vipulkumbhar / aue893_robust_predictive_control

This repository contains classwork and practice examples based on Model Predictive Control. Robust and Stochastic control methods applied to and studied for linear/non-linear plants.

AuE893: Robust Predictive Control, summary of all work

Final Project: Comparison of Stochastic Predictive Control Techniques Applied to Hybrid Energy System (Microgrid)

Figure: Hybrid microgrid plant model

MPC methods studied and compared for KPIs

1] Nominal MPC
2] Uncertain MPC with Kalman filter based state estimator
3] Multi-scenerio based MPC
4] Chance-constrained MPC
5] Tree-based MPC

Figure: Hybrid microgrid plant model with tree-based MPC

HW04:

Robust MPC methods

1] Bounding tube based state constraints for uncertain system
2] MPC without disturbance
3] MPC with disturbance
4] MPC with (an ancillary) feedback controller

Figure: System state trajectory and system control trajectory

HW03:

1] MPC performance for partially stable or unstable systems

Figure: State and input for process noise covariance (α) = 0.06

2] Comparision of MPC performance for systems with time delay to PID controller

Figure: MPC performance for system with time delay

HW02:

1] Nominal MPC problems
2] Nominal MPC with Kalman filter based state estimators

HW01:

1] Linear, non-linear models, Laplace domain transformations, linearization and descretization of plant models, state space realization
2] Time-varying linear quadratic problems, rate of change penalty
3] Steady-state Riccati equation