This study addresses the issue of communication link interruptions in train platoon control under the complex operating environment of high-speed railways. An adaptive trajectory tracking control approach based on a finite-time sliding mode is proposed under jointly connected switching topologies. The proposed framework ensures platoon consensus under jointly connected switching topologies, where the leader’s information need not reach all followers in each topology but only collectively over a finite interval, thus relaxing connectivity requirements and enhancing practicality. Within this framework, the sliding surface is designed to incorporate relative error signals determined by the communication topology, and an adaptive mechanism is employed to effectively handle unknown external disturbances without requiring prior knowledge of their bounds or derivatives. Simulation results demonstrate that, compared with MPC and non-adaptive approaches, the proposed strategy reduces position errors by approximately 80% and velocity errors by around 40%, significantly improving platoon tracking accuracy. Furthermore, simulations under both periodic and random topology switching indicate that periodic switching achieves performance closer to that of a fully connected topology, further enhancing trajectory tracking effectiveness.

System-level design, and dependability prediction of safety-critical systems demand integration of architectural and analysis artifacts in a single development environment. Hybrid systems, with mutual dependencies and extensive interactions between the control portion and its physical environment, further intensify this need. Architecture Analysis and Design Language (AADL) is a model-based engineering language for the architectural design and analysis of embedded control systems. Core AADL has been extended with sub-languages for modeling and analysis of discrete behavior of the control portion, but not for continuous behavior of the physical environment. In a previous work, we have introduced Hybrid Annex for continuous behavior modeling as part of initial findings of an ongoing research effort on fulfilling the need for integrated modeling of the computing system along with its physical environment. In this article, we first detail complete structure of the Hybrid Annex along with appropriate examples for each section. Then, we present formal semantics of the synchronous subset of AADL models annotated with Hybrid Annex specifications using Hybrid Communicating Sequential Processes (HCSP). Formal semantics are used to verify correctness of AADL models (with Hybrid Annex specifications) using Hybrid Hoare Logic (HHL). A case study on a realistically-scaled automatic cruise control system is provided to demonstrate modeling and verification of hybrid systems using AADL with the proposed extension.

Trajectory prediction of the train ahead is vital for deciding the minimum safe distance for train separation. An important research challenge, in this regard, is how to effectively and accurately estimate the trajectory of the train ahead using spatiotemporal approaches with train operating data. In this paper, we present a novel hybrid model for predicting train trajectories by integrating Long Short-Term Memory (LSTM) and Kalman Filter (KF). In the proposed hybrid LSTM-KF model, the LSTM model is used to analyze time series data and discover the long-term dependencies of train trajectory data, which can be assumed as observation data for the KF model. The KF model can combine train dynamics mechanism to extract local features of train operation data, so as to smooth the train trajectory predicted by LSTM model. A novel on-the-fly algorithm is devised for efficient realization of the proposed LSTM-KF model. Experiments are carried out using the train data collected from Chengdu Metro Line 8. The results indicate that our hybrid LSTM-KF model has greatly improved the accuracy of long-term train trajectory prediction.

Developing software for high-dependable space applications and systems is a formidable task. With new political and market pressures on the space industry to deliver more software at a lower cost, optimization of their methods and standards need to be investigated. The industry has to follow standards that strictly set quality goals and prescribes engineering processes and methods to fulfill them. The overall goal of this study is to evaluate if current use of the standards from the European Cooperation for Space Standardization (ECSS) is cost efficient and if there are ways to make the process leaner while still maintaining quality and to analyze if their verification and validation (V&V) activities can be optimized. This paper presents results from two industrial case studies of companies in the European space industry that are following ECSS standards in various V&V activities. The case studies reported here focus on how ECSS standards are used by the companies, how that affects their processes and, in the end, how their V&V activities can be further optimized.