Research on the pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization

Research on the pneumatic-electric braking collaborative control strategy for heavy-haul trains based on heuristic dual-end optimization

Blog Article

The pneumatic-electric braking operation of heavy-haul trains on long and steep downgrade sections is fundamentally an optimal control problem, involving nonlinear state constraints, control constraints, and long-distance end constraints.Traditional collaborative control strategies for pneumatic-electric braking often struggle to simultaneously address these constraints, making it difficult to ensure the safety and stability of heavy-haul trains during the pneumatic-electric braking coordinative control process.To tackle this issue, this paper proposes a pneumatic-electric braking collaborative control strategy Windows - Guides for heavy-haul trains based on heuristic dual-end optimization.Firstly, the dynamic characteristics of heavy-haul trains were analyzed, leading to the extraction of nonlinear state constraints, control constraints, and end constraints in the pneumatic-electric braking coordinative control process.

Next, a gradient search was performed focusing on the stability objective within the nonlinear state constraints and control constraints, which resulted Fitness in the formation of a finite set sequence based on the position domain.At the same time, a neural network was designed to identify parameters for a nonlinear pneumatic braking model, thereby yielding predicted pneumatic braking forces.Subsequently, an A * algorithm was developed for iterative refinement within the finite set sequence, collaborative control sequence that satisfies the end constraints.Finally, the effectiveness of the proposed pneumatic-electric collaborative control strategy for heavy-haul trains was verified through a semi-physical simulation platform.