Mechatronic systems are a class of cyber-physical systems, whose increasing complexitymakes their validation and verification more and more difficult, while their requirements becomemore challenging. This paper introduces a development method based on model-based design,co-simulation and formal verification. The objective of this paper is to show the applicabilityof the method in an industrial setting. An application case study comes from the field of precisionservo-motors, where formal verification has been used to find acceptable intervals of values for designparameters of the motor controller, which have been further explored using co-simulation to findoptimal values. The reported results show that the method has been applied successfully to the casestudy, augmenting the current model-driven development processes by formal verification of stability,formal identification of acceptable parameter ranges, and automatic design-space exploration.
Wireless Sensor and Actuator Networks are becoming attractive also for industrial applications, since recent standardization efforts have introduced significant improvement to reliability and deterministic communication delays. In this context, IEEE 802.15.4e is widely considered the major improvement, introducing many enhancements to the original IEEE 802.15.4 standard aimed at supporting critical applications. Among the new defined MAC protocols, Deterministic and Synchronous Multi-channel Extension (DSME) represents the most suitable option for applications with time-varying requirements. In this paper, an analysis of the IEEE 802.15.4 DSME MAC protocol during network formation is presented. The goal is to study the protocol performance and propose solutions to reduce the network formation time, improving energy and resource efficiency. To carry out the performance evaluation, DSME has been fully implemented in Contiki OS, an actual operating system for sensor nodes. The study has highlighted issues and inefficiencies in the network formation process, allowing to consequently propose effective solutions. In particular, it is proposed a set of guidelines for DSME configuration to the original MAC protocol that are proved to increase significantly the network formation efficiency
Semi-autonomous systems are capable of sensing their environment and perform their tasks autonomously, but they may also be supervised by humans. The shared manual/automatic control makes the dynamics of such systems more complex, and undesirable and hardly predictable behaviours can arise from human-machine interaction. When these systems are used in critical applications, such as autonomous driving or robotic surgery, the identification of conditions that may lead the system to violate safety requirements is of main concern, since people actually entrust their life on them. In this paper, we extend an FMI-based co-simulation framework for cyber-physical systems with the possibility of modelling semi-autonomous robots. Co-simulation can be used to gain more insights on the system under analysis at early stages of system development, and to highlight the impact of human interaction on safety. This approach is applied to the Line Follower Robot case study, available in the INTO-CPS project.
UAVs can be assigned different tasks such as e.g., rendezvous and space coverage, which require processing and communication capabilities. This work extends the architecture ROS/Gazebo with the possibility of simulation of co-operative UAVs. We assume UAV with the underlying attitude controller based on the open-source Ardupilot software. The integration of the co-ordination algorithm in Gazebo is implemented with software modules extending Ardupilot with the capability of sending/receiving messages to/from drones, and executing the co-ordination protocol. As far as it concerns the simulation environment, we have extended the world in Gazebo to hold more than one drone and to open a specific communication port per drone. In the paper, results on the simulation of a representative co-ordination algorithm are shown and discussed, in a scenario where a small number of Iris Quadcopters are deployed.
This paper presents a proof-of-concept application of an approach to system development based on the integration of formal verification and co-simulation. A simple autonomous vehicle has the task of reaching an assigned straight path and then follow it, and it can be controlled by varying its turning speed. The correctness of the proposed control law has been formalized and verified by interactive theorem proving with the Prototype Verification System. Concurrently, the system has been co-simulated using the Prototype Verification System and the MathWorks Simulink tool: The vehicle kinematics have been simulated in Simulink, whereas the controller has been modeled in the logic language of the Prototype Verification System and simulated with the interpreter for the same language available in the theorem proving environment. With this approach, co-simulation and formal verification corroborate each other, thus strengthening developers' confidence in their analysis
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