Alberto Sangiovanni Vincentelli

Modeling Cyber–Physical Systems

This paper focuses on the challenges of modeling cyber-physical systems (CPSs) that arise from the intrinsic heterogeneity, concurrency, and sensitivity to timing of such systems. It uses a portion of an aircraft vehicle management system (VMS), specifically the fuel management subsystem, to illustrate the challenges, and then discusses technologies that at least partially address the challenges. Specific technologies described include hybrid system modeling and simulation, concurrent and heterogeneous models of computation, the use of domain-specific ontologies to enhance modularity, and the joint modeling of functionality and implementation architectures.

ESPRESSO-SIGNATURE: A New Exact Minimizer for Logic Functions

We present a new algorithm for exact two-level logic optimization which radically improves the Quine-McCluskey (QM) procedure. The new algorithm derives the covering problem directly and implicitly without generating the set of all prime implicants. It then generates only those prime implicants involved in the covering problem. We represent a set of primes by the cube of their intersection. Therefore, the unique set of sets of primes which forms the covering problem can be implicitly represented by a set of cubes which forms a minimum canonical cover. We obtain the minimum canonical cover starting from any initial cover and then derive the covering problem. The method is effective; it improves on the runtime and memory usage of ESPRESSO-EXACT by average factors of 1.78 and 1.19 respectively on the 114 of 134 benchmark examples that could be completed by ESPRESSO-EXACT. Of the remaining 20 hard problems, we solve 14 exactly. For 3 of the remaining 6 the covering problem is derived but it could not be solved exactly.

Definition of Task Allocation and Priority Assignment in Hard Real-Time Distributed Systems

The complexity and physical distribution of modern active safety, chassis and powertrain automotive applications requires the use of distributed architectures. Complex functions designed as networks of function blocks exchanging signal information are deployed onto the physical HW and implemented in a SW architecture consisting of a set of tasks and messages. The typical configuration features priority-based scheduling of tasks and messages and imposes end- to-end deadlines. In this work, we optimize the task placement and the signal to message mapping and we automate the assignment of priorities to tasks and messages in order to meet end-to-end deadline constraints and minimize latencies. This is accomplished by leveraging worst case response time analysis within a mixed integer linear optimization framework. Our approach is applied to an automotive case study to prove its feasibility.

Synthesis of task and message activation models in real-time distributed automotive systems

Modern automotive architectures support the execution of distributed safety- and time-critical functions on a complex networked system with several buses and tens of ECUs. Schedulability theory allows the analysis of the worst case end-to-end latencies and the evaluation of the possible architecture configurations options with respect to timing constraints. The paper presents an optimization framework, based on an ILP formulation of the problem, to select the communication and synchronization model that leverages the trade-offs between the purely periodic and the precedence constrained data-driven activation models to meet the latency and jitter requirements of the application. The authors demonstrate its effectiveness by optimizing a complex automotive architecture

Designing a Cyber–Physical System for Fall Prevention by Cortico–Muscular Coupling Detection

The authors present wearable noninvasive electronics that prevent a human from falling. It deducts a probable fall from EEG and EMG information and provides a real-time alarm signal for protection.

ACTUAL ENGAGED GEAR IDENTIFICATION: A HYBRID OBSERVER APPROACH

Abstract The knowledge of the actual engaged gear is essential to achieve high-quality control of an automotive power train. In cars equipped with manual gear shift, this information is not directly available. A hybrid observer for on-line identification of the actual engaged gear is proposed. Two hybrid models of an automotive driveline, a detailed one for verification and a reduced-order one for synthesis, have been developed. The identification algorithm is based on a novel approach to observer design for hybrid systems. The algorithm was tested on experimental data obtained at Magneti Marelli Powertrain on an Opel Astra equipped with a Diesel engine and a robotized gearbox and yielded excellent results.

Dr. Frankenstein's dream made possible: implanted electronic devices

The developments in micro-nano-electronics, biology and neuro-sciences make it possible to imagine a new world where vital signs can be monitored continuously, artificial organs can be implanted in human bodies and interfaces between the human brain and the environment can extend the capabilities of men thus making the dream of Dr. Frankenstein become true. This paper surveys some of the most innovative implantable devices and offers some perspectives on the ethical issues that come with the introduction of this technology.

Hybrid system reduction

We propose a methodology for hybrid system model reduction that deals with the abstraction of both the continuous and the discrete behaviors of the system. Balanced residualization for continuous dynamics and pseudo-equivalent location elimination for the graph are used for model reduction in the continuous and discrete time domain respectively.

Let's get physical: Adding physical dimensions to cyber systems

ion “physical modeling” Equation-based modelTechnology advances are creating major shifts in the industrial landscape. Traditional sectors such as transportation, medical and avionics, are witnessing fundamental changes in the supply chain and in the content where the interactions between the physical world and the computing world are becoming increasingly tight. Cyber Physical Systems, Systems of Systems, Internet of Things, Industrie 4.0, Swarm Systems and The Fog are all sectors that attract massive attention from the research communities and massive investment from industry. These concepts are tightly intertwined and describe a movement towards a fully interconnected planet where billions of devices interact via a complex mesh of wireless and wired communication infrastructures. The most compelling vision for the future of technology and industry is one where a swarm of devices is connected with the cloud to provide platforms for myriad of new applications. In this new world, new companies will arise and established ones will have to change radically their business model. The increasing sophistication and heterogeneity of these systems requires radical changes in the way sense-and-control platforms are designed to regulate them. In this presentation, I highlight some of the design challenges due to the complexity, heterogeneity and power consumption of CPS. Indeed, low power consumption is an essential requirement for the swarm of devices especially in the domain of wearable devices for healthcare. Coupled with low cost and reliability, power consumption has to be taken into consideration for any CPS deployment.

A complexity metric for concurrent finite state machine based embedded software

The development cost of safety-critical embedded systems is dominated today by the cost of software including verification and validation. This cost is typically related to the complexity of the software functions implementing the desired system behavior in nominal and off-nominal conditions. A widely used measure of complexity is the cyclomatic number, which is computed on the implementation code. However this technique is not effective when model-based development and code generation are used because the complexity of the software also depends on the communication and execution semantics of the models. This paper proposes a model-based complexity number that is defined on the decision diagram (DD) representation of the system functionality. The proposed complexity number gives an upper bound on the number of tests that are necessary to achieve Condition/Decision (C/D) coverage (which is required for safety critical systems). We show that the number of tests is related to the min-flow/max-cut computed on the DD. By comparing the proposed metric with the cyclomatic complexity, we show that the former seems to be better suited for capturing the complexity of the model than the latter. A case study on an aircraft power system shows that the complexity metric has applications in functional partitioning and architecture selection.