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

Motion Control of Smart Material Based Actuators: Modeling, Controller Design and Experimental Evaluation

Smart material based actuators, such as piezoelectric, magnetostrictive, and shape memory alloy actuators, are known to exhibit hysteresis effects. When the smart actuators are preceded with plants, such non-smooth nonlinearities usually lead to poor tracking performance, undesired oscillation, or even potential instability in the control systems. The development of control strategies to control the plants preceded with hysteresis actuators has become to an important research topic and imposed a great challenge in the control society. In order to mitigate the hysteresis effects, the most popular approach is to construct the inverse to compensate such effects. In such a case, the mathematical descriptions are generally required. In the literature, several mathematical hysteresis models have been proposed. The most popular hysteresis models perhaps are Preisach model, Prandtl-Ishlinskii model, and Bouc-Wen model. Among the above mentioned models, the Prandtl-Ishlinskii model has an unique property, i.e., the inverse Prandtl-Ishlinskii model can be analytically obtained, which can be used as a feedforward compensator to mitigate the hysteresis effect in the control systems. However, the shortcoming of the Prandtl-Ishlinskii model is also obvious because it can only describe a certain class of hysteresis shapes. Comparing to the Prandtl-Ishlinskii model, a generalized Prandtl-Ishlinskii model has been reported in the literature to describe a more general class of hysteresis shapes in the smart actuators. However, the inverse for the generalized Prandtl-Ishlinskii model has only been given without the strict proof due to the difficulty of the initial loading curve construction though the analytic inverse of the Prandtl-Ishlinskii model is well documented in the literature. Therefore, as a further development, the generalized Prandtl-Ishlinskii model is re-defined and a modified generalized Prandtl-Ishlinskii model is proposed in this dissertation which can still describe similar general class of hysteresis shapes. The benefit is that the concept of initial loading curve can be utilized and a strict analytical inverse model can be derived for the purpose of compensation. The effectiveness of the obtained inverse modified generalized Prandtl-Ishlinskii model has been validated in the both simulations and in experiments on a piezoelectric micropositioning stage. It is also affirmed that the proposed modified generalized Prandtl-Ishlinskii model fulfills two crucial properties for the operator based hysteresis models, the wiping out property and the congruency property. Usually the hysteresis nonlinearities in smart actuators are unknown, the direct open-loop feedforward inverse compensation will introduce notably inverse compensation error with an estimated inverse construction. A closed-loop adaptive controller is therefore required. The challenge in fusing the inverse compensation and the robust adaptive control is that the strict stability proof of the closed loop control system is difficult to obtain due to the fact that an error expression of the inverse compensation has not been established when the hysteresis is unknown. In this dissertation research, by developing the error expression of the inverse compensation for modified generalized Prandtl-Ishlinskii model, two types of inverse based robust adaptive controllers are designed for a class of uncertain systems preceded by a smart material based actuator with hysteresis nonlinearities. When the system states are available, an inverse based adaptive variable structure control approach is designed. The strict stability proof is established thereafter. Comparing with other works in the literature, the benefit for such a design is that the proposed inverse based scheme can achieve the tracking without necessarily adapting the uncertain parameters (the number could be large) in the hysteresis model, which leads to the computational efficiency. Furthermore, an inverse based adaptive output-feedback control scheme is developed when the exactly knowledge of most of the states is unavailable and the only accessible state is the output of the system. An observer is therefore constructed to estimate the unavailable states from the measurements of a single output. By taking consideration of the analytical expression of the inverse compensation error, the global stability of the close-loop control system as well as the required tracking accuracy are achieved. The effectiveness of the proposed output-feedback controller is validated in both simulations and experiments

An inverse Prandtl–Ishlinskii model based decoupling control methodology for a 3-DOF flexure-based mechanism

A modified Prandtl–Ishlinskii (P–I) hysteresis model is developed to form the feedforward controller for a 3-DOF flexure-based mechanism. To improve the control accuracy of the P–I hysteresis model, a hybrid structure that includes backlash operators, dead-zone operators and a cubic polynomial function is proposed. Both the rate-dependent hysteresis modeling and adaptive dead-zone thresholds selection method are investigated. System identification was used to obtain the parameters of the newly-developed hysteresis model. Closed-loop control was added to reduce the influence from external disturbances such as vibration and noise, leading to a combined feedforward/feedback control strategy. The cross-axis coupling motion of the 3-DOF flexure-based mechanism has been explored using the established controller. Accordingly, a decoupling feedforward/feedback controller is proposed and implemented to compensate the coupled motion of the moving platform. Experimental tests are reported to examine the tracking capability of the whole system and features of the controller. It is demonstrated that the proposed decoupling control methodology can distinctly reduce the coupling motion of the moving platform and thus improve the positioning accuracy and trajectory tracking capability

Hysteresis Characterization andCompensation of Smart Material-BasedActuators via a New Modified Bouc-WenModel

芝浦工業大学2016年

Modeling and Control of Liquid Crystal Elastomer Based Soft Robots

Soft robots are robotic systems which are inherently compliant, and can exhibit body deformation in normal operations. This type of systems has unprecedented advantage over rigid-body robots since they can mimic biological systems to perform a series of complicated tasks, work in confined spaces, and interact with the environment much more safely. Usually, the soft robots are composed of subsystems including the actuator, the sensor, the driving electronics, the computation system, and the power source. In these subsystems, the actuator is of great importance. This is because in most situations the actuator works to carry out the operations of the soft robot. It decides the functionalities and physical features of the whole system. Meanwhile, other subsystems work to aid the successful functioning of the actuator. Thus, the study on soft robot actuators, especially the modeling and control of soft robot actuators is the key to soft robot applications. However, characteristics of soft robot actuators vary greatly due to the usage of different actuator materials. These materials include the variable length tendons, rubbers, smart materials, etc.. Among these different materials, smart material based actuators have the advantage of fast response, light weight, and can respond to various types of external stimuli such as electrical signal, magnetic signal, light, heat, etc.. As a result, smart material based actuators have been studied widely for possible soft robot applications. Recent years, among smart materials, the liquid crystal elastomer (LCE) starts to catch researchers' attention. LCE is a type of smart material which can deform under the stimulation of light. Unlike conventional actuators, the LCE actuator can be separated from the power source, suggesting a simpler and lighter design, possible for applications that are totally different from conventional electro-driven or magneto-driven actuators. However, just like other smart materials, the deformation characteristics of the LCE actuator exhibits a complicated hysteretic behavior highly dependent on environmental factors, which brings difficulty to the modeling and control. Furthermore, the deformation of the photo-responsive LCE actuator is a multi-step process, resulting greater inaccuracy when compared with conventional smart material based actuators. These are huge challenges that need to be overcome for the modeling and control of the LCE actuator, which is still in its preliminary stage. This dissertation aims to develop suitable modeling and control strategies for the photo-responsive LCE actuator with the purpose of using it in soft robot applications. Here, by looking into the physical nature of the light-induced deformation of the LCE actuator, it can be concluded that LCE's deformation is inherently the macroscopic shape change resulted from the microscopic phase change of LCE molecules. Based on this deformation mechanism, an experimental platform including a computer, an I/O module, a programmable laser, the LCE actuator, a thermal camera, and a laser distance sensor is established to study the modeling and control of the photo-responsive LCE actuator. Experiments are performed and the results show that the deformation characteristics of the LCE actuator indeed exhibit obvious hysteresis, which is dependent on environmental factors. Based on the deformation mechanism of LCE, basic modeling scheme and positioning control scheme for the photo-responsive LCE actuator are established. For the modeling of the LCE actuator, the goal is to obtain its temperature-deformation relationship and describe the hysteresis with small errors. Here, the average order parameter is introduced to give a quantitative description of the macroscopic average phase of LCE molecules. Then, the key to obtain the temperature-deformation relationship is to first find the relationship between the temperature of the LCE actuator and the average order parameter, and then find the relationship between the average order parameter and the macroscopic deformation. The overall model is the combination of the above two relationships. According to this modeling scheme, a basic physical model for the photo-responsive LCE actuator is established. This model aims to develop a quantitative model that reflects the actual physics of the LCE actuator. By assuming that the phase transition of LCE molecules is under dynamic equilibrium at each specific moment, a simple analytical relationship between the temperature and deformation of the LCE actuator can be obtained. For this model, the Landau-de Gennes expansion of free energy for nematic LCEs is utilized to calculate the average order parameter. First, under the above assumption, the relationship between the temperature and the average order parameter is obtained. Meanwhile, thermal dynamic analysis gives the relationship between the average order parameter and the deformation. The above two relationships are then combined together to give the overall model. Model parameters are calculated based on nonlinear least squares method. Experimental results show that this model works to give a good prediction of the deformation characteristics. Based on the above basic model, an improved model is then established to give a more detailed description on the hysteresis by considering the actual dynamic process of the phase transition of LCE molecules. In order to reflect the actual dynamic process, a small variation of the temperature is considered, and the corresponding number of LCE molecules that undergo phase transition is calculated based on thermal dynamic analysis and a polynomial expansion of the transition rate. As a result, a dynamic equation that gives the temperature-deformation relationship is obtained. To obtain the values of model parameters with efficiency, a two-step parameter identification method based on the differential evolution algorithm and nonlinear least squares method is established. Experiments show that the improved model can describe the hysteretic deformation characteristic of the photo-responsive LCE actuator with high accuracy. Meanwhile, based on the physical nature of the LCE actuator, the positioning control of the photo-responsive LCE actuator is studied. Analysis on the deformation of the LCE actuator from the energy perspective shows that the positioning control of the photo-responsive LCE actuator is a multi-step process, which brings difficulties in control accuracy. To reduce the positioning control errors, a double closed-loop control structure with a feed-forward module is designed for the positioning control of the photo-responsive LCE actuator. Utilizing positioning control scheme together with the developed models, controllers are designed for the positioning control of the photo-responsive LCE actuator. For the proposed double-closed loop structure, the inner loop uses a PID controller to control the temperature of the LCE actuator, the parameters of the inner loop controller are tuned using a stimulation-experiment combined method based on the Hammerstein-Wiener model. Meanwhile, the outer loop consists of a PID controller and a feed-forward controller, the feed-forward controller is a numerical inverse model of the simple physical model that is established in the modeling part, and calculates the target temperature for the inner loop based on the positioning control objective. Parameters of the outer loop controller are directly tuned through experiments. Based on the proposed control strategy, experiments with different control targets are carried out to prove that the proposed controller can achieve the positioning control target with high accuracy. Comparison experiments also show that the proposed double closed-loop structure is faster in response, and has smaller control errors than conventional single closed-loop control structure. In the end, design guidelines for LCE based soft robots are discussed from the application perspective. Designs of a two-legged walking robot and a light-controlled rolling robot based on the photo-responsive LCE actuator are introduced, conclusions are made together with possible working directions for future studies

Design, Fabrication, Modeling and Control of Artificial Muscle Actuated Wrist Joint System

This research dissertation presents the design, fabrication, modeling and control of an artificial muscle (AM) actuated wrist joint system, i.e., a thermoelectric (TEM) antagonistically driven shape memory alloy (SMA) actuator, to mimic the muscle behavior of human beings. In the developed AM based wrist joint system, the SMA, exhibiting contraction and relaxation corresponding to its temperature, is utilized as the actuator in the AM. Similar to the nerve stimulation, TEM is introduced to provide heat stimulation to the SMA, which involves heating and cooling of the SMA. SMA possesses superelastic behavior that provides a large force over its weight and effective strain in practical applications. However, such superior material has been underutilized due to its high nonlinear hysteresis behavior, strongly affected by the loading stress. Using the data obtained from the experiments, based on the Prandtl-Ishlinskii (PI) model, a Stress-Dependent Generalized Prandtl-Ishlinskii (SD-GPI) model is proposed, which can describe the hysteresis behavior of the SMA under the influence of various stresses. The parameters of the SD-GPI models at various stresses are obtained using a fitting function from the Matlab. The simulation results of the SD-GPI showed that prediction error is achieved at mean values of ±2% and a standard deviation of less than 7%. Meanwhile, the TEM model is also developed based on the heat balance theory. The model parameters are identified via experimental data using Range-Kutta fourth order integration equation and Matlab curve fitting function. The TEM model has shown a satisfactory temperature prediction. Then, by combining the obtained two models, an integrated model is developed to describe the whole dynamics of the wrist joint system. To control the SMA actuated wrist system, the SD-GPI inverse hysteresis compensator is developed to mitigate the hysteresis effect. However, such a compensator shows errors in compensating the hysteresis effect. Therefore, the inverse hysteresis compensator error and the system tracking error are analyzed, and the adaptive back-stepping based control approach is adopted to develop the inverse based adaptive control for the antagonistic AM wrist joint. Subsequently, a corresponding control law is developed for the TEM system to generate the required temperature obtained from the adaptive controller. Simulations verified the developed approach. Finally, experiments are conducted to verify the proposed system. Input sinusoidal signal with frequency 0.1rad/s and amplitude of ±0.524rad (±30°) is applied to the wrist joint system. Experimental results verified that the TEMs antagonistically driven SMA actuators for artificial muscle resembling wrist joint has been successfully achieved

From model-driven to data-driven : a review of hysteresis modeling in structural and mechanical systems

Hysteresis is a natural phenomenon that widely exists in structural and mechanical systems. The characteristics of structural hysteretic behaviors are complicated. Therefore, numerous methods have been developed to describe hysteresis. In this paper, a review of the available hysteretic modeling methods is carried out. Such methods are divided into: a) model-driven and b) datadriven methods. The model-driven method uses parameter identification to determine parameters. Three types of parametric models are introduced including polynomial models, differential based models, and operator based models. Four algorithms as least mean square error algorithm, Kalman filter algorithm, metaheuristic algorithms, and Bayesian estimation are presented to realize parameter identification. The data-driven method utilizes universal mathematical models to describe hysteretic behavior. Regression model, artificial neural network, least square support vector machine, and deep learning are introduced in turn as the classical data-driven methods. Model-data driven hybrid methods are also discussed to make up for the shortcomings of the two methods. Based on a multi-dimensional evaluation, the existing problems and open challenges of different hysteresis modeling methods are discussed. Some possible research directions about hysteresis description are given in the final section

Investigation into vibration assisted micro milling: theory, modelling and applications

PhD ThesisPrecision micro components are increasingly in demand for various engineering industries, such as biomedical engineering, MEMS, electro-optics, aerospace and communications. The proposed requirements of these components are not only in high accuracy, but also in good surface performance, such as drag reduction, wear resistance and noise reduction, which has become one of the main bottlenecks in the development of these industries. However, processing these difficult-to-machine materials efficiently and economically is always a challenging task, which stimulates the development and subsequent application of vibration assisted machining (VAM) over the past few decades. Vibration assisted machining employs additional external energy sources to generate high frequency vibration in the conventional machining process, changing the machining (cutting) mechanism, thus reducing cutting force and cutting heat and improving machining quality. The current awareness on VAM technology is incomplete and effective implementation of the VAM process depends on a wide range of technical issues, including vibration device design and setup, process parameters optimization and performance evaluation. In this research, a 2D non-resonant vibration assisted system is developed and evaluated. Cutting mechanism and relevant applications, such as functional surface generation and microfluidic chips manufacturing is studies through both experimental and finite element analysis (FEA) method. A new two-dimensional piezoelectric actuator driven vibration stage is proposed and prototyped. A double parallel four-bar linkage structure with double layer flexible hinges is designed to guide the motion and reduce the displacement coupling effect between the two directions. The compliance modelling and dynamic analysis are carried out based on the matrix method and lagrangian principle, and the results are verified by finite element analysis. A closed loop control system is developed and proposed based on LabVIEW program consisting of data acquisition (DAQ) devices and capacitive sensors. Machining experiments have been carried out to evaluate the performance of the vibration stage and the results show a good agreement with the tool tip trajectory simulation results, which demonstrates the feasibility and effectiveness of the vibration stage for vibration assisted micro milling. The textured surface generation mechanism is investigated through both modelling and experimental methods. A surface generation model based on homogenous matrices transformation is proposed by considering micro cutter geometry and kinematics of vibration assisted milling. On this basis, series of simulations are performed to provide insights into the effects of various vibration parameters (frequency, amplitude and phase difference) on the generation mechanism of typical textured surfaces in 1D and 2D vibration-assisted micro milling. Furthermore, the wettability tests are performed on the machined surfaces with various surface texture topographies. A new contact model, which considers both liquid infiltration effects and air trapped in the microstructure, is proposed for predicting the wettability of the fish scales surface texture. The following surface textures are used for T-shaped and Y-shaped microchannels manufacturing to achieve liquid one-way flow and micro mixer applications, respectively. The liquid flow experiments have been carried out and the results indicate that liquid flow can be controlled effectively in the proposed microchannels at proper inlet flow rates. Burr formation and tool wear suppression mechanisms are studied by using both finite element simulation and experiment methods. A finite element model of vibration assisted micro milling using ABAQUS is developed based on the Johnson-Cook material and damage models. The tool-workpiece separation conditions are studied by considering the tool tip trajectories. The machining experiments are carried out on Ti-6Al-4V with coated micro milling tool (fine-grain tungsten carbides substrate with ZrO2-BaCrO4 (ZB) coating) under different vibration frequencies (high, medium and low) and cutting states (tool-workpiece separation or nonseparation). The results show that tool wear can be reduced effectively in vibration assisted micro milling due to different wear suppression mechanisms. The relationship between tool wear and cutting performance is studied, and the results indicate that besides tool wear reduction, better surface finish, lower burrs and smaller chips can also be obtained as vibration assistance is added

Frontiers in Ultra-Precision Machining

Ultra-precision machining is a multi-disciplinary research area that is an important branch of manufacturing technology. It targets achieving ultra-precision form or surface roughness accuracy, forming the backbone and support of today’s innovative technology industries in aerospace, semiconductors, optics, telecommunications, energy, etc. The increasing demand for components with ultra-precision accuracy has stimulated the development of ultra-precision machining technology in recent decades. Accordingly, this Special Issue includes reviews and regular research papers on the frontiers of ultra-precision machining and will serve as a platform for the communication of the latest development and innovations of ultra-precision machining technologies