DMAC approximates system dynamics from data with forgetting-factor RLS and synthesizes online full-state feedback controllers with integral action, proving convergence and boundedness.
Robust output regulation and reinforcement learning-based output tracking design f or unknown linear discrete-time systems
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Model-Free Dynamic Mode Adaptive Control for Data-Driven Control Synthesis
DMAC approximates system dynamics from data with forgetting-factor RLS and synthesizes online full-state feedback controllers with integral action, proving convergence and boundedness.