9 research outputs found
On Model Based Synthesis of Embedded Control Software
Many Embedded Systems are indeed Software Based Control Systems (SBCSs), that
is control systems whose controller consists of control software running on a
microcontroller device. This motivates investigation on Formal Model Based
Design approaches for control software. Given the formal model of a plant as a
Discrete Time Linear Hybrid System and the implementation specifications (that
is, number of bits in the Analog-to-Digital (AD) conversion)
correct-by-construction control software can be automatically generated from
System Level Formal Specifications of the closed loop system (that is, safety
and liveness requirements), by computing a suitable finite abstraction of the
plant.
With respect to given implementation specifications, the automatically
generated code implements a time optimal control strategy (in terms of set-up
time), has a Worst Case Execution Time linear in the number of AD bits , but
unfortunately, its size grows exponentially with respect to . In many
embedded systems, there are severe restrictions on the computational resources
(such as memory or computational power) available to microcontroller devices.
This paper addresses model based synthesis of control software by trading
system level non-functional requirements (such us optimal set-up time, ripple)
with software non-functional requirements (its footprint). Our experimental
results show the effectiveness of our approach: for the inverted pendulum
benchmark, by using a quantization schema with 12 bits, the size of the small
controller is less than 6% of the size of the time optimal one.Comment: Accepted for publication by EMSOFT 2012. arXiv admin note:
substantial text overlap with arXiv:1107.5638,arXiv:1207.409
Reconciling interoperability with efficient Verification and Validation within open source simulation environments
A Cyber–Physical System (CPS) comprises physical as well as software subsystems. Simulation-
based approaches are typically used to support design and Verification and Validation (V&V)
of CPSs in several domains such as: aerospace, defence, automotive, smart grid and healthcare.
Accordingly, many simulation-based tools are available to support CPS design. This, on one
side, enables designers to choose the toolchain that best suits their needs, on the other side
poses huge interoperability challenges when one needs to simulate CPSs whose subsystems have
been designed and modelled using different toolchains. To overcome such an interoperability
problem, in 2010 the Functional Mock-up Interface (FMI) has been proposed as an open
standard to support both Model Exchange (ME) and Co-Simulation (CS) of simulation models
created with different toolchains. FMI has been adopted by several modelling and simulation
environments. Models adhering to such a standard are called Functional Mock-up Units (FMUs).
Indeed FMUs play an essential role in defining complex CPSs through, e.g., the System Structure
and Parametrisation (SSP) standard.
Simulation-based V&V of CPSs typically requires exploring different simulation scenarios
(i.e., exogenous input sequences to the CPS under design). Many such scenarios have a shared
prefix. Accordingly, to avoid simulating many times such shared prefixes, the simulator state at
the end of a shared prefix is saved and then restored and used as a start state for the simulation
of the next scenario. In this context, an important FMI feature is the capability to save and re-
store the internal FMU state on demand. This is crucial to increase efficiency of simulation-based
V&V. Unfortunately, the implementation of this feature is not mandatory and it is available
only within some commercial software. As a result, the interoperability enabled by the FMI
standard cannot be fully exploited for V&V when using open-source simulation environments.
This motivates developing such a feature for open-source CPS simulation environments.
Accordingly, in this paper, we focus on JModelica, an open-source modelling and simulation
environment for CPSs based on an open standard modelling language, namely Modelica. We
describe how we have endowed JModelica with our open-source implementation of the FMI 2.0
functions needed to save and restore internal states of FMUs for ME. Furthermore, we present
experimental results evaluating, through 934 benchmark models, correctness and efficiency
of our extended JModelica. Our experimental results show that simulation-based V&V is, on
average, 22 times faster with our get/set functionality than without it
Linearising discrete time hybrid systems
Model-based design approaches for embedded systems aim at generating correct-by-construction control software, guaranteeing that the closed-loop system (controller and plant) meets given system level formal specifications. This technical note addresses control synthesis for safety and reachability properties of possibly nonlinear discrete-time hybrid systems. By means of a syntactical transformations that requires nonlinear terms to be Lipschitz continuous functions, we overapproximate nonlinear dynamics with a linear system whose controllers are guaranteed to be controllers of the original system. We evaluate performance of our approach on meaningful control synthesis benchmarks, also comparing it to a state-of-the-art tool
The Use of Self-Reflective Essays in Creative Writing
Many Embedded Systems are indeed Software Based Control Systems, that is control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for automatic synthesis of embedded systems control software. This paper addresses control software synthesis for discrete time nonlinear hybrid systems. We present a methodology to overapproximate the dynamics of a discrete time nonlinear hybrid system H by means of a discrete time linear hybrid system LH, in such a way that controllers for LH are guaranteed to be controllers for H. We present experimental results on control software synthesis for the inverted pendulum, a challenging and meaningful control problem. © 2012 IEEE
Optimal Personalised Treatment Computation through In Silico Clinical Trials on Patient Digital Twins
In Silico Clinical Trials (ISCT), i.e. clinical experimental campaigns carried out by means of computer simulations, hold the promise to decrease time and cost for the safety and efficacy assessment of pharmacological treatments, reduce the need for animal and human testing, and enable precision medicine. In this paper we present methods and an algorithm that, by means of extensive computer simulation-based experimental campaigns (ISCT) guided by intelligent search, optimise a pharmacological treatment for an individual patient (precision medicine). We show the effectiveness of our approach on a case study involving a real pharmacological treatment, namely the downregulation phase of a complex clinical protocol for assisted reproduction in humans
Optimal Personalised Treatment Computation through In Silico Clinical Trials on Patient Digital Twins
In Silico Clinical Trials (ISCT), i.e., clinical experimental campaigns carried out by means of computer simulations, hold the promise to decrease time and cost for the safety and efficacy assessment of pharmacological treatments, reduce the need for animal and human testing, and enable precision medicine.
In this paper we present methods and an algorithm that, by means of extensive computer simulation– based experimental campaigns (ISCT) guided by intelligent search, optimise a pharmacological treatment for an individual patient (precision medicine). We show the effectiveness of our approach on a case study involving a real pharmacological treatment, namely the downregulation phase of a complex clinical protocol for assisted reproduction in humans
A glimpse of SmartHG project test-bed and communication infrastructure
The SmartHG project goal is to develop a suite of integrated software services (the SmartHG Platform) aiming at steering residential users energy demand in order to: keep operating conditions of the electrical grid within given healthy bounds, minimize energy costs, and minimize CO2 emissions. This is achieved by exploiting knowledge (demand awareness) of electrical energy prosumption of residential users as gained from SmartHG sensing and communication infrastructure. This paper describes such an infrastructure along with user demand patterns emerging from the data gathered from ~600 sensors installed in ~40 homes participating in SmartHG test-bed
An Integrative Approach for Model Driven Computation of Treatments in Reproductive Medicine
We present an overview of the current status of the European collaborative project PAEON. The challenge of PAEON is to provide specialists in reproductive medicine with a computerised model of the menstrual cycle under normal and various pathological conditions, which will allow them to get further insight in fertility dynamics. This model also enables the simulation of treatment protocols, which were used within in vitro fertilization. By the definition of virtual patients through biologically admissible parametrizations our approach allows not only the evaluation of a given treatment strategy in silico, but also the design and optimization of such protocols. Once a protocol is formalized in the virtual hospital, the success can be controlled by a treatment execution monitor, which works then as a clinical decision support system. All these tools will be combined in a virtual hospital environment, enabling the access to the PAEON services through the web