Selected numerical analysis tools, mostly in Python or MATLAB.

Process control


  • ml-obs - MATLAB scripts to implement various process observers, including Kalman filter, EKF, and multi-model observers.

  • SL4WT - MATLAB implementation and evaluation of the Adaptive Real Time Exploration and Optimization (ARTEO) algorithm.

  • mpc-code - MATLAB scripts to implement MPC prediction equations and control laws for linear system models.

Simulations environments

  • gym-CartPole-bt-v0 - A modified version of the cart-pole OpenAI Gym environment for testing different control policies.

  • gym-julia - Julia version of above cart-pole test environment.

  • process-models - MATLAB process simulation models for control system design.

I am also a contributor to the open source Python Control Systems Library.

MATLAB Utility scripts

  • ml-data-utils - Various functions to manage experimental data in MATLAB

  • ml-plot-utils - Various functions to make nice plots in MATLAB

  • ml-sys-id - Various functions for identifying AR and ARX models in MATLAB

Machine learning

  • dyn-opt - Python tools for data pre-processing and dynamic system model identification.

  • testing-rl - Python experiments to test basic reinforcement learning algorithms on cart-pole control problem.

  • experiments - Tools to setup and manage machine learning tests and experiments on a remote machine.

Energy optimization

  • energy-opt - Python functions for analyzing energy consumption in industrial process operations.