Xiaobo Tan

Modeling of Biomimetic Robotic Fish Propelled by An Ionic Polymer–Metal Composite Caudal Fin

In this paper, a physics-based model is proposed for a biomimetic robotic fish propelled by an ionic polymer-metal composite (IPMC) actuator. Inspired by the biological fin structure, a passive plastic fin is further attached to the IPMC beam. The model incorporates both IPMC actuation dynamics and the hydrodynamics, and predicts the steady-state cruising speed of the robot under a given periodic actuation voltage. The interactions between the plastic fin and the IPMC actuator are also captured in the model. Experimental results have shown that the proposed model is able to predict the motion of robotic fish for different tail dimensions. Since most of the model parameters are expressed in terms of fundamental physical properties and geometric dimensions, the model is expected to be instrumental in optimal design of the robotic fish.

Adaptive identification and control of hysteresis in smart materials

Hysteresis hinders the effective use of smart materials in sensors and actuators. This paper addresses recursive identification and adaptive inverse control of hysteresis in smart material actuators, where hysteresis is modeled by a Preisach operator with a piecewise uniform density function. Two classes of identification schemes are proposed and compared, one based on the hysteresis output, the other based on the time-difference of the output. Conditions for parameter convergence are presented in terms of the input to the Preisach operator. An adaptive inverse control scheme is developed by updating the Preisach operator (and thus its inverse) with the output-based identification method. The asymptotic tracking property of this scheme is established, and for periodic reference trajectories, the parameter convergence behavior is characterized. Practical issues in the implementation of the adaptive identification and inverse control methods are also investigated. Simulation and experimental results based on a magnetostrictive actuator are provided to illustrate the proposed approach.

A Control-Oriented and Physics-Based Model for Ionic Polymer--Metal Composite Actuators

Ionic polymer-metal composite (IPMC) actuators have promising applications in biomimetic robotics, biomedical devices, and micro/nanomanipulation. In this paper, a physics- based model is developed for IPMC actuators, which is amenable to model reduction and control design. The model is represented as an infinite-dimensional transfer function relating the bending displacement to the applied voltage. It is obtained by exactly solving the governing partial differential equation in the Laplace domain for the actuation dynamics, where the effect of the distributed surface resistance is incorporated. The model is expressed in terms of fundamental material parameters and actuator dimensions, and is thus, geometrically scalable. To illustrate the utility of the model in controller design, an Hinfin controller is designed based on the reduced model and applied to tracking control. Experimental results are presented to validate the proposed model and its effectiveness in real-time control design.

Approximate inversion of the Preisach hysteresis operator with application to control of smart actuators

Hysteresis poses a challenge for control of smart actuators. A fundamental approach to hysteresis control is inverse compensation. For practical implementation, it is desirable for the input function generated via inversion to have regularity properties stronger than continuity. In this paper, we consider the problem of constructing right inverses for the Preisach model for hysteresis. Under mild conditions on the density function, we show the existence and weak-star continuity of the right-inverse, when the Preisach operator is considered to act on Holder continuous functions. Next, we introduce the concept of regularization to study the properties of approximate inverse schemes for the Preisach operator. Then, we present the fixed point and closest-match algorithms for approximately inverting the Preisach operator. The convergence and continuity properties of these two numerical schemes are studied. Finally, we present the results of an open-loop trajectory tracking experiment for a magnetostrictive actuator.

Modeling and control of a magnetostrictive actuator

The rate-dependent hysteresis existing in magnetostrictive actuators presents a challenge in control of these actuators. In this paper we propose a novel dynamical model for the hysteresis in a thin magnetostrictive actuator. The model features the coupling of the Preisach operator with an ordinary differential equation (ODE). We prove the well-posedness of the model, study the parameter identification methods, and propose an inverse control scheme. The effectiveness of the identification and inverse control schemes is demonstrated through experimental results.

Control of hysteretic systems through inverse compensation

Inverse compensation is a fundamental technique in the control of systems with hysteresis. In this expository article, we present algorithms for constructing the inverse of the Preisach operator, a hysteresis model with application to magnetics, smart materials, terrestrial hydrology, and economics. Adaptive inverse control is discussed for cases where hysteresis parameters are not known precisely. To meet the demand of highly dynamic applications, an embedded inversion approach is presented that exploits the parallelism offered by FPGAs.

A dynamic model for ionic polymer-metal composite sensors

A dynamic, physics-based model is presented for ionic polymer–metal composite (IPMC) sensors. The model is an infinite-dimensional transfer function relating the short-circuit sensing current to the applied deformation. It is obtained by deriving the exact solution to the governing partial differential equation (PDE) for the sensing dynamics, where the effect of distributed surface resistance is incorporated. The PDE is solved in the Laplace domain, subject to the condition that the charge density at the boundary is proportional to the applied stress. The physical model is expressed in terms of fundamental material parameters and sensor dimensions and is thus scalable. It can be easily reduced to low-order models for real-time conditioning of sensor signals in targeted applications of IPMC sensors. Experimental results are provided to validate the proposed model.

An Autonomous Robotic Fish for Mobile Sensing

In this paper an innovative approach to robotics education is reported, where hands-on learning is integrated with cutting-edge research in the development of an autonomous, biomimetic robotic fish. The project aims to develop an energy-efficient, noiseless, untethered swimming robot for mobile sensing purposes. The robot is propelled by an ionic polymer-metal composite (IPMC) actuator and equipped with a GPS receiver, a ZigBee wireless communication module, a microcontroller, and a temperature sensor for autonomous navigation, control, and sensing. The two phases of the development are described, emphasizing both the technical approaches and the learning paradigms. The developed robotic fish will be further used as an educational kit for K-12 students and as a research tool for investigating multi-robot collaborative sensing

Quasi-Static Positioning of Ionic Polymer-Metal Composite (IPMC) Actuators

Ionic polymer-metal composites (IPMCs) generate large bending motions under a low driving voltage (about 1 V). In this paper quasi-static actuation of IPMC is investigated with the goal of precise positioning. It is found that IPMC exhibits hysteresis between its bending curvature and the applied quasi-static voltage. The Preisach operator is proposed to model the hysteresis, and its density function identified experimentally. An open-loop positioning strategy is presented based on efficient inversion of the Preisach operator, and its efficacy is demonstrated by experimental results. Finally a cascaded model structure is proposed to capture both the hysteresis and the dynamics of IPMC actuators.

Control of Hysteresis: Theory and Experimental Results

Hysteresis in smart materials hinders the wider applicability of such materials in actuators. In this paper, a systematic approach for coping with hysteresis is presented. The method is illustrated through the example of controlling a commercially available magnetostrictive actuator. We utilize the low-dimensional model for the magnetostrictive actuator that was developed in earlier work. For low frequency inputs, the model approximates to a rate-independent hysteresis operator, with current as its input and magnetization as its output. Magnetostrictive strain is proportional to the square of the magnetization. In this paper, we use a classical Preisach operator for the rate-independent hysteresis operator. In this paper, we present the results of experiments conducted on a commercial magnetostrictive actuator, the purpose of which was the control of the displacement/strain output. A constrained least-squares algorithm is employed to identify a discrete approximation to the Preisach measure. We then discuss a nonlinear inversion algorithm for the resulting Preisach operator, based on the theory of strictly-increasing operators. This algorithm yields a control input signal to produce a desired magnetostrictive response. The effectiveness of the inversion scheme is demonstrated via an open-loop trajectory tracking experiment.