scholarly journals Biomimetic-Based Output Feedback for Attitude Stabilization of Rigid Bodies: Real-Time Experimentation on a Quadrotor

Micromachines ◽  
2015 ◽  
Vol 6 (8) ◽  
pp. 993-1022
Author(s):  
José Guerrero-Castellanos ◽  
Hala Rifaï ◽  
Nicolas Marchand ◽  
Rafael Cruz-José ◽  
Samer Mohammed ◽  
...  
Keyword(s):  
Real Time ◽  
Output Feedback ◽  
Rigid Bodies ◽  
Attitude Stabilization

Real-time simulation of lightweight rigid bodies

2013 ◽  
Vol 30 (1) ◽  
pp. 81-92 ◽  
Author(s):  
Haoran Xie ◽  
Kazunori Miyata
Keyword(s):  
Real Time ◽  
Rigid Bodies ◽  
Real Time Simulation ◽  
Time Simulation

Real-Time Explicit Flexible Multibody Dynamics Solver With Application to Virtual-Reality Based E-Learning

2011 ◽  
Author(s):  
Tamer M. Wasfy ◽  
Hatem M. Wasfy ◽  
Jeanne M. Peters
Keyword(s):  
Virtual Reality ◽  
Finite Elements ◽  
Rigid Body ◽  
Real Time ◽  
Multibody Dynamics ◽  
Flexible Multibody Dynamics ◽  
Rigid Bodies ◽  
Flexible Bodies ◽  
Joint Contact ◽  
E Learning

A flexible multibody dynamics explicit time-integration parallel solver suitable for real-time virtual-reality applications is presented. The hierarchical “scene-graph” representation of the model used for display and user-interaction with the model is also used in the solver. The multibody system includes rigid bodies, flexible bodies, joints, frictional contact constraints, actuators and prescribed motion constraints. The rigid bodies rotational equations of motion are written in a body-fixed frame with the total rigid body rotation matrix updated each time step using incremental rotations. Flexible bodies are modeled using total-Lagrangian spring, truss, beam and hexahedral finite elements. The motion of the elements is referred to a global inertial Cartesian reference frame. A penalty technique is used to impose joint/contact constraints. An asperity-based friction model is used to model joint/contact friction. A bounding box binary tree contact search algorithm is used to allow fast contact detection between finite elements and other elements as well as general triangular/quadrilateral rigid-body surfaces. The real-time solver is used to model virtual-reality based experiments (including mass-spring systems, pendulums, pulley-rope-mass systems, billiards, air-hockey and a solar system) for a freshman university physics e-learning course.

Multi-dimensional Taylor network modelling and optimal control of SISO nonlinear systems for tracking by output feedback

2019 ◽  
Vol 37 (3) ◽  
pp. 699-717 ◽  
Author(s):  
Qi-Ming Sun ◽  
Hong-Sen Yan
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Nonlinear Systems ◽  
Real Time ◽  
Output Feedback ◽  
Tracking Error ◽  
Real Time Control ◽  
Network Modelling ◽  
Single Input Single Output ◽  
Time Control

Abstract In this paper, a multi-dimensional Taylor network (MTN) output feedback tracking control of nonlinear single-input single-output (SISO) systems in discrete-time form is studied. To date, neural networks are generally used to identify unknown nonlinear systems. However, the neuron of neural networks includes the exponential function, which contributes to the complexity of calculation, making the neural network control unable to meet the real-time requirements. In order to identify the controlled object whose model is unknown, the MTN, which requires only addition and multiplication, is utilized for successful real-time control of the SISO nonlinear system based on only its output feedback. Lyapunov analysis proves that output signals in the closed-loop system remain bounded and the tracking error converges to an arbitrarily small neighbourhood around the origin. In contrast to the back propagation (BP) neural network self-adaption reconstitution controller, the edge of the scheme is that the MTN optimal controller promises desirable response speed, robustness and real-time control.

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