The 2025 series of the Decision Advantage Sprint for Human-Machine Teaming marked a significant step forward in the ...
In ever-changing field environments, conditions can shift rapidly, eroding the best-laid plans with little time to react.
Abstract: The existing adaptive iterative learning control approaches with variable constraints mainly consider the matched uncertainties and only ensure the boundedness of parameter estimation errors ...
Abstract: This paper presents a robust decentralized control approach using iterative learning for interconnected multi-machine systems with uncertainties. The ...
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