Robust adaptive controls of nonlinear systems with actuator hysteresis represented by Prandtl-Ishlinskii models

The development of control techniques to mitigate the effects of unknown hysteresis preceding with plants, has recently re-attracted significant attention. This thesis deals with robust adaptive control of nonlinear systems preceded by unknown hysteresis nonlinearities. In the literature, the most common methods to reduce hysteresis effects to the controlled systems are based on the inverse hysteresis compensations. Due to the complexity of hysteresis behavior, this approach has its limit. By thoroughly investigating the Prandtl-Ishlinskii models of hysteresis, a robust adaptive control scheme was developed, which makes it possible to fuse the model of hysteresis with the available control techniques without necessarily constructing a hysteresis inverse. The global stability of the adaptive system and to track a desired trajectory to a certain precision are achieved. Two classes of nonlinear systems preceded by unknown hysteresis nonlinearities are studied. One class of systems is with parametric uncertainties and known nonlinear functions. By integrating proposed hysteresis adaptation law with sliding mode control and back-stepping techniques, the global stability and tracking a desired trajectory to a certain precision are achieved. Simulation results attained for an example of this class of nonlinear system are presented to illustrate and further validate the effectiveness of the proposed approaches. Then the approach is extended to a more general class of systems in the presence of parametric uncertainties and unknown nonlinear functions with bounded disturbances and preceded by unknown hysteresis nonlinearities. Combined with neural networks adaptation control method, it is proved that for any bounded initial conditions, all closed-loop signals are bounded and the state vector x ( t ) converges to a neighborhood of the desired trajectory. Concerning the practical applications, determination of the density function of the Prandtl-Ishlinskii model is crucial. In this study, a discretional approach is developed to approximate density function p ( r ) based on the memory effects of the play operator F r [ v ]( t

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

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

Generalized Prandtl-Ishlinskii hysteresis model and its analytical inverse for compensation of hysteresis in smart actuators

Smart actuators such as piezoceramics, magnetostrictive and shape memory alloy actuators, invariably, exhibit hysteresis, which has been associated with oscillations in the open-loop system's responses, and poor tracking performance and potential instabilities of the close-loop system. A number of phenomological operator-based hysteresis models such as the Preisach model, Krasnosel'skii-Pokrovskii model and Prandtl-Ishlinskii model, have been formulated to describe the hysteresis nonlinearities and to seek compensation of the hysteresis effects. Among these, the Prandtl-Ishlinskii model offers greater flexibility and unique property that its inverse can be attained analytically. The Prandtl-Ishlinskii model, however, is limited to rate-independent and symmetric hysteresis nonlinearities. In this dissertation research, the unique flexibility of the Prandtl-Ishlinskii model is explored for describing the symmetric as well as nonlinear hysteresis and output saturation properties of smart actuators, and for deriving an analytical inverse for effective compensation. A generalized play operator with dissimilar envelope functions is proposed to describe asymmetric hysteresis and output saturation nonlinearities of different smart actuators, when applied in conjunction with the classical Prandtl-Ishlinskii model. Dynamic density and dynamic threshold functions of time rate of the input are further proposed and integrated in the classical model to describe rate-dependent symmetric and asymmetric hysteresis properties of smart actuators. A fundamental relationship between the thresholds of the classical and the resulting generalized models is also formulated to facilitate parameters identification. The validity of the resulting generalized Prandtl-Ishlinskii models is demonstrated using the laboratory-measured data for piezoceramic, magnetostrictive and SMA actuators under different inputs over a broad range of frequencies. The results suggest that the proposed generalized models can effectively characterize the rate-dependent as well as rate-independent hysteresis properties of a broad class of smart actuators with output saturation. The properties of the proposed generalized models are subsequently explored to derive its inverse to seek an effective compensator for the asymmetric as well as rate-dependent hysteresis effects. The resulting inverse is applied as a feedforward compensator and simulation results are obtained to demonstrate its effectiveness in compensating the symmetric as well as asymmetric hysteresis of different smart actuators. The effectiveness of the proposed analytical inverse model-based real-time compensator is further demonstrated through its implementation in the laboratory for a piezoceramic actuator. Considering that the generalized Prandtl-Ishlinskii model provides an estimate of the hysteresis properties and the analytical inverse is a hysteresis model, the output of the inverse compensation is expected to yield hysteresis, although of a considerably lower magnitude. The expected compensation error, attributed to possible errors in hysteresis characterization, is analytically derived on the basis of the generalized model and its inverse. The design of a robust controller is presented for a system preceded by the hysteresis effects of an actuator using the proposed error model. The primary purpose is to fuse the analytical inverse compensation error model with an adaptive controller to achieve to enhance tracking precision. The global stability of the chosen control law and the entire closed-loop system is also analytically established. The results demonstrated significantly enhanced tracking performance, when the inverse of the estimated Prandtl-Ishlinskii model is considered in the closed-loop control system

On the adaptive controls of nonlinear systems with different hysteresis model representations

The hysteresis phenomenon occurs in diverse disciplines ranging from physics to biology, from material science to mechanics, and from electronics to economics. When the hysteresis nonlinearity precedes a controlled system, the nonlinearity usually causes the overall closed-loop system to exhibit inaccuracies or oscillations, even leading to instability. Control techniques to mitigate the unwanted effects of hysteresis have been studied for decades and have recently once again attracted significant attention. In this thesis, several adaptive control strategies are developed for systems with different hysteresis model representations to guarantee the basic stability requirement of the closed-loop systems and to track a desired trajectory with a certain precision. These proposed strategies to mitigate the effects of hysteresis are as follows: i). With the classical Duhem model, an observer-based adaptive control scheme for a piezoelectric actuator system is proposed. Due to the unavailability of the hysteresis output, an observer-based adaptive controller incorporating a pre-inversion neural network compensator is developed for the purpose of mitigating the hysteretic effects; ii). With the Prandtl-Ishlinskii model, an adaptive tracking control approach is developed for a class of nonlinear systems in p-normal form by using the technique of adding a power integrator to address the challenge of how to fuse this hysteresis model with the control techniques to mitigate hysteresis, without necessarily constructing a hysteresis inverse; iii). With a newly proposed hysteresis model using play-like operators, two control strategies are proposed for a class of nonlinear systems: one with sliding mode control and the other with backstepping technique

Adaptive neural network control of a robotic manipulator with unknown backlash-like hysteresis

This study proposes an adaptive neural network controller for a 3-DOF robotic manipulator that is subject to backlashlike hysteresis and friction. Two neural networks are used to approximate the dynamics and the hysteresis non-linearity. A neural network, which utilises a radial basis function approximates the robot's dynamics. The other neural network, which employs a hyperbolic tangent activation function, is used to approximate the unknown backlash-like hysteresis. The authors also consider two cases: full state and output feedback control. For output feedback, where system states are unknown, a high gain observer is employed to estimate the states. The proposed controllers ensure the boundedness of the control signals. Simulations are also performed to show the effectiveness of the controllers

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

Adaptive neural control of nonlinear systems with hysteresis

Ph.DDOCTOR OF PHILOSOPH

A stop operator-based Prandtl-Ishlinskii model for compensation of smart actuator hysteresis effects

The positioning and tracking performance of smart materials actuators is strongly limited due to the presence of hysteresis nonlinearity. The hysteresis of smart actuators, employed in micro-positioning tasks, is known to cause oscillations in the open-loop system's responses, and poor tracking performance and potential instabilities of the close-loop system. Considerable efforts are thus being made continuously to seek effective compensation of hysteresis effects in real-time applications. In this dissertation research, a stop operator-based-Prandtl-Ishlinskii model (SOPI) is proposed as a feedforward compensator for the hysteresis nonlinearities in smart actuators. The complementary properties of the proposed stop operator-based model in relation to the most widely used play operator-based Prandtl-Ishlinskii model are illustrated and applied to realize the desired compensation. It is shown that the stop operator-based model yields hysteresis loops in the clockwise direction, opposite to that of the piezoceramic micro-positioning actuators. It is further proven that the stop operator-based model exhibits concave initial loading behavior, while the play operator-based model, used to characterize the hysteresis behavior, follows a convex initial loading relation between the output and the input. On the basis of these complementary properties, it is hypothesized that a stop operator-based Prandtl-Ishlinskii model may serve as an effective compensator for known hysteresis nonlinearity that is described 'by a play operator-based model. The proposed stop operator-based model is subsequently implemented as a feedforward compensator in conjunction with the play operator-based model describing a known hysteresis nonlinearity. The effectiveness of the proposed compensator is demonstrated through simulation and experimental results attained with a piezoceramic micro-positioning stage. Both the simulation and the experimental results show that the proposed stop operator-based model can serve as an effective feedforward hysteresis compensator. A methodology for identifying the stop operator-based model parameters is proposed using those of a known play operator hysteresis model. Relations between the stop and play operator based-model parameters are also derived in the order to facilitate parameter identification. Furthermore, the relation between the stop operator based Prandtl-Ishlinskii model and the inverse Prandtl-Ishlinskii model, which has been proven effective hysteresis compensator, is demonstrated