Han Zhou

Bio-inspired Flow Sensing and Prediction for Fish-like Undulating Locomotion: A CFD-aided Approach

Feedback flow information is of significance to enable underwater locomotion controllers with higher adaptability and efficiency within varying environments. Inspired from fish sensing their external flow via near-body pressure, a computational scheme is proposed and developed in this paper. In conjunction with the scheme, Computational Fluid Dynamics (CFD) is employed to study the bio-inspired fish swimming hydrodynamics. The spatial distribution and temporal variation of the near-body pressure of fish are studied over the whole computational domain. Furthermore, a filtering algorithm is designed and implemented to fuse near-body pressure of one or multiple points for the estimation on the external flow. The simulation results demonstrate that the proposed computational scheme and its corresponding algorithm are both effective to predict the inlet flow velocity by using near-body pressure at distributed spatial points.

Computational Hydrodynamics and Statistical Modeling on Biologically Inspired Undulating Robotic Fins: A Two-Dimensional Study

Undulation fishes, whose propulsion is mainly achieved by undulating ribbon fins, are good at maneuvering or stabilizing at low speeds. This paper suggests and proposes a two-dimensional approximate computational model, which is used to conduct an initial analysis on undulation propulsion scheme. It is believed that this undulating mode has a better potential for exploitation in artificial underwater systems. Hydrodynamics of two-dimensional undulating fins under a series of kinematical parameter sets is explored via numerical simulation. The periodicity of undulation forces and moments is studied. The effects of inlet velocity, wavelength, undulation frequency, and undulation amplitude are investigated. Furthermore, a dimensionless two-parameter model for undulation surge force is established with a given wavelength (in terms of, a single wavelength or a dual wavelength) using statistical method. The work in this paper is able to provide studies on bionic undulation mode. It has also formed a meaningful basis for three-dimensional (3D) hydrodynamics and corresponding control methods in bionic undulation robots.

Theoretical Insights on Contraction-Type Iterative Learning Control for Biorobotic Systems with Preisach Hysteresis

This article offers new insights on the learning control approach developed by [Hu et al. IEEE/ASME Trans. Mechatronics, 19(1): 191–200, 2014]. Theoretical insights are further proposed to unveil why the contraction-type iterative learning control (ILC) schemes are suitable and effective in compensating for hysteresis, widely existing in biorobotic locomotion. Under such circumstances, iteration-based second-order dynamics is adopted to describe the biorobotic systems acted upon by one unknown Preisach hysteresis term. The memory clearing operator is mathematically proven to enable feasibility of contraction-type ILC methods, regardless of whether the initial state is accurately set or not. The simulation examples confirm that the developed iteration-based controller combined with a preceded operator effectively reduce tracking errors caused by the hysteresis nonlinearity. Furthermore, the new insights on theoretical feasibility are definitively corroborated in accordance with the previously published experimental results.

Simulation Platform for Fishlike Swimming

Computational fluid dynamics (CFD) technique is considered as an effective approach for analysis of fishlike swimming, which quantitatively visualizes interaction between fishes and their fluid environment. This paper proposed and developed a simulation environment for understanding fish locomotion and hydrodynamic effects during the self-propulsion in a flow field. Approximate kinetic model or/and shape description based camera observation are recommended to specify active deformation of the body. Burst-Coast swimming is analyzed as an illustration of the simulation platform.

A Bio-Inspired Strategy for Robotic Fish Swimming in Unsteday Flows

Fish can swim swiftly in complicated flow environments, which conceives inspirations for man-made underwater vehicles. The paper concentrates on some bio-inspired strategies to enable robotic fish better adaptability within changing environments. An adaptive neural method corresponding to environment is proposed and developed with a pair of coupled neural oscillators. A parameters forecasting algorithm is also designed. On the other hand, a notional four joints robotic fish is designed to validate the effectiveness of the model. Simulation results show that the proposed algorithms predict the altering kinematics parameters exactly and improved model can depict the fishs adaptable behaviors. Therefore the effectiveness is further validated for potential applications into robotic fish.

Modeling and control on hysteresis nonlinearity in biomimetic undulating fins

In this paper, biomimetic undulating fins are considered with the focus on their hysteresis nonlinearity. Hysteresis is confirmed with experimental data on the biorobotic fin prototype, and qualitative modeling on this nonlinear action is then achieved by using Preisach equations. The developed iterative learning control is applied to eliminate hysteresis nonlinearity in biorobotic undulating fins. Both the simulation and experimental results show that the proposed control method is effective and feasible to improve the tracking performance of biorobotic fins by considering the hysteresis effect. Furthermore, the control methods should facilitate biomimetic investigation on propulsive modes and waveforms of fish swimming.

Statistical hydrodynamics modeling of two-dimensional undulating fins for robotic fish

Undulation fishes, whose propulsion is mainly achieved by undulating ribbon fins, are good at maneuvering or stabilizing at low speeds. This paper suggests and proposes a two-dimensional approximate computational model before presenting an initial analysis on undulation propulsion scheme. It is believed that this mode has a better potential for exploitation in artificial underwater systems. Hydrodynamics of two-dimensional undulating fins under a series of kinematical parameter sets is explored via numerical simulation. The periodicity of undulation forces and moments is herein studied. The effects of wavelength, undulation frequency, and undulation amplitude are investigated. Furthermore, a dimensionless two-parameter model for undulation surge force is established with a given wavelength (for example, a single wavelength or dual wavelength). The work in this paper is able to provide studies on bionic undulation mode. It has also formed a meaningful basis for three-dimensional hydrodynamics and corresponding control methods in bionic undulation robots.

Modeling of Fish Adaptive Behaviors in Unsteady Flows

Fish can swim swiftly in complicated flow environments, which conceives inspirations for man-made underwater vehicles. This paper concentrates on observation and modeling of fish adaptive behaviors in unsteady flows. A good representative of bony fish, crucian, is taken as the experimental specimen for investigating biological adaptation with response to alteration of surrounding flow patterns. Difference of swimming parameters is confirmed by recorded samples within several flow patterns. Furthermore, a bio-inspired gait model is constructed to stimulate fish adaptive behaviors, since the traditional model is hardly suitable. The model is inspired and supported by biological neural oscillators. By using the developed neural oscillator model, not only certain rhythmic motions under a steady flow pattern can be generated, but also behavioral transitions between multiple different patterns within unsteady flows come true. Experimental results validate the effectiveness of the developed neural model in continuously and smoothly regulating fish propulsive patterns within unsteady flows.