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I demonstrate a methodology to implement Linear MPC on a non-Linear system of Quadrotor. While the underlying non-linear dynamics are encapsulated, the high-level control is employed to achieve a Linear control system to use a Linear MPC controller.
This program runs in console. It lets the user choose an algorithm to try to solve the 8-square problem with a random starting state. The algorithms included are depth-limited search, uniform-cost search, (greedy) best-first search, and A* search.
This project demonstrates the deployment of a Model Predictive Controller to balance a ball rolling on a tiltabel platform. OpenCV is employed to get the postional feedback of the ball from the platform for closed-loop control.
The Tower Problem, as addressed in the Milton Friedman University's course, is successfully solved through the application of space state representation.
Series of 11 works, covering: State-Space Representations, Search, Adversarial Search, Logic, Automated Reasoning, Reasoning with Uncertainty and Vagueness and Machine Learning