4,798 research outputs found

    TIP trajectory tracking of flexible-joint manipulators

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    In most robot applications, the control of the manipulator’s end-effector along a specified desired trajectory is the main concern. In these applications, the end-effector (tip) of the manipulator is required to follow a given trajectory. Several methods have been so far proposed for the motion control of robot manipulators. However, most of these control methods ignore either joint friction or joint elasticity which can be caused by the transmission systems (e.g. belts and gearboxes). This study aims at development of a comprehensive control strategy for the tip-trajectory tracking of flexible-joint robot manipulators. While the proposed control strategy takes into account the effect of the friction and the elasticity in the joints, it also provides a highly accurate motion for the manipulator’s end-effector. During this study several approaches have been developed, implemented and verified experimentally/numerically for the tip trajectory tracking of robot manipulators. To compensate for the elasticity of the joints two methods have been proposed; they are a composite controller whose design is based on the singular perturbation theory and integral manifold concept, and a swarm controller which is a novel biologically-inspired controller and its concept is inspired by the movement of real biological systems such as flocks of birds and schools of fishes. To compensate for the friction in the joints two new approaches have been also introduced. They are a composite compensation strategy which consists of the non-linear dynamic LuGre model and a Proportional-Derivative (PD) compensator, and a novel friction compensation method whose design is based on the Work-Energy principle. Each of these proposed controllers has some advantages and drawbacks, and hence, depending on the application of the robot manipulator, they can be employed. For instance, the Work-Energy method has a simpler form than the LuGre-PD compensator and can be easily implemented in industrial applications, yet it provides less accuracy in friction compensation. In addition to design and develop new controllers for flexible-joint manipulators, another contribution of this work lays in the experimental verification of the proposed control strategies. For this purpose, experimental setups of a two-rigid-link flexible-joint and a single-rigid-link flexible-joint manipulators have been employed. The proposed controllers have been experimentally tested for different trajectories, velocities and several flexibilities of the joints. This ensures that the controllers are able to perform effectively at different trajectories and speeds. Besides developing control strategies for the flexible-joint manipulators, dynamic modeling and vibration suppression of flexible-link manipulators are other parts of this study. To derive dynamic equations for the flexible-link flexible-joint manipulators, the Lagrange method is used. The simulation results from Lagrange method are then confirmed by the finite element analysis (FEA) for different trajectories. To suppress the vibration of flexible manipulators during the manoeuvre, a collocated sensor-actuator is utilized, and a proportional control method is employed to adjust the voltage applied to the piezoelectric actuator. Based on the controllability of the states and using FEA, the optimum location of the piezoelectric along the manipulator is found. The effect of the controller’s gain and the delay between the input and output of the controller are also analyzed through a stability analysis

    Dynamic Modeling and Simulation of a Rotating Single Link Flexible Robotic Manipulator Subject to Quick Stops

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    Single link robotic manipulators are extensively used in industry and research operations. The main design requirement of such manipulators is to minimize link dynamic deflection and its active end vibrations, and obtain high position accuracy during its high speed motion. To achieve these requirements, accurate mathematical modeling and simulation of the initial design, to increase system stability and precision and to obtain very small amplitudes of vibration, should be considered. In this paper the modeling of such robotic arm with a rigid guide and a flexible extensible link subject to quick stops after each complete revolution is considered and its dynamical behavior analyzed. The extensible link which rotates with constant angular velocity has one end constrained to a predefined trajectory. The constrained trajectory allows trajectory control and obstacle avoidance for the active end of the robotic arm. The dynamic evolution of the system is investigated and the flexural response of the flexible link analyzed under the combined effect of clearance and flexibility.

    Robust tuning of robot control systems

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    The computed torque control problem is examined for a robot arm with flexible, geared, joint drive systems which are typical in many industrial robots. The standard computed torque algorithm is not directly applicable to this class of manipulators because of the dynamics introduced by the joint drive system. The proposed approach to computed torque control combines a computed torque algorithm with torque controller at each joint. Three such control schemes are proposed. The first scheme uses the joint torque control system currently implemented on the robot arm and a novel form of the computed torque algorithm. The other two use the standard computed torque algorithm and a novel model following torque control system based on model following techniques. Standard tasks and performance indices are used to evaluate the performance of the controllers. Both numerical simulations and experiments are used in evaluation. The study shows that all three proposed systems lead to improved tracking performance over a conventional PD controller

    Hybrid iterative learning control of a flexible manipulator

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    This paper presents an investigation into the development of a hybrid control scheme with iterative learning for input tracking and end-point vibration suppression of a flexible manipulator system. The dynamic model of the system is derived using the finite element method. Initially, a collocated proportional-derivative (PD) controller using hub angle and hub velocity feedback is developed for control of rigid-body motion of the system. This is then extended to incorporate a non-collocated proportional-integral-derivative (PID) controller with iterative learning for control of vibration of the system. Simulation results of the response of the manipulator with the controllers are presented in the time and frequency domains. The performance of the hybrid iterative learning control scheme is assessed in terms of input tracking and level of vibration reduction in comparison to a conventionally designed PD-PID control scheme. The effectiveness of the control scheme in handling various payloads is also studied

    Experimental comparison of parameter estimation methods in adaptive robot control

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    In the literature on adaptive robot control a large variety of parameter estimation methods have been proposed, ranging from tracking-error-driven gradient methods to combined tracking- and prediction-error-driven least-squares type adaptation methods. This paper presents experimental data from a comparative study between these adaptation methods, performed on a two-degrees-of-freedom robot manipulator. Our results show that the prediction error concept is sensitive to unavoidable model uncertainties. We also demonstrate empirically the fast convergence properties of least-squares adaptation relative to gradient approaches. However, in view of the noise sensitivity of the least-squares method, the marginal performance benefits, and the computational burden, we (cautiously) conclude that the tracking-error driven gradient method is preferred for parameter adaptation in robotic applications

    Control of free-flying space robot manipulator systems

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    New control techniques for self contained, autonomous free flying space robots were developed and tested experimentally. Free flying robots are envisioned as a key element of any successful long term presence in space. These robots must be capable of performing the assembly, maintenance, and inspection, and repair tasks that currently require human extravehicular activity (EVA). A set of research projects were developed and carried out using lab models of satellite robots and a flexible manipulator. The second generation space robot models use air cushion vehicle (ACV) technology to simulate in 2-D the drag free, zero g conditions of space. The current work is divided into 5 major projects: Global Navigation and Control of a Free Floating Robot, Cooperative Manipulation from a Free Flying Robot, Multiple Robot Cooperation, Thrusterless Robotic Locomotion, and Dynamic Payload Manipulation. These projects are examined in detail

    Dynamic modeling, property investigation, and adaptive controller design of serial robotic manipulators modeled with structural compliance

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    Research results on general serial robotic manipulators modeled with structural compliances are presented. Two compliant manipulator modeling approaches, distributed and lumped parameter models, are used in this study. System dynamic equations for both compliant models are derived by using the first and second order influence coefficients. Also, the properties of compliant manipulator system dynamics are investigated. One of the properties, which is defined as inaccessibility of vibratory modes, is shown to display a distinct character associated with compliant manipulators. This property indicates the impact of robot geometry on the control of structural oscillations. Example studies are provided to illustrate the physical interpretation of inaccessibility of vibratory modes. Two types of controllers are designed for compliant manipulators modeled by either lumped or distributed parameter techniques. In order to maintain the generality of the results, neither linearization is introduced. Example simulations are given to demonstrate the controller performance. The second type controller is also built for general serial robot arms and is adaptive in nature which can estimate uncertain payload parameters on-line and simultaneously maintain trajectory tracking properties. The relation between manipulator motion tracking capability and convergence of parameter estimation properties is discussed through example case studies. The effect of control input update delays on adaptive controller performance is also studied

    Control of flexible joint robotic manipulator using tuning functions design

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    The goal of this thesis is to design the controller for a single arm manipulator having a flexible joint for the tracking problem in two different cases. A controller is designed for a deterministic case wherein the plant parameters are assumed to be known while another is designed for an adaptive case where all the plant parameters are assumed to be unknown. In general the tracking problem is; given a smooth reference trajectory, the end effector has to track the reference while maintaining the stability. It is assumed that only the output of the manipulator, which is the link angle, is available for measurement. Also without loss of generality, the fast dynamics, that is the dynamics of the driver side of the system are neglected for the sake of simplicity; In the first case, the design procedure adopted is called observer backstepping. Since the states of the system are unavailable for measurement, an observer is designed that estimates the system states. These estimates are fed to the controller which in turn produces the control input to the system; The second case employs a design procedure called tuning functions design. In this case, since the plant parameters are unknown, the observer designed in case one cannot be used for determining the state estimates. For this purpose, parameter update laws and filters are designed for estimation of plant parameters. The filters employed are k-filters. The k-filters and the parameter update laws are given as input to the controller, which generates the control input to the system; For both cases, the mathematical models are simulated using Matlab/Simulink, and the results are verified
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