scholarly journals A Novel Data-Driven Modeling and Control Design Method for Autonomous Vehicles

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 517
Author(s):  
Dániel Fényes ◽  
Balázs Németh ◽  
Péter Gáspár
Keyword(s):  
Autonomous Vehicles ◽  
Design Method ◽  
Nonlinear Modeling ◽  
Autonomous Vehicle ◽  
Control Design ◽  
Path Following ◽  
Simulation Software ◽  
Model Parameters ◽  
Modeling And Control ◽  
And Control

This paper presents a novel modeling method for the control design of autonomous vehicle systems. The goal of the method is to provide a control-oriented model in a predefined Linear Parameter Varying (LPV) structure. The scheduling variables of the LPV model through machine-learning-based methods using a big dataset are selected. Moreover, the LPV model parameters through an optimization algorithm are computed, with which accurate fitting on the dataset is achieved. The proposed method is illustrated on the nonlinear modeling of the lateral vehicle dynamics. The resulting LPV-based vehicle model is used for the control design of path following functionality of autonomous vehicles. The effectiveness of the modeling and control design methods through comprehensive simulation examples based on a high-fidelity simulation software are illustrated.

scholarly journals Modeling, System Measurements and Controller Investigation of a Small Battery-Powered Fixed-Wing UAV

Machines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 333
Author(s):  
Yue Wang ◽  
Hang Zhu ◽  
Zeyang Zhao ◽  
Cui Zhang ◽  
Yubin Lan
Keyword(s):  
Nonlinear Model ◽  
Controller Design ◽  
Nonlinear Modeling ◽  
Path Following ◽  
Large Error ◽  
Modeling And Control ◽  
Aerodynamic Model ◽  
Set Up ◽  
Cfd Method ◽  
And Control

In this paper, a complete set of nonlinear modeling and controller design process for a small electric fixed-wing unmanned aerial vehicle (UAV) is presented. The nonlinear mathematical model and aerodynamic model of the small fixed-wing UAV are derived. The computational fluid dynamics (CFD) method was used to obtain the aerodynamic coefficients of the UAV, and the models of propulsion system components were established through experiments. Since the linearized and decoupled model of the fixed-wing UAV has a large error, a nonlinear model is established based on Simulink, which is utilized to design and verify the control algorithms. Based on the established nonlinear model, a stability controller, path following controller and path management controller of the aircraft are set up. The results indicate that system parameters of the aircraft can be quickly acquired and an efficient and practical model can be established by the methods. In addition, the controller designed and applied in this paper has good performance and small steady-state error, which can meet the basic flight mission requirements, including stability of flight attitude, path following and switching of different waypoints. These modeling and control methods can also be employed in other small battery-powered fixed-wing UAV projects.

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.

scholarly journals Nonlinear Modeling and Control Design of Active Helicopter Blades

2012 ◽  
Vol 57 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Matthias Althoff ◽  
Mayuresh J. Patil ◽  
Johannes P. Traugott
Keyword(s):  
Structural Model ◽  
Simulation Analysis ◽  
Nonlinear Modeling ◽  
Control Design ◽  
Beam Model ◽  
Linear Quadratic ◽  
Cross Sectional ◽  
Modeling And Control ◽  
Helicopter Blades ◽  
And Control

This paper presents the theoretical basis for the simulation and control of active helicopter blades. The analysis is based on a model that considers the structural dynamics, the aerodynamics, as well as the integrated blade actuation and sensing. The effect of the integral actuation enters the beam model via an active beam cross-sectional analysis. A two-dimensional incompressible, inviscid, quasi-steady aerodynamic model is coupled to the active structural model. For simulation, analysis, and control design, the blade model is discretized in space using a Galerkin approach. The resulting nonlinear model of high order is reduced using the aeroelastic modes of the blade. Finally, the usefulness of a reduced-order model is demonstrated by designing an energy optimal linear-quadratic-Gaussian (LQG) control.

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