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A time-domain approach (TDA) is formulated to analyze oscillations that are induced by control valve stiction in feedback control loops. Analytical relationships are established between the proportional-integral controller parameters, and the oscillation amplitude and period of the process output. Based on the relationships and the robustness to model uncertainties, a new compensation method by tuning controller parameters is proposed to reduce the oscillation amplitude to a desired value. Compared with the describing function approach, the TDA achieves a significant improvement in accuracy in calculating the oscillation amplitude and period. By contrast to the counterparts in the literature, the proposed compensation method is quantitative and avoids tuning the controller parameters in a trial-and-error manner to compensate oscillations. Experimental examples illustrate the effectiveness of the obtained results.

Autonomous underwater gliders have become valuable tools for a myriad of applications ranging from ocean exploration to fish tracking to environmental sampling. To be suitable for these types of applications, precise sensing and monitoring is desired, which makes accurate trajectory control important. However, highly nonlinear under-actuated dynamics present significant challenges in control of gliders. In this work a backstepping-based controller is proposed for an underwater glider to track a desired position and heading reference in the sagittal plane with only two control inputs, the buoyancy and center of gravity along the longitudinal direction. In particular,the under-actuation issue is addressed by exploiting the coupled dynamics and introducing a new modified error that combines the tracking errors of heading and position references. In addition, an auxiliary system is incorporated to account for input constraints. Finally, a sliding mode observer is designed to obtain the estimates of body-fixed velocities, to facilitate practical implementation of the designed controller. The effectiveness of the proposed control scheme is demonstrated via simulations and its advantages are shown via comparison with a PID controller.

Paired pectoral fins that are capable of rowing motions are an important actuation mechanism for robotic fish. Existing work in this area typically adopts a rigid connection between the actuator and the pectoral fins, which requires a faster actuation speed in the power stroke than in the recovery stroke to produce a net thrust or moment. In addition to increasing the control complexity, the latter requirement leads to slow robot speeds due to prolonged deceleration during the recovery stroke. In this paper, we propose the design of a novel flexible passive joint that connects the servomotor arm to the pectoral fin, to overcome the aforementioned problem. A dynamic model is developed for the joint and for a robotic fish equipped with such joints. The design and the model are evaluated with extensive experimental results. With symmetric actuation patterns during the power and recovery strokes, the robotic fish with the proposed joints shows clear speed advantage over the case involving rigid joints and asymmetric actuation. Motivated by the need for design optimization, the model is further utilized to investigate the influence of the joint length and stiffness on the robot locomotion performance and efficiency. It is found that, for low fin-beat frequencies, longer or more flexible joints lead to higher speeds, and the trend is reversed at high fin-beat frequencies. On the other hand, while the mechanical efficiency shows a decreasing trend when the frequency increases, it is higher with shorter joints. These findings suggest the utility of the proposed model for multiobjective design of the joint and its operating frequency.

In this paper, a composite hysteresis model is proposed for self-sensing feedback control of vanadium dioxide ( $\mathrm{VO_2}$ )-integrated microactuators. The deflection of the microactuator is estimated with the resistance measurement through the proposed model. To capture the complicated hysteresis between the resistance and the deflection, we exploit the physical understanding that both the resistance and the deflection are determined by hysteretic relationships with the temperature. Since direct temperature measurement is not available, the concept of temperature surrogate, representing the constant current value in Joule heating that would result in a given temperature at the steady state, is explored in the modeling. In particular, the hysteresis between the deflection and the temperature surrogate and the hysteresis between the resistance and the temperature surrogate are captured with a generalized Prandtl–Ishlinskii (GPI) model and an extended GPI (EGPI) model, respectively. The composite self-sensing model is obtained by cascading the EGPI model with the inverse GPI model. For comparison purposes, two algorithms, based on a Preisach model and an EGPI model, respectively, are also used to estimate the deflection based on the resistance measurement directly. The proposed self-sensing scheme is evaluated with proportional-integral control of the microactuator under step and sinusoidal references, and its superiority over the other schemes is demonstrated by experimental results.

An artificial lateral line (ALL) system consists of a set of flow sensors around a fish-like body. An ALL system aims to identify surrounding moving objects, a common example of which is a vibrating sphere, called a dipole. Accurate identification of a vibrating dipole is a challenging task because of the presence of different types of uncertainty in measurements or in the underlying flow model. Proper selection of design parameters of the ALL system, including the shape, size, number and location of the sensors, can highly influence the identification accuracy. This study aims to find such an optimum design by developing a specialized bi-level optimization methodology. It identifies and simulates different sources of uncertainty in the problem formulation. A parametric fitness function addresses computational and practical goals and encompasses the effect of different sources of uncertainty. It can also analyse the trade-off between localization accuracy and the number of sensors. Comparison of t...

Averaging of robotic fish dynamics is of interest for the purposes of path planning and controller design due to the rhythmic movement of the robot. For a faithful dynamic model of robotic fish, however, classical averaging or geometric averaging typically cannot produce an average model that is accurate and in the meantime amenable to analysis or control design. In this paper, a novel averaging approach is proposed for tail-actuated robotic fish dynamics, in which the tail-generated hydrodynamic force is modeled with the Lighthill's large-amplitude elongated-body theory. The approach consists of scaling the force and moment terms and, then, conducting classical averaging. Numerical investigation reveals that the scaling function for the force term is a constant independent of tail-beat patterns, while the scaling function for the moment term depends linearly on the tail-beat bias. Extensive simulation and experimental results, comparing the predictions from the original and average models, are presented to support the effectiveness of the averaging approach. Existence and local stability of the equilibria for the average model are further analyzed. These equilibria are subsequently used to obtain an analytical solution for steady turning parameters, such as turning period and turning radius, without running simulation of the original or average dynamic models.

The six papers in this special section highlight some recent accomplishments in the modeling and control of smart mechatronic systems with pronounced hysteresis, and to motivate new ideas from the community to address outstanding challenges.

Inspired by the lateral line of aquatic vertebrates, an artificial lateral line (ALL) system can localize and track an underwater moving object by analyzing the ambient flow caused by its motion. There are several studies on object detection, localization and tracking by ALL systems, but only a few have investigated the optimal design of the ALL system, the one that on average provides the highest characterization accuracy. Design optimization is particularly important because the uncertainties in the employed flow model and in sensor measurements deteriorate the reliability of sensing. This study investigates the optimal design of the ALL system in three-dimensional (3D) space for dipole source characterization. It highlights some challenges specific to the 3D setting and demonstrates the shortcomings of the designs in which all sensors and their sensing directions are in the same plane. As an alternative, it proposes two design concepts, called 'Offset Strategy' and 'Angle Strategy' to overcome these shortcomings. It investigates potentials of having a swarm of cooperative ALLs as well. It performs design optimization in the presence of sensor and model uncertainties and analyzes the trade-off between the number of sensors and characterization accuracy. The obtained solutions are analyzed to reveal their strategies in solving the problem efficiently. The dependency of the optimized solutions on the uncertainties is also demonstrated.

This paper presents the first studies on robust closed-loop deflection control of vanadium dioxide (VO $_{2}$ )-based microactuators using self-sensing. The deflection output of the microactuator is estimated by VO $_{2}$ resistance-based self-sensing through a high-order polynomial in order to eliminate the need for complicated external sensing mechanisms. An $H_\infty $ robust controller is designed and implemented for precision deflection control, where uncertainties produced by the hysteresis between the deflection and the temperature input and the error in the self-sensing model are accommodated. The performance of the robust controller is tested in experiments under step and multisinusoidal reference inputs and compared to that of a proportional–integral–derivative (PID) controller. The robust controller outperforms the PID controller with 36% and 18% less tracking error for the step and multisinusoidal reference responses, respectively. To further show the robust performance of the $H_\infty $ controller, a multisinusoidal reference tracking experiment with simulated white noise current signal is conducted, where the error using robust control is 34% less than that with PID control.

Ionic polymer-metal composites (IPMCs) tend to have inconsistent sensing properties when operating in air under different humidity levels, or after exposure to different ambient media. Motivated by the need to ensure consistent sensing performance of IPMCs under different ambient environments, in this paper we propose thick (up to 25 micrometers) parylene C coating for IPMC sensors, develop effective coating processes, and evaluate the performance of the encapsulated sensors, along with the comparison with the typical naked IPMC sensors. The proposed fabrication process features the water drive-in step which enables the control and adjustment of the hydration level of an encapsulated IPMC. Experiments are conducted to evaluate the sensing consistency of IPMC sensors in a humidity chamber, first under different humidity levels, and then following exposure to solutions with different cations and different organic solvents. Experimental results show that the proposed thick parylene coating can effectively keep the water content inside the IPMC, isolate the IPMC sensor from various ambient environments, and maintain the sensing consistency, which allows IPMC sensors to be used in practical applications.

The concept of gliding robotic fish combines gliding and fin-actuation mechanisms to realize energy-efficient locomotion and high maneuverability. Such robots hold strong promise for mobile sensing in versatile aquatic environments. In this paper, we present the design and implementation of a miniature glider, a key enabling component for gliding robotic fish. The steady-state glide equation is first presented and then solved numerically for given net-buoyancy and movable mass displacement. Scaling analysis is conducted to understand the tradeoff between the glide performance and energy cost. Comprehensive design for the glider is provided. Experimentation and modeling analysis are further conducted to investigate the impacts of movable mass displacement, net buoyancy, and wing size on the gliding performance.

The architecture of cognitive decision engine should enable fast decision making, long-term knowledge accumulating based on past operating experience, and capabilities of knowledge updating to adapt to new situations. In this paper, a hybrid architecture of cognitive decision engine based on particle swarm optimization algorithms and case database is proposed. Considering the user’s quality of service preferences and the wireless situations, how to determine the radio’s link parameters such as modulation type, symbol rate, and transmit power can be formulated as a multi-objective optimization problem. In the architecture, this problem is solved by using particle swarm optimization algorithms, which make cognitive radio have the fast decision-making ability when facing unknown wireless situations. The case database, which stores the past running experiences of the cognitive radio is also integrated into the proposed architecture to improve the radio’s response speed and endows the radio with the ability of learning from its previous operating experiences. Simulation results show the effectiveness of the architecture, and the proposed cognitive decision engine can dynamically and properly reconfigure the radio according to the changes in wireless environment.

In this paper we present a dynamic model for a tail-actuated robotic fish by merging rigid-body dynamics with Lighthill’s large-amplitude elongated-body theory. The model is validated with extensive experiments conducted on a robotic fish prototype. We investigate the role of incorporating the body motion in evaluating the tail-generated hydrodynamic force, and show that ignoring the body motion (as often done in the literature) results in significant overestimate of the thrust force and robot speed. By exploiting the strong correlation between the angle of attack and the tail-beat bias, a computationally efficient approach is further proposed to adapt the drag coefficients of the robotic fish, and its effectiveness is supported by experimental results.

We propose an adaptive servocompensator utilizing frequency estimation and slow adaptation for systems subject to inputs of unknown frequencies. We show that the proposed controller can achieve zero tracking error for a class of periodic references and disturbances, including scenarios specifically relevant to piezo-actuated nanopositioning systems. In particular, for the case of a sinusoidal reference input, we establish the exponential stability of the closed-loop system in the presence of harmonic disturbances, under certain conditions on the amplitudes of the reference and disturbances. We also prove exponential stability in the case of sinusoidal reference and disturbance with two distinct frequencies. Additionally, we show that the proposed method, in conjunction with approximate hysteresis inversion, can attenuate the effect of hysteresis nonlinearity preceding linear dynamics and ensure the boundedness of the closed-loop system. Experiments conducted on a commercially available nanopositioner confirm our theoretical analysis and demonstrate the effectiveness of the proposed method as compared to Iterative Learning Control, a competitive technique in nanopositioning for tracking periodic references.

For an efficient free-space optical communication, the receiver should have a close-to-line-of-sight(LOS) link with the transmitter. Maintaining an alignment for LOS is a difficult task due to the constant movement of the underlying mobile platform or unwanted disturbances. The previously proposed Extended Kalman Filter-based algorithm uses light intensity measurements from single receiver photo-diode and a scanning technique to estimate the relative orientation between the receiver and the transmitter and adjust the receiver's orientation accordingly. This work focuses on the experimental implementation of the algorithms, and evaluates the estimation and control performance through an extensive set of simulation and experiments. In particular, it is found that the proposed algorithms are effective when unknown relative movements are relatively slow.

Light-emitting diode (LED)-based optical communication is emerging as a low-power, low-cost and high-data rate alternative to acoustic communication. However, it requires a close-to-line-of-sight link between the transmitter and the receiver. Alignment for maintaining line of sight is challenging due to the constant movement of the underlying mobile platform that is caused by unwanted disturbances and/or the propulsion. In this work we propose a novel extended Kalman filter (EKF)-based alignment algorithm, which estimates the relative orientation between the receiver and the transmitter based on the received light intensity, and uses the latter to adjust the scanning motion of the receiver. The scanning pattern is designed such that the rank condition for EKF convergence is satisfied. The efficacy of the proposed estimation and control scheme is illustrated with simulation results and preliminary experimental results.

In this paper time-domain analysis is performed for limit cycles in control loops that are induced by control valve stiction, and an analytical relationship between the proportional-integral controller parameters and the oscillation amplitude and period of process output is established. Based on this relationship, a novel controller design approach is proposed to achieve the desired oscillation amplitude. Compared with the qualitative controller tuning methods in the literature, the proposed approach is quantitative, and it avoids tuning the controller parameters in a trial-and-error manner for compensation of control valve stiction. The validity of the limit cycle analysis and the effectiveness of the proposed compensation approach are illustrated with numerical examples.

While acoustic modems have long been the dominant wireless communication method for underwater applications, they incur high cost and large power, and can only deliver low data rates. Recently, light-emitting diode (LED)-based optical communication has emerged as a promising approach to low-power, high-rate data transfer underwater over short-to-medium distances. However, LED-based communication relies on a close-to-line-of-sight link between the transmitter and the receiver, which presents significant challenges in its underwater robotic applications, where the underlying robots undergo constant motions due to propulsion and/or disturbances. In this paper we propose a novel and compact LED-based communication system with active alignment control, which maintains the communication link despite the underlying platform movement. Details on the system design and implementation are provided. The prototype is able to communicate at 115,200 bps over at least 23 m in swimming pool tests. Experiments involving a stationary transmitter and a mobile receiver mounted on a terrestrial robot are conducted to demonstrate the performance of the alignment maintenance system. In particular, it is shown that, for a communication distance of 3 m, the data loss under active alignment control is 9.9% at the transmission rate of 115,200 bps, when the robot orientation varies ±60°, while in comparison, the data loss is 56.2% in the absence of alignment control.

In this paper a novel flexible joint is proposed for robotic fish pectoral fins, which enables a swimming behavior emulating the fin motions of many aquatic animals. In particular, the pectoral fin operates primarily in the rowing mode, while undergoing passive feathering during the recovery stroke to reduce hydrodynamic drag on the fin. The latter enables effective locomotion even with symmetric base actuation during power and recovery strokes. A dynamic model is developed to facilitate the understanding and design of the joint, where blade element theory is used to calculate the hydrodynamic forces on the pectoral fins, and the joint is modeled as a paired torsion spring and damper. Experimental results on a robotic fish prototype are presented to illustrate the effectiveness of the joint mechanism, validate the proposed model, and indicate the utility of the proposed model for the optimal design of joint depth and stiffness in achieving the trade-off between swimming speed and mechanical efficiency.

Most fish and aquatic amphibians use the lateral line system, consisting of arrays of hair-like neuromasts, as an important sensory organ for prey/predator detection, communication, and navigation. In this paper a novel bio-inspired artificial lateral line system is proposed for underwater robots and vehicles by exploiting the inherent sensing capability of ionic polymer–metal composites (IPMCs). Analogous to its biological counterpart, the IPMC-based lateral line processes the sensor signals through a neural network. The effectiveness of the proposed lateral line is validated experimentally in the localization of a dipole source (vibrating sphere) underwater. In particular, as a proof of concept, a prototype with body length (BL) of 10 cm, comprising six millimeter-scale IPMC sensors, is constructed and tested. Experimental results have shown that the IPMC-based lateral line can localize the source from 1–2 BLs away, with a maximum localization error of 0.3 cm, when the data for training the neural netwo...

Gliding robotic fish combine the strengths of both underwater gliders and robotic fish, resulting in long duration of operation and high maneuverability. In this paper we study the distributed tracking of a leader's gliding path, represented by its velocity magnitude and gliding angle, by a multi-agent network when the leader's state is available to only a subset of the followers. The high nonlinearities in the robot's dynamics along with the coupling between its input channels and the gliding path parameters impose significant challenges in controlling the robot. Feedback linearization is one of the popular techniques when dealing with such systems. However, when considering the velocity magnitude and gliding angle of the robot as output, it is not possible to linearize the system using a static feedback control law. Therefore, dynamic feedback linearization is utilized for extending the state space of the robot, which enables the design of a distributed linear controller to solve the leader-follower tracking problem. Distributed estimators are designed for each agent to estimate the synthetic input of the leader and its linearized state. The virtual control for each agent is then mapped back to the actual input in order to track the leader's velocity and gliding angle. The effectiveness of the proposed approach is verified with simulation results.

Robotic fish accomplish swimming by deforming their bodies or other fin-like appendages. As an emerging class of embedded computing system, robotic fish are anticipated to play an important role in environmental monitoring, inspection of underwater structures, tracking of hazardous wastes and oil spills, and the study of live fish behaviors. While integration of flexible materials (into the fins and/or body) holds the promise of improved swimming performance (in terms of both speed and maneuverability) for these robots, such components also introduce significant design challenges due to the complex material mechanics and hydrodynamic interactions. The problem is further exacerbated by the need for the robots to meet multiple objectives (e.g., both speed and energy efficiency). In this paper, we propose an evolutionary multiobjective optimization approach to the design and control of a robotic fish with a flexible caudal fin. Specifically, we use the NSGA-II algorithm to investigate morphological and control parameter values that optimize swimming speed and power usage. Several evolved fin designs are validated experimentally with a small robotic fish, where fins of different stiffness values and sizes are printed with a multi-material 3D printer. Experimental results confirm the effectiveness of the proposed design approach in balancing the two competing objectives.

Small (decimeter-scale) robotic fish are promising mobile sensor platforms for aquatic environments. Fine-grained localization for dense networks of such robotic fish presents a challenge because of noisy underwater environment, required submeter accuracy, and constraints on onboard processing power and hardware complexity. In this paper, we present an efficient time-of-flight-based acoustic ranging system for localization of robotic fish with limited onboard resources. The system involves simple hardware: a single pair of monotone buzzer and microphone. The distance between two nodes is determined by the time it takes for an acoustic signal generated by the buzzer on the first node to reach the microphone on the second node. The arrival of the signal is detected with the sliding discrete Fourier transform (SDFT) algorithm, where the rise dynamics of the signal is modeled and used for compensation of detection latency. The algorithm is implemented onboard a small biomimetic robotic fish, and experiments in an indoor pool have shown that the compensated SDFT algorithm results in an underwater ranging error of 1.9 wavelengths (1 m), and is thus promising for localization of dense aquatic networks.

Conjugated polymers are promising actuation materials for bio- and micromanipulation systems, biomimetic robots, and biomedical devices. Sophisticated electrochemomechanical dynamics in these materials, however, poses significant challenges in ensuring their consistent, robust performance in applications. In this paper, an effective adaptive control strategy is proposed for conjugated polymer actuators. A self-tuning regulator is designed based on a simple actuator model, which is obtained through reduction of an infinite-dimensional physical model and captures the essential actuation dynamics. The control scheme is made robust against unmodeled dynamics and measurement noises with parameter projection, which forces the parameter estimates to stay within physically meaningful regions. The robust adaptive control method is applied to a trilayer polypyrrole (PPy) actuator that demonstrates significant time-varying actuation behavior in air due to the solvent evaporation. Experimental results show that, during 4-h continuous operation, the proposed scheme delivers consistent tracking performance with the normalized tracking error decreasing from 11% to 7%, while the error increases from 7% to 28% and to 50% under a proportional-integral-derivative (PID) controller and a fixed model-following controller, respectively. In the meantime, the control effort under the robust adaptive control scheme is much less than that under PID, which is important for prolonging the lifetime of the actuator.

Oceanic sustainability has been a growing global concern due to the increase of potential threats to the integrity of aquatic ecosystems. As a result, more attention has been paid to the monitoring of such environments, leading to the need for autonomous aquatic robots that are capable of monitoring them in an efficient and accurate manner. A gliding robotic fish is a type of underwater robot that stems from combining the energy-efficient underwater glider with the highly maneuverable robotic fish. For accurate trajectory control and precise sensor measurement, stabilization of both pitch and yaw during gliding is of great importance. In this paper we propose a multi-input-multi-output sliding mode controller for simultaneous stabilization of pitch and yaw. In this design, the outputs of both actuators, tail angle and center of gravity, are determined by the errors in both pitch and yaw. The effectiveness of the proposed approach is demonstrated via simulation with comparison to several alternative designs, including a pair of sliding mode controllers dealing with yaw and pitch separately, and a PI controller.Copyright © 2015 by ASME

In this study, we investigate the modeling framework for a robotic fish actuated by a flexible caudal fin, which is filled with electrorheological (ER) fluid and thus enables tunable stiffness. This feature can be used in optimizing the robotic fish speed or maneuverability in different operating regimes. The robotic fish is assumed to be anchored and the flexible tail undergoes undulation activated by a servomotor at the base. Lighthill’s large-amplitude elongated-body theory is used to calculate the hydrodynamic force on the caudal fin, and Hamilton’s principle is used to derive the dynamic equations of motion of the caudal fin. The dynamic equations are then discritized using the finite element method, to obtain an approximate numerical solution. In particular, simulation is conducted to understand the influence of the applied electric field on the stiffness and thrust performance of the caudal fin.Copyright © 2015 by ASME

The problem of stabilizing steady gliding is critical for an underwater glider, which is subject to many non-negligible disturbances from the aquatic environment. In this paper, we propose a new systematic controller design and implementation approach for the stabilization problem, including a nonlinear, passivity-based controller and a nonlinear model-based observer, where the actuation is realized through a whale tail-like control surface. The controller is designed based on an approximation of a reduced model that is obtained through singular perturbation analysis, and consequently, it does not require full state feedback. The local stability of the full closed-loop system is established through linearization analysis. The nonlinear observer is designed to estimate the velocity-related system states, which are difficult to measure for such low-speed underwater vehicles. Simulation results are first provided to demonstrate that the proposed controller achieves rapid convergence in stabilization and the proposed observer has good performance especially in robustness against measurement noise. Experimental results using a gliding robotic fish are presented to support the effectiveness of both the controller and the observer.

Gliding robotic fish, a hybrid of underwater gliders and robotic fish, are energy-efficient and highly maneuverable, and hold strong promise for long-duration sampling of underwater environments. In this paper a novel systematic autonomous water-column-based sampling scheme for gliding robotic fish is proposed to measure the three-dimensional spatial distributions of variables of interest in aquatic environments. The scheme exploits energy-efficient spiral-down motion to sample each water column, followed by sagittal-plane glide-up towards the direction of next water column. Once surfacing, the robot uses GPS guidance to reach the next column location through swimming. To enhance the path tracking performance, a two-degree-of-freedom controller involving H ∞ control is used in the spiral motion, and a sliding-mode controller is employed to regulate the yaw angle during glide-up. The sampling scheme has been implemented on a gliding robotic fish prototype, “Grace”, and verified first in pool experiments, and then in field experiments involving the sampling of harmful algae concentration in the Wintergreen Lake, Michigan.

Excellent swimmers, such as tuna, rays, and goldfish, take advantage of their flexible fins, compliant bodies, and swimming bladders to achieve fast, highly maneuverable, and energy-efficient locomotion. Ionic polymer-metal composites (IPMCs) present attractive opportunities for implementation in flexible underwater propulsion systems due to their intrinsic compliancy and underwater actuation capability. IPMCs can also perform as lightweight and compact catalysts for water electrolysis, which can be used to generate gas for buoyancy control. In this chapter, the potential of IPMCs in underwater propulsion is explored, including caudal fin propulsion, pectoral fin propulsion, and buoyancy control. Enabling technologies, including fabrication methods, modeling and control strategies, and design approaches, are developed for creating bio-inspired robots using IPMC as artificial muscle and buoyancy engine. Three types of underwater robots have been developed to evaluate their performance. First, a robotic fish propelled by an IPMC caudal fin is developed to evaluate its caudal fin propulsion. Second, a bio-inspired robotic cownose ray propelled by two IPMC actuated pectoral fins is demonstrated to evaluate its pectoral fin propulsion. Third, a buoyancy control device enabled by IPMC-enhanced electrolysis is developed to explore its buoyancy control performance.

In prior work of the authors and co-workers, a vision-based system was developed for characterizing the tribological behavior of silicon-micromachined linear microball bearings. Plain difference methods introduce amplitude and/or phase distortion in computing the derivative signals (e.g., velocity and acceleration) based on the position snapshots. In this paper frequency-dependent amplitude and phase compensation algorithms are developed for both the forward difference and the central difference methods to retrieve without distortion the friction and the relative velocity between bearing elements. Processing of experimental data with these techniques reveals nonlinear, viscous frictional behavior in the bearing. A viscoelastic model based on a continuum of mass-spring-damper elements is then proposed for the ball-groove interaction. Numerical results show that this model captures the nonlinear velocity dependence of the rolling friction observed in experiments.

Three-dimensional curve tracking is an important and challenging research topic for autonomous underwater vehicles and robots. In this paper we consider the tracking control of gliding robotic fish, a new type of energy-efficient and highly maneuverable robots representing a hybrid of underwater gliders and robotic fish; in particular, buoyancy-driven gliding with a deflected tail results in efficient spiral maneuvers. We propose to decompose a space curve into continuously evolving spirals from the viewpoint of differential geometry, and then utilize the spiral trajectory characteristics for three-dimensional curve tracking. Due to the nonlinear dynamics and strong coupling among multiple control inputs, the design of controller is highly demanding. A novel two degree-of-freedom (DOF) tracking control strategy is proposed, which consists of a feedforward inverse controller and a robust H ∞ controller designed based on linearized dynamics. Simulation results are presented to demonstrate the effectiveness of the proposed two-DOF control scheme, in comparison with a PI controller and a pure feedforward inverse controller.

In this paper, we apply evolutionary multiobjective optimization to the design of a robotic fish with a flexible caudal fin. Specifically, we use the NSGA-II algorithm to discover solutions (physical dimensions, flexibility, and control parameters) that optimize both swimming performance and power efficiency. The optimization is conducted in a custom simulation environment based on an accurate yet computationally-efficient model of hydrodynamics. The results of these simulations reveal general principles that can be applied in the design of robotic fish morphology and control. To verify that the simulation results are physically relevant, we selected several of the evolved solutions, fabricated flexible caudal fins using a multi-material 3D printer, and attached them to a robotic fish prototype. Experimental results, conducted in a large water tank, correspond reasonably well to simulation results in both swimming performance and power efficiency, demonstrating the usefulness of evolutionary computation methods to this application domain.

Hysteresis in smart material actuators makes the effective use of these actuators quite challenging. The Preisach operator has been widely used to model smart material hysteresis. Motivated by positioning applications of smart actuators, this paper addresses the value inversion problem for a class of discretized Preisach operators, i.e., to find an optimal input trajectory given a desired output value. This problem is solved through optimal state transition of a finite state machine (FSM) that corresponds to the discretized Preisach operator. A state-space reduction scheme for the FSM is developed, which significantly saves the memory and the computation time. Experimental results on micro-positioning control of a magnetostrictive actuator are presented to demonstrate the effectiveness of the proposed approach. © 2004 Elsevier B.V. All rights reserved.

A novel dynamic model is proposed for the hysteresis in magnetostrictive actuators by coupling a Preisach operator to an ordinary differential equation, and a parameter identification method is described. An efficient inversion algorithm for a class of Preisach operators with piecewise uniform density functions is then introduced, based upon which an inverse control scheme for the dynamic hysteresis model is presented. Finally the inversion error is quantified and l"1 control theory is applied to improve the robustness of inverse compensation. Simulation and experimental results based on a Terfenol-D actuator are provided.

In wireless sensor actuator networks, actuator nodes are very important to network coverage for wireless sensor. So according to the characteristics that wireless communication is easy to be affected by the environment, in this wireless sensor actuator network the actuator nodes are abstracted to be service providers and the sensor nodes are abstracted to be service consumers. Furthermore, the messages transferred from actuator nodes to sensor nodes are abstracted to be service requests and the coverage of sensor nodes by actuator nodes is service providing. Moreover, the service faulty ratio of actuator nodes is defined in this paper. Based on that, an actuator node coverage algorithm that satisfies the maximum request expectation is put forwarded. Its goal is to solve the mathematical expectation of maximizing the number of service requests with fixed number of sensor nodes and actuator nodes. So the optimal position of actuator nodes could be identified. The theoretic proof and simulation result show that this algorithm is more efficient compared with similar algorithms

In this paper, we propose a novel design for a pectoral fin joint of a robotic fish. This joint uses a flexible part to enable the rowing pectoral fin to feather passively and thus reduce the hydrodynamic drag in the recovery stroke. On the other hand, a mechanical stopper allows the fin to maintain its motion prescribed by the servomotor in the power stroke. The design results in net thrust even when the fin is actuated symmetrically for the power and recovery strokes. A dynamic model for this joint and for a pectoral fin-actuated robotic fish involving such joints is presented. The pectoral fin is modeled as a rigid plate connected to the servo arm through a pair of torsional spring and damper that describes the flexible joint. The hydrodynamic force on the fin is evaluated with blade element theory, where all three components of the force are considered due to the feathering degree of freedom of the fin. Experimental results on robotic fish prototype are provided to support the effectiveness of the design and the presented dynamic model. We utilize three different joints (with different sizes and different flexible materials), produced with a multi-material 3D printer, and measure the feathering angles of the joints and the forward swimming velocities of the robotic fish. Good match between the model predictions and experimental data is achieved, and the advantage of the proposed flexible joint over a rigid joint, where the power and recovery strokes have to be actuated at different speeds to produce thrust, is demonstrated.Copyright © 2014 by ASME

An ionic polymer-metal composite (IPMC) sensor typically consists of a thin ion-exchange membrane with electrodes on both surfaces. Such IPMC sensors respond to deflections in the beam-bending directions only and thus are considered one-dimensional. In this paper, a novel IPMC sensor capable of two-dimensional sensing is presented. This tubular thin-wall IPMC has one common inner electrode and four outer electrodes, which form four routes of common-ground outputs. The fabrication method is reported along with the sensor package. A custom-designed experimental setup, which provides dynamic tip bending with adjustable orientations and controlled bending amplitude, is used to characterize the sensor response (short-circuit current) to the 2D mechanical stimulus in air. Based on the characterization results, we further model the proposed 2D tubular IPMC sensor by treating pairs of infinitesimal portion of tube wall as one-dimensional IPMC sensors and integrating them around the tube. Experimental results show that the fabricated IPMC sensor responds to omnidirectional stimulus within the cross-section plane and the proposed model captures well the sensor responses, indicating that this tubular IPMC sensor can be potentially used for 2D flow and displacement sensing.Copyright © 2014 by ASME

Pectoral fins are important actuation mechanisms in achieving maneuvering and propulsion for robotic fish. Existing designs predominantly adopt a rigid joint connecting the actuator to the pectoral fin, which requires differential actuation speeds in the power and recovery strokes in order to produce thrust and thus limits the overall actuation frequency. To address this problem, in this paper we propose a novel design of a flexible joint, which enables the pectoral fin to sweep back passively along the fish body in the recovery stroke, to minimize the drag, while maintaining the prescribed motion in the power stroke. A dynamic model is presented for a robotic fish propelled by pectoral fins incorporating such flexible joints, where the pectoral fin mechanism is modeled by two rigid segments connected with a pair of torsional spring and damper. This design results in a net thrust even with the same recovery and power stroke speed within each fin beat cycle, which simplifies the fin control. Experimental results on a robotic fish prototype are presented to validate the effectiveness of the proposed model, and to demonstrate the significant advantage of the proposed fin joint over the rigid joint. Furthermore, modeling analysis and experimental investigation are used to examine the influence of the joint length and stiffness on the locomotion performance.

In this paper, we develop a new dynamic model for a robotic fish propelled by a flexible tail actuated at the base. The tail is modeled by multiple rigid segments connected in series through rotational springs and dampers, and the hydrodynamic force on each segment is evaluated using Lighthill’s large-amplitude elongated-body theory. For comparison, we also construct a model using linear beam theory to capture the beam dynamics. To assess the accuracy of the models, we conducted experiments with a free-swimming robotic fish. The results show that the two models have almost identical predictions when the tail undergoes small deformation, but only the proposed multisegment model matches the experimental measurement closely for all tail motions, demonstrating its promise in the optimization and control of tail-actuated robotic fish. [DOI: 10.1115/1.4028056]

Gliding robotic fish is a new type of underwater robots for aquatic environmental monitoring applications. The robot features both buoyancy-driven gliding and active tail- actuated swimming or maneuvering. In our previous work, a passivity-based controller was designed for stabilizing the glide motion. Estimation of the system states including the velocities, which is essential for the feedback control implementation, is challenging for such a low-speed and low-cost underwater robot with highly nonlinear dynamics. In this paper, a nonlinear model-based observer is proposed to estimate the system states. For comparison purposes, a linear observer based on linearized dynamics is also considered. The nonlinear observer proves to have better performance over the linear observer, especially in terms of the robustness against the measurement noise. The proposed nonlinear observer is then implemented in the passivity-based stabilization controller on a gliding robotic fish, and the experimental results are presented to support the effectiveness of both the controller and the observer.

Gliding robotic fish is a new type of underwater robots that combines the energy-efficiency of underwater gliders and the high maneuverability of robotic fish. The tail fin of a gliding robotic fish provides the robot more control authority, especially for the lateral motion, compared with traditional underwater gliders. In this paper, the design and development of a gliding robotic fish prototype is first presented, followed by its dynamic model. We then focus on the problem of tail-enabled yaw stabilization during gliding, where a sliding mode controller is proposed. Both simulation and experimental results are demonstrated to validate the effectiveness of the proposed controller.Copyright © 2013 by ASME

In this paper we apply backstepping technique to develop a novel hybrid target-tracking control scheme for a carangiform robotic fish, based on a dynamic model that combines rigid-body dynamics with Lighthill’s large-amplitude elongated-body theory. This hybrid controller consists of an open-loop turning controller and a closed-loop approaching controller. A hysteretic switching strategy based on the orientation error is designed. Using Lyapunov analysis, we show that the trajectory of the robotic fish will converge to the target point. The effectiveness of the proposed control strategy is demonstrated through both simulations and experiments.Copyright © 2013 by ASME

A novel self-sensing and robust control technique is presented for a vanadium dioxide (VO2)-coated silicon (Si) microactuator. The deflection output of the microactuator is estimated by resistance-based self-sensing through a high-order polynomial model in order to eliminate the need for complicated sensing mechanisms. To accommodate the uncertainties produced by the hysteresis between the deflection and the temperature input, and the error in the self-sensing model, an H∞ robust controller is designed and implemented for deflection control. The performance of the robust controller is tested in experiments under step and sinusoidal reference inputs and compared to that of a proportional-integral-derivative (PID) controller. The H∞ controller outperforms the PID controller with 31% and 43% less root-mean-square-error for the step and sinusoidal references, respectively, while maintaining 3.1% less control effort for the latter.

This paper presents the dynamic modeling, design and fabrication of a free-swimming robotic fish with flexible pectoral fins. To capture the flexibility of the fins, a multi-segment model with torsional springs and viscous dampers is introduced and the hydrodynamic force on each segment is calculated based on the blade element theory. Other forces such as added mass, quasi-static lift, and drag are also considered in modeling the dynamics of the robot. A robotic fish has been prototyped, which has a 3D-printed body and a pair of servo-actuated flexible pectoral fins. The proposed dynamic model is validated with experiments done on the robotic fish, where the model predictions of forward swimming speeds and steady turning periods and radii are found to match closely the experimental measurements when the pectoral fins are actuated at different frequencies.

Mobile networking and collaboration of underwater robots is of interest in many applications such as oceanography, environmental monitoring, and underwater surveillance. In this paper, an LED-based underwater optical communication system is designed and implemented for such applications. In contrast with laser-based communication systems, the characteristics of small size and low cost of the LED-based systems are very appealing, especially for small underwater robots. The presented system has a sound balance among desired characteristics of small size (in the order of centimeters), low energy consumption (500 mW on average), and median communication distance (20-30 m, in comparison with several meters available from most similar LED-based systems). The system design is described including the realization of the transmitter and the receiver, as well as the methods for achieving robustness to noise. System performance is experimentally tested in terms of signal strength and waveform shape versus communication distance and transmitting frequency. Experiments on data transmission is conducted to check the bit error rate under different baud rates. The experimental results show that the presented system has a good balance between communication performance and robustness.

With the wide application of the computer, it has been integrated into the professional fields of all kinds of industry, which also means that requirements for the education of Basis of Computer Engineering in colleges and universities have become higher and higher. This thesis makes an analysis of problems and phenomena existing in the teaching of PE major in colleges and universities, and then makes a discussion on the educational reform of Basis of Computer Engineering. Index Terms - Education of Basis of Computer Engineering, Composite Talents of PE and Computer, Discussion I. Introduction With the rapid development of the computer, it is more and more applied to all walks of life. So, in this new situation, requirements for the new generation's computer knowledge and application skills have become higher and higher. Computer education of the students of PE major should also conform to the major features, to help students combine the basic computer knowledge with their expertise, so as to meet the social demand for talents. At present, most colleges and universities have set up the course of "Basis of Computer Engineering", but it is just an ordinary public compulsory course with no concern about the teaching methods and teaching contents. Schools generally adopt the teaching method of natural classes, in which all the students in different degree sit together and learn the course together. Some colleges and universities even mix students of different majors in the same class to have this course. Due to the particularity of the PE major and the difference of students' growth environment, their understanding of the computer and the actual operation levels are also different from each other. Therefore, this hybrid teaching method will have some influences on the teaching and students' learning effects. II. Problems Existing in the Current Teaching of PE Major in Colleges and Universities A. Single teaching contents fail to meet the demand of PE major For PE major students, the purpose of learning the computer is able to pass the computer grade examination in order to get a diploma. Of course, this can provide an incentive to non-computer science students learn computer, But out of touch with the professional teaching basic computer teaching can not meet the demand for professionals in sports. Students

The Preisach hysteresis model has been adopted extensively in magnetic and smart material-based systems. Fidelity of the model hinges on accurate identification of the Preisach density function. Existing work on the identification of the density function usually involves applying an input that provides sufficient excitation and measuring a large set of output data. In this paper, we propose a novel compressive sensing-based approach for Preisach model identification that requires fewer measurements. The proposed approach adopts the discrete cosine transform of the output data to obtain a sparse vector, where the order of all the output data is assumed to be known. The model parameters can be efficiently reconstructed using the proposed scheme. For comparison purposes, a constrained least-squares scheme using the same number of measurements is also considered. The root-mean-square error is adopted to examine the model identification performance. The proposed identification approach is shown to have better performance than the least-squares scheme through both simulation and experiments involving a vanadium dioxide ()-integrated microactuator.

Among the various designs of robotic fish, tail-actuation is particularly attractive since it is simple, enables both swimming and turning, and allows a rigid body for housing sensors and electronics. In this paper we present a new dynamic model for robotic fish propelled by a flexible tail that is actuated at the base, and explore the effect of stiffness of the tail beam on the locomotion performance of the robot. The tail is approximated by multiple rigid elements connected in series through rotational springs and dampers, to effectively and efficiently capture the large deformation of the beam. The hydrodynamic force on each segment is evaluated with Lighthill’s large-amplitude elongated-body theory. Model analysis shows that, given the same base movement, the stiffness of the tail has a prominent influence on the tail dynamics and the resulting motion (e.g., speed) of the robotic fish. Experiments are conducted on a robotic fish prototype when it is mounted with a rigid and flexible tail, respectively. The results show that the model is able to predict the motion of the robot for both cases, when the tail base is actuated with a variety of patterns. The model is expected to be instrumental in the optimization and control of robotic fish.Copyright © 2012 by ASME