Abstract: This paper investigates optimal tracking control of linear stochastic systems with multiplicative state-dependent and input-dependent noise via a novel model-free integral reinforcement ...
Abstract: Ensuring constraint satisfaction in control systems without relying on accurate models is essential for real-world applications. Learning-based Reference Governors (LRGs) address this ...
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