TY - JOUR
T1 - Distributed adaptive dynamic programming for data-driven optimal control
AU - Tang, Wentao
AU - Daoutidis, Prodromos
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2018/10
Y1 - 2018/10
N2 - Adaptive dynamic programming (ADP), as an important optimal control technique, can be exploited in the setting of data-driven control based on an approximate regression-based solution of the Hamilton–Jacobi–Bellman (HJB) equations. Distributed optimization algorithms, which are extensively studied in statistics and machine learning, have not yet been applied to the solution of data-driven ADP problems. In this work, we identify the data-driven ADP problem as a consensus optimization problem for nonlinear affine systems, and apply the alternating direction method of multipliers (ADMM) and its accelerated variants for its solution. For the input-constrained optimal control problem, we define a combined optimal primal–dual function to develop a data-based version of the input-constrained HJB equation.
AB - Adaptive dynamic programming (ADP), as an important optimal control technique, can be exploited in the setting of data-driven control based on an approximate regression-based solution of the Hamilton–Jacobi–Bellman (HJB) equations. Distributed optimization algorithms, which are extensively studied in statistics and machine learning, have not yet been applied to the solution of data-driven ADP problems. In this work, we identify the data-driven ADP problem as a consensus optimization problem for nonlinear affine systems, and apply the alternating direction method of multipliers (ADMM) and its accelerated variants for its solution. For the input-constrained optimal control problem, we define a combined optimal primal–dual function to develop a data-based version of the input-constrained HJB equation.
KW - Adaptive dynamic programming
KW - Data-driven control
KW - Distributed optimization
KW - Process control
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U2 - 10.1016/j.sysconle.2018.08.002
DO - 10.1016/j.sysconle.2018.08.002
M3 - Article
AN - SCOPUS:85053123123
SN - 0167-6911
VL - 120
SP - 36
EP - 43
JO - Systems and Control Letters
JF - Systems and Control Letters
ER -