Paper Info
Title
Lq Optimal Tracking With Unbounded Cost For Unknown Dynamics: An Adaptive Dynamic Programming Approach
Abstract
In case of unknown system dynamics, we consider linear quadratic optimal tracking on infinite horizons with generally unbounded cost. For the first time, we deal with this problem in the framework of adaptive dynamic programming. So far, existing methods require bounded costs which essentially limits the applicability and achievable performance. Thus, we develop a new algorithm that yields a strongly overtaking optimal control which is an adequate solution. After collecting measurement data in an exploration phase, the algorithm implicitly solves the necessary and sufficient algebraic equations in [3], but without knowledge of the dynamics. Then, implementing the control results in an optimal transition to an optimal stationary trajectory. A simulation example of almost exact tracking for an over-actuated system demonstrates a highly efficient saving of input-energy in contrast to state-of-the-art approaches.
Year
DOI
Venue
2018
10.23919/ECC.2018.8550391
2018 EUROPEAN CONTROL CONFERENCE (ECC)
Field
DocType
Citations 
Dynamic programming,Mathematical optimization,Optimal control,Adaptive system,Computer science,Algebraic equation,System dynamics,Stationary state,Trajectory,Bounded function
Conference
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Sebastian Bernhard101.01
Jürgen Adamy219239.49