Hydraulically-driven parallel robots are extensively deployed in heavy machinery for their superior force-to-weight ratios, yet precise trajectory tracking remains constrained by unmeasurable internal states, strong inter-actuator couplings, and time-varying operational uncertainties. Conventional optimal controllers p...
Vladimir Stojanovic, Dragan Prsic, Ljubiša Dubonjić et al.· Conference proceedings· 0 citations
Robotic systems frequently operate under parametric uncertainties and constrained communication bandwidths, motivating data-driven control architectures that ensure optimal performance without explicit model identification. Conventional adaptive dynamic programming (ADP) methods for output-feedback control typically re...
Sasa Prodanovic, Emanuel Bernardi, X. Luan et al.· Conference proceedings· 0 citations
The deployment of learning-based controllers in modern networked cyber-physical systems is constrained by bandwidth limitations, partial state observability, and parametric uncertainties. Traditional adaptive dynamic programming (ADP) relies on full-state feedback and periodic sampling, inducing network congestion and...
Ljubiša Dubonjić, J. P. Machado, Dragan Prsic et al.· Conference proceedings· 0 citations
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