Dynamic Programming and Suboptimal Control: A Survey from ADP to MPC

By Dimitri P. Bertsekas. European Journal of Control, 2005

362 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/51678fc7424bff74307f8fb49ae546f0ae4468e3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cardiology and Cardiovascular Medicine

1. Warrren B Powell

In Control and Systems Engineering

1. Sergey Levine
2. Pieter Abbeel
3. E. Todorov
4. Vikash Kumar
5. Chelsea Finn
6. Yuval Tassa
7. Tom Erez
8. Igor Mordatch

Citations in the corpus

• A Brief Survey of Deep Reinforcement Learning (2017, neutral): “This approach to solving POMDPs is related to other problems using dynamical systems and state space models, where the true state can only be estimated [12].”
• A unified framework for stochastic optimization (2019, background): “Rollout policies were originally introduced and anayzed in Bertsekas and Castanon (1999) .”
• Closed-loop and activity-guided optogenetic control. (2015, neutral): “…such problems including precomputed lookup tables (Rauov et al., 2009; Maurovic et al., 2011), suboptimal control strategies (Wang and Boyd, 2010; Bertsekas, 2005a), and fast explicit solutions that may be carried out at each step (Wang and Boyd, 2011b ) as well as GPU and FPGA computing could…”
• Reinforcement learning for control: Performance, stability, and deep approximators (2018, background): “Accordingly, MPC is model-based, not adaptive, with high online complexity, but with a mature stability, feasibility and robustness theory as well as inherent constraint handling.”
• Stochastic Model Predictive Control: An Overview and Perspectives for Future Research (2016, neutral): “Addressing the general OCP for uncertain systems would involve solving the dynamic programming (DP) problem over (arbitrary) feedback control laws ( ) $ r [7], [8].”
• Infinite-Horizon Model Predictive Control for Periodic Tasks with Contacts (2011, background): “More elaborate proposals include algorithms by Jacobson and Mayne [12] (see appendix), Bryson and Ho [6] and Bertsekas and Dunn [9].”