Neural network identification, predictive modeling and control with a sliding mode learning mechanism: an application to the robotic manipulators

2003 ◽  
Author(s):  
A.V. Topalov ◽  
O. Kaynak ◽  
N.G. Shakev
Keyword(s):  
Neural Network ◽  
Predictive Modeling ◽  
Sliding Mode ◽  
Robotic Manipulators ◽  
Modeling And Control ◽  
Learning Mechanism ◽  
Network Identification ◽  
And Control

Sliding Mode Controller with Neural Network Identification

2015 ◽  
Vol 13 (12) ◽  
pp. 3754-3757 ◽  
Author(s):  
Jose Egidio Azzaro ◽  
Ricardo Alfredo Veiga
Keyword(s):  
Neural Network ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Network Identification

Dynamic Modeling and Control Techniques for a Quadrotor

2019 ◽  
pp. 20-66
Author(s):  
Heba Elkholy ◽  
Maki K. Habib
Keyword(s):  
Pid Controller ◽  
Degrees Of Freedom ◽  
Sliding Mode ◽  
Dynamic Performance ◽  
Simulation Environment ◽  
Modeling And Control ◽  
Controller Gain ◽  
Aerial Vehicle ◽  
And Control ◽  
The Mathematical Model

This chapter presents the detailed dynamic model of a Vertical Take-Off and Landing (VTOL) type Unmanned Aerial Vehicle (UAV) known as the quadrotor. The mathematical model is derived based on Newton Euler formalism. This is followed by the development of a simulation environment on which the developed model is verified. Four control algorithms are developed to control the quadrotor's degrees of freedom: a linear PID controller, Gain Scheduling-based PID controller, nonlinear Sliding Mode, and Backstepping controllers. The performances of these controllers are compared through the developed simulation environment in terms of their dynamic performance, stability, and the effect of possible disturbances.

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