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Gripping Force Modeling of a Variable Inclined Air Pillow Soft Pneumatic Actuator
Soft pneumatic actuators grasping tasks is one of the essential rules in robot manipulation methods. The grasping forces can be adapted to handle delicate and hard objects without leaving any damages on the object surfaces. This paper investigates the influence of the inclination angle of the soft pneumatic actuator (SPA) on its gripping force at its end tip. A range of inclination angles for SPA is analyzed using Finite Element Analysis (FEA) to estimate the gripping force at the end tip regarding SPA inner faces pressure. FEA study is conducted based on Hyperelastic material modeling
Two-Degree of Freedom Proportional Integral Derivative (2-DOF PID) Controller for Robotic Infusion Stand
Infusion Stand is one of the medical supportive tools in the field of biomedical that assist in holding and carrying medications to patients via intravenous injections. Mobilization of Infusion Stand from a place to another place is necessary not only for the patients itself but also for the nurses. Therefore, this leads to not only uneasiness but also inconvenience for both parties. Therefore, to improve the existing situation and current Infusion Stand in the market, a proposal to design and implement a prototypic Robotic Infusion Stand is submitted. In this paper, 2-Degree of Freedom
Tactile sensing biohybrid soft E-skin based on bioimpedance using aloe vera pulp tissues
Soft and flexible E-skin advances are a subset of soft robotics field where the soft morphology of human skin is mimicked. The number of prototypes that conformed the use of biological tissues within the structure of soft robots—to develop “Biohybrid Soft Robots”—has increased in the last decade. However, no research was conducted to realize Biohybrid E-skin. In this paper, a novel biohybrid E-skin that provides tactile sensing is developed. The biohybrid E-skin highly mimics the human skin softness and morphology and can sense forces as low as 0.01 newton. The tactile sensing feature is
Robust Path Tracking of Mobile Robot Using Fractional Order PID Controller
This paper represents the control of the Pioneer-3 Mobile Robot as a complex non-linear system which provides an object for research nonlinear system kinematics and dynamics analysis. In this paper, the system modeling and simulation is divided into two main parts. The first part is the modeling and simulation using MATLAB and the second part is the whole mechanical design and its characteristics as a function of the motor speed and the torque depending on the system using Virtual Robot Environment Program (V-REP). The study uses Proportional–Integral–Derivative (PID) and Fractional Order PID
Memristive Bio-Impedance Modeling of Fruits and Vegetables
Recent works show that the plants can exhibit nonlinear memristive behavior when excited with low-frequency signals. However, in the literature, only linear bio-impedance models are extensively considered to model the electrical properties of biological tissues without acknowledging the nonlinear behavior. In this paper, we show with experiments, for the first time, the pinched hysteresis behavior in seven fruits and vegetables including tomato, orange, lemon, aubergine, and kiwi which exhibit single pinch-off point, and others such as carrot and cucumber exhibit double pinch-off points (i.e
Implementation and analysis of tunable fractional-order band-pass filter of order 2α
This paper proposes a new design of a 2α-order fractional-order band-pass filter with tunability feature. The proposed filter is approximated with the Continued Fraction Expansion and Matsuda second-order approximations. The realized filter transfer function is based on the Inverse Follow the Leader Feedback configuration, with Operational Transconductance Amplifiers as active elements. As a result, the order of the proposed filter can be adjusted by changing a single parameter, which is the bias current Ibias. A comparison with the previous works is performed, showing the advantage of the
Path Planning Control for 3-Omni Fighting Robot Using PID and Fuzzy Logic Controller
This paper addresses a comparison between some control methods of three Omni wheels firefighting robot due to the variety of maneuverability. To achieve path planning for firefighting robot to reach a specific point with the shortest path, a kinematics model of omni wheel robot is applied with some control algorithms based on PID controller, Fuzzy logic controller and self-tuned PID using fuzzy logic techniques. Hardware prototype has been tested to validate the simulation results. © 2020, Springer Nature Switzerland AG.
Design and Implementation of a Ball and Beam PID Control System Based on Metaheuristic Techniques
The paper introduces a comparative analysis between three meta-heuristic techniques in the optimization of Proportional-Integral-Derivative (PID) controller for a cascaded control of a ball and beam system. The meta-heuristic techniques presented in this study are Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) and Bat Algorithm Optimization (BAO). The model uses a DC motor with encoder to move the beam and a camera as a feedback for the ball position on the beam. The control theory of the system depends on two loops; the first (inner) loop is the DC motor for position control
PID Controller for 2-DOFs Twin Rotor MIMO System Tuned with Particle Swarm Optimization
This paper presents the modelling and control of a 2-DOFs Twin rotor multi input multi output (MIMO) system which is a laboratory setup resembling the dynamics of a helicopter. In this paper, the system modelling process is done using the common conventional mathematical model based on Euler-Lagrange method. The transfer functions of the model are used in the different tuning methods to reach the optimal PID gain values. The study uses conventional Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) controllers to obtain a robust controller for the system. Particle Swarm
Modeling of Nonlinear Enhanced Air Levitation System using NARX Neural Networks
the proposed paper aims to design and model an air levitation system, which is a highly nonlinear system because of its fast dynamics and low damping. The system is trained using a Nonlinear Autoregressive model with exogenous input (NARX model). An enhanced height measurement system, modified setup, and several training techniques have been used to overcome the restrictions that the non-linearity of the system imposes in the literature. The system mathematical model has been illustrated, followed by an identified model using NARX model trained on several input-output data from the physical
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