. Kazerooni

The first functional load-carrying and energetically autonomous exoskeleton was demonstrated at U.C. Berkeley, walking at the average speed of 0.9 m/s (2 mph) while carrying a 34 kg (75 lb) payload. The original BLEEX sensitivity amplification controller, based on positive feedback, was designed to increase the closed loop system sensitivity to its wearer’s forces and torques without any direct measurement from the wearer. The controller was successful at allowing natural and unobstructed load support for the pilot. This article presents an improved control scheme we call “mixed” control that adds robustness to changing BLEEX backpack payload. The walking gait cycle is divided into stance control and swing control phases. Position control is used for the BLEEX stance leg (including torso and backpack) and the sensitivity amplification controller is used for the swing leg. The controller is also designed to smoothly transitions between these two schemes as the pilot walks. With mixed control, the controller does not require a good model of the BLEEX torso and payload, which is difficult to obtain and subject to change as payload is added and removed. As a tradeoff, the position control used in this method requires the human to wear seven inclinometers to measure human limb and torso angles. These additional sensors require careful design to securely fasten them to the human and increase the time to don (and doff) BLEEX.


2018 ◽  
Vol 61 ◽  
pp. 00007
Author(s):  
Ibrahim Farouk Bouguenna ◽  
Ahmed Azaiz ◽  
Ahmed Tahour ◽  
Ahmed Larbaoui

In this paper a neuro-fuzzy-sliding mode control (NFSMC) with extended state observer (ESO) technique; is designed to guarantee the traction of an electric vehicle with two distinct permanent magnet synchronous motor (PMSM). Each PMSM systems (source-convertermotor) are attached to an electronic differential (ED), in order to adjust the senses of direction of the vehicle, and sustain a stable speed by adapting the difference in velocity of each motor-wheel according to the direction in the case of a turn. Two types of controllers are employed by a hybrid control scheme to assure the control and the performance of the vehicle. This hybrid control scheme guarantees the stability of the vehicle by ED, reduces the chattering phenomena in the PMSM electric motor, and improves the disturbance rejection ability which employs tow types of controllers. The neuro-fuzzy sliding mode control on the direct current loop and ESO controller on the speed loop, and the quadratic current loop; taking into account the dynamic of the vehicle. Simulation runs under Matlab/Simulink to assess the efficiency, and strength of the recommended control method on the closed loop system.


Author(s):  
P. F. Le Roux ◽  
R.C. Bansal

An electrical network constantly faces unforeseen events such as faults on lines, loss of load and loss of generation. Under-frequency load shedding and generator tripping are traditional methods used to stabilise a network when a transient fault occurs. These methods will prevent any network instability by shedding load or tripping the most critical generator at a calculated time when required. By executing these methods, the network can be stabilised in terms of balancing the generation and the load of a power system. A hybrid control scheme is proposed where the traditional methods are combined to reduce the stress levels exerted on the network and to minimise the load to be shed.


Author(s):  
Jin-Wei Liang ◽  
Hung-Yi Chen ◽  
Lyu-Cyuan Zeng

A hybrid control scheme that combines a self-tuning PID-feedback loop and TDC-based feedforward scheme is proposed in this study to cope with an active pneumatic vibration isolator. In order to establish an effective TDC feedforward control a reliable mathematical model of the pneumatic isolator is required and developed firstly. Numerical and experimental investigations on the validity of the mathematical model are performed. It is found that although slight discrepancy exists between predicted and observed behaviors of the system, the overall model performance is acceptable. The resultant model is then applied in the design of the TDC feedforward scheme. A neuro-based adaptive PID control is integrated with the TDC feedforward algorithm to form the hybrid control. Numerical and experimental isolation tests are carried out to examine the suppression performances of the proposed hybrid control scheme. The results show that the proposed hybrid control method outperforms solely TDC feedforward while the latter outperforms the passive isolation system. Moreover, the proposed hybrid control scheme can suppress the vibration near the system’s resonance.


2020 ◽  
Vol 13 (3) ◽  
Author(s):  
Atthasit Tawai ◽  
Kanyarat Kitsubthawee ◽  
Chanin Panjapornpon ◽  
Weiming Shao

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