scholarly journals Developing a control framework for self-adjusting prosthetic sockets incorporating tissue injury risk estimation and generalized predictive control

2021 ◽  
Author(s):  
F. M. Mbithi ◽  
A. J. Chipperfield ◽  
J. W. Steer ◽  
A. S. Dickinson
Keyword(s):  
Predictive Control ◽  
Injury Risk ◽  
Tissue Injury ◽  
Risk Estimation ◽  
Generalized Predictive Control ◽  
Control Framework

scholarly journals Developing a control framework for self-adjusting prosthetic sockets incorporating tissue injury risk estimation and Generalized Predictive Control

2021 ◽  
Author(s):  
Florence M Mbithi ◽  
Joshua Steer ◽  
Andrew J Chipperfield ◽  
Alexander Dickinson
Keyword(s):  
Predictive Control ◽  
Lower Limb ◽  
Injury Risk ◽  
Tissue Injury ◽  
Risk Estimation ◽  
Soft Tissue Injury ◽  
Estimation Method ◽  
Generalized Predictive Control ◽  
Prosthetic Socket ◽  
Interfacial Pressure

Purpose: To perform activities of daily living (ADL), people with lower limb amputation depend on the prosthetic socket for stability and proprioceptive feedback. Poorly fitting sockets can cause discomfort, pain, limb tissue injuries, limited device usage, and potential rejection. Semi-passively controlled adjustable socket technologies exist, but these depend upon the user’s perception to determine safe interfacial pressure levels. This paper presents a framework for automatic control of an adjustable transtibial prosthetic socket that enables active adaptation of residuum-socket interfacial loading through localized actuators, based on soft tissue injury risk estimation. Method: Using finite element analysis, local interfacial pressure vs. compressive tissue strain relationships were estimated for three anatomical actuator locations, for tissue injury risk assessment within a control structure. Generalized Predictive Control of multiple actuators was implemented to maintain interfacial pressure within estimated safe and functional limits. Results: Controller simulation predicted satisfactory dynamic performance in several scenarios, based on previous related studies. Actuation rates of 0.06 – 1.51kPa/s with 0.67% maximum overshoot, and 0.75 – 1.58kPa/s were estimated for continuous walking, and for a demonstrative loading sequence of ADL, respectively. Conclusion: The developed platform could be useful for extending recent efforts in adjustable lower limb prosthetic socket design, particularly for individuals with residuum sensory impairment.

scholarly journals Experimental Results on Actuator/Sensor Failures in Adaptive GPC Position Control

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 43
Author(s):  
Dariusz Horla
Keyword(s):  
Predictive Control ◽  
Position Control ◽  
Experimental Results ◽  
Generalized Predictive Control ◽  
Sensor Failure ◽  
Servo Drive ◽  
Sensor Failures ◽  
Control Framework ◽  
Free Case ◽  
Performance Deterioration

This work relates to the reliable generalized predictive control issues in the case when actuator or sensor failures take place. The experimental results that form the basis from which the conclusions are drawn from have been obtained in the position control of a servo drive task, and extend the results from the prior research of the author, dedicated to velocity control problems. On the basis of numerous experiments, it has been shown which configuration of prediction horizons is most advantageous from the control performance viewpoint in the adaptive generalized predictive control framework, to cope with the latter failures, and related to a minimum performance deterioration in comparison with the nominal, i.e., failure-free, case. This case study is the main novelty of the presented work, as the other papers available in the field rather focus on additional modifications of the predictive control framework, and not leaving possible room for optimization/alteration of prediction horizons’ values. The results are shown on the basis of the experiments conducted on the laboratory stand with the Modular Servo System of Inteco connected to a mechanical backlash module to cause actuator/sensor failure-like behavior, and with a magnetic brake module to show the performance in the case of an unexpected load.

scholarly journals An Active Equalization Method for Lithium-ion Batteries Based on Flyback Transformer and Variable Step Size Generalized Predictive Control

Energies ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 207
Author(s):  
Jianwen Cao ◽  
Bizhong Xia ◽  
Jie Zhou
Keyword(s):  
Energy Consumption ◽  
Lithium Ion Batteries ◽  
Predictive Control ◽  
Lithium Ion ◽  
Generalized Predictive Control ◽  
Variable Step Size ◽  
Size Factor ◽  
Step Size ◽  
Variable Step ◽  
Equalization Method

The inconsistency in large-scale battery pack significantly degrades the performance of electric vehicles. In order to diminish the inconsistency, the study designs an active equalization method comprising of equalizer and equalization strategy for lithium-ion batteries. A bidirectional flyback transformer equalizer (BFTE) is designed and analyzed. The BFTE is controlled by a pulse width modulation (PWM) controller to output designated balancing currents. Under the purpose of shortening equalization time and reducing energy consumption during the equalization process, this paper proposes an equalization strategy based on variable step size generalized predictive control (VSSGPC). The VSSGPC is improved on the generalized predictive control (GPC) by introducing the Step Size Factor. The VSSGPC surmounts the local limitation of GPC by expanding the control and output horizons to the global equalization process without increasing computation owing to the Step Size Factor. The experiment results in static operating condition indicate that the equalization time and energy consumption are reduced by 8.3% and 16.5%, respectively. Further validation in CC-CV and EUDC operating conditions verifies the performance of the equalizer and rationality of the VSSGPC strategy.

scholarly journals Incorporating model predictive control with fuzzy approximation for robot manipulation under remote center of motion constraint

2021 ◽  
Author(s):  
Hang Su ◽  
Junhao Zhang ◽  
Ziyu She ◽  
Xin Zhang ◽  
Ke Fan ◽  
...  
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Robot Manipulator ◽  
Robot Assisted ◽  
External Disturbances ◽  
Fuzzy Approximation ◽  
Control Framework ◽  
Motion Constraint

AbstractRemote center of motion (RCM) constraint has attracted many research interests as one of the key challenges for robot-assisted minimally invasive surgery (RAMIS). Although it has been addressed by many studies, few of them treated the motion constraint with an independent workspace solution, which means they rely on the kinematics of the robot manipulator. This makes it difficult to replicate the solutions on other manipulators, which limits their population. In this paper, we propose a novel control framework by incorporating model predictive control (MPC) with the fuzzy approximation to improve the accuracy under the motion constraint. The fuzzy approximation is introduced to manage the kinematic uncertainties existing in the MPC control. Finally, simulations were performed and analyzed to validate the proposed algorithm. By comparison, the results prove that the proposed algorithm achieved success and satisfying performance in the presence of external disturbances.

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