Search Results (10)

ARINC 653 Part 1 Supplement 5 (ARINC 653P1-5) provides temporal partitioning capabilities for real-time applications running on the multicore processors in Integrated Modular Avionics (IMAs) systems. However, it is difficult to schedule a set of ARINC 653 multicore partitions to achieve a minimum processor occupancy. This paper proposes a model-based optimization method for ARINC 653 multicore partition scheduling. The IMA multicore processing system is modeled as a network of timed automata in UPPAAL. A parallel genetic algorithm is employed to explore the solution space of the IMA system. Owing to a lack of priori information for the system model, the configuration of genetic operators is self-adaptively controlled by a Q-learning algorithm. During the evolution, each individual in a population is evaluated independently by compositional model checking, which verifies each partition in the IMA system and combines all the schedulability results to form a global fitness evaluation. The experiments show that our model-based method outperforms the traditional analytical methods when handling the same task loads in the ARINC 653 multicore partitions, while alleviating the state space explosion of model checking via parallelization acceleration. Full article

Single-Pilot Operations (SPO) mode is set to reshape the decision-making process between human-machine and air-ground operations. However, the limited on-board computing resources impose greater demands on the organization of performance parameters and the optimization of process efficiency in SPO mode. To address this challenge, this paper first investigates the flexible requirements of avionics systems arising from changes in SPO operational scenarios, then analyzes the architecture of Reconfigurable Integrated Modular Avionics (RIMA) and its resource allocation framework in the context of scarcity and configurability. A “mission-function-resource” mapping relationship is established between the reconfiguration service elements of SPO mode and avionics resources. Subsequently, the Proximal Policy Optimization (PPO) algorithm is introduced to simulate the resource allocation process of IMA reconfiguration in SPO mode. The objective optimization process is transformed into a sequential decision-making problem by considering constraints and optimization criteria such as load, latency, and power consumption within the feasible domain of avionics system resources. Finally, the resource allocation scheme for avionics system reconfiguration is determined by controlling the probability of action selection during the interaction between the agent and the environment. The experimental results show that the resource allocation scheme based on the PPO algorithm can effectively reduce power consumption and latency, and the DRL model has strong anti-interference and generalization. This enables avionics resources to respond dynamically to the capabilities required in SPO mode and enhances their ability to support the aircraft mission at all stages. Full article

A coaxial helicopter with a maximum take-off weight of 600 kg was converted to an unmanned aerial vehicle. A minimally invasive robotic actuator system was developed, which can be retrofitted onto the copilot seat of the rotorcraft in a short period of time to enable automatic flight. The automatic flight control robot includes electromechanical actuators, which are connected to the cockpit inceptors and control the helicopter. Most of the sensors and avionic components were integrated into the modular robotic system for faster integration into the rotorcraft. The mechanical design of the control system, the development of the robot control software, and the control system architecture are described in this paper. Furthermore, the multi-body simulation of the robotic system and the estimation of the linear low-order actuator models from hover-frame flight test data are discussed. The developed technologies in this study are not specific to a coaxial helicopter and can be applied to the conversion of any crewed flight vehicle with mechanical controls to unmanned or fly-by-wire. This agile development of a full-size flying test-bed can accelerate the testing of advanced flight control laws, as well as advanced air mobility-related functions. Full article

As the synthesis, modularization, and integration of avionics systems increase, the interconnections between systems and equipment within subsystems become increasingly complex, posing risks to the safety and reliability of the integrated avionics system. To address the risk of fault propagation due to functional cascade failures in integrated avionics systems, this paper proposes a discrete dynamic fault propagation analysis method, which was applied to an all-electric braking system to assess its feasibility. First, the architectural features of the Distributed Integrated Modular Avionics system are summarized. Subsequently, the constructed system layer model is described, establishing the function–resource hierarchical architecture. Subsequently, the behavior of cascading failure propagation in discrete dynamic systems is analyzed by integrating the cascading failure analysis method from SAE ARP 4761A and considering the coupling characteristics between system properties and functions comprehensively. This approach facilitates the development of a cascading failure propagation model for DIMA based on discrete dynamic systems. Finally, by using the all-electric braking system under DIMA architecture as a case study, key Core Processing Modules and failure-prone functions are identified. The findings reveal that within this system, CPM2 and CPM6 are particularly susceptible to failure propagation, and the automatic brake function is notably vulnerable. Data show that the system’s failure rate escalates markedly after $2\times {10}^4$ h of operation. Performing maintenance before reaching this threshold can further mitigate risks. This practice aligns with current international aircraft maintenance time regulations. The method proposed in this paper can be applied early in the allocation of DIMA resources to enhance security and support DIMA design. Full article

The architecture of Integrated Modular Avionics (IMA) provides airborne software with a robust temporal partitioning mechanism, which achieves the reliable fault containment between avionics applications. However, the partition scheduling of an IMA system is a complex nonlinear non-convex optimization problem, making it difficult to solve the optimal temporal allocation for partitions using traditional analytical methods. This paper presents a model-based approach to optimizing the partition scheduling of IMA systems, whose temporal behavior is modeled as a network of timed automata. Given a system model, the optimizer employs a parallel genetic algorithm to search for the optimal partition resource parameters with respect to minimum processor occupancy. For each promising parameter combination, the schedulability constraints and processor occupancy of the system are precisely evaluated by Classical and Statistical Model Checking (i.e., CMC and SMC), respectively. We also apply SMC hypothesis testing to the fast falsification of non-schedulable solutions, thereby speeding up the schedulability verification based on CMC. Two case studies demonstrate that our proposed approach outperforms classical analytical methods on the processor occupancy of typical IMA systems. Full article

With the development of integrated modular avionics (IMA), the dynamic reconfiguration of IMA not only provides great advantages in resource utilization and aircraft configuration, but also acts as a valid means for resource failure management. It is vital to ensure the correction of the IMA dynamic reconfiguration process. The analysis of the dynamic reconfiguration process is a significant task. The Architecture Analysis & Design Language (AADL) is widely used in complicated real-time embedded systems. The language can describe the system configuration and the execution behaviors, such as configuration changes. Petri net is a widely used tool to conduct simulation analysis in many aspects. In this study, a model-based analyzing method with multiple constraints for the IMA dynamic reconfiguration process was proposed. First, several design constraints on the process were investigated. Second, the dynamic reconfiguration process was modeled based on the AADL. Then, a set of rules for the transition of the model from AADL to Petri net was generated, and the multi-constraints proposed were incorporated into Petri net for analysis. Finally, a simulation multi-constraint analysis with Petri net for the process of IMA dynamic reconfiguration was conducted. Finally, a case study was employed to demonstrate this method. This method is advantageous to the validity of IMA dynamic reconfiguration at the beginning of the system design. Full article

With an increasing number of aircraft systems, a fully manual developmental approach is impractical for finding optimal hardware and software mapping from overwhelming configurations for Distributed Integrated Modular Avionics (DIMA) systems. The automation of finding such optimized mapping should be available and thoroughly understood. This paper is an investigation on the foundations of optimal hardware and software mapping for DIMA. We begin by reviewing the DIMA system architecture. Following that, we present the problem statement of hardware and software mapping and its ensuring mathematical optimization models. A set of primary architectural quality metrics (e.g., reliability and scalability) and aircraft constraints (e.g., segregation and resource constraints) are identified, which can be used to compose an objective function or compare and trade alternatives. Based on the quality metrics and aircraft constraints, we synthesize an encompassing formulation by means of multi-objective optimization. Various optimization approaches for hardware and software mapping are then reviewed and compared. Case studies of DIMA optimization are presented for avionics systems, in which running time is reported for different optimization problems with different objectives and constraints. In addition, we present and discuss open issues and future trends, from which future developments may draw upon. Full article

Heterogeneity of the small aircraft category (e.g., small air transport (SAT), urban air mobility (UAM), unmanned aircraft system (UAS)), modern avionic solution (e.g., fly-by-wire (FBW)) and reduced aircraft (A/C) size require more compact, integrated, digital and modular air data system (ADS) able to measure data from the external environment. The MIDAS project, funded in the frame of the Clean Sky 2 program, aims to satisfy those recent requirements with an ADS certified for commercial applications. The main pillar lays on a smart fusion between COTS solutions and analytical sensors (patented technology) for the identification of the aerodynamic angles. The identification involves both flight dynamic relationships and data-driven state observer(s) based on neural techniques, which are deterministic once the training is completed. As this project will bring analytical sensors on board of civil aircraft as part of a redundant system for the very first time, design activities documented in this work have a particular focus on airworthiness certification aspects. At this maturity level, simulated data are used, real flight test data will be used in the next stages. Data collection is described both for the training and test aspects. Training maneuvers are defined aiming to excite all dynamic modes, whereas test maneuvers are collected aiming to validate results independently from the training set and all autopilot configurations. Results demonstrate that an alternate solution is possible enabling significant savings in terms of computational effort and lines of codes but they show, at the same time, that a better training strategy may be beneficial to cope with the new neural network architecture. Full article

The integrated modular avionics (IMA) system is widely used in all classes of aircraft as a result of its high functional integration and resource utilization in developing advanced avionics systems. However, a series of challenges related to safety assessment exist in the background of the logical architecture for multi-message interactions of the IMA system. Traditional safety assessment methods are mainly based on engineering experience, and are difficult to reuse, incomplete, and even error-prone. Here we propose a method to assess the availability of the IMA system based on the thinking of model-based safety analysis. To aid the proposed method, we implement a tool to generate a AltaRica 3.0 file used to assess the IMA system model. The simulation results show that the proposed method makes the availability assessment fast, efficient, and effective. Moreover, we apply this method to the modification analysis of the IMA system under the condition of satisfying the safety requirement. Our study can enhance the safety assessment of safety-critical systems effectively, assist the design of IMA systems, and reduce the amount of errors during the programming process of the safety model. Full article

The development of time-critical Distributed Avionics Applications (DAAs) pushes beyond the limit of existing modeling methodologies to design dependable systems. Aerospace and industrial automation entail high-integrity applications where execution time is essential for dependability. This tempts us to use modeling technologies from one domain in another. The challenge is to demonstrate that they can be effectively used across domains whilst assuring temporally dependable applications. This paper shows that an IEC61499-modeled DAA can satisfy temporal dependability requirements as to end-to-end flow latency when it is properly scheduled and realized in a fully deterministic avionics platform that entails Integrated Modular Avionics (IMA) computation along with Time-Triggered Protocol (TTP) communication. Outcomes from the execution design of an IEC61499-based DAA model for an IMA-TTP platform are used to check runtime correctness through DAA control stability. IEC 61499 is a modeling standard for industrial automation, and it is meant to facilitate distribution and reconfiguration of applications. The DAA case study is a Distributed Fluid Control System (DFCS) for the Airbus-A380 fuel system. Latency analysis results from timing metrics as well as closed-loop control simulation results are presented. Experimental outcomes suggest that an IEC61499-based DFCS model can achieve desired runtime latency for temporal dependability when executed in an IMA-TTP platform. Concluding remarks and future research direction are also discussed. Full article