The Use of a Statistical Filter and Metaheuristics to Model and Control The DC Motor of the Mobile Robot Used on NXP Cup

2018 ◽  
Vol 1 (1) ◽  
pp. 11
Author(s):  
Artur Ferreira Moreira ◽  
Andressa Silva Fernandes ◽  
José Ailton Batista Silva ◽  
Alan Vinicius de Araújo Batista ◽  
Pedro Henrique Almeida Miranda
Keyword(s):  
Mobile Robot ◽  
Autonomous Navigation ◽  
Pid Controller ◽  
Dc Motor ◽  
Level Control ◽  
Hybrid Approaches ◽  
Research Fields ◽  
Internal States ◽  
High Level ◽  
And Control

Over the past decades, Robotics is one of the research fields with more advances. From methodologies of low-level control, used on actuators, to high-level control, used with artificial intelligence approaches. One of the most interesting problem that a mobile robot faces is autonomous navigation. For the robot be able to navigate on the environment autonomously, it have to make use of sensory input from one or more sensors that are used to perceive the robot surroundings as well as sensors that measure internal states of the robot. One of the most used control theory methodology is the proportional-integrative-derivative (PID) controller, where its parameters are estimated through a variety of ways, from raw mathematical modeling to the application of hybrid approaches that uses both a mathematical model and metaheuristics such as genetic algorithms. This paper aims to estimate the parameters of the direct current motor through a Kalman filter and use those to estimate the PID parameters to control the DC motor by the usage of a genetic algorithm. Results shows that the derived PID controller is quite efficient on the control of the DC motor used, thus validating the methodology.

scholarly journals Robust Tracking Controller for a DC/DC Buck-Boost Converter–Inverter–DC Motor System

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2500 ◽  
Author(s):  
Eduardo Hernández-Márquez ◽  
Carlos Avila-Rea ◽  
José García-Sánchez ◽  
Ramón Silva-Ortigoza ◽  
Gilberto Silva-Ortigoza ◽  
...  
Keyword(s):  
Motor System ◽  
Dc Motor ◽  
Boost Converter ◽  
Differential Flatness ◽  
Robust Tracking ◽  
Level Control ◽  
Tracking Controller ◽  
The One ◽  
High Level ◽  
Better Than

This paper has two aims. The first is to develop a robust hierarchical tracking controller for the DC/DC Buck-Boost–inverter–DC motor system. This controller considers a high level control for the inverter–DC motor subsystems and a low level control for the DC/DC Buck-Boost converter subsystem. Such controls solve the tracking task associated with the angular velocity of the motor shaft and the output voltage of the converter, respectively, via the differential flatness approach. The second aim is to present a comparison of the robust hierarchical controller to a passive controller. This, with the purpose of showing that performance achieved with the hierarchical controller proposed in this paper, is better than the one achieved with the passive controller. Both controllers are experimentally implemented on a prototype of the DC/DC Buck-Boost–inverter–DC motor system by using Matlab-Simulink along with the DS1104 board from dSPACE. According to experimental results, the proposal in the present paper achieves a better performance than the passive controller.

Powered Ankle-Foot Prostheses: A Survey on Sensing Systems and Control Strategies

2019 ◽  
Author(s):  
Erik Chumacero-Polanco ◽  
James Yang
Keyword(s):  
Control Strategies ◽  
Level Control ◽  
Low Level ◽  
Kinetic Information ◽  
Sensing Systems ◽  
Systems And Control ◽  
Finite State ◽  
High Level ◽  
And Control

Abstract People who have suffered a transtibial amputation show diminished ambulation and impaired quality of life. Powered ankle foot prostheses (AFP) are used to recover some mobility of transtibial amputees (TTAs). Powered AFP is an emerging technology that has great potential to improve the quality of life of TTAs with important avenues for research and development in different fields. This paper presents a survey on sensing systems and control strategies applied to powered AFPs. Sensing kinematic and kinetic information in powered AFPs is critical for control. Ankle angle position is commonly obtained via potentiometers and encoders directly installed on the joint, velocities can be estimated using numerical differentiators, and accelerations are normally obtained via inertial measurement units (IMUs). On the other hand, kinetic information is usually obtained via strain gauges and torque sensors. On the other hand, control strategies are classified as high- and low-level control. The high-level control sets the torque or position references based on pattern generators, user’s intent of motion recognition, or finite-state machine. The low-level control usually consists of linear controllers that drive the ankle’s joint position, velocity, or torque to follow an imposed reference signal. The most widely used control strategy is the one based on finite-state machines for the high-level control combined with a proportional-derivative torque control for low-level. Most designs have been experimentally assessed with acceptable results in terms of walking speed. However, some drawbacks related to powered AFP’s weight and autonomy remain to be overcome. Future research should be focused on reducing powered AFP size and weight, increasing energy efficiency, and improving both the high- and the low-level controllers in terms of efficiency and performance.

scholarly journals Conservation law for self-paced movements

2016 ◽  
Vol 113 (31) ◽  
pp. 8831-8836 ◽  
Author(s):  
Dongsung Huh ◽  
Terrence J. Sejnowski
Keyword(s):  
Optimal Control ◽  
Scaling Law ◽  
Control Variable ◽  
Level Control ◽  
Internal Motivation ◽  
Internal States ◽  
Motivation Level ◽  
High Level ◽  
The Brain ◽  
Biological Motor

Optimal control models of biological movements introduce external task factors to specify the pace of movements. Here, we present the dual to the principle of optimality based on a conserved quantity, called “drive,” that represents the influence of internal motivation level on movement pace. Optimal control and drive conservation provide equivalent descriptions for the regularities observed within individual movements. For regularities across movements, drive conservation predicts a previously unidentified scaling law between the overall size and speed of various self-paced hand movements in the absence of any external tasks, which we confirmed with psychophysical experiments. Drive can be interpreted as a high-level control variable that sets the overall pace of movements and may be represented in the brain as the tonic levels of neuromodulators that control the level of internal motivation, thus providing insights into how internal states affect biological motor control.

Mechatronics Engineering on the Example of a Multipurpose Mobile Robot

2009 ◽  
Vol 147-149 ◽  
pp. 61-66 ◽  
Author(s):  
Marek Stania ◽  
Ralf Stetter
Keyword(s):  
Mobile Robot ◽  
Design Process ◽  
Level Control ◽  
Mechatronic System ◽  
Mechatronic Systems ◽  
Mechatronic Design ◽  
Planning And Control ◽  
And Control

This paper presents the patented mechanical concept for steering and level control of a mobile robot equipped with four driving units and the methods that lead to the development of this mechatronic system. The mobile robot exhibits excellent maneuverability and considerable advantages when moving in difficult environments such as rough landscapes. The paper discusses a refined approach to develop mechatronic systems which is based on the well-known V-model. The refined approach allows a conscious planning and control of a mechatronic design process.

Modeling and Robust Low Level Control of an Omnidirectional Mobile Robot

2017 ◽  
Vol 139 (4) ◽  
Author(s):  
Ramon Comasolivas ◽  
Joseba Quevedo ◽  
Teresa Escobet ◽  
Antoni Escobet ◽  
Juli Romera
Keyword(s):  
Mobile Robot ◽  
Pi Controller ◽  
Control Technique ◽  
Level Control ◽  
Parameter Uncertainties ◽  
Control Effort ◽  
Friction Forces ◽  
Low Level ◽  
Stability And Control ◽  
And Control

This paper presents the modeling and robust low-level control design of a redundant mobile robot with four omnidirectional wheels, the iSense Robotic (iSRob) platform, that was designed to test safe control algorithms. iSRob is a multivariable nonlinear system subject to parameter uncertainties mainly due to friction forces. A multilinear model is proposed to approximate the behavior of the system, and the parameters of these models are estimated from closed-loop experimental data applying Gauss–Newton techniques. A robust control technique, quantitative feedback theory (QFT), is applied to design a proportional–integral (PI) controller for robust low-level control of the iSRob system, being this the main contribution of the paper. The designed controller is implemented, tested, and compared with a gain-scheduling PI-controller based on pole assignment. The experimental results show that robust stability and control effort margins against system uncertainties are satisfied and demonstrate better performance than the other controllers used for comparison.

scholarly journals Identification and Speed Control of DC Motor Using Fractional Order PID: Microcontroller

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Magdi M. El-Saadawi ◽  
Eid Abdelbaqi Gouda ◽  
Mostafa A. Elhosseini ◽  
Mohamed Said Essa
Keyword(s):  
Fractional Order ◽  
Pid Control ◽  
Pid Controller ◽  
Dc Motor ◽  
Grey Wolf ◽  
Control Effect ◽  
Grey Wolf Optimization ◽  
And Control ◽  
Fractional Order Pid

This paper uses Fractional-order PID control (FOPID) to control the speed of the DC motor.  FOPID is more flexible and confident in controlling control higher-order systems compared to classical PID. In this work, the FOPID controller tuning is carried out using different methods ranging from classical techniques to most recent heuristic methods are Fractional Grey wolf Optimization and Nelder-Mead. Moreover, parameter estimation of real-world DC motor is carried out experimentally using Matlab/Simulink interfaced to an Arduino Uno board. The feasibility of FOPID is demonstrated through applications to well-known DC motor case study and the estimated DC motor. Based on ISE, ITE, and ISTE performance measures, the proposed approach provide less settling time, rise time and comparable overshoot compared with existing literature approaches. A robustness assessment with differences in the DC motor components is performed. Simulation finding provide validation of the suggested work and the FOPID controller effectiveness as compared to classical PID controller in terms of robustness and control effect.

scholarly journals Development of a Low-Level Control System for the ROV Visor3

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Santiago Rúa ◽  
Rafael E. Vásquez
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Nonlinear Observer ◽  
Navigation Systems ◽  
Level Control ◽  
Remotely Operated Vehicle ◽  
Low Level ◽  
Level Control System ◽  
High Level ◽  
And Control

This paper addresses the development of the simulation of the low-level control system for the underwater remotely operated vehicle Visor3. The 6-DOF mathematical model of Visor3 is presented using two coordinated systems: Earth-fixed and body-fixed frames. The navigation, guidance, and control (NGC) structure is divided into three layers: the high level or the mission planner; the mid-level or the path planner; and the low level formed by the navigation and control systems. The nonlinear model-based observer is developed using the extended Kalman filter (EKF) which uses the linearization of the model to estimate the current state. The behavior of the observer is verified through simulations using Simulink®. An experiment was conducted with a trajectory that describes changes in the x and y and yaw components. To accomplish this task, two algorithms are compared: a multiloop PID and PID with gravity compensation. These controllers and the nonlinear observer are tested using the 6-DOF mathematical model of Visor3. The control and navigation systems are a fundamental part of the low-level control system that will allow Visor3’s operators to take advantage of more advanced vehicle’s capabilities during inspection tasks of port facilities, hydroelectric dams, and oceanographic research.

scholarly journals Brushless DC Motor Modeling Using Bond Graph Method and Control using LabVIEW

1970 ◽  
Vol 5 (1.) ◽  
Author(s):  
Ammar Alsabbagh ◽  
Péter Tamás Szemes ◽  
Abdulkader Baki
Keyword(s):  
Dynamic Model ◽  
Pid Controller ◽  
Dc Motor ◽  
Bond Graph ◽  
Brushless Dc Motor ◽  
Graph Method ◽  
Brushless Dc ◽  
Three Phase ◽  
Labview Program ◽  
And Control

This paper aims to simulate and control a three-phase Brushless DC Motor. Bond Graph method has been used to obtain fast and simple dynamic model. The system has been controlled by classical PID controller. All the paper results were fulfilled using LabVIEW program.

Dynamics and Control of a Novel Active Yaw Stabilizer to Enhance Vehicle Lateral Motion Stability

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
Fengchen Wang ◽  
Yan Chen
Keyword(s):  
Degrees Of Freedom ◽  
Hierarchical Control ◽  
Lateral Force ◽  
Stability Control ◽  
Level Control ◽  
Road Friction ◽  
Dynamics And Control ◽  
High Level ◽  
And Control ◽  
Yaw Moment

In this paper, a novel active yaw stabilizer (AYS) system is proposed for improving vehicle lateral stability control. The introduced AYS, inspired by the recent in-wheel motor (IWM) technology, has two degrees-of-freedom with independent self-rotating and orbiting movements. The dynamic model of the AYS is first developed. The capability of the AYS is then investigated to show its maximum generation of corrective lateral forces and yaw moments, given a limited vehicle space. Utilizing the high-level Lyapunov-based control design and the low-level control allocation design, a hierarchical control architecture is established to integrate the AYS control with active front steering (AFS) and direct yaw moment control (DYC). To demonstrate the advantages of the AYS, generating corrective lateral force and yaw moment without relying on tire–road interaction, double lane change maneuvers are studied on road with various tire–road friction coefficients. Co-simulation results, integrating CarSim® and MATLAB/Simulink®, successfully verify that the vehicle with the assistance of the AYS system has better lateral dynamics stabilizing performance, compared with cases in which only AFS or DYC is applied.

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