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This chapter proposes a comprehensive overview of the main paradigms that are handled in the book, namely: optimal control problems (OCPs)Optimal control problem, Model Predictive Control (MPC)Model Predictive Control in its ideal and real-timeReal-time oriented versions, Stochastic Dynamic Programming (SDP)Stochastic dynamic programming, Reinforcement LearningReinforcement Learning, Nonlinear State EstimationState estimation and Probabilistic CertificationProbabilistic certification. The concepts are introduced without a priori knowledge required by the reader. Moreover, for each concept, the link with the main topic of the book, namely, handling the presence of uncertainties, is explained and motivated.

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Definitions, Notation and Main Concepts

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  • 发表日期：

    2026年

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  • Mazen Alamir

摘要

This chapter proposes a comprehensive overview of the main paradigms that are handled in the book, namely: optimal control problems (OCPs)Optimal control problem, Model Predictive Control (MPC)Model Predictive Control in its ideal and real-timeReal-time oriented versions, Stochastic Dynamic Programming (SDP)Stochastic dynamic programming, Reinforcement LearningReinforcement Learning, Nonlinear State EstimationState estimation and Probabilistic CertificationProbabilistic certification. The concepts are introduced without a priori knowledge required by the reader. Moreover, for each concept, the link with the main topic of the book, namely, handling the presence of uncertainties, is explained and motivated.