Online Fault Detection Approach of Unpredictable Inputs: Application to Handwriting System

Many investigators are interested in improving the control strategies of hand prosthesis to make it functional and more convenient to use. The most used control approach is based on the forearm muscles activities, named ‘ElectroMyoGraphic’ (EMG) signal. However, these biological signals are very sensitive to many disturbances and are generally unpredictable in time, type, and level. This leads to inaccurate identification of user intent and threatens the prosthesis control reliability. This paper proposed a real-time fault detection and localization approach applied to handwriting device on the plane. This approach allows connecting inputs (IEMG signals)/outputs (pen tip coordinates) data as a parametric model for Multi-Inputs Multi-Outputs (MIMO) system. The proposed approach is considered as a model-independent abrupt or intermittent fault detection method and as an alternative solution to the unpredictable input observer based techniques, without any observability requirements. This approach allows detecting, in real time, several types of faults in one or two inputs signals and in the same or different instants. Our study is appropriate for many rapidly expanding fields and practices, including biomedical engineering, robotics, and biofeedback therapy or even military applications

Automation of a Hybrid Control for Electrohydraulic Servo-Actuators with Residual Dynamics

In this paper, a hybrid position/force controller for electrohydraulic servo-actuators is designed in the presence of residual dynamics. The purpose is to apply a cycle of movement that is mostly used in industrial fatigue test applications, which consists in imposing a specified force on a flexible load after a movement to some position. This cycle can be repeated several times with different magnitudes and frequencies of force and position trajectories. Some damages could occur at switching times, especially in the presence of some residual dynamics. To avoid any damages at switching times, a force trajectory generator is designed. Then, our contribution defines a method to automatically generate the switching signal in order to commute between two controllers with any abrupt change of state. To show the effectiveness of the proposed approach, several simulation tests are carried out on the electrohydraulic system

Systematic Literature Review and Benchmarking for Photovoltaic MPPT Techniques

There are a variety of maximum power point tracking (MPPT) algorithms for improving the energy efficiency of solar photovoltaic (PV) systems. The mode of implementation (digital or analog), design simplicity, sensor requirements, convergence speed, range of efficacy, and hardware costs are the primary distinctions between these algorithms. Selecting an appropriate algorithm is critical for users, as it influences the electrical efficiency of PV systems and lowers costs by reducing the number of solar panels required to achieve the desired output. This research is relevant since PV systems are an alternative and sustainable solution for energy production. The main aim of this paper is to review the current advances in MPPT algorithms. This paper first undertakes a systematic literature review (SLR) of various MPPT algorithms, highlighting their strengths and weaknesses; a detailed summary of the related reviews on this topic is then presented. Next, quantitative and qualitative comparisons of the most popular and efficient MPPT methods are performed. This comparison is based on simulation results to provide efficient benchmarking of MPPT algorithms. This benchmarking validates that intelligent MPPTs, such as artificial neural network (ANN), fuzzy logic control (FLC), and adaptive neuro-fuzzy inference system (ANFIS), outperform other approaches in tracking the MPPT of PV systems. Specifically, the ANN technique had the highest efficiency of 98.6%, while the ANFIS and FLC methods were close behind with efficiencies of 98.34% and 98.29%, respectively. Therefore, it is recommended that these intelligent MPPT techniques be considered for use in future photovoltaic systems to achieve optimal power output and maximize energy production