Modeling and parameter estimation of rheological objects for simultaneous reproduction of force and deformation

Abstract-Many deformable objects in our living life demonstrate rheological behaviors, such as human organs and tissues, clays and various food products. Rheological objects include both elastic and plastic properties. Due to the presence of residual (permanent) deformation, it is difficult to model rheological objects, especially to reproduce both force and residual deformation simultaneously. In this paper, a series of physical models was investigated for simulating rheological behaviors. Generalized formulations of the constitutive laws were derived for serial and parallel physical models, respectively. We found that the serial models are appropriate for formulating strain, whereas the parallel models allow a convenient calculation of stress. Analytical expressions of force and residual deformation were then derived for generalized parallel models. Theoretical discussions suggested the difficulty to reproduce both force and deformation simultaneously using linear physical models. A 2D FE (finite element) model was then formulated and an efficient method for estimating physical parameters were proposed by taking the advantages of analytical force expressions. Experimental results with commercial clay and Japanese sweets material were presented to validate our modeling and parameter estimation methods. A dual-moduli viscous element was also introduced to improve our FE model for reproducing rheological force and deformation simultaneously

On Sensorless Collision Detection and Measurement of External Forces in Presence of Modeling Inaccuracies

The field of human-robot interaction has garnered significant interest in the last decade. Every form of human-robot coexistence must guarantee the safety of the user. Safety in human-robot interaction is being vigorously studied, in areas such as collision avoidance, soft actuators, light-weight robots, computer vision techniques, soft tissue modeling, collision detection, etc. Despite the safety provisions, unwanted collisions can occur in case of system faults. In such cases, before post-collision strategies are triggered, it is imperative to effectively detect the collisions. Implementation of tactile sensors, vision systems, sonar and Lidar sensors, etc., allows for detection of collisions. However, due to the cost of such methods, more practical approaches are being investigated. A general goal remains to develop methods for fast detection of external contacts using minimal sensory information. Availability of position data and command torques in manipulators permits development of observer-based techniques to measure external forces/torques. The presence of disturbances and inaccuracies in the model of the robot presents challenges in the efficacy of observers in the context of collision detection. The purpose of this thesis is to develop methods that reduce the effects of modeling inaccuracies in external force/torque estimation and increase the efficacy of collision detection. It is comprised of the following four parts: 1. The KUKA Light-Weight Robot IV+ is commonly employed for research purposes. The regressor matrix, minimal inertial parameters and the friction model of this robot are identified and presented in detail. To develop the model, relative weight analysis is employed for identification. 2. Modeling inaccuracies and robot state approximation errors are considered simultaneously to develop model-based time-varying thresholds for collision detection. A metric is formulated to compare trajectories realizing the same task in terms of their collision detection and external force/torque estimation capabilities. A method for determining optimal trajectories with regards to accurate external force/torque estimation is also developed. 3. The effects of velocity on external force/torque estimation errors are studied with and without the use of joint force/torque sensors. Velocity-based thresholds are developed and implemented to improve collision detection. The results are compared with the collision detection module integrated in the KUKA Light-Weight Robot IV+. 4. An alternative joint-by-joint heuristic method is proposed to identify the effects of modeling inaccuracies on external force/torque estimation. Time-varying collision detection thresholds associated with the heuristic method are developed and compared with constant thresholds. In this work, the KUKA Light-Weight Robot IV+ is used for obtaining the experimental results. This robot is controlled via the Fast Research Interface and Visual C++ 2008. The experimental results confirm the efficacy of the proposed methodologies

Identification of Mechanical Properties of Nonlinear Materials and Development of Tactile Displays for Robotic Assisted Surgery Applications

This PhD work presents novel methods of mechanical property identification for soft nonlinear materials and methods of recreating and modeling the deformation behavior of these nonlinear materials for tactile feedback systems. For the material property identification, inverse modeling method is employed for the identification of hyperelastic and hyper-viscoelastic (HV) materials by use of the spherical indentation test. Identification experiments are performed on soft foam materials and fresh harvested bovine liver tissue. It is shown that reliability and accuracy of the identified material parameters are directly related to size of the indenter and depth of the indentation. Results show that inverse FE modeling based on MultiStart optimization algorithm and the spherical indentation, is a reliable and scalable method of identification for biological tissues based on HV constitutive models. The inverse modeling method based on the spherical indentation is adopted for realtime applications using variation and Kalman filter methods. Both the methods are evaluated on hyperelastic foams and biological tissues on experiments which are analogous to the robot assisted surgery. Results of the experiments are compared and discussed for the proposed methods. It is shown that increasing the indentation rate eliminates time dependency in material behavior, thus increases the successful recognition rate. The deviation of an identified parameter at indentation rates of V=1, 2 and 4 mm/s was found as 28%, 21.3% and 7.3%. It is found that although the Kalman filter method yields less dispersion in identified parameters compared to the variance method, it requires almost 900 times more computation power compared to the variance method, which is a limiting factor for increasing the indentation rate. Three bounding methods are proposed and implemented for the Kalman filter estimation. It was found that the Projection and Penalty bounding methods yield relatively accurate results without failure. However, the Nearest Neighbor method found with a high chance of non-convergence. The second part of the thesis is focused on the development of tactile displays for modeling the mechanical behavior of the nonlinear materials for human tactile perception. An accurate finite element (FE) model of human finger pad is constructed and validated in experiments of finger pad contact with soft and relatively rigid materials. Hyperfoam material parameters of the identified elastomers from the previous section are used for validation of the finger pad model. A magneto-rheological fluid (MRF) based tactile display is proposed and its magnetic FE model is constructed and validated in Gauss meter measurements. FE models of the human finger pad and the proposed tactile display are used in a model based control algorithm for the proposed display. FE models of the identified elastomers are used for calculation of control curves for these elastomers. An experiment is set up for evaluation of the proposed display. Experiments are performed on biological tissue and soft nonlinear foams. Comparison between curves of desired and recreated reaction force from subject's finger pad contact with the display showed above 84% accuracy. As a complementary work, new modeling and controlling approaches are proposed and tested for tactile displays based on linear actuators. Hertzian model of contact between the human finger pad and actuator cap is derived and curves of material deformation are obtained and improved based on this model. A PID controller is designed for controlling the linear actuators. Optimization based controller tuning approach is explained in detail and robust stability of the system is also investigated. Results showed maximum tracking error of 16.6% for the actuator controlled by the PID controller. Human subject tests of recreated softness perception show 100% successful recognition rate for group of materials with high difference in their softness

A hybrid approach to determining cornea mechanical properties using a combination of inverse finite element analysis and experimental techniques

It is of great clinical importance to predict the behaviour of the cornea in various diseases and post-surgical recovery. Therefore, a numerical model that is able to simulate the corneal behaviour, considering corneal material properties obtained from individuals is highly desirable. In this work a combined numerical-experimental technique has been developed that can characterize the mechanical properties of a cornea properties from two aspects: time-dependency and spatial variation. Initially, an analysis of the material properties of porcine corneas was performed to investigate the time-dependent behaviour of the cornea. A simple stress relaxation test was used to determine the viscoelastic properties of a cornea and a rheological model was built based on the Generalized Maxwell (GM) approach. A validation experiment using nano-indentation showed that an isotropic GM model was insufficient for describing the corneal time-dependent behaviour when exposed to a complex stress state. A technique was proposed that takes into account the microstructural composition of the cornea and is based on a combination of nano-indentation experiment, isotropic and transversely isotropic numerical models, and an inverse finite element method. The good agreement using this method suggests that this is a promising technique for measuring the time-dependent properties of the cornea. The spatial variation of the properties was then investigated. This time, the long term structural response of the cornea was targeted. A full field displacement response of a loaded cornea was evaluated from Optical Coherence Tomography (OCT) volume reconstructions of the cornea using Digital Volume Correlation (DVC). The inverse finite element method was employed with two models sequentially; first, a radially partitioned model and then a circumferentially partitioned model, in order to recover the elastic parameters in radial and circumferential directions. The good agreement using this method suggests that this is a promising and reliable technique for identifying the distribution of the corneal properties. In this research, we have shown that it is possible to determine the local time-dependent properties of the cornea and the in-depth (2D) distribution of the properties using the hybrid technique. This technique has the potential to be implemented in vivo. However, further work should focus on the feasibility of this technique in practice

Advanced suspension system using magnetorheological technology for vehicle vibration control

In the past forty years, the concept of controllable vehicle suspension has attracted extensive attention. Since high price of an active suspension system and deficiencies on a passive suspension, researchers pay a lot attention to semi-active suspension. Magneto-rheological fluid (MRF) is always an ideal material of semi-active structure. Thanks to its outstanding features like large yield stress, fast response time, low energy consumption and significant rheological effect. MR damper gradually becomes a preferred component of semi-active suspension for improving the riding performance of vehicle. However, because of the inherent nonlinear nature of MR damper, one of the challenging aspects of utilizing MR dampers to achieve high levels of performance is the development of an appropriate control strategy that can take advantage of the unique characteristics of MR dampers. This is why this project has studied semi-active MR control technology of vehicle suspensions to improve their performance. Focusing on MR semi-active suspension, the aim of this thesis sought to develop system structure and semi-active control strategy to give a vehicle opportunity to have a better performance on riding comfort. The issues of vibration control of the vehicle suspension were systematically analysed in this project. As a part of this research, a quarter-car test rig was built; the models of suspension and MR damper were established; the optimization work of mechanical structure and controller parameters was conducted to further improve the system performance; an optimized MR damper (OMRD) for a vehicle suspension was designed, fabricated, and tested. To utilize OMRD to achieve higher level of performance, an appropriate semi-active control algorithm, state observer-based Takagi-Sugeno fuzzy controller (SOTSFC), was designed for the semi-active suspension system, and its feasibility was verified through an experiment. Several tests were conducted on the quarter-car suspension to investigate the real effect of this semiactive control by changing suspension damping. In order to further enhance the vibration reduction performance of the vehicle, a fullsize variable stiffness and variable damping (VSVD) suspension was further designed, fabricated, and tested in this project. The suspension can be easily installed into a vehicle suspension system without any change to the original configuration. A new 3- degree of freedom (DOF) phenomenological model to further accurately describe the dynamic characteristic of the VSVD suspension was also presented. Based on a simple on-off controller, the performance of the variable stiffness and damping suspension was verified numerically. In addition, an innovative TS fuzzy modelling based VSVD controller was designed. The TS fuzzy modelling controller includes a skyhook damping control module and a state observer based stiffness control module which considering road dominant frequency in real-time. The performance evaluation of the VSVD control algorithm was based on the quarter-car test rig which equipping the VSVD suspension. The experiment results showed that this strategy increases riding comfort effectively, especially under off-road working condition. The semi-active control system developed in this thesis can be adapted and used on a vehicle suspension in order to better control vibration

A Review on the Magnetorheological Fluid, Damper and Its Applications for Seismic Mitigation

Magnetorheological (MR) fluids and dampers have wide advances as smart materials because of its unique properties, notably, viscosity increases in the presence when magnetic field applied MR Fluids composed of three key components, including carrier fluid, surfactants and metal particles. The major applications of MR Fluids are in brakes, dampers, journal bearings, fluid clutches, pneumatic artificial muscles, aerospace etc. where electrical energy is converted to mechanical energy (Damping Force) in a controlled manner. Within a few milliseconds the fluid converts from liquid to semi solid state. Over the years, researchers were concerned on the ways to enhance the modelling precision. Though the proposed Dynamic models of MR Dampers represent displacement and force behaviour. In this review paper, the advances of MR Fluids, MR Damper, Damper Models, Energy harvesting and their applications for seismic resistance of structures are briefly discussed in the present study

Advances of Italian Machine Design

This 2028 Special Issue presents recent developments and achievements in the field of Mechanism and Machine Science coming from the Italian community with international collaborations and ranging from theoretical contributions to experimental and practical applications. It contains selected contributions that were accepted for presentation at the Second International Conference of IFToMM Italy, IFIT2018, that has been held in Cassino on 29 and 30 November 2018. This IFIT conference is the second event of a series that was established in 2016 by IFToMM Italy in Vicenza. IFIT was established to bring together researchers, industry professionals and students, from the Italian and the international community in an intimate, collegial and stimulating environment

12th International Conference on Vibrations in Rotating Machinery

Since 1976, the Vibrations in Rotating Machinery conferences have successfully brought industry and academia together to advance state-of-the-art research in dynamics of rotating machinery. 12th International Conference on Vibrations in Rotating Machinery contains contributions presented at the 12th edition of the conference, from industrial and academic experts from different countries. The book discusses the challenges in rotor-dynamics, rub, whirl, instability and more. The topics addressed include: - Active, smart vibration control - Rotor balancing, dynamics, and smart rotors - Bearings and seals - Noise vibration and harshness - Active and passive damping - Applications: wind turbines, steam turbines, gas turbines, compressors - Joints and couplings - Challenging performance boundaries of rotating machines - High power density machines - Electrical machines for aerospace - Management of extreme events - Active machines - Electric supercharging - Blades and bladed assemblies (forced response, flutter, mistuning) - Fault detection and condition monitoring - Rub, whirl and instability - Torsional vibration Providing the latest research and useful guidance, 12th International Conference on Vibrations in Rotating Machinery aims at those from industry or academia that are involved in transport, power, process, medical engineering, manufacturing or construction

Deterministic Artificial Intelligence

Kirchhoff’s laws give a mathematical description of electromechanics. Similarly, translational motion mechanics obey Newton’s laws, while rotational motion mechanics comply with Euler’s moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research culminating here with a text on the ability to make rigid bodies in rotation become self-aware, and even learn. This book is meant for basic scientifically inclined readers commencing with a first chapter on the basics of stochastic artificial intelligence to bridge readers to very advanced topics of deterministic artificial intelligence, espoused in the book with applications to both electromechanics (e.g. the forced van der Pol equation) and also motion mechanics (i.e. Euler’s moment equations). The reader will learn how to bestow self-awareness and express optimal learning methods for the self-aware object (e.g. robot) that require no tuning and no interaction with humans for autonomous operation. The topics learned from reading this text will prepare students and faculty to investigate interesting problems of mechanics. It is the fondest hope of the editor and authors that readers enjoy the book