5,349 research outputs found

    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

    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

    Intelligent active force control of a three-link manipulator using fuzzy logic

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    The paper presents a novel approach to estimate the inertia matrix of a robot arm using a fuzzy logic (FL) mechanism in order to trigger the active force control (AFC) strategy. A comprehensive study is performed on a rigid three-link manipulator subjected to a number of external disturbances. The robustness and effectiveness of the proposed control scheme are investigated considering the trajectory track performance of the robotic arm taking into account the application of external disturbances and that the arm is commanded to describe a reference trajectory given a number of initial and operating conditions. The results show that the FL mechanism used in the study successfully computes appropriate estimated inertia matrix value to execute the control action. The proposed scheme exhibits a high degree of robustness and accuracy as the track error is bounded within an acceptable range of value even under the influence of the introduced disturbances

    Experiments in identification and control of flexible-link manipulators

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    Interest in the study of flexible-link manipulators for space-based applications has risen strongly in recent years. Moreover, numerous experimental results have appeared for the various problems in the modeling, identification and control of such systems. Nevertheless, relatively little literature has appeared involving laboratory verification of tuning controllers for certain types of realistic flexible-link manipulators. Specifically flexible-link manipulators which are required to maintain endpoint accuracy while manipulating loads that are possibly unknown and varying as they undergo disturbance effects from the environment and workspace. Endpoint position control of flexible-link manipulators in these areas are discussed, with laboratory setups consisting of one and two-link manipulators

    A discrete decentralized variable structure robotic controller

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    A decentralized trajectory controller for robotic manipulators is designed and tested using a multiprocessor architecture and a PUMA 560 robot arm. The controller is made up of a nominal model-based component and a correction component based on a variable structure suction control approach. The second control component is designed using bounds on the difference between the used and actual values of the model parameters. Since the continuous manipulator system is digitally controlled along a trajectory, a discretized equivalent model of the manipulator is used to derive the controller. The motivation for decentralized control is that the derived algorithms can be executed in parallel using a distributed, relatively inexpensive, architecture where each joint is assigned a microprocessor. Nonlinear interaction and coupling between joints is treated as a disturbance torque that is estimated and compensated for

    Robust control of geared and direct-drive robotic manipulators under parameter and model uncertainties

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    Thesis (M.S.) University of Alaska Fairbanks, 2005The major contribution of this thesis is the design and evaluation of a chattering-free sliding mode controller (SMC), which is a novel application for 2 degree-of-freedom (DOF) planar robot arms exposed to load variations. The performance of the SMC is evaluated in comparison to a proportional-derivative-plus (PD+) controller, as an example of nonlinear model-based controllers, as well as classical linear controllers, such as proportional-derivative (PD) and proportional-integral-derivative (PID). The performance of all four methods has been tested via realistic and detailed simulation models developed for both geared and direct-drive type 2-DOF planar robot arms. The model used in simulations reflects the dynamics of the arm, as well as the actuator dynamics and pulse width modulation (PWM) switching of the power converters. Simulations are performed under unknown load variations for both step and sinusoidal type reference joint trajectories. The results demonstrate that the chattering-free SMC provides increased accuracy and robustness than that of the other controllers and requires no prior knowledge of the system dynamic model and the load variation that the end-effector is subjected to. The results obtained could be extended to the control of a variety of geared and direct-drive type robotic configurations.Introduction -- Modeling of 2-DOF planar elbow manipulator -- Control of 2-DOF planar elbow manipulator -- Simulation results -- Conclusions and future work -- References -- Appendix
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