394 research outputs found

    Improvement of flight simulator feeling using adaptive fuzzy backlash compensation

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    In this paper we addressed the problem of improving the control of DC motors used for the specific application of a 3 degrees of freedom moving base flight simulator. Indeed the presence of backlash in DC motors gearboxes induces shocks and naturally limits the flight feeling. In this paper, dynamic inversion with Fuzzy Logic is used to design an adaptive backlash compensator. The classification property of fuzzy logic techniques makes them a natural candidate for the rejection of errors induced by the backlash. A tuning algorithm is given for the fuzzy logic parameters, so that the output backlash compensation scheme becomes adaptive. The fuzzy backlash compensator is first validated using a realistic model of the mechanical system and is actually tested on the real flight simulator

    Adaptive neural network control of a robotic manipulator with unknown backlash-like hysteresis

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    This study proposes an adaptive neural network controller for a 3-DOF robotic manipulator that is subject to backlashlike hysteresis and friction. Two neural networks are used to approximate the dynamics and the hysteresis non-linearity. A neural network, which utilises a radial basis function approximates the robot's dynamics. The other neural network, which employs a hyperbolic tangent activation function, is used to approximate the unknown backlash-like hysteresis. The authors also consider two cases: full state and output feedback control. For output feedback, where system states are unknown, a high gain observer is employed to estimate the states. The proposed controllers ensure the boundedness of the control signals. Simulations are also performed to show the effectiveness of the controllers

    Control of mechanical systems with backlash problem

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    Master'sMASTER OF ENGINEERIN

    Neural Network Direct Control with Online Learning for Shape Memory Alloy Manipulators

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    New actuators and materials are constantly incorporated into industrial processes, and additional challenges are posed by their complex behavior. Nonlinear hysteresis is commonly found in shape memory alloys, and the inclusion of a suitable hysteresis model in the control system allows the controller to achieve a better performance, although a major drawback is that each system responds in a unique way. In this work, a neural network direct control, with online learning, is developed for position control of shape memory alloy manipulators. Neural network weight coefficients are updated online by using the actuator position data while the controller is applied to the system, without previous training of the neural network weights, nor the inclusion of a hysteresis model. A real-time, low computational cost control system was implemented; experimental evaluation was performed on a 1-DOF manipulator system actuated by a shape memory alloy wire. Test results verified the effectiveness of the proposed control scheme to control the system angular position, compensating for the hysteretic behavior of the shape memory alloy actuator. Using a learning algorithm with a sine wave as reference signal, a maximum static error of 0.83º was achieved when validated against several set-points within the possible range

    Effect of compliance and backlash on the output speed of a transmission system

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    Backlash is one of the most commonly encountered nonlinearities in drive systems employing gears or ball-screws and indicates the play between adjacent movable parts. Presence of backlash causes delays and oscillations and consequently gives rise to inaccuracies in the position and velocity of the machine. Coupled with this, if the drive system consists of compliant members, torsional oscillations may also occur. Though the presence of backlash may not be of utmost significance in the case of a general speed controlled drive system, web handling systems stand as a unique exception to this observation; any small change in the web speed causes large changes in the controlled tension and hence tight control of speed is an essential requirement in web handling systems. Also, it is of interest to know an estimate of the accuracy of speed achievable in a given closed-loop control system. This paper addresses the effects of compliance and backlash on the output speed of the transmission system.A model to include the effects of compliance and backlash is proposed under the assumption that the collisions due to backlash are sufficiently plastic to avoid bouncing. The proposed model considers the compliance (which may be either due to the elasticity of the shafts or belt in a belt-pulley transmission system) and backlash appearing in series in a drive system. In contrast to the classical backlash model which considers both input and output to the backlash as displacements, the proposed model considers (torque) force as input to the backlash and (angular velocity) velocity of the driven member as the output of the backlash. Thus, the proposed model does not assume that the load is stationary when contact is lost due to backlash width, i.e., momentum of the load is taken into account in the proposed model.From the proposed model, a bound on the speed error due to the presence of backlash is derived. To derive the bound on speed error due to backlash, two situations are considered: (i) closed-loop speed control system with a given backlash, and (ii) the same closed-loop system with no backlash. The difference between the outputs of these two systems indicates the error caused by the backlash and represents the achievable accuracy of the closed-loop system. Closed-loop experiments were conducted on a rectilinear system to obtain the error caused by different backlash widths. The bound obtained from the experimental results agrees with the theoretically computed bound.Mechanical and Aerospace Engineerin

    Identification of robotic manipulators' inverse dynamics coefficients via model-based adaptive networks

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    The values of a given manipulator's dynamics coefficients need to be accurately identified in order to employ model-based algorithms in the control of its motion. This thesis details the development of a novel form of adaptive network which is capable of accurately learning the coefficients of systems, such as manipulator inverse dynamics, where the algebraic form is known but the coefficients' values are not. Empirical motion data from a pair of PUMA 560s has been processed by the Context-Sensitive Linear Combiner (CSLC) network developed, and the coefficients of their inverse dynamics identified. The resultant precision of control is shown to be superior to that achieved from employing dynamics coefficients derived from direct measurement. As part of the development of the CSLC network, the process of network learning is examined. This analysis reveals that current network architectures for processing analogue output systems with high input order are highly unlikely to produce solutions that are good estimates throughout the entire problem space. In contrast, the CSLC network is shown to generalise intrinsically as a result of its structure, whilst its training is greatly simplified by the presence of only one minima in the network's error hypersurface. Furthermore, a fine-tuning algorithm for network training is presented which takes advantage of the CSLC network's single adaptive layer structure and does not rely upon gradient descent of the network error hypersurface, which commonly slows the later stages of network training

    Topics in Machining with Industrial Robots and Optimal Control of Vehicles

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    Two main topics are considered in this thesis: Machining with industrial robots and optimal control of road-vehicles in critical maneuvers. The motivation for research on the first subject is the need for flexible and accurate production processes employing industrial robots as their main component. The challenge to overcome here is to achieve high-accuracy machining solutions, in spite of strong process forces affecting the robot end-effector. Because of the process forces, the nonlinear dynamics of the manipulator, such as the joint compliance and backlash, significantly degrade the achieved position accuracy of the machined part. In this thesis, a macro/micro manipulator configuration is considered to the purpose of increasing the position accuracy. In particular, a model-based control architecture is developed for control of the micro manipulator. The macro/micro manipulator configuration are validated by experimental results from milling tests in aluminium. The main result is that the proposed actuator configuration, combined with the control architecture proposed in this thesis, can be used for increasing the accuracy of industrial machining processes with robots. The interest for research on optimal control of road-vehicles in timecritical maneuvers is mainly driven by the desire to devise improved vehicle safety systems. Primarily, the solution of an optimal control problem for a specific cost function and model configuration can provide indication of performance limits as well as inspiration for control strategies in time-critical maneuvering situations. In this thesis, a methodology for solving this kind of problems is discussed. More specifically, vehicle and tire modeling and the optimization formulation required to get useful solutions to these problems are investigated. Simulation results are presented for different vehicle models, under varying road-surface conditions, in aggressive maneuvers, where in particular the tires are performing at their limits. The obtained results are evaluated and compared. The main conclusion here is that even simplified road-vehicle models are able to replicate behavior observed when experienced drivers are handling vehicles in time-critical maneuvers. Hence, it is plausible that the results presented in this thesis provide a basis for development of future optimization-based driver assistance technologies

    Filtering method in backlash phenomena analysis

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    The behavior of robotic manipulators with backlash is analyzed. Based on the pseudo-phase plane two indices are proposed to evaluate the backlash effect upon the robotic system: the root mean square error and the fractal dimension. For the dynamical analysis the noisy signals captured from the system are filtered through wavelets. Several tests are developed that demonstrate the coherence of the results

    Hybrid Magneto-Rheological Actuators for Human Friendly Robotic Manipulators

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    In recent years, many developments in the field of the physical human robot interaction (pHRI) have been witnessed and significant attentions have been given to the subject of safety within the interactive environments. Ensuring the safety has led to the design of the robots that are physically unable to hurt humans. However, Such systems commonly suffer from the safety-performance trade-off. Magneto-Rheological (MR) fluids are a special class of fluids that exhibit variable yield stress with respect to an applied magnetic field. Devices developed with such fluids are known to provide the prerequisite requirements of intrinsic safe actuation while maintaining the dynamical performance of the actuator. In this study, a new concept for generating magnetic field in Magneto-Rheological (MR) clutches is presented. The main rationale behind this concept is to divide the magnetic field generation into two parts using an electromagnetic coil and a permanent magnet. The main rationale behind this concept is to utilize a hybrid combination of electromagnetic coil and a permanent magnet. The combination of permanent magnets and electromagnetic coils in Hybrid Magneto-Rheological (HMR) clutches allows to distribute the magnetic field inside an MR clutch more uniformly. Moreover, The use of a permanent magnet dramatically reduces the mass of MR clutches for a given value of the nominal torque that results in developing higher torque-to-mass ratio. High torque-to-mass and torque-to-inertia ratios in HMR clutches promotes the use of these devices in human-friendly actuation

    Supervisory control of machine tool feed drives.

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    While motion control of machine tool feed drives is the targeted application. The goal of this study is to explore the relative performance potentials of supervisory control systems against the classical servo control systems; Reconfiguration aspects at the control level are the scope of this study. One of the most essential nonlinear problems faced during modeling and control stages of the CNC machining systems is called backlash. Reversal of motion for each moving axis can lead to that area of disengagement where backlash occurs due to inherently unavoidable clearance between linkages of the machine tool feed drive system. Due to backlash, efficiency of machine tools will be undesirably turned down causing higher vibrations, lower contouring accuracy, and may draw the whole system into instability region. A Switching control scheme is designed to manage the control process where two different controllers with two different control functionalities, acting differently in two vital zones---one of them where the backlash lies, and the other when moving past the backlash---seem to be an important need. (Abstract shortened by UMI.)Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .S53. Source: Masters Abstracts International, Volume: 43-03, page: 0961. Adviser: Waguih ElMaraghy. Thesis (M.A.Sc.)--University of Windsor (Canada), 2004
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