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

Precision Control of Piezo Electric Actuator

芝浦工業大学201

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

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

Design and Control of Electrical Motor Drives

Dear Colleagues, I am very happy to have this Special Issue of the journal Energies on the topic of Design and Control of Electrical Motor Drives published. Electrical motor drives are widely used in the industry, automation, transportation, and home appliances. Indeed, rolling mills, machine tools, high-speed trains, subway systems, elevators, electric vehicles, air conditioners, all depend on electrical motor drives.However, the production of effective and practical motors and drives requires flexibility in the regulation of current, torque, flux, acceleration, position, and speed. Without proper modeling, drive, and control, these motor drive systems cannot function effectively.To address these issues, we need to focus on the design, modeling, drive, and control of different types of motors, such as induction motors, permanent magnet synchronous motors, brushless DC motors, DC motors, synchronous reluctance motors, switched reluctance motors, flux-switching motors, linear motors, and step motors.Therefore, relevant research topics in this field of study include modeling electrical motor drives, both in transient and in steady-state, and designing control methods based on novel control strategies (e.g., PI controllers, fuzzy logic controllers, neural network controllers, predictive controllers, adaptive controllers, nonlinear controllers, etc.), with particular attention to transient responses, load disturbances, fault tolerance, and multi-motor drive techniques. This Special Issue include original contributions regarding recent developments and ideas in motor design, motor drive, and motor control. The topics include motor design, field-oriented control, torque control, reliability improvement, advanced controllers for motor drive systems, DSP-based sensorless motor drive systems, high-performance motor drive systems, high-efficiency motor drive systems, and practical applications of motor drive systems. I want to sincerely thank authors, reviewers, and staff members for their time and efforts. Prof. Dr. Tian-Hua Liu Guest Edito

Adaptive Neural Network Fixed-Time Control Design for Bilateral Teleoperation With Time Delay.

In this article, subject to time-varying delay and uncertainties in dynamics, we propose a novel adaptive fixed-time control strategy for a class of nonlinear bilateral teleoperation systems. First, an adaptive control scheme is applied to estimate the upper bound of delay, which can resolve the predicament that delay has significant impacts on the stability of bilateral teleoperation systems. Then, radial basis function neural networks (RBFNNs) are utilized for estimating uncertainties in bilateral teleoperation systems, including dynamics, operator, and environmental models. Novel adaptation laws are introduced to address systems' uncertainties in the fixed-time convergence settings. Next, a novel adaptive fixed-time neural network control scheme is proposed. Based on the Lyapunov stability theory, the bilateral teleoperation systems are proved to be stable in fixed time. Finally, simulations and experiments are presented to verify the validity of the control algorithm

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