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Design and FEA-based Methodology for a Novel 3 Parallel Soft Muscle Actuator
Recently, soft robotics represents a new era of advanced robotics systems. Based on the flexible nature of soft robots, they are more adequate to have safe interaction with humans and handle complex or delicate objects. Due to the nature of soft robotics, there is a crucial need to propose new designs, fabrication, and control systems suitable for the flexibility nature. In this research project, a novel three parallel soft muscle actuator is proposed. The proposed design and analytical models for predicting actuation behavior are based on a set of design parameters. First, the actuator
A Neuro-Fuzzy Based Approach for Energy Consumption and Profit Operation Forecasting
In recent years, the massive growth in the scale of data is being a key factor in the needed data processing approaches. The efficiency of the algorithms of knowledge extraction depends significantly on the quality of the raw data, which can be improved by employing preprocessing techniques. In the field of energy consumption, the forecasting of power cost needed plays a vital role in determining the expected profit. To achieve a forecasting with higher accuracy, it is needed to deal with the large amount of data associated with power plants. It is shown in the literature that the use of
Self-Driving Car Lane-keeping Assist using PID and Pure Pursuit Control
Detection of lane boundaries is the primary role for monitoring an autonomous car's trajectory. Three lane identification methodologies are explored in this paper with experimental illustration: Edge detection, Hough transformation, and Birds eye view. The next step after obtaining the boundary points is to add a regulation rule to effectively trigger the regulation of steering and velocity to the motors. A comparative analysis is made between different steering controllers like PID or by using PID with a pure pursuit controller for the Lane Keeping Assist (LKA) system. A camera that sends
Active Morphing Control of Airfoil At Low Reynolds Number Using Level-Set Method
The active control of flow around an airfoil through morphing is numerically investigated. The lock-in phenomenon was predicted while using a fixed grid. Galerkin/Least-Squares Finite Element Method was used to simulate incompressible flow over an airfoil with leading edge morphing at a Reynolds number, Re = 5000, and angle of attack, α = 6°. The numerical simulation was carried out using the in-house FORTRAN code. The code was validated with the literature by simulating the flow over an oscillating cylinder. The paperwork implemented a locally oscillating surface on the airfoil with a
Modeling and control of 3-omni wheel Robot using PSO optimization and Neural Network
Omni mobile robots are one of the mobile robots that interact with humans in many areas where it is needed to be collaborative and accurate. Committing robotics with artificial intelligence-based controllers became nowadays mandatory for more association of these robots with distinct environments. This paper proposes the distinction of the 3WD Omni Vision feedback model between Simscape and actual information to obtain a surmised model. Study applying some artificial control procedures on this model for path planning and speed control as the artificial neural system and PSO optimization
Direct Power Control of a three-phase PWM-Rectifier based on Petri nets for the selection of Switching States
This article proposes a new simple scheme for direct power control of a PWM rectifier without a switch table and voltage sensor. The selection of the switching state of the converter is based on the transition of a Petri net, using the instantaneous active and reactive power tracking errors and the angular position of the network line voltage estimated as variables of Controller input based on Petri nets. Simulation and experimental results demonstrated better performance and verified the validity of the new command with the Petri nets applied to the bridge rectifier connected to the
All-Dynamic Synchronization of Rotating Fractional-Order Chaotic Systems
This paper proposes generalized controllable strange attractors through dynamic rotation of fractional-order chaotic systems. Dynamic rotation angle enables the generation of multi-scroll and multi-wing attractors from single and double-scroll ones. The rotating systems are integrated with a generalized dynamic switched synchronization scheme. Dynamic control switches determine whether each system plays the role of master or slave. Based on dynamic scaling factors, the master can be one system or a combination of several ones with new strange attractors. The rotating fractional-order systems
Mathematical modeling of Upflow Anaerobic Sludge Blanket reactor in domestic wastewater treatment
This paper introduces a dynamic model to adequately describe an Upflow Anaerobic Sludge Blanket (UASB) reactor. Some available models of a UASB reactor are discussed in order to modify their drawbacks and propose a new improved model with less complexity and more reliability. The developed model is a combination of two recent models introduced in Sweden. According to this model, a UASB rector is divided hydraulically into three compartments with integration of a kinetic model. Simulations are performed to investigate the validity of the developed model which indicates a good agreement with
Drone deep reinforcement learning: A review
Unmanned Aerial Vehicles (UAVs) are increasingly being used in many challenging and diversified applications. These applications belong to the civilian and the military fields. To name a few; infrastructure inspection, traffic patrolling, remote sensing, mapping, surveillance, rescuing humans and animals, environment monitoring, and Intelligence, Surveillance, Target Acquisition, and Reconnaissance (ISTAR) operations. However, the use of UAVs in these applications needs a substantial level of autonomy. In other words, UAVs should have the ability to accomplish planned missions in unexpected
Dynamic behavior of polyurea composites subjected to high strain rate loading
A comprehensive theoretical and experimental investigation is presented of the behavior of polyurea composites subjected to high strain-rate impact loading. The composites under consideration consist of an assembly of steel sections and inserts manufactured from layers of polyurea or polyurea augmented with aluminum layers (AL). A finite element model (FEM) is developed to predict the dynamics of this class of polyurea composites by integrating the dynamics of the solid steel sections with those of polyurea using the Golla-Hughes-Mctavish (GHM) mini-oscillator approach. The predictions of the
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