Fault Detection and Identification Method Based on Genetic Algorithms to Monitor Degradation of Electrohydraulic Servomechanisms

Electro Hydraulic Actuators (EHAs) keep their role as the leading solution for the control of current generation primary flight control systems: the main reason can be found in their high power to weight ratio, much better than other comparable technologies. To enhance efficiency and reliability of modern EHAs, it is possible to leverage the diagnostics and prognostics disciplines; these two tools allow reducing life cycle costs without losing reliability, and provide the bases for health management of integrated systems, in compliance with regulations. This paper is focused on the development of a fault detection algorithm able to identify the early signs of EHA faults, through the recognition of their precursors and related degradation patterns. Our methodology provides the advantage of anticipating incoming failures, triggering proper alerts for the maintenance team to schedule adequate corrective actions, such as the replacement of the degraded component. A new EHA model-based fault detection and identification (FDI) method is proposed; it is based on deterministic and heuristic solvers able to converge to the actual state of wear of the tested actuator. Three different progressive failure modes were chosen as test cases for the proposed FDI strategy: clogging of the first stage of the flapper-nozzle valve, spool-sleeve friction increase, and jack-cylinder friction increase. A dedicated simulation model was created for the purpose. The results highlighted that the method is adequate in robustness, since EHA malfunctions were identified with a low occurrence of false alarms or missed failures

Closed loop digital control of electrohydraulic systems

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Numerical Simulations

This book will interest researchers, scientists, engineers and graduate students in many disciplines, who make use of mathematical modeling and computer simulation. Although it represents only a small sample of the research activity on numerical simulations, the book will certainly serve as a valuable tool for researchers interested in getting involved in this multidisciplinary field. It will be useful to encourage further experimental and theoretical researches in the above mentioned areas of numerical simulation

Real-Time Inverse Dynamic Deep Neural Network Tracking Control for Delta Robot Based on a COVID-19 Optimization

This paper presents a new technique to design an inverse dynamic model for a delta robot experimental setup to obtain an accurate trajectory. The input/output data were collected using an NI DAQ card where the input is the random angles profile for the three-axis and the output is the corresponding measured torques. The inverse dynamic model was developed based on the deep neural network (NN) and the new COVID-19 optimization to find the optimal initial weights and bias values of the NN model. Due to the system uncertainty and nonlinearity, the inverse dynamic model is not enough to track accurately the preselected profile. So, the PD compensator is used to absorb the error deviation of the end effector. The experimental results show that the proposed inverse dynamic deep NN with PD compensator achieves good performance and high tracking accuracy. The suggested control was examined using two different methods. The spiral path is the first, with a root mean square error of 0.00258 m, while the parabola path is the second, with a root mean square error of 0.00152 m

Modelling of an electro-hydraulic actutor using extended adaptive distance gap statistic approach

The existence of high degree of non-linearity in Electro-Hydraulic Actuator (EHA) system has imposed a challenging task in developing its model so that effective control algorithm can be proposed. In general, there are two modelling approaches available for EHA system, which are the dynamic equation modelling method and the system identification modelling method. Both approaches have disadvantages, where the dynamic equation modelling is hard to apply and some parameters are difficult to obtain, while the system identification method is less accurate when the system’s nature is complicated with wide variety of parameters, nonlinearity and uncertainties. This thesis presents a new modelling procedure of an EHA system by using fuzzy approach. Two sets of input variables are obtained, where the first set of variables are selected based on mathematical modelling of the EHA system. The reduction of input dimension is done by the Principal Component Analysis (PCA) method for the second set of input variables. A new gap statistic with a new within-cluster dispersion calculation is proposed by introducing an adaptive distance norm in distance calculation. The new gap statistic applies Gustafson Kessel (GK) clustering algorithm to obtain the optimal number of cluster of each input. GK clustering algorithm also provides the location and characteristic of every cluster detected. The information of input variables, number of clusters, cluster’s locations and characteristics, and fuzzy rules are used to generate initial Fuzzy Inference System (FIS) with Takagi-Sugeno type. The initial FIS is trained using Adaptive Network Fuzzy Inference System (ANFIS) hybrid training algorithm with an identification data set. The ANFIS EHA model and ANFIS PCA model obtained using proposed modelling procedure, have shown the ability to accurately estimate EHA system’s performance at 99.58% and 99.11% best fitting accuracy compared to conventional linear Autoregressive with External Input (ARX) model at 94.97%. The models validation result on different data sets also suggests high accuracy in ANFIS EHA and ANFIS PCA model compared to ARX model

Modelling of servo-controlled pneumatic drives: a generalised approach to pneumatic modelling and applications in servo-drive design

The primary objective of this research is to develop a general modelling facility for modular pneumatic servo-drives. The component-oriented approach has been adopted as the modelling technique to provide the flexibility of modelling a wide variety of components and the segmentation of the non-linear system to less complex uncoupled component modules. A significant part of the research work has been devoted to identify a series of component modules of the single axis linear pneumatic servomechanism with standardised linking variables. The mathematical models have been implemented in a simulation software which produces time domain responses for design evaluation purposes. Alternative components for different servomechanism design were modelled as mutually exclusive modules which could be selected for assembly as if they were real physical entities. The philosophy of the approach was validated by tests on prototype servo-drives with matching components. Design analysis could be performed by simulating and comparing the performance of alternative system structures. [Continues.

Proportional electro-hydraulic valves: from analogue to digital control

Proportional electro-hydraulic valves are ubiquitous as flow actuators in hydraulic systems. Flow regulation is the result of the accurate positioning of a spool driven by a solenoid and a position sensor, usually a Linear Variable Differential Transformer. The overall control consists of two hierarchical loops: the inner loop is the solenoid current regulator with a closed-loop bandwidth close to 1 kHz. A model-based digital regulator of this kind has been presented elsewhere: requirements and performance are here reminded. The outer loop is a position tracking control, in charge of an accurate positioning of the spool with respect to the valve openings. The paper addresses the outer loop and concentrates on the conversion of an existing industrial analogue controller into a digital one. The analogue controller is a nonlinear proportional, integrative and derivative controller including a second-order derivative, and is capable of recovering a dead-band hysteresis. The digital conversion provides the necessary position derivatives through a state predictor, in order to withstand the 5-kHz Nyquist limit of the power supplier. As such it departs from traditional conversions dating back to more than ten years ago. The digital control law is fed by the state predictions and repeats the analogue control law with some improvements. Preliminary experiments prove that the conversion repeats and improves analogue performance. Some flaws of the resulting digital controller are outlined and discussed in view of a model-based conversion.

Proportional electro-hydraulic valves: from analogue to digital control

Proportional electro-hydraulic valves are ubiquitous as flow actuators in hydraulic systems. Flow regulation is the result of the accurate positioning of a spool driven by a solenoid and a position sensor, usually a Linear Variable Differential Transformer. The overall control consists of two hierarchical loops: the inner loop is the solenoid current regulator with a closed-loop bandwidth close to 1 kHz. A model-based digital regulator of this kind has been presented elsewhere: requirements and performance are here reminded. The outer loop is a position tracking control, in charge of an accurate positioning of the spool with respect to the valve openings. The paper addresses the outer loop and concentrates on the conversion of an existing industrial analogue controller into a digital one. The analogue controller is a nonlinear proportional, integrative and derivative controller including a second-order derivative, and is capable of recovering a dead-band hysteresis. The digital conversion provides the necessary position derivatives through a state predictor, in order to withstand the 5-kHz Nyquist limit of the power supplier. As such it departs from traditional conversions dating back to more than ten years ago. The digital control law is fed by the state predictions and repeats the analogue control law with some improvements. Preliminary experiments prove that the conversion repeats and improves analogue performance. Some flaws of the resulting digital controller are outlined and discussed in view of a model-based conversion.