566 research outputs found

    Biomimetic Manipulator Control Design for Bimanual Tasks in the Natural Environment

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    As robots become more prolific in the human environment, it is important that safe operational procedures are introduced at the same time; typical robot control methods are often very stiff to maintain good positional tracking, but this makes contact (purposeful or accidental) with the robot dangerous. In addition, if robots are to work cooperatively with humans, natural interaction between agents will make tasks easier to perform with less effort and learning time. Stability of the robot is particularly important in this situation, especially as outside forces are likely to affect the manipulator when in a close working environment; for example, a user leaning on the arm, or task-related disturbance at the end-effector. Recent research has discovered the mechanisms of how humans adapt the applied force and impedance during tasks. Studies have been performed to apply this adaptation to robots, with promising results showing an improvement in tracking and effort reduction over other adaptive methods. The basic algorithm is straightforward to implement, and allows the robot to be compliant most of the time and only stiff when required by the task. This allows the robot to work in an environment close to humans, but also suggests that it could create a natural work interaction with a human. In addition, no force sensor is needed, which means the algorithm can be implemented on almost any robot. This work develops a stable control method for bimanual robot tasks, which could also be applied to robot-human interactive tasks. A dynamic model of the Baxter robot is created and verified, which is then used for controller simulations. The biomimetic control algorithm forms the basis of the controller, which is developed into a hybrid control system to improve both task-space and joint-space control when the manipulator is disturbed in the natural environment. Fuzzy systems are implemented to remove the need for repetitive and time consuming parameter tuning, and also allows the controller to actively improve performance during the task. Experimental simulations are performed, and demonstrate how the hybrid task/joint-space controller performs better than either of the component parts under the same conditions. The fuzzy tuning method is then applied to the hybrid controller, which is shown to slightly improve performance as well as automating the gain tuning process. In summary, a novel biomimetic hybrid controller is presented, with a fuzzy mechanism to avoid the gain tuning process, finalised with a demonstration of task-suitability in a bimanual-type situation.EPSR

    Vision-Based Control of Flexible Robot Systems

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    This thesis covers the controlling of flexible robot systems by using a camera as a measurement device. To accomplish the purpose of the study, the estimation process of dynamic state variables of flexible link robot has been examined based on camera measurements. For the purpose of testing two application examples for flexible link have been applied, an algorithm for the dynamic state variables estimation is proposed. Flexible robots can have very complex dynamic behavior during their operations, which can lead to induced vibrations. Since the vibrations and its derivative are not all measurable, therefore the estimation of state variables plays a significant role in the state feedback control of flexible link robots. A vision sensor (i.e. camera) realizing a contact-less measurement sensor can be used to measure the deflection of flexible robot arm. Using a vision sensor, however, would generate new effects such as limited accuracy and time delay, which are the main inherent problems of the application of vision sensors within the context. These effects and related compensation approaches are studied in this thesis. An indirect method for link deflection (i.e. system states) sensing is presented. It uses a vision system consisting of a CCD camera and an image processing unit. The main purpose of this thesis is to develop an estimation approach combining suitable measurement devices which are easy to realize with improved reliability. It includes designing two state estimators; the first one for the traditional sensor type (negligible noise and time delay) and the second one is for the camera measurement which account for the dynamic error due to the time delay. The estimation approach is applied first using a single link flexible robot; the dynamic model of the flexible link is derived using a finite element method. Based on the suggested estimation approach, the first observer estimates the vibrations using strain gauge (fast and complete dynamics), and the second observer estimates the vibrations using vision data (slow dynamical parts). In order to achieve an optimal estimation, a proper combination process of the two estimated dynamical parts of the system dynamics is described. The simulation results for the estimations based on vision measurements show that the slow dynamical states can be estimated and the observer can compensate the time delay dynamic errors. It is also observed that an optimal estimation can be attained by combining slow dynamical estimated states with those of fast observer-based on strain gauge measurement. Based on suggested estimation approach a vision-based control for elastic shipmounted crane is designed to regulate the motion of the payload. For the observers and the controller design, a linear dynamic model of elastic-ship mounted crane incorporating a finite element technique for modeling flexible link is employed. In order to estimate the dynamic states variables and the unknown disturbance two state observers are designed. The first one estimates the state variables using camera measurement (augmented Kalman filter). The second one used potentiometers measurement (PI-Observer). To realize a multi-model approach of elastic-ship mounted crane, a variable gain controller and variable gain observers are designed. The variable gain controller is used to generate the required damping to control the system based on the estimated states and the roll angle. Simulation results show that the variable gain observers can adequately estimate the states and the unknown disturbance acting on the payload. It is further observed that the variable gain controller can effectively reduce the payload pendulations. Experiments are conducted using the camera to measure the link deflection of scaled elastic ship-mounted crane system. The results shown that the variable gain controller based on the combined states observers mitigated the vibrations of the system and the swinging of the payload. The presented material above is embedded into an interrelated thesis. A concise introduction to the vision-based control and state estimation problems is attached in the first chapter. An extensive survey of available visual servoing algorithms that include the rigid robot system and the flexible robot system is also presented. The conclusions of the work and suggestions for the future research are provided at the last chapter of this thesis

    Sliding-Mode control for high-precision motion control systems

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    In many of today's mechanical systems, high precision motion has become a necessity. As performance requirements become more stringent, classical industrial controllers such as PID can no longer provide satisfactory results. Although many control approaches have been proposed in the literature, control problems related to plant parameter uncertainties, disturbances and high-order dynamics remain as big challenges for control engineers. Theory of Sliding Mode Control provides a systematic approach to controller design while allowing stability in the presence of parametric uncertainties and external disturbances. In this thesis a brief study of the concepts behind Sliding Mode Control will be shown. Description of Sliding Mode Control in discrete-time systems and the continuous Sliding Mode Control will be shown. The description will be supported with the design and robustness analysis of Sliding Mode Control for discrete-time systems. In this thesis a simplified methodology based on discrete-time Sliding Mode Control will be presented. The main issues that this thesis aims to solve are friction and internal nonlinearities. The thesis can be outlined as follows: -Implementation of discrete-time Sliding Mode Control to systems with nonlinearities and friction. Systems include; piezoelectric actuators that are known to suffer from nonlinear hysteresis behavior and ball-screw drives that suffer from high friction. Finally, the controller will be implemented on a 6-dof Stewart platform which is a system of higher complexity. -It will also be shown that performance can be enhanced with the aid of disturbance compensation based on a nominal plant disturbance observer

    Applied Mathematics to Mechanisms and Machines

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    This book brings together all 16 articles published in the Special Issue "Applied Mathematics to Mechanisms and Machines" of the MDPI Mathematics journal, in the section “Engineering Mathematics”. The subject matter covered by these works is varied, but they all have mechanisms as the object of study and mathematics as the basis of the methodology used. In fact, the synthesis, design and optimization of mechanisms, robotics, automotives, maintenance 4.0, machine vibrations, control, biomechanics and medical devices are among the topics covered in this book. This volume may be of interest to all who work in the field of mechanism and machine science and we hope that it will contribute to the development of both mechanical engineering and applied mathematics

    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

    Evolutionary swarm algorithm for modelling and control of horizontal flexible plate structures

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    Numerous advantages offered by the horizontal flexible structure have attracted increasing industrial applications in many engineering fields particularly in the airport baggage conveyor system, micro hand surgery and semiconductor manufacturing industry. Nevertheless, the horizontal flexible structure is often subjected to disturbance forces as vibration is easily induced in the system. The vibration reduces the performance of the system, thus leading to the structure failure when excessive stress and noise prevail. Following this, it is crucial to minimize unwanted vibration so that the effectiveness and the lifetime of the structure can be preserved. In this thesis, an intelligent proportional-integral-derivative (PID) controller has been developed for vibration suppression of a horizontal flexible plate structure. Initially, a flexible plate experimental rig was designed and fabricated with all clamped edges boundary conditions at horizontal position. Then, the data acquisition and instrumentation systems were integrated into the experimental rig. Several experimental procedures were conducted to acquire the input-output vibration data of the system. Next, the dynamics of the system was modeled using linear auto regressive with exogenous, which is optimized with three types of evolutionary swarm algorithm, namely, the particle swarm optimization (PSO), artificial bee colony (ABC) and bat algorithm (BAT) model structure. Their effectiveness was then validated using mean squared error, correlation tests and pole zero diagram stability. Results showed that the PSO algorithm has superior performance compared to the other algorithms in modeling the system by achieving lowest mean squared error of 6103947.4 , correlation of up to 95 % confidence level and good stability. Next, five types of PID based controllers were chosen to suppress the unwanted vibration, namely, PID-Ziegler Nichols (ZN), PID-PSO, PID-ABC, Fuzzy-PID and PID-Iterative Learning Algorithm (ILA). The robustness of the controllers was validated by exerting different types of disturbances on the system. Amongst all controllers, the simulation results showed that PID tuned by ABC outperformed other controllers with 47.60 dB of attenuation level at the first mode (the dominant mode) of vibration, which is equivalent to 45.99 % of reduction in vibration amplitude. By implementing the controllers experimentally, the superiority of PID-ABC based controller was further verified by achieving an attenuation of 23.83 dB at the first mode of vibration and 21.62 % of reduction in vibration amplitude. This research proved that the PID controller tuned by ABC is superior compared to other tuning algorithms for vibration suppression of the horizontal flexible plate structure

    From plain visualisation to vibration sensing: using a camera to control the flexibilities in the ITER remote handling equipment

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    Thermonuclear fusion is expected to play a key role in the energy market during the second half of this century, reaching 20% of the electricity generation by 2100. For many years, fusion scientists and engineers have been developing the various technologies required to build nuclear power stations allowing a sustained fusion reaction. To the maximum possible extent, maintenance operations in fusion reactors are performed manually by qualified workers in full accordance with the "as low as reasonably achievable" (ALARA) principle. However, the option of hands-on maintenance becomes impractical, difficult or simply impossible in many circumstances, such as high biological dose rates. In this case, maintenance tasks will be performed with remote handling (RH) techniques. The International Thermonuclear Experimental Reactor ITER, to be commissioned in southern France around 2025, will be the first fusion experiment producing more power from fusion than energy necessary to heat the plasma. Its main objective is “to demonstrate the scientific and technological feasibility of fusion power for peaceful purposes”. However ITER represents an unequalled challenge in terms of RH system design, since it will be much more demanding and complex than any other remote maintenance system previously designed. The introduction of man-in-the-loop capabilities in the robotic systems designed for ITER maintenance would provide useful assistance during inspection, i.e. by providing the operator the ability and flexibility to locate and examine unplanned targets, or during handling operations, i.e. by making peg-in-hole tasks easier. Unfortunately, most transmission technologies able to withstand the very specific and extreme environmental conditions existing inside a fusion reactor are based on gears, screws, cables and chains, which make the whole system very flexible and subject to vibrations. This effect is further increased as structural parts of the maintenance equipment are generally lightweight and slender structures due to the size and the arduous accessibility to the reactor. Several methodologies aiming at avoiding or limiting the effects of vibrations on RH system performance have been investigated over the past decade. These methods often rely on the use of vibration sensors such as accelerometers. However, reviewing market shows that there is no commercial off-the-shelf (COTS) accelerometer that meets the very specific requirements for vibration sensing in the ITER in-vessel RH equipment (resilience to high total integrated dose, high sensitivity). The customisation and qualification of existing products or investigation of new concepts might be considered. However, these options would inevitably involve high development costs. While an extensive amount of work has been published on the modelling and control of flexible manipulators in the 1980s and 1990s, the possibility to use vision devices to stabilise an oscillating robotic arm has only been considered very recently and this promising solution has not been discussed at length. In parallel, recent developments on machine vision systems in nuclear environment have been very encouraging. Although they do not deal directly with vibration sensing, they open up new prospects in the use of radiation tolerant cameras. This thesis aims to demonstrate that vibration control of remote maintenance equipment operating in harsh environments such as ITER can be achieved without considering any extra sensor besides the embarked rad-hardened cameras that will inevitably be used to provide real-time visual feedback to the operators. In other words it is proposed to consider the radiation-tolerant vision devices as full sensors providing quantitative data that can be processed by the control scheme and not only as plain video feedback providing qualitative information. The work conducted within the present thesis has confirmed that methods based on the tracking of visual features from an unknown environment are effective candidates for the real-time control of vibrations. Oscillations induced at the end effector are estimated by exploiting a simple physical model of the manipulator. Using a camera mounted in an eye-in-hand configuration, this model is adjusted using direct measurement of the tip oscillations with respect to the static environment. The primary contribution of this thesis consists of implementing a markerless tracker to determine the velocity of a tip-mounted camera in an untrimmed environment in order to stabilise an oscillating long-reach robotic arm. In particular, this method implies modifying an existing online interaction matrix estimator to make it self-adjustable and deriving a multimode dynamic model of a flexible rotating beam. An innovative vision-based method using sinusoidal regression to sense low-frequency oscillations is also proposed and tested. Finally, the problem of online estimation of the image capture delay for visual servoing applications with high dynamics is addressed and an original approach based on the concept of cross-correlation is presented and experimentally validated

    Soft-computing based intelligent adaptive control design of complex dynamic systems

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