Bio-Inspired Design, Modeling, and Control of Robotic Fish Propelled by a Double-Slider-Crank Mechanism Driven Tail

2021 ◽  
Author(s):  
Wenyu Zuo ◽  
Frank Fish ◽  
Zheng Chen
Keyword(s):  
Linear Model ◽  
Swimming Speed ◽  
Robotic Fish ◽  
State Feedback Control ◽  
Modeling And Control ◽  
Swimming Motion ◽  
Heading Angle ◽  
Undulatory Locomotion ◽  
Oscillating Foil ◽  
And Control

Abstract This paper presents the design, modeling, and control of a three-joint robotic fish propelled by a Double-Slider-Crank (DSC) driven caudal fin. DSC is a mechanism that can use one DC motor to achieve oscillating foil propulsion. Its design is guided by a traveling wave equation that mimics a fish’s undulatory locomotion. After multiple tests, the robotic fish displayed good performance in mimicking a real fish’s swimming motion. DSC mechanism is proven to be an effective propulsion technique for a robotic fish. With the help of another servo motor at the first joint of the fish’s tail, the robotic fish can have a two-dimensional free-swimming capability. In experiments, the robotic fish can achieve a swimming speed of 0.35 m/s at 3 Hz, equivalent to 0.98 body length (BL) per second. Its steering rate is proportional to a bias angle. The DSC benefits the control of the robotic fish by independently adjusting its steering and swimming speed. This characteristic is studied in a hydrodynamic model that derives the thrust within a DSC frame. Besides the dynamic model, a semi-physics-based and data-driven linear model is established to connect bias angle to robotic fish’s heading angle. The linear model is used for designing a state feedback control, and the controller has been examined in simulation and experiments.

Novel Method for the Modeling and Control Investigation of Efficient Swimming for Robotic Fish

2012 ◽  
Vol 59 (8) ◽  
pp. 3176-3188 ◽  
Author(s):  
Li Wen ◽  
Tianmiao Wang ◽  
Guanhao Wu ◽  
Jianhong Liang ◽  
Chaolei Wang
Keyword(s):  
Robotic Fish ◽  
Modeling And Control ◽  
Novel Method ◽  
And Control

MODELING AND CONTROL DESIGN OF AN ANGUILLIFORM ROBOTIC FISH

2012 ◽  
Vol 03 (04) ◽  
pp. 1250018 ◽  
Author(s):  
JIAN-XIN XU ◽  
XUE-LEI NIU ◽  
QIN-YUAN REN
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Control Design ◽  
Robotic Fish ◽  
Torque Control ◽  
Underactuated System ◽  
Parameter Uncertainties ◽  
Modeling And Control ◽  
Mode Control ◽  
And Control

In this paper, the modeling and control design of a biomimetic robotic fish is presented. The Anguilliform robotic fish consists of N links and N - 1 joints, and the driving forces are the torques applied to the joints. Considering kinematic constraints, Lagrangian formulation is used to obtain the dynamics of the fish model. The computed torque control method is applied first, which can provide satisfactory tracking responses for fish joints. Since this robotic fish is essentially an underactuated system, the reference trajectories for the orientation of the N links are planned in such a way that, at a neighborhood of the equilibrium point, the tracking task of N angles can be achieved by using N - 1 joint torques. To deal with parameter uncertainties that exist in the actual environment, sliding mode control is adopted. Considering feasibility and complexity issues, a simplified sliding mode control algorithm is given. A four-link robotic fish is modeled and simulated, and the results validate the effectiveness of reference planning and the proposed controllers.

scholarly journals Modeling and Control of Distillation Column in a Petroleum Process

2009 ◽  
Vol 2009 ◽  
pp. 1-14 ◽  
Author(s):  
Vu Trieu Minh ◽  
Ahmad Majdi Abdul Rani
Keyword(s):  
Linear Model ◽  
Distillation Column ◽  
Reference Model ◽  
Adaptive Controller ◽  
Modeling And Control ◽  
Reduced Order ◽  
Order Linear ◽  
Balance Structure ◽  
And Control ◽  
Model Reference Adaptive

This paper introduces a calculation procedure for modeling and control simulation of a condensate distillation column based on the energy balance structure. In this control, the reflux rate and the boilup rate are used as the inputs to control the outputs of the purity of the distillate overhead and the impurity of the bottom products. The modeling simulation is important for process dynamic analysis and the plant initial design. In this paper, the modeling and simulation are accomplished over three phases: the basic nonlinear model of the plant, the full-order linearised model, and the reduced-order linear model. The reduced-order linear model is then used as the reference model for a model-reference adaptive control (MRAC) system to verify the applicable ability of a conventional adaptive controller for a distillation column dealing with the disturbance and the model-plant mismatch as the influence of the plant feed disturbances.

Experimental Results in the Modeling and Control of a Small Furnace

1981 ◽  
Vol 103 (4) ◽  
pp. 370-374
Author(s):  
R. S. Baheti ◽  
R. R. Mohler
Keyword(s):  
Linear Model ◽  
Binary Sequence ◽  
Power Input ◽  
Sample Temperature ◽  
Model Parameters ◽  
Input Output ◽  
Pseudorandom Binary Sequence ◽  
Modeling And Control ◽  
Small Furnace ◽  
And Control

A dynamic model is developed to control the temperature of a specimen in a laboratory furnace. The control variables are the power input to the furnace and the rate of airflow inside the chamber. For a constant airflow input, the furnace can be represented by a linear model and a static gain dependent on the sample temperature. The power input to the furnace is perturbed with a pseudorandom binary sequence and the model parameters are estimated from the input-output measurements. The controller parameters are selected to minimize the variance in the sample temperature.

scholarly journals Modeling and Control of a Soft Robotic Fish with Integrated Soft Sensing

2021 ◽  
pp. 2000244
Author(s):  
Yu-Hsiang Lin ◽  
Robert Siddall ◽  
Fabian Schwab ◽  
Toshihiko Fukushima ◽  
Hritwick Banerjee ◽  
...  
Keyword(s):  
Robotic Fish ◽  
Soft Sensing ◽  
Modeling And Control ◽  
And Control

Modeling and control of tubular solid-oxide fuel cell systems. I: Physical models and linear model reduction

2011 ◽  
Vol 196 (1) ◽  
pp. 196-207 ◽  
Author(s):  
Andrew M. Colclasure ◽  
Borhan M. Sanandaji ◽  
Tyrone L. Vincent ◽  
Robert J. Kee
Keyword(s):  
Fuel Cell ◽  
Solid Oxide Fuel Cell ◽  
Model Reduction ◽  
Linear Model ◽  
Solid Oxide ◽  
Physical Models ◽  
Oxide Fuel ◽  
Cell Systems ◽  
Modeling And Control ◽  
And Control

Learning Based Speed Control of Soft Robotic Fish

2018 ◽  
Author(s):  
Sunil Kumar Rajendran ◽  
Feitian Zhang
Keyword(s):  
Design Method ◽  
Control Design ◽  
Artificial Muscle ◽  
Speed Control ◽  
Robotic Fish ◽  
Design Approach ◽  
Modeling And Control ◽  
Model Free ◽  
Bioinspired Robotics ◽  
And Control

Bioinspired robotics takes advantage of biological systems in nature for morphology, action and perception to build advanced robots of compelling performance and wide application. This paper focuses on the design, modeling and control of a bioinspired robotic fish. The design utilizes a recently-developed artificial muscle named super coiled polymer for actuation and a soft material (silicone rubber) for building the robot body. The paper proposes a learning based speed control design approach for bioinspired robotic fish using model-free reinforcement learning. Based on a mathematically tractable dynamic model derived by approximating the robotic fish with a three-link robot, speed control simulation is conducted to demonstrate and validate the control design method. Exampled with a three-link reduced-order dynamic system, the proposed learning based control design approach is applicable to many and various complicated bioinspired robotic systems.

Modeling, Control, and Stability Analysis of Heterogeneous Thermostatically Controlled Load Populations Using Partial Differential Equations

2015 ◽  
Vol 137 (10) ◽  
Author(s):  
Azad Ghaffari ◽  
Scott Moura ◽  
Miroslav Krstić
Keyword(s):  
Power Control ◽  
Electricity Consumption ◽  
State Feedback Control ◽  
Seasonal Temperature ◽  
Partial Differential ◽  
Modeling And Control ◽  
Proposed Model ◽  
The Stability ◽  
Utility Managers ◽  
And Control

Thermostatically controlled loads (TCLs) account for more than one-third of the U.S. electricity consumption. Various techniques have been used to model TCL populations. A high-fidelity analytical model of heterogeneous TCL (HrTCL) populations is of special interest for both utility managers and customers (that facilitates the aggregate synthesis of power control in power networks). We present a deterministic hybrid partial differential equation (PDE) model which accounts for HrTCL populations and facilitates analysis of common scenarios like cold load pick up, cycling, and daily and/or seasonal temperature changes to estimate the aggregate performance of the system. The proposed technique is flexible in terms of parameter selection and ease of changing the set-point temperature and deadband width all over the TCL units. We investigate the stability of the proposed model along with presenting guidelines to maintain the numerical stability of the discretized model during computer simulations. Moreover, the proposed model is a close fit to design feedback algorithms for power control purposes. Hence, we present output- and state-feedback control algorithms, designed using the comparison principle and Lyapunov analysis, respectively. We conduct various simulations to verify the effectiveness of the proposed modeling and control techniques.

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