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mlp icon mlp

matlab code for a simple MLP

mpc-and-mhe-implementation-in-matlab-using-casadi icon mpc-and-mhe-implementation-in-matlab-using-casadi

This is a workshop on implementing model predictive control (MPC) and moving horizon estimation (MHE) on Matlab. The implementation is based on the Casadi Package which is used for numerical optimization. A non-holonomic mobile robot is used as a system for the implementation. The workshop video recording can be found here https://www.youtube.com/playlist?list=PLK8squHT_Uzej3UCUHjtOtm5X7pMFSgAL ... Casadi can be downloaded here https://web.casadi.org/

prescribed-time-control icon prescribed-time-control

This repository includes different versions of the prescribed-time controller as Simulink blocks and MATLAB script codes for engineering applications.

prescribed-time-observer icon prescribed-time-observer

This repository includes different versions of the prescribed-time (extended state) observer as Simulink blocks and MATLAB script codes for different engineering uses.

prescribed-time-observer-examples icon prescribed-time-observer-examples

This repository includes some simulation examples for the prescribed-time extended state observer (PESO) and the prescribed-time disturbance rejection control (PDRC) applied to several mechanical and aerospace systems

rnntool icon rnntool

RNNTool is a matlab toolbox for Recurrent Neural Network

robotic-manipulator-nn-hysteresis icon robotic-manipulator-nn-hysteresis

Code for paper: Adaptive Neural Network Control of a Robotic Manipulator With Backlash hysteresis. http://ieeexplore.ieee.org/document/7866058/

robust-attitude-controller-for-uav-using-dynamic-inversion-and-extended-state-observer-controller icon robust-attitude-controller-for-uav-using-dynamic-inversion-and-extended-state-observer-controller

A robust feedback linearization controller is presented for attitude control of an unmanned aerial vehicle (UAV). The objective of this controller is to make the roll angle, pitch angle, and yaw angle track the given trajectories(commands) respectively. This design is developed using dynamic inversion and extended state observer (ESO). Firstly, dynamic inversion is used to linearize and decouple UAV attitude system into three single-input-single-output (SISO) systems, then three proportional-derivative (PD) controllers are designed for these linearized systems. Extended state observers are used to estimate and compensate unmodeled dynamics and extent disturbances. Simulation results show that the proposed controller is effective and robust.

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