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Neural Network Predictive Control of Swing Phase for a Variable-Damping Knee Prosthesis with Novel Hydraulic Valve
2020
IEEE Access
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To improve the gait symmetry, this study proposed a variable-damping knee prosthesis with a novel hydraulic damper using neural network predictive control (NNPC) scheme during swing phase. ...
the online feasibility and effectiveness of the algorithm at different speeds. ...
CONCLUSION This study proposed a variable-damping knee prosthesis with a novel hydraulic damper using neural network predictive control (NNPC) scheme during swing phase. ...
doi:10.1109/access.2020.3035896
fatcat:niuirnzqpjgv7hwjce2grwusjy
Modeling and Experimental Study for Online Measurement of Hydraulic Cylinder Micro Leakage Based on Convolutional Neural Network
2019
Sensors
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Finally, the convolutional neural network (CNN), BP neural network (BPNN), Radial Basis Function Network (RBF), and Support Vector Regression (SVR) are used to predict the hydraulic cylinder leakage; the ...
Firstly, the principle of internal leakage online measurement is proposed, including the online measurement system, the fixed mode of the strain gauge and the mathematical model of the flow-strain signal ...
Conclusions This paper studies the online measurement of hydraulic cylinder leakage based on CNN: (1) A method for online measurement of leakage in hydraulic cylinder is proposed, which uses a strain gauge ...
doi:10.3390/s19092159
fatcat:o3qx2cxiejeznpgis7dhof42yi
Development and Modelling of Hydro-formed circular sheet Using Neural Networks
2014
International Journal of Engineering Research
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This paper deals with the development of a sheet hydro forming (SHF ) set up and model to predict the deformation caused by the hydro forming using Artificial Neural Networks(ANN). ...
Single-and two-hidden-layer feed forward neural network models were used to capture the nonlinear correlations between the input(hydraulic pressure, thickness and diameter of work piece) and output (dome ...
A Matlab based artificial neural network (A NN) toolbo x was used for prediction of dome height of alumin iu m and copper piece after applying hydraulic pressure. ...
doi:10.17950/ijer/v3s4/410
fatcat:w34oxlkeujbf5k4wpneonobnf4
Neural network-based model predictive control of a servo-hydraulic vehicle suspension system
2009
AFRICON 2009
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This paper presents multi-layer feedforward neural network-based identification and approximate predictive controller (NNAPC) for a two degree-of-freedom (DOF), quarter-car servohydraulic vehicle suspension ...
A SISO neural network (NN) model based on Nonlinear AutoRegressive with eXogenous input (NARX) is developed using input-output data sets obtained from mathematical model simulation. ...
The nonlinear system was identified using a two layer MLPNN with five hidden layer neurons and the quality of the neural network model that resulted from the system identification is evident from the model ...
doi:10.1109/afrcon.2009.5308111
fatcat:jfigxlrsw5auxgwlokryacopfm
Testing Method for Intelligent Loading of Mining Emulsion Pump Based on Digital Relief Valve and BP Neural Network Control Algorithm
2022
Machines
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A backpropagation (BP) artificial neural network (ANN) model is used to fit a functional relationship between the three parameters. ...
Next, a BP ANN model is constructed, and its reliability is verified; the BP neural network algorithm and proportional-integral-derivative (PID) algorithm are compared through simulation. ...
Laboratory of Nondestructive Testing (Nanchang Hangkong University), Ministry of Education (EW202180222), and the National Natural Science Foundation of China under grant 51774293. ...
doi:10.3390/machines10100896
fatcat:ol7wjrzumjelpao5efjnmhuqfe
Monitoring of solenoid parameters based on neural networks and optical fiber squeezer for solenoid valves diagnosis
2021
International Journal of Power Electronics and Drive Systems (IJPEDS)
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The authors propose a new methodology for the functional diagnosis of electromagnetic solenoids (EMS) used in hydraulic systems. ...
The result of this simulation is used for training the neural network, then a simulation is proposed using the neural net fitting toolbox to determine the solenoid parameters (Resistance of the coil R, ...
The proposed neural networks model has satisfactory performance of prediction and has met the monitoring requirement. ...
doi:10.11591/ijece.v11i2.pp1697-1708
fatcat:usofjf7guvewlghtal6qbcbnpy
Performance Degradation Analysis and Optimization of the Stepless Capacity Regulation System for Reciprocating Compressors
2020
Applied Sciences
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In order to calculate the rate of degradation, a load prediction model based on a modified back-propagation neural network was established. ...
The rate of degradation can be calculated using the predicted results. ...
Barroso-Maldonado et al. developed two models: one using an artificial neural network and another one using a probabilistic neural network to predict and simulate the behavior of a reciprocating compressor ...
doi:10.3390/app10020704
fatcat:4726vk267jeefj4r6tsim2nehu
APPLICATION OF SELF-TUNING FUZZY PID CONTROLLER ON INDUSTRIAL HYDRAULIC ACTUATOR USING SYSTEM IDENTIFICATION APPROACH
2009
International Journal on Smart Sensing and Intelligent Systems
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The model is performed in linear discrete model to obtain a discrete transfer function for the system. Model estimation procedures are done by using System Identification Toolbox in Matlab. ...
The controller is designed based on the mathematical model of the system which is estimated by using System Identification technique. ...
In the last few years, neural networks have been developed in form online identification using Recurrent High Order Neural Networks (RHONN) method [5] . ...
doi:10.21307/ijssis-2017-349
fatcat:m5bdbgqpf5bw5nyzfc5x5sivnq
Tire-road friction estimation and uncertainty assessment to improve electric aircraft braking system
[article]
2022
arXiv
pre-print
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Other Versions
2021
2021 29th Mediterranean Conference on Control and Automation (MED)
unpublished
doi:10.1109/med51440.2021.9480241 fatcat:7ajifyennfgphnh3fghq36vdkq
doi:10.1109/med51440.2021.9480241 fatcat:7ajifyennfgphnh3fghq36vdkq
The accurate online estimation of the road-friction coefficient is an essential feature for any advanced brake control system. ...
A stochastic NN weights drop-out mechanism is used to online estimate the confidence interval of the estimated best friction coefficient thus providing a characterization of the epistemic uncertainty associated ...
of (λ, µ) pairs as input, and using a Quarter Car Model (QCM) for the system dynamics. ...
arXiv:2211.10336v1
fatcat:iyfx2yb3dnggrm32pifhvqtzta
Dynamic Bayesian Networks for Prognosis
2013
Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM
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In this paper, a methodology for probabilistic prognosis of a system using a dynamic Bayesian network (DBN) is proposed. ...
From this state estimate, future states of the system are predicted using the DBN and sequential Monte Carlo sampling. ...
Liu et al. (2010) use adaptive recurrent neural networks for the estimation of battery RUL. ...
doi:10.36001/phmconf.2013.v5i1.2246
fatcat:t7fyjne5bzgmnk5ue367du6qvy
Current Status and Applications for Hydraulic Pump Fault Diagnosis: A Review
2022
Sensors
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To implement Prognostics Health Management (PHM) for hydraulic pumps, it is very important to study the faults of hydraulic pumps to ensure the stability and reliability of the whole life cycle. ...
The research on fault diagnosis has been very active, but there is a lack of systematic analysis and summary of the developed methods. ...
[131] developed an online health monitoring system for hydraulic pumps by using feature extraction, a fuzzy reasoning system, and knowledge fusion technology. Bykov et al. ...
doi:10.3390/s22249714
pmid:36560083
pmcid:PMC9788536
fatcat:ldy4tjebcnf6dlvud5ifackgei
Electro-Hydraulic Proportional System Real Time Tracking Control Development Based on Pulse width Modulation Method
2021
Communications - Scientific letters of the University of Zilina
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A mathematical model of the EHPS is presented using electro- hydraulic proportional valve (EHPV) by Matlab-Simulink, which facilitates the simulation of the hydraulic behavior inside the main control unit ...
The controller of the system is an Arduino uno, which is considered as a processor of the system. The model is validated by the experimental system. ...
Vaughan and Gamble [1] presented a nonlinear dynamic model of a high-speed direct acting solenoid valve, the model accurately predicted both the dynamic and steady state response of the valve to voltage ...
doi:10.26552/com.c.2021.4.b336-b345
fatcat:jgq42qwburatzali52eiohd2ym
Review of Brake-by-Wire System and Control Technology
2022
Actuators
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Based on the analysis of the structure and design flow of the brake-by-wire (BBW) system, this paper analyzes the research status and development trend of the control methods of braking force, coordination ...
A new requirement of the X-by-wire system, including the response, accuracy, energy consumption and fault-tolerance, is put forward. ...
Cao studied a controller that combines a neural network and SMC, and the RBF neural network is used to adaptively adjust the switching gain of the sliding mode controller, which effectively reduces the ...
doi:10.3390/act11030080
fatcat:45gfwqr5ovbxrpqhp4efg5uazm
Precision Motion Control of Robotized Industrial Hydraulic Excavators via Data-Driven Model Inversion
2022
IEEE Robotics and Automation Letters
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The data-driven model and its inversion are trained offline in a supervised manner using the real operational data since online learning methods can damage the machine and surroundings. ...
Rather than employing a single neural network to approximate the whole excavator dynamics, including input delays and dead-zones, we construct a physics-inspired data-driven model with a modular structure ...
Learning the data-driven model and its inversion online can endanger the excavator and the environments, thus the learning is done offline in a supervised manner using the operational data of the real ...
doi:10.1109/lra.2022.3142389
fatcat:dvvm3ug7nrgtvgc43gnv523yqm
Feasibility of Deep Neural Network Surrogate Models in Fluid Dynamics
2019
Modeling, Identification and Control
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This paper studies reduced-order-models for the fluid flow problem of a digital valve, and whether it may efficiently be formulated by a deep Artificial Neural Network (ANN) to model e.g. the valve flow ...
A similar model is built as a deep ANN which is trained with data from the analytical model to investigate the amount of data required for an ANN and its fitting capabilities. ...
System Analysis The functionality of a digital hydraulic valve is simple: open and close a fluid gateway. ...
doi:10.4173/mic.2019.2.1
fatcat:escvuzu3ofcixc7xm5up3nw66q
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