Discrete Modeling and Sliding Mode Control of Piezoelectric Actuators

With the ability to generate fine displacements with a resolution down to sub-nanometers, piezoelectric actuators (PEAs) have found wide applications in various nano-positioning systems. However, existence of various effects in PEAs, such as hysteresis and creep, as well as dynamics can seriously degrade the PEA performance or even lead to instability. This raises a great need to model and control PEAs for improved performance, which have drawn remarkable attention in the literature. Sliding mode control (SMC) shows its potential to the control of PEA, by which the hysteresis and other nonlinear effects can be regard as disturbance to the dynamic model and thus rejected or compensated by its switching control. To implement SMC in digital computers, this research is aimed at developing novel discrete models and discrete SMC (DSMC)-based control schemes for PEAs, along with their experimental validation. The first part of this thesis concerns with the modeling and control of one-degree of freedom (DOF) PEA, which can be treated as a single-input-single-output (SISO) system. Specifically, a novel discrete model based on the concept of auto-regressive moving average (ARMA) was developed for the PEA hysteresis; and to compensate for the PEA hysteresis and improve its dynamics, an output tracking integrated discrete proportional-integral-derivative-based SMC (PID-SMC) was developed. On this basis, by making use of the availability of PEA hysteresis models, two control schemes, named “the discrete inversion feedforward based PID-SMC” and “the discrete disturbance observer (DOB)-based PID-SMC”, were further developed. To illustrate the effectiveness of the developed models and control schemes, experiments were designed and conducted on a commercially available one-DOF PEA, as compared with the existing ones. The second part of the thesis presents the extension of the developed modeling and control methods to multi-DOF PEAs. Given the fact that details with regard to the PEA internal configurations is not typically provided by the manufacturer, a state space model based on the black box system identification was developed for the three-DOF PEA. The developed model was then integrated in the output tracking based discrete PID-SMC, with its effectiveness verified through the experiments on a commercially available three-DOF PEA. The superiority of the proposed control method over the conventional PID controller was also experimentally investigated and demonstrated. Finally, by integrating with a DOB in the discrete PID-based SMC, a novel control scheme is resulted to compensate for the nonlinearities of the three-DOF PEA. To verify its effectiveness, the discrete DOB based PID-SMC was applied in the control experiments and compared with the existing SMC. The significance of this research lies in the development of the discrete models and PID-based SMC for PEAs, which is of great help to improve their performance. The successful application of the proposed method in the control of multi-DOF PEA allows the application of SMC to the control of complicated multi-inputs-multi-outputs (MIMO) systems without details regarding the internal configuration. Also, integration of the inversion based feedforward control and the DOB in the SMC design has been proven effective for the tracking control of PEAs

マルチ スケール キノウ ヲ ユウスル コウソク ジドウ マイクロ マニピュレーション システム

Ebubekir Avci, Chanh-Nghiem Nguyen, Kenichi Ohara, Yasushi Mae, Tatsuo Arai, Analysis and suppression of residual vibration in microhand for high-speed single-cell manipulation, International Journal of Mechatronics and Automation, 2013-Vol.3, No.2, pp.110-11

Industrial Robotics

This book covers a wide range of topics relating to advanced industrial robotics, sensors and automation technologies. Although being highly technical and complex in nature, the papers presented in this book represent some of the latest cutting edge technologies and advancements in industrial robotics technology. This book covers topics such as networking, properties of manipulators, forward and inverse robot arm kinematics, motion path-planning, machine vision and many other practical topics too numerous to list here. The authors and editor of this book wish to inspire people, especially young ones, to get involved with robotic and mechatronic engineering technology and to develop new and exciting practical applications, perhaps using the ideas and concepts presented herein

Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin

Collaborative robots are expected to physically interact with humans in daily living and the workplace, including industrial and healthcare settings. A key related enabling technology is tactile sensing, which currently requires addressing the outstanding scientific challenge to simultaneously detect contact location and intensity by means of soft conformable artificial skins adapting over large areas to the complex curved geometries of robot embodiments. In this work, the development of a large-area sensitive soft skin with a curved geometry is presented, allowing for robot total-body coverage through modular patches. The biomimetic skin consists of a soft polymeric matrix, resembling a human forearm, embedded with photonic fibre Bragg grating transducers, which partially mimics Ruffini mechanoreceptor functionality with diffuse, overlapping receptive fields. A convolutional neural network deep learning algorithm and a multigrid neuron integration process were implemented to decode the fibre Bragg grating sensor outputs for inference of contact force magnitude and localization through the skin surface. Results of 35 mN (interquartile range 56 mN) and 3.2 mm (interquartile range 2.3 mm) median errors were achieved for force and localization predictions, respectively. Demonstrations with an anthropomorphic arm pave the way towards artificial intelligence based integrated skins enabling safe human–robot cooperation via machine intelligence

Dynamics and Control of Flexure-based Large Range Nanopositioning Systems.

The objective of this thesis is to demonstrate desktop-size and cost-effective flexure-based multi-axis nanopositioning capability over a motion range of several millimeters per axis. Increasing the motion range will overcome one of the main drawbacks of existing nanopositioning systems, thereby significantly improving the coverage area in nanometrology and nanomanufacturing applications. A single-axis nanopositioning system, comprising a symmetric double parallelogram flexure bearing and a traditional-architecture moving magnet actuator, is designed, fabricated, and tested. A figure of merit for the actuator is derived and shown to directly impact the system-level trade-offs in terms of range, resolution, bandwidth, and temperature rise. While linear feedback controllers provide good positioning performance for point-to-point commands, the tracking error for dynamic commands prove to be inadequate due to the nonlinearities in the actuator and its driver. To overcome this, an iterative learning controller is implemented in conjunction with linear feedback to reduce the periodic component of the tracking error by more than two orders of magnitude. Experimental results demonstrate 10 nm RMS tracking error over 8 mm motion range in response to a 2 Hz bandlimited triangular command. For the XY nanopositioning system, a lumped-parameter model of an existing XY flexure bearing is developed in order to understand the unexplained variation observed in the transfer function zeros over the operating range of motion. It is shown that the kinematic coupling, due to geometric nonlinearities in the beam mechanics, and small dimensional asymmetry, due to manufacturing tolerances, may conspire to produce complex-conjugate nonminimum phase zeros at certain operating points in the system's workspace. This phenomenon significantly restricts the overall performance of the feedback control system. After intentional use of large asymmetry is employed to overcome this problem, independent feedback and iterative learning controllers are implemented along each axis. Experimental results demonstrate 20 nm RMS radial tracking error while traversing a 2 mm diameter circle at 2 Hz.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107086/1/parmar_1.pd

Towards Semi-Autonomous Control of Heavy-Duty Tracked Earth-Moving Mobile Manipulators : Use Case: The Bulldozer

A mobile manipulator (MM) comprises a manipulator attached to a mobile base, making it capable of manipulation tasks in large workspaces. In the field of construction, heavy-duty MMs are extensively used for soil excavation at construction sites. One such machine is the bulldozer, which is widely used because of its robustness and maneuverability. With its onboard blade, the bulldozer shapes terrain and transports soil material by pushing it. However, operating the blade with joysticks to accurately shape the terrain surface and moving material productively are difficult tasks that require extensive training and experience. Automating the motion of the blade, therefore, has the potential to reduce skill requirements, improve productivity, and reduce operators’ workloads. This thesis studies and develops methods for the semi-autonomous control of a bulldozer to increase surface quality and earthmoving productivity. These goals were reflected in the main research problems (RPs). Furthermore, as bulldozers drive over the terrain shape generated by the blade, the RPs are coupled because earthmoving productivity is partially dependent on surface quality. The RPs and their coupling were addressed in four publications by coordinating the mobile base and manipulator control and by using the surrounding terrain shape in automatic blade motion reference computations. Challenges to automatic control emerge from the tracked mobile platform driving on rough terrain while the manipulator tool interacts with the soil. It is shown in the first two publications that coordinating the control of the MM mobile base and blade manipulator subsystems can improve surface quality and productivity by temporarily slowing down the machine when the required manipulator joint rates increase or when the tractive performance reduces. The third publication showed that feedforward–feedback control of the blade manipulator can be used on a real-world bulldozer for accurate terrain shaping. The thesis work culminates in the final publication with an experimental implementation of a semi-autonomous blade control system that continuously maps the worksite terrain and uses it to compute the required blade motion

High-precision grasping and placing for mobile robots

This work presents a manipulation system for multiple labware in life science laboratories using the H20 mobile robots. The H20 robot is equipped with the Kinect V2 sensor to identify and estimate the position of the required labware on the workbench. The local features recognition based on SURF algorithm is used. The recognition process is performed for the labware to be grasped and for the workbench holder. Different grippers and labware containers are designed to manipulate different weights of labware and to realize a safe transportation

Selected topics in robotics for space exploration

Papers and abstracts included represent both formal presentations and experimental demonstrations at the Workshop on Selected Topics in Robotics for Space Exploration which took place at NASA Langley Research Center, 17-18 March 1993. The workshop was cosponsored by the Guidance, Navigation, and Control Technical Committee of the NASA Langley Research Center and the Center for Intelligent Robotic Systems for Space Exploration (CIRSSE) at RPI, Troy, NY. Participation was from industry, government, and other universities with close ties to either Langley Research Center or to CIRSSE. The presentations were very broad in scope with attention given to space assembly, space exploration, flexible structure control, and telerobotics

Accuracy Enhancement for High Precision Gantry Stage

Ph.DDOCTOR OF PHILOSOPH

Haptics-Enabled Teleoperation for Robotics-Assisted Minimally Invasive Surgery

The lack of force feedback (haptics) in robotic surgery can be considered to be a safety risk leading to accidental tissue damage and puncturing of blood vessels due to excessive forces being applied to tissue and vessels or causing inefficient control over the instruments because of insufficient applied force. This project focuses on providing a satisfactory solution for introducing haptic feedback in robotics-assisted minimally invasive surgical (RAMIS) systems. The research addresses several key issues associated with the incorporation of haptics in a master-slave (teleoperated) robotic environment for minimally invasive surgery (MIS). In this project, we designed a haptics-enabled dual-arm (two masters - two slaves) robotic MIS testbed to investigate and validate various single-arm as well as dual-arm teleoperation scenarios. The most important feature of this setup is the capability of providing haptic feedback in all 7 degrees of freedom (DOF) required for RAMIS (3 translations, 3 rotations and pinch motion of the laparoscopic tool). The setup also enables the evaluation of the effect of replacing haptic feedback by other sensory cues such as visual representation of haptic information (sensory substitution) and the hypothesis that surgical outcomes may be improved by substituting or augmenting haptic feedback by such sensory cues