Key result
Data-based adaptive dynamic programming using initial excitation solves cooperative adaptive cruise control without persistent excitation.
A data-based adaptive dynamic programming method using initial excitation effectively solves the cooperative adaptive cruise control problem for vehicle platoons without requiring persistent excitation or data storage for integral computation.
May advance platoon control design; leaves open real-world validation and robustness testing.
This paper studies the cooperative adaptive cruise control (CACC) problem for a platoon of vehicles with unknown system parameters. Data-based adaptive dynamic programming (ADP) method is adopted to solve the control gains of the vehicles from algebraic Ricatti equations by using online data. The ADP takes a two-layer filter structure, which only requires the initial excitation (IE) condition instead of the restricted persistent excitation (PE) condition when solving the iterative equation. Moreover, data-storage for integral computation is obviated compared with existing data-driven approaches. The simulation results show the effectiveness of the proposed method.
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Yang et al. (2024) studied Vehicular platoons with unknown system parameters. Data-based adaptive dynamic programming (ADP) method with initial excitation (IE) vs. Existing data-driven approaches (requiring persistent excitation) was evaluated on Control gains of the vehicles from algebraic Ricatti equations. A data-based adaptive dynamic programming method using initial excitation effectively solved cooperative adaptive cruise control for vehicular platoons without requiring persistent excitation.
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