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Designed LQR and iLQR controllers for multiple non-linear systems describing scenarios such as cart-pole balancing, helicopter hovering, hopper stabilization, and trajectory following for helicopter flight.

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Implementation of LQR, iLQR, DDP and Feedback Linearization techniques.

Part 1: Cartpole-Balancing

A non linear cartpole balancing system was provided. The objective was to balance the cartpole at a single point. Hence, the system was linearized about that single point. This linearized system was used to solve for the infinite horizon controller using LQR.

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Part 2: Helicopter Hover

A similar non linear helicopter hovering system was provided. The objective was to stabilize the hovering system. The infinite horizon controller was determined for the linearized system.

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Part 3: Hopper Stabilization

The objective was to stabilize and observe the hopper under different levels of perturbations for a set of points.

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Part 4: Trajectory following for a helicopter flight

Given a non-linear system, the objective was to trabsform the system into a LTV setting and run LQR. A reference trajectory was provided, that is approximately feasible.

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Setup

Refer to requirements.txt to install all the necessary dependencies. To set up Anaconda environment, refer https://www.anaconda.com/ For Mujoco-py installation, refer https://github.com/openai/mujoco-py

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Designed LQR and iLQR controllers for multiple non-linear systems describing scenarios such as cart-pole balancing, helicopter hovering, hopper stabilization, and trajectory following for helicopter flight.

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