Nonlinear Control for Trajectory Tracking of a Nonholonomic RC-Hovercraft with Discrete Inputs

This work studies the problem of trajectory tracking for an underactuated RC-hovercraft, the control of which must be done by means of discrete inputs. Thus, the aim is to control a vehicle with very simple propellers that produce only a discrete set of control commands, and with minimal information about the dynamics of the actuators. The control problem is approached as a cascade control problem, where the outer loop stabilizes the position error, and the inner loop stabilizes the orientation of the vehicle. Stability of the controller is theoretically demonstrated and the robustness of the control law against disturbances and noise is established. Simulation examples and experiments on a real setup validate the control law showing the real system to be robust against disturbances, noise, and outdated dynamics.

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Observer-Based Output Feedback Control of Nonlinear Systems Non-Affine in the Unmeasured States

ASME 2009 Dynamic Systems and Control Conference, Volume 2 ◽

10.1115/dscc2009-2620 ◽

2009 ◽

Cited By ~ 1

Author(s):

Yannick Morel ◽

Alexander Leonessa

Keyword(s):

Feedback Control ◽

Nonlinear Systems ◽

Control Problem ◽

Output Feedback ◽

Control Algorithm ◽

Output Feedback Control ◽

State Feedback Control ◽

Real System ◽

Control Law ◽

The Real

The presented work addresses the output feedback control problem for a large class of nonlinear systems. The control strategy shares similarities to separation-based algorithms commonly found in the literature, in the sense that the control problem is solved using an observer-predictor, in conjunction with a state feedback control law. The approach however distinguishes itself in significant ways. In particular, the control algorithm is not designed to control the actual system’s output, as is usually the case in separation-based approaches, but it is rather designed to control the output of the observer-predictor. The latter is designed to ensure that, for any admissible control signal, its output converges to a neighborhood of the corresponding output of the real system. The observer-predictor is thus used to indirectly control the real system. Results of numerical simulations are provided to illustrate performance of the obtained control algorithm.

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Synthetic Jet Actuator-Based Aircraft Tracking Using a Continuous Robust Nonlinear Control Strategy

International Journal of Aerospace Engineering ◽

10.1155/2017/4934281 ◽

2017 ◽

Vol 2017 ◽

pp. 1-13

Author(s):

N. Ramos-Pedroza ◽

W. MacKunis ◽

M. Reyhanoglu

Keyword(s):

Nonlinear Control ◽

Trajectory Tracking ◽

Parameter Uncertainty ◽

Tracking Error ◽

Synthetic Jet ◽

Parameter Estimates ◽

Control Law ◽

Robust Nonlinear Control ◽

Trajectory Tracking Control ◽

Nonlinear Control Law

A robust nonlinear control law that achieves trajectory tracking control for unmanned aerial vehicles (UAVs) equipped with synthetic jet actuators (SJAs) is presented in this paper. A key challenge in the control design is that the dynamic characteristics of SJAs are nonlinear and contain parametric uncertainty. The challenge resulting from the uncertain SJA actuator parameters is mitigated via innovative algebraic manipulation in the tracking error system derivation along with a robust nonlinear control law employing constant SJA parameter estimates. A key contribution of the paper is a rigorous analysis of the range of SJA actuator parameter uncertainty within which asymptotic UAV trajectory tracking can be achieved. A rigorous stability analysis is carried out to prove semiglobal asymptotic trajectory tracking. Detailed simulation results are included to illustrate the effectiveness of the proposed control law in the presence of wind gusts and varying levels of SJA actuator parameter uncertainty.

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A Novel Nonlinear Control Law with Trajectory Tracking Capability for Nonholonomic Mobile Robots: Closed-Form Solution Design

Applied Mathematics & Information Sciences ◽

10.12785/amis/070244 ◽

2013 ◽

Vol 7 (2) ◽

pp. 749-754 ◽

Cited By ~ 3

Author(s):

Yung-Hsiang Chen ◽

Tzuu-Hseng S. Li ◽

Yung-Yue Chen

Keyword(s):

Nonlinear Control ◽

Mobile Robots ◽

Closed Form ◽

Trajectory Tracking ◽

Closed Form Solution ◽

Form Solution ◽

Control Law ◽

Nonholonomic Mobile Robots ◽

Solution Design ◽

Nonlinear Control Law

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A Novel Working Point Control Method with Solving the Nonlinear Control Problem of I-V Outer-loop for Space Solar Array Simulator

2019 4th International Conference on Power and Renewable Energy (ICPRE) ◽

10.1109/icpre48497.2019.9034739 ◽

2019 ◽

Author(s):

Shanshan Jin ◽

Donglai Zhang ◽

Zicai Wang ◽

Hua Zhang

Keyword(s):

Nonlinear Control ◽

Control Problem ◽

Control Method ◽

Solar Array ◽

Outer Loop ◽

Point Control ◽

Working Point

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Intuitive dynamic modeling and flatness-based nonlinear control of a mobile robot

SIMULATION ◽

10.1177/0037549717741192 ◽

2017 ◽

Vol 94 (9) ◽

pp. 797-820 ◽

Cited By ~ 4

Author(s):

Saumya R Sahoo ◽

Shital S Chiddarwar ◽

Veer Alakshendra

Keyword(s):

Nonlinear Control ◽

Mobile Robot ◽

Dynamic Model ◽

Dynamic Modeling ◽

Trajectory Tracking ◽

Graph Model ◽

Control Algorithms ◽

Control Law ◽

Backstepping Controller ◽

Simulation Results

In this paper, a bond graph model of a mobile robot with four Mecanum wheels is developed to extract a dynamic model of the robot. This is achieved using the BG_V21 tool box of MATLAB. The dynamic model thus obtained is used to derive the control law for trajectory tracking by the robot. There are two control algorithms that are used, namely, the flatness-based controller and the backstepping controller. From the simulation results, it is evident that the extracted dynamic model of the robot is accurate. Moreover, the flatness-based controller proved to have the upper hand in performance over the backstepping controller.

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A Tool for the Analysis and Characterization of School Mathematical Models

Mathematics ◽

10.3390/math9131569 ◽

2021 ◽

Vol 9 (13) ◽

pp. 1569

Author(s):

Jesús Montejo-Gámez ◽

Elvira Fernández-Ahumada ◽

Natividad Adamuz-Povedano

Keyword(s):

Mathematical Modeling ◽

Mathematical Models ◽

Educational Research ◽

Analysis Procedure ◽

Real System ◽

The Real ◽

School Model ◽

Corresponding Analysis ◽

Three Components

This paper shows a tool for the analysis of written productions that allows for the characterization of the mathematical models that students develop when solving modeling tasks. For this purpose, different conceptualizations of mathematical models in education are discussed, paying special attention to the evidence that characterizes a school model. The discussion leads to the consideration of three components, which constitute the main categories of the proposed tool: the real system to be modeled, its mathematization and the representations used to express both. These categories and the corresponding analysis procedure are explained and illustrated through two working examples, which expose the value of the tool in establishing the foci of analysis when investigating school models, and thus, suggest modeling skills. The connection of this tool with other approaches to educational research on mathematical modeling is also discussed.

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Robust Synchronization of Delayed Chaotic FitzHugh-Nagumo Neurons under External Electrical Stimulation

Computational and Mathematical Methods in Medicine ◽

10.1155/2012/230980 ◽

2012 ◽

Vol 2012 ◽

pp. 1-11 ◽

Cited By ~ 15

Author(s):

Muhammad Rehan ◽

Keum-Shik Hong

Keyword(s):

Electrical Stimulation ◽

Nonlinear Control ◽

Control Law ◽

Input Control ◽

Control Schemes ◽

Multiple Input ◽

Cognitive Diseases ◽

Single Input ◽

Error Dynamics ◽

Nonlinear Control Law

Synchronization of chaotic neurons under external electrical stimulation (EES) is studied in order to understand information processing in the brain and to improve the methodologies employed in the treatment of cognitive diseases. This paper investigates the dynamics of uncertain coupled chaotic delayed FitzHugh-Nagumo (FHN) neurons under EES for incorporated parametric variations. A global nonlinear control law for synchronization of delayed neurons with known parameters is developed. Based on local and global Lipschitz conditions, knowledge of the bounds on the neuronal states, the Lyapunov-Krasovskii functional, and theL2gain reduction, a less conservative local robust nonlinear control law is formulated to address the problem of robust asymptotic synchronization of delayed FHN neurons under parametric uncertainties. The proposed local control law guarantees both robust stability and robust performance and provides theL2bound for uncertainty rejection in the synchronization error dynamics. Separate conditions for single-input and multiple-input control schemes for synchronization of a wide class of FHN systems are provided. The results of the proposed techniques are verified through numerical simulations.

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