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Implementing Tube-Based Robust MPC Controller #24
base: v1.0.0-alpha
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Implementing Tube-Based Robust MPC Controller #24
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… the MPC controllers, modified tracking example accordingly. Re-organized some code in MPC so that it flowed better. Created a new controller called tube_mpc by copy-pasting linear_mpc code.
… the disturbance bounds from running linear MPC.
…oal is actually [0, 1].
… mRPI, making x0 an optimization variable, and then using that with the optimal feedback controller.
… to compute the mRPI set. It seems to work well for cartpole. tube_mpc will throw an exception if you ask it to compute mRPI for anything other than cartpole and 1d quadrotor. Users now have the option to manually specify an mRPI.
…cart-pole to be feasible. fixed a bug with x_init.
…an run the experiments
…log violations on original and tightened constraints
Non TubeMPC Changes:
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Execution Instructions
Expected OutputThe submitted results were for 14 scenarios, each with 100 trials and took approximately 8hrs to run. The results after each trial are printed to the terminal and the aggregated results are exported as a pickle. Here are the expected results for undisturbed scenarios with 1 trial: LQR Stabilization:NUM SUCCESSES: 1 Linear MPC StabilizationNUM SUCCESSES: 1 Tube MPC StabilizationNUM SUCCESSES: 1 LQR TrackingNUM SUCCESSES: 1 Linear MPC TrackingNUM SUCCESSES: 0 Tube MPC TrackingNUM SUCCESSES: 0 |
I have an even leaner version of LQR coded up that removes all the extra logging and debugging that the other controllers don't have and leaves only the core LQR. I prefer this. Let me know if you want me to add this simpler LQR to this PR since I am already cutting down LQR in this PR |
Implementing the Robust Tube Model Predictive Control based on:
D. Mayne, M. Seron and S. Raković "Robust model predictive control of constrained linear systems with bounded disturbance," in Automatica 41(2): 219–224. 2005. doi: https://doi.org/10.1016/ j.automatica.2004.08.019