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Obtaining the best coefficients of Inverse Dynamics Controller, for a dynamical system, with Optimization Algorithms.

License: MIT License

MATLAB 100.00%
pid optimization dynamic-system matlab metaheuristic-algorithms genetic-algorithm dynamic dynamic-model dynamic-modelling mass-spring-damper

optimized-inverse-dynamics-controller's Introduction

Optimized-Inverse-Dynamics-Controller

Problem

In this project, a dynamical system has been controlled using Optimized Inverse Dynamics method. The system is a nonlinear mass-spring and represented with a second order Oridinary Differential Equation (ODE). In addition the system has been exposed to harmonic disturbance and white gaussian noise. To find the best coefficents of the controller, optimization algorithms were used. The algorithms are Gradient Descent and Genetic.

Dynamical system, inputs and other variables

System response

how ot run

1.Clone the repository.

2.Change parameters of the dynamical system in simulation_fcn.m and input_constraint.m files if you want.

3.Change parameters of main.m file if you want.

4.Run main.m file in Matlab.

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