Direct torque control for cable conduit mechanisms for the robotic foot for footwear testing

© 2018 Elsevier Ltd As the shoe durability is affected directly by the dynamic force/pressure between the shoe and its working environments (i.e., the contact ground and the human foot), a footwear testing system should replicate correctly this interaction force profile during gait cycles. Thus, in developing a robotic foot for footwear testing, it is important to power multiple foot joints and to control their output torque to produce correct dynamic effects on footwear. The cable conduit mechanism (CCM) offers great advantages for designing this robotic foot. It not only eliminates the cumbersome actuators and significant inertial effects from the fast-moving robotic foot but also allows a large amount of energy/force to be transmitted/propagated to the compact robotic foot. However, CCMs cause nonlinearities and hysteresis effects to the system performance. Recent studies on CCMs and hysteresis systems mostly addressed the position control. This paper introduces a new approach for modelling the torque transmission and controlling the output torque of a pair of CCMs, which are used to actuate the robotic foot for footwear testing. The proximal torque is used as the input signal for the Bouc–Wen hysteresis model to portray the torque transmission profile while a new robust adaptive control scheme is developed to online estimate and compensate for the nonlinearities and hysteresis effects. Both theoretical proof of stability and experimental validation of the new torque controller have been carried out and reported in this paper. Control experiments of other closed-loop control algorithms have been also conducted to compare their performance with the new controller effectiveness. Qualitative and quantitative results show that the new control approach significantly enhances the torque tracking performance for the system preceded by CCMs

MR Fluid Damper and Its Application to Force Sensorless Damping Control System

Vibration suppression is considered as a keyresearch field in civil engineering to ensure the safety and comfort of their occupants and users of mechanical structures. To reduce the system vibration, an effective vibration control with isolation is necessary. Vibration control techniques have classically been categorized into two areas, passive and active controls. For a long time, efforts were made to make the suspension system work optimally by optimizing its parameters, but due to the intrinsic limitations of a passive suspension system, improvements were effective only in a certain frequency range. Compared with passive suspensions, active suspensions can improve the performance of the suspension system over a wide range of frequencies. Semi-active suspensions were proposed in the early 1970s [1], and can be nearly as effective as active suspensions. When the control system fails, the semi-active suspension can still work under passive conditions. Compared with active and passive suspension systems, the semi-active suspension system combines the advantages of both active and passive suspensions because it provides better performance when compared with passive suspensions and is economical, safe and does not require either higher-power actuators or a large power supply as active suspensions do [2]

High-Performance Tracking for Piezoelectric Actuators Using Super-Twisting Algorithm Based on Artificial Neural Networks

Piezoelectric actuators (PEA) are frequently employed in applications where nano-Micr-odisplacement is required because of their high-precision performance. However, the positioning is affected substantially by the hysteresis which resembles in an nonlinear effect. In addition, hysteresis mathematical models own deficiencies that can influence on the reference following performance. The objective of this study was to enhance the tracking accuracy of a commercial PEA stack actuator with the implementation of a novel approach which consists in the use of a Super-Twisting Algorithm (STA) combined with artificial neural networks (ANN). A Lyapunov stability proof is bestowed to explain the theoretical solution. Experimental results of the proposed method were compared with a proportional-integral-derivative (PID) controller. The outcomes in a real PEA reported that the novel structure is stable as it was proved theoretically, and the experiments provided a significant error reduction in contrast with the PID.This research was funded by Basque Government and UPV/EHU projects

Hysteresis Modeling and Adaptive Model Predictive Control of Tap-Water Driven McKibben Muscles

芝浦工業大学201

Modelling and control of magnetorheological dampers for vehicle suspension systems

Magnetorheological (MR) dampers are adaptive devices whose properties can be adjusted through the application of a controlled voltage signal. A semi-active suspension system incorporating MR dampers combines the advantages of both active and passive suspensions. For this reason, there has been a continuous effort to develop control algorithms for MR-damped vehicle suspension systems to meet the requirements of the automotive industry. The overall aims of this thesis are twofold: (i) The investigation of non-parametric techniques for the identification of the nonlinear dynamics of an MR damper. (ii) The implementation of these techniques in the investigation of MR damper control of a vehicle suspension system that makes minimal use of sensors, thereby reducing the implementation cost and increasing system reliability. The novel contributions of this thesis can be listed as follows: 1- Nonparametric identification modelling of an MR damper using Chebyshev polynomials to identify the damping force from both simulated and experimental data. 2- The neural network identification of both the direct and inverse dynamics of an MR damper through an experimental procedure. 3- The experimental evaluation of a neural network MR damper controller relative to previously proposed controllers. 4- The application of the neural-based damper controller trained through experimental data to a semi-active vehicle suspension system. 5- The development and evaluation of an improved control strategy for a semi-active car seat suspension system using an MR damper. Simulated and experimental validation data tests show that Chebyshev polynomials can be used to identify the damper force as an approximate function of the displacement, velocity and input voltage. Feed-forward and recurrent neural networks are used to model both the direct and inverse dynamics of MR dampers. It is shown that these neural networks are superior to Chebyshev polynomials and can reliably represent both the direct and inverse dynamic behaviours of MR dampers. The neural network models are shown to be reasonably robust against significant temperature variation. Experimental tests show that an MR damper controller based a recurrent neural network (RNN) model of its inverse dynamics is superior to conventional controllers in achieving a desired damping force, apart from being more cost-effective. This is confirmed by introducing such a controller into a semi-active suspension, in conjunction with an overall system controller based on the sliding mode control algorithm. Control performance criteria are evaluated in the time and frequency domains in order to quantify the suspension effectiveness under bump and random road excitations. A study using the modified Bouc-Wen model for the MR damper, and another study using an actual damper fitted in a hardware-in-the-loop- simulation (HILS), both show that the inverse RNN damper controller potentially gives significantly superior ride comfort and vehicle stability. It is also shown that a similar control strategy is highly effective when used for a semi-active car seat suspension system incorporating an MR damper.EThOS - Electronic Theses Online ServiceEgyptian GovenmentGBUnited Kingdo

Advanced Control of Piezoelectric Actuators.

168 p.A lo largo de las últimas décadas, la ingeniería de precisión ha tenido un papel importante como tecnología puntera donde la tendencia a la reducción de tamaño de las herramientas industriales ha sido clave. Los procesos industriales comenzaron a demandar precisión en el rango de nanómetros a micrómetros. Pese a que los actuadores convencionales no pueden reducirse lo suficiente ni lograr tal exactitud, los actuadores piezoeléctricos son una tecnología innovadora en este campo y su rendimiento aún está en estudio en la comunidad científica. Los actuadores piezoeléctricos se usan comúnmente en micro y nanomecatrónica para aplicaciones de posicionamiento debido a su alta resolución y fuerza de actuación (pueden llegar a soportar fuerzas de hasta 100 Newtons) en comparación con su tamaño. Todas estas características también se pueden combinar con una actuación rápida y rigidez, según los requisitos de la aplicación. Por lo tanto, con estas características, los actuadores piezoeléctricos pueden ser utilizados en una amplia variedad de aplicaciones industriales. Los efectos negativos, como la fluencia, vibraciones y la histéresis, se estudian comúnmente para mejorar el rendimiento cuando se requiere una alta precisión. Uno de los efectos que más reduce el rendimiento de los PEA es la histéresis. Esto se produce especialmente cuando el actuador está en una aplicación de guiado, por lo que la histéresis puede inducir errores que pueden alcanzar un valor de hasta 22%. Este fenómeno no lineal se puede definir como un efecto generado por la combinación de acciones mecánicas y eléctricas que depende de estados previos. La histéresis se puede reducir principalmente mediante dos estrategias: rediseño de materiales o algoritmos de control tipo feedback. El rediseño de material comprende varias desventajas por lo que el motivo principal de esta tesis está enfocado al diseño de algoritmos de control para reducir la histéresis. El objetivo principal de esta tesis es el desarrollo de estrategias de control avanzadas que puedan mejorar la precisión de seguimiento de los actuadores piezoeléctricos comerciale

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

Enhancing the Structural Performance with Active and Semi-Active Devices Using Adaptive Control Strategy

Changes in the characteristics of the structure, such as damage, have not been considered in most of the active and semi-active control methods that have been used to control and optimize the response of civil engineering structures. In this dissertation, a direct adaptive control which can deal with the existence of measurement errors and changes in structural characteristics or load conditioning is used to control the performance of structures. A Simple Adaptive Control Method (SACM) is modified to control civil structures and improve their performance. The effectiveness of the SACM is verified by several numerical examples. The SACM is used to reduce the structural response such as drift and acceleration using active and semi-active devices, and its performance is compared with that of other control methods. Also, a probabilistic indirect adaptive control method is developed and its behavior is compared to the SACM using a simple numerical example. In addition to the simplicity of the SACM implementation, the results show that SACM is very effective to reduce the response of structures with linear and non-linear behavior in comparison with other control methods

Modeling and Control of Magnetostrictive-actuated Dynamic Systems

Magnetostrictive actuators featuring high energy densities, large strokes and fast responses appear poised to play an increasingly important role in the field of nano/micro positioning applications. However, the performance of the actuator, in terms of precision, is mainly limited by 1) inherent hysteretic behaviors resulting from the irreversible rotation of magnetic domains within the magnetostrictive material; and 2) dynamic responses caused by the inertia and flexibility of the magnetostrictive actuator and the applied external mechanical loads. Due to the presence of the above limitations, it will prevent the magnetostrictive actuator from providing the desired performance and cause the system inaccuracy. This dissertation aims to develop a modeling and control methodology to improve the control performance of the magnetostrictive-actuated dynamic systems. Through thorough experimental investigations, a dynamic model based on the physical principle of the magnetostrictive actuator is proposed, in which the nonlinear hysteresis effect and the dynamic behaviors can both be represented. Furthermore, the hysteresis effect of the magnetostrictive actuator presents asymmetric characteristics. To capture these characteristics, an asymmetric shifted Prandtl-Ishlinskii (ASPI) model is proposed, being composed by three components: a Prandtl-Ishlinskii (PI) operator, a shift operator and an auxiliary function. The advantages of the proposed model are: 1) it is able to represent the asymmetric hysteresis behavior; 2) it facilitates the construction of the analytical inverse; 3) the analytical expression of the inverse compensation error can also be derived. The validity of the proposed ASPI model and the entire dynamic model was demonstrated through experimental tests on the magnetostrictive-actuated dynamic system. According to the proposed hysteresis model, the inverse compensation approach is applied for the purpose of mitigating the hysteresis effect. However, in real systems, there always exists a modeling error between the hysteresis model and the true hysteresis. The use of an estimated hysteresis model in deriving the inverse compensator will yield some degree of hysteresis compensation error. This error will cause tracking error in the closed-loop control system. To accommodate such a compensation error, an analytical expression of the inverse compensation error is derived first. Then, a prescribed adaptive control method is developed to suppress the compensation error and simultaneously guaranteeing global stability of the closed loop system with a prescribed transient and steady-state performance of the tracking error. The effectiveness of the proposed control scheme is validated on the magnetostrictive-actuated experimental platform. The experimental results illustrate an excellent tracking performance by using the developed control scheme