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Observer-based hybrid dynamic event-triggered adaptive neural network control for heterogeneous vehicular platoon
Bingyin Feng1, Xiaopeng He2, Hongsheng Zhao1
1Department of Automotive Engineering, Hebei Vocational University of Technology and Engineering, Xingtai 054000, Hebei, China; Hebei Special Vehicle Modification Technology Innovation Center, Xingtai, 054000, Hebei, China.
ISA Transactions
|July 15, 2026
Summary
This study presents an adaptive neural network (NN) hybrid dynamic event-triggered control (HDETC) for heterogeneous vehicular platoons. The method ensures stability and reduces communication load for safer autonomous driving.
Area of Science:
- Control Systems Engineering
- Artificial Intelligence in Automotive Applications
- Networked Autonomous Systems
Background:
- Heterogeneous vehicular platoon systems (HVPSs) face challenges in stability and communication efficiency.
- Uncertainties and disturbances in HVPSs require robust control strategies.
- Event-triggered control is crucial for managing limited communication bandwidth in vehicular networks.
Purpose of the Study:
- To investigate output-feedback control for nonlinear HVPSs using adaptive neural networks (NNs) and hybrid dynamic event-triggered control (HDETC).
- To develop a communication mechanism that reduces data transmission frequency while ensuring system stability.
- To address the non-differentiability of virtual control signals in backstepping design.
Main Methods:
- Utilizing NNs for approximating lumped uncertainties in HVPSs.
- Employing extended state observers (ESOs) to estimate unknown states and disturbances.
- Designing a novel HDETC communication mechanism to minimize data transmission.
- Developing high-order feedback filters for smooth output estimates.
- Applying Lyapunov stability analysis to ensure system boundedness and string stability.
Main Results:
- An adaptive NN-HDETC control scheme was developed for HVPSs.
- The proposed method ensures boundedness of all signals and achieves string stability.
- The HDETC mechanism effectively reduces communication frequency, optimizing bandwidth usage.
- High-order feedback filters resolved non-differentiability issues in control signals.
Conclusions:
- The developed adaptive NN-HDETC scheme guarantees both individual and string stability for HVPSs.
- The control strategy is effective in managing uncertainties and disturbances in heterogeneous platoons.
- Simulation results validate the efficacy of the proposed heterogeneous vehicular platoon control (HVPC) scheme.
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