An observer-based type-3 fuzzy control for non-holonomic wheeled robots

Non-holonomic wheeled robots (NWR) comprise a type of robotic system; they use wheels for movement and offer several advantages over other types. They are efficient, highly, and maneuverable, making them ideal for factory automation, logistics, transportation, and healthcare. The control of this type of robot is complicated, due to the complexity of modeling, asymmetrical non-holonomic constraints, and unknown perturbations in various applications. Therefore, in this study, a novel type-3 (T3) fuzzy logic system (FLS)-based controller is developed for NWRs. T3-FLSs are employed for modeling, and the modeling errors are considered in stability analysis based on the symmetric Lyapunov function. An observer is designed to detect the error, and its effect is eliminated by a developed terminal sliding mode controller (SMC). The designed technique is used to control a case-study NWR, and the results demonstrate the good accuracy of the developed scheme under non-holonomic constraints, unknown dynamics, and nonlinear disturbances

A fault-hiding approach for the switching quasi-LPV fault-tolerant control of a four-wheeled omnidirectional mobile robot

This paper proposes a reference model approach for the trajectory tracking of a four-wheeled omnidirectional mobile robot. In particular, the error model is brought to a quasi-linear-parameter-varying (LPV) form suitable for designing an error-feedback controller. It is shown that, if polytopic techniques are used to reduce the number of constraints from infinite to finite, a solution within the standard LPV framework could not exist due to a singularity that appears in the possible values of the input matrix. Adding a switching component to the controller allows solving this problem. Moreover, a switching LPV virtual actuator is added to the control loop in order to obtain fault tolerance within the fault-hiding paradigm, keeping the stability and some desired performances under the effect of actuator faults without the need of retuning the nominal controller. The effectiveness of the proposed approach is shown and proved through simulation and experimental results.This work has been funded by the Spanish MINECO through the project CYCYT SHERECS (ref. DPI2011-26243), by the European Commission through contract i-Sense (ref. FP7-ICT-2009-6-270428), by AGAUR through the contracts FI-DGR 2013 (ref. 2013FIB00218) and FI-DGR 2014 (ref. 2014FI B1 00172) and by the DGR of Generalitat de Catalunya (SAC group Ref. 2014/SGR/374).Peer Reviewe

Comprehensive review on controller for leader-follower robotic system

985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies

PID-based with Odometry for Trajectory Tracking Control on Four-wheel Omnidirectional Covid-19 Aromatherapy Robot

Inhalation therapy is one of the most popular treatments for many pulmonary conditions. The proposed Covid-19 aromatherapy robot is a type of Unmanned Ground Vehicle (UGV) mobile robot that delivers therapeutic vaporized essential oils or drugs needed to prevent or treat Covid-19 infections. It uses four omnidirectional wheels with a controlled speed to possibly move in all directions according to its trajectory. All motors for straight, left, or right directions need to be controlled, or the robot will be off-target. The paper presents omnidirectional four-wheeled robot trajectory tracking control based on PID and odometry. The odometry was used to obtain the robot's position and orientation, creating the global map. PID-based controls are used for three purposes: motor speed control, heading control, and position control. The omnidirectional robot had successfully controlled the movement of its four wheels at low speed on the trajectory tracking with a performance criterion value of 0.1 for the IAEH, 4.0 for MAEH, 0.01 for RMSEH, 0.00 for RMSEXY, and 0.06 for REBS. According to the experiment results, the robot's linear velocity error rate is 2%, with an average test value of 1.3 percent. The robot heading effective error value on all trajectories is 0.6%. The robot's direction can be monitored and be maintained at the planned trajectory. Doi: 10.28991/esj-2021-SPER-13 Full Text: PD

A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Feasible, Robust and Reliable Automation and Control for Autonomous Systems

The Special Issue book focuses on highlighting current research and developments in the automation and control field for autonomous systems as well as showcasing state-of-the-art control strategy approaches for autonomous platforms. The book is co-edited by distinguished international control system experts currently based in Sweden, the United States of America, and the United Kingdom, with contributions from reputable researchers from China, Austria, France, the United States of America, Poland, and Hungary, among many others. The editors believe the ten articles published within this Special Issue will be highly appealing to control-systems-related researchers in applications typified in the fields of ground, aerial, maritime vehicles, and robotics as well as industrial audiences

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Cooperative Object Transport in Multi-robot Systems:A Review of the State-of-the-Art

In recent years, there has been a growing interest in designing multi-robot systems (hereafter MRSs) to provide cost effective, fault-tolerant and reliable solutions to a variety of automated applications. Here, we review recent advancements in MRSs specifically designed for cooperative object transport, which requires the members of MRSs to coordinate their actions to transport objects from a starting position to a final destination. To achieve cooperative object transport, a wide range of transport, coordination and control strategies have been proposed. Our goal is to provide a comprehensive summary for this relatively heterogeneous and fast-growing body of scientific literature. While distilling the information, we purposefully avoid using hierarchical dichotomies, which have been traditionally used in the field of MRSs. Instead, we employ a coarse-grain approach by classifying each study based on the transport strategy used; pushing-only, grasping and caging. We identify key design constraints that may be shared among these studies despite considerable differences in their design methods. In the end, we discuss several open challenges and possible directions for future work to improve the performance of the current MRSs. Overall, we hope to increase the visibility and accessibility of the excellent studies in the field and provide a framework that helps the reader to navigate through them more effectivelypublishersversionPeer reviewe

Slip Modelling, Estimation and Control of Omnidirectional Wheeled Mobile Robots with Powered Caster Wheels

Ph.DDOCTOR OF PHILOSOPH

Robust Model Predictive Control for Linear Parameter Varying Systems along with Exploration of its Application in Medical Mobile Robots

This thesis seeks to develop a robust model predictive controller (MPC) for Linear Parameter Varying (LPV) systems. LPV models based on input-output display are employed. We aim to improve robust MPC methods for LPV systems with an input-output display. This improvement will be examined from two perspectives. First, the system must be stable in conditions of uncertainty (in signal scheduling or due to disturbance) and perform well in both tracking and regulation problems. Secondly, the proposed method should be practical, i.e., it should have a reasonable computational load and not be conservative. Firstly, an interpolation approach is utilized to minimize the conservativeness of the MPC. The controller is calculated as a linear combination of a set of offline predefined control laws. The coefficients of these offline controllers are derived from a real-time optimization problem. The control gains are determined to ensure stability and increase the terminal set. Secondly, in order to test the system's robustness to external disturbances, a free control move was added to the control law. Also, a Recurrent Neural Network (RNN) algorithm is applied for online optimization, showing that this optimization method has better speed and accuracy than traditional algorithms. The proposed controller was compared with two methods (robust MPC and MPC with LPV model based on input-output) in reference tracking and disturbance rejection scenarios. It was shown that the proposed method works well in both parts. However, two other methods could not deal with the disturbance. Thirdly, a support vector machine was introduced to identify the input-output LPV model to estimate the output. The estimated model was compared with the actual nonlinear system outputs, and the identification was shown to be effective. As a consequence, the controller can accurately follow the reference. Finally, an interpolation-based MPC with free control moves is implemented for a wheeled mobile robot in a hospital setting, where an RNN solves the online optimization problem. The controller was compared with a robust MPC and MPC-LPV in reference tracking, disturbance rejection, online computational load, and region of attraction. The results indicate that our proposed method surpasses and can navigate quickly and reliably while avoiding obstacles