2022
DOI: 10.3390/e24070889
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Trajectory Tracking within a Hierarchical Primitive-Based Learning Approach

Abstract: A hierarchical learning control framework (HLF) has been validated on two affordable control laboratories: an active temperature control system (ATCS) and an electrical rheostatic braking system (EBS). The proposed HLF is data-driven and model-free, while being applicable on general control tracking tasks which are omnipresent. At the lowermost level, L1, virtual state-feedback control is learned from input–output data, using a recently proposed virtual state-feedback reference tuning (VSFRT) principle. L1 ens… Show more

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Cited by 5 publications
(2 citation statements)
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“…Another article for comparison is the work designed in [30]. Here, a hierarchical primitive-based learning framework (HLF) for trajectory tracking was proposed.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Another article for comparison is the work designed in [30]. Here, a hierarchical primitive-based learning framework (HLF) for trajectory tracking was proposed.…”
Section: Introductionmentioning
confidence: 99%
“…Figure 2: solution x(t) approaching reference r(t) shows that x(t) is tracking reference r(t) when controllers (32a) and (32b) are applied to the system (30).…”
mentioning
confidence: 99%