2,229 research outputs found

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

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    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

    Terminal sliding mode control strategy design for second-order nonlinear system

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    This study mainly focuses on the terminal sliding mode control (TSMC) strategy design, including an adaptive terminal sliding mode control (ATSMC) and an exact-estimator-based terminal sliding mode control (ETSMC) for second-order nonlinear dynamical systems. In the ATSMC system, an adaptive bound estimation for the lump uncertainty is proposed to ensure the system stability. On the other hand, an exact estimator is designed for exact estimating system uncertainties to solve the trouble of chattering phenomena caused by a sign function in ATSMC law in despite of the utilization of a fixed value or an adaptive tuning algorithm for the lumped uncertainty bound. The effectiveness of the proposed control schemes can be verified in numerical simulations.<br /

    Intelligent swarm algorithms for optimizing nonlinear sliding mode controller for robot manipulator

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    This work introduces an accurate and fast approach for optimizing the parameters of robot manipulator controller. The approach of sliding mode control (SMC) was proposed as it documented an effective tool for designing robust controllers for complex high-order linear and nonlinear dynamic systems operating under uncertain conditions. In this work Intelligent particle swarm optimization (PSO) and social spider optimization (SSO) were used for obtaining the best values for the parameters of sliding mode control (SMC) to achieve consistency, stability and robustness. Additional design of integral sliding mode control (ISMC) was implemented to the dynamic system to achieve the high control theory of sliding mode controller. For designing particle swarm optimizer (PSO) and social spider optimization (SSO) processes, mean square error performances index was considered. The effectiveness of the proposed system was tested with six degrees of freedom robot manipulator by using (PUMA) robot. The iteration of SSO and PSO algorithms with mean square error and objective function were obtained, with best fitness for (SSO) =4.4876 -6 and (PSO)=3.4948 -4

    Development of Novel Compound Controllers to Reduce Chattering of Sliding Mode Control

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    The robotics and dynamic systems constantly encountered with disturbances such as micro electro mechanical systems (MEMS) gyroscope under disturbances result in mechanical coupling terms between two axes, friction forces in exoskeleton robot joints, and unmodelled dynamics of robot manipulator. Sliding mode control (SMC) is a robust controller. The main drawback of the sliding mode controller is that it produces high-frequency control signals, which leads to chattering. The research objective is to reduce chattering, improve robustness, and increase trajectory tracking of SMC. In this research, we developed controllers for three different dynamic systems: (i) MEMS, (ii) an Exoskeleton type robot, and (iii) a 2 DOF robot manipulator. We proposed three sliding mode control methods such as robust sliding mode control (RSMC), new sliding mode control (NSMC), and fractional sliding mode control (FSMC). These controllers were applied on MEMS gyroscope, Exoskeleton robot, and robot manipulator. The performance of the three proposed sliding mode controllers was compared with conventional sliding mode control (CSMC). The simulation results verified that FSMC exhibits better performance in chattering reduction, faster convergence, finite-time convergence, robustness, and trajectory tracking compared to RSMC, CSMC, and NSFC. Also, the tracking performance of NSMC was compared with CSMC experimentally, which demonstrated better performance of the NSMC controller

    Synchronizing of Stabilizing Platform Mounted on a Two-Wheeled Robot

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    This paper represents the designing, building, and testing of a self-stabilizing platform mounted on a self-balancing robot. For the self-stabilizing platform, a servo motor is used and for the self-balancing robot, two dc motors are used with an encoder, inertial measurement unit, motor driver, an Arduino UNO microcontroller board. A PID controller is used to control the balancing of the system. The PID controller gains (Kp, Ki, and Kd) were evaluated experimentally. The value of the tilted angle from IMU was fed to the PID controller to control the actuated motors for balancing the system. For the self-stabilizing control part, whenever the robot tilted, it maintained the horizontal position by rotating that much in the opposite direction

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

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    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

    Extended grey wolf optimization–based adaptive fast nonsingular terminal sliding mode control of a robotic manipulator

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    This article proposes a novel hybrid metaheuristic technique based on nonsingular terminal sliding mode controller, time delay estimation method, an extended grey wolf optimization algorithm and adaptive super twisting control law. The fast convergence is assured by nonsingular terminal sliding mode controller owing to its inherent nonlinear property and no prior knowledge of the robot dynamics is required due to time delay estimation. The proposed extended grey wolf optimization algorithm determines an optimal approximation of the inertial matrix of the robot. Moreover, adaptive super twisting control based on the Lyapunov approach overcomes the disturbances and compensate the higher dynamics not achievable by the time delay estimation method. First, the fast nonsingular terminal sliding mode controller relying on time delay estimation is designed and is combined with super twisting control for chattering attenuation. The constant gain matrix of the time delay is determined by the proposed extended grey wolf optimization algorithm. Second, an adaptive law based on Lyapunov stability theorem is designed for improving tracking performance in the presence of uncertainties and disturbances. The novelty of the proposed method lies in the adaptive law where the prior knowledge of parametric uncertainties and disturbances is not needed. Moreover, the constant gain matrix of time delay estimation method is obtained using the proposed algorithm. The control method has been tested in simulation on a 3-degrees of freedom robotic manipulator in trajectory tracking mode in the presence of control disturbances and uncertainties. The results obtained confirmed the effectiveness, robustness and the superior precision of the proposed control method compared to the classical ones

    New Trends in the Control of Robots and Mechatronic Systems

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    In recent years, research into the control of robotic and mechatronic systems has led to a wide variety of advanced paradigms and techniques, which have been extensively analysed and discussed in the scientific literature [...

    Review and Analysis on Main Technology of Exoskeletal Robot System for Upper Limbs Rehabilitation

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    Major function of exoskeletal robot system for upper limbs rehabilitation is to assist patient to carry out upper limbs’ rehabilitation training. Main technology of exoskeletal robot system for upper limbs rehabilitation includes design of mechanical structure of exoskeletal robot, design of control system of exoskeletal robot and implemention of data and information transmission between exoskeletal robot and upper limbs of human body. Currently implemention of data and information transmission rely mainly on methods of acquiring sEMG signal and force feedback. Reviewing and analyzing the specific technical development and deficiency in field of exoskeletal robot system for upper limbs rehabilitation will be important way in improving and upgrading the technology in future
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