Robust control of systems with output hysteresis and input saturation using a finite time stability approach

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a robust control approach for a class of nonlinear dynamic systems consisting of a linear plant connected in series with a hysteresis operator, and affected by control input saturation. Such a class of systems commonly appears in applications concerning smart materials, in particular thermal shape memory alloys wire actuators. The goal of this paper is to design a robust controller, in the form of an output PI law, which ensures set-point regulation with a desired decay rate and, at the same time, accounts for the effects of both hysteresis and input saturation. The resulting controller appears as attractive on the implementation stand-point, since no accurate hysteresis compensator is required. In order to deal with the proposed problem, the hysteretic plant is first reformulated as a linear parameter-varying system. Subsequently, a finite time stability approach is used to impose constraints on the control input. A new set of bilinear matrix inequalities is developed, in order to perform the design with reduced conservatism by properly exploiting some structural properties of the model. The effectiveness of the method is finally validated by means of a numerical case of study. © 2018 IEEE.Peer ReviewedPostprint (author's final draft

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

Sinteza H-beskonačno regulatora s unaprijednom granom za kompenzaciju histereze kod piezoelektričnih aktuatora

Piezoelectric actuators, widely used in different micro/nanopositioning applications, generally exhibit nonlinear hysteresis characteristics. The compensation of hysteretic behavior of piezoelectric actuators is mandatory for precise micro/nanopositioning. In this paper, nonlinear hysteresis effect is first characterized using the Prandtl-Ishlinskii hysteresis model. The inverse of the Prandtl-Ishlinskii hysteresis model is employed as a feed-forward controller to compensate for hysteresis nonlinearities of the piezoelectric actuator. Slight hysteresis nonlinearity is still observed in the experimental results due to small mismatch between the identified hysteresis model and the measured hysteresis loop. To further enhance the performance of the piezoelectric actuator in terms of mitigation of hysteresis nonlinearity and precise reference tracking, advanced robust full-order as well as fixed-order H-infinity feedback controllers are designed and applied to this actuator in the presence of feed-forward compensator. The experimental results verify the effectiveness of the proposed control scheme in achieving the improved tracking performance with peak-to-peak tracking error of less than 1% for the desired displacement of 12 um with tracking frequency of 10 Hz.Piezoelektrični aktuatori, rasprostranjeni u različitim primjenama mikro/nanopozicioniranja, općenito su izloženi nelinearnim histereznim karakteristikama. Kompenzacija histereznog ponašanja piezoelektričnih aktuatora nužna je za precizno mikro/nanopozicioniranje. Inverzni Prandtl-Ishlinskii histerezni model korišten je za unaprijednu kompenzaciju histereznih nelinearnosti piezoelektričnog aktuatora. Neznatna histerezna nelinearnost još uvijek je vidljiva u eksperimentalnim rezultatima zbog malog neslaganja između identificiranog histereznog modela i mjerene histerezne petlje. Za daljnje poboljšanje performansi piezoelektričnog aktuatora u smislu smanjenja histerezne nelinearnosti i preciznog slijeđenja reference, napredni robusni H-beskonačno regulatori punog i određenog reda sintetizirani su i primijenjeni na ovaj aktuator uz prisutnost unaprijednog kompenzatora. Eksperimentalni rezultati potvrđuju efektivnost predložene upravljačke strukture u postizanju poboljšanih performansi slijeđenja, uz vršnu vrijednost pogreške manju od 1% za ciljani pomak od 12 um s frekvencijom slijeđenja od 10 Hz

Adaptive, Intelligent Methods for Real Time Structural Control and Health Monitoring

By framing the structural health monitoring and control problem as being one of enhancing structural system intelligence, novel solutions can be achieved through applications of computational strategies that mimic human learning and attempt to replicate human response to sensory feedback. This thesis proposes several new methods which promote adaptive, intelligent decision making by structural systems relying on sensory feedback and actuator compensation. Four significant contributions can be found in this thesis study. The first method employs an adaptable subclass of Artificial Neural Networks (ANNs), called Radial Basis Function Networks (RBFNs) for robust control in the presence of sensory failure. The second method exploits this computationally efficient network to detect and isolate system faults in real time. The third algorithm utilizes an RBFN to effectively linearize the nonlinear actuator dynamics of a Magnetorheological (MR) damper, thereby improving control of the semiactive device. Lastly, an open loop observer is implemented experimentally to both detect damage and act as a trigger for control of the newly developed Adaptive Length Pendulum-Smart Tuned Mass Damper (ALP-STMD). Some limitation of existing algorithms in the field of real time structural health monitoring and control are that they rely heavily on fixed parameter methods, assume standard linear time invariant assumptions, or mandate accurate modeling of system dynamics. By embedding the proposed reasoning and decision making algorithms into the feedback methodology and design, greater generalization and system adaptivity is possible. Specifically, the proposed methods develop novel solutions for adaptive neural control, fault (sensor failure) tolerant control, real time damage detection, adaptive dynamic inversion, and control applications for STMDs. The neural network adaptive control formulation is successful in rejecting first mode disturbances despite online sensor failure. It is also capable of improving the performance of a baseline Hoc controller in the presence of sensor failure and earthquake ground motion. The proposed fault tolerant controller is validated on a two degree of freedom shear frame subjected to six earthquake records. Furthermore, this application involves the use of piezoelectric patches as sensors and actuators. The RBFN algorithm in combination with an open loop observer is capable of both detecting and isolating stiffness degradation and recovery in multi-degree of freedom systems in real time. The method is validated on experimental data taken from online damage tests using the Semi-Active Independent Variable Stiffness (SAIVS) device. Other validations involve simulations on a two degree of freedom system and a ten degree of freedom system with both independent and coupled damage case scenarios. In all scenarios, the RBFN is capable of identifying the length of time and degree of freedom in which stiffness variation occurred. A neural network formulation is developed to perform dynamic inversion for semiactive control of an MR damper. The MR damper acts as a base isolator in a scaled two story building. Both the building and damper models were based on tests performed at Rice University. The control performance of the adaptive RBFN dynamic inversion method is compared to both passive-off and passive-on methods of semiactive control for MR dampers. The last contribution serves to combine both real time structural health monitoring and control in a proof of concept experimental study. An open loop observer is used to trigger an ALP -STMD device in the presence of base excitation and stiffness damage. The stiffness damage is generated from strategically regulating the current applied to Shape Memory Alloy (SMA) braces in a two degree of freedom shear frame. Once damage exceeds a predefined threshold, the ALP-STMD uses a another SMA to adjust its pendulum length to tune in real time to the dominant pulse present in the base excitation

Computational Methods for Design of Smart Material Morphing Structures with Localized Activation and Actuation

There is significant ongoing interest to develop smart structure technologies, such as those that can automatically detect their condition and/or actively change their geometry or material behaviors to adapt to adverse conditions or otherwise improve operational efficiency. Of the structural materials under development for smart structure applications, active smart materials are attracting increasing attentions due to their abilities to exhibit controlled variable stiffness through activation (e.g., thermal, electrical, or light activation) and experience extremely large deformations and shape changes without damage. Active smart materials, such as shape memory polymers, are currently being explored and show promise as morphing skins, replacements to mechanical hinges, and other structural components. Moreover, in a general sense any structure or structural component that is fully composed of active smart materials could have limitless shape-changing functionality if provided sufficient activation and actuation. Towards the design or control of smart structures to utilize such functionality, it is of paramount importance to develop strategies to efficiently solve the coupled multi-physics inverse problems of identifying the optimal activation stimulus and mechanical actuation to achieve desired morphing processes. The objective of the present work is to develop and investigate a computational strategy for computationally efficient estimation of the parameters relating to the distribution and sequencing of activation and actuation for a morphing smart material structure or structural component to efficiently and effectively achieve a desired morphing function. This strategy combines a numerical representation of the morphing process with an optimization algorithm to estimate the activation and actuation parameters that best address cost functions and constraints relating to energy consumption, target shape change(s), morphing time, and/or damage prevention. In particular, the strategy is presented in the context of morphing structures or structural components composed of thermally responsive smart materials, and with specific properties based on thermally responsive shape memory polymers. First, as a proof of concept, an initial computational framework is presented which combines a numerical representation of linear thermo-mechanical behavior of conceptual smart material structures with a non-gradient based optimization technique to identify the activation and actuation parameters to achieve the desired morphing process. The computational inverse mechanics approach is shown through numerical tests to provide a generalized and flexible means to facilitate the use of smart material structures to achieve desired morphing processes with controllable localized activation and actuation. Towards improving the computational efficiency, a variation of the computational framework based on a gradient-based optimization algorithm using the adjoint method is then presented. Numerical examples are shown to verify and test the computational approach, in which the synchronization of multiple activation and actuation parameters is optimized with respect to the energy cost and target shape changes in morphing skeletal structural components. The computational design approach with the adjoint method is shown to provide the capability to efficiently identify activation and actuation parameters to achieve desired morphing capabilities. Moreover, the computational approach is shown to be capable of determining energy-efficient design solutions for a diverse set of target shape changes with fixed instrumentation, providing the potential for substantial functionality beyond what could be expected through traditional empirical design strategies. Finally, to establish the theories and implementation aspects that would be applicable to a variety of structural behaviors, material types and morphing concepts, the efficient computational framework using the adjoint method is generalized to be applicable to various thermally-responsive smart materials. Numerical tests are shown to verify the generalized computational framework, in which the synchronization of multiple activation and actuation parameters is optimized with respect to energy cost and target shape changes in morphing structures with nonlinear thermo-mechanical behaviors (rather than the purely linear behaviors considered previously). In addition, the significant influence of the nonlinearity in the thermal modeling on the morphing processes, and ultimately the design solutions is explored

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

Fuzzy Controllers

Trying to meet the requirements in the field, present book treats different fuzzy control architectures both in terms of the theoretical design and in terms of comparative validation studies in various applications, numerically simulated or experimentally developed. Through the subject matter and through the inter and multidisciplinary content, this book is addressed mainly to the researchers, doctoral students and students interested in developing new applications of intelligent control, but also to the people who want to become familiar with the control concepts based on fuzzy techniques. Bibliographic resources used to perform the work includes books and articles of present interest in the field, published in prestigious journals and publishing houses, and websites dedicated to various applications of fuzzy control. Its structure and the presented studies include the book in the category of those who make a direct connection between theoretical developments and practical applications, thereby constituting a real support for the specialists in artificial intelligence, modelling and control fields