This post is password protected. To view it please enter your password below:

Password:

This post is password protected. To view it please enter your password below:

Password:

Abstract: Many modern engineering systems can be mathematically modeled as hybrid systems. For many such systems, there may be uncertain parameters and also parameters that can be adjusted so that the system achieves some optimal performance. It is important to develop efficient numerical tools and software to optimize for these adjustable parameters. We focus on a specific class of hybrid systems where mode transitions are dependent only on the amount of time spent in a mode (or equivalently a clock value). The amount of time spent in each mode is assumed to be a random variable with a known distribution. We aim to design or choose values for the free parameters in each mode of the hybrid system so that the expected value of some meaningful cost-function is minimized. This can be framed as a stochastic optimization problem. We use the sample average approximation method to solve the resulting stochastic optimization problem. We illustrate the method for the optimal design of a thermal management system of a prototypical aircraft.

PDF
@inproceedings{v2d2_cdc_2011,
author = {George Mathew and Alessandro Pinto},
title = {Optimal Design of Hybrid Systems with Uncertain Parameters},
booktitle = {Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference CDC-ECC ’11. },
year = {2011}}

Dynamic Systems and Control Conference

Abstract: A hierarchical control architecture for balancing comfort and energy consumption in buildings is presented. The control design is based on a simplified, yet accurate model of the temperature within each room of the building. The model is validated against real measurements. The control architecture comprises a first level that regulates low level quantities such as air flow, and a second level that balances comfort (i.e. distance between the desired and actual temperature) and energy consumption (i.e. total energy consumed for the required level of comfort). We show the effectiveness of our approach by simulation using validated models.

The Seventh International Conference on Networking and Services, ICNS 2011

Abstract: The building automation industry is experiencing a sudden increase in the complexity of control systems, mainly due to the push towards energy efficient buildings. These systems are necessarily distributed and rely on a communication network to gather data from sensors, produce intermediate results, and send commands to actuators. These networks should be cost effective, and should be flexible enough to be easily reconfigured if the building usage changes over the years. Wireless sensor and actuator networks are, therefore, key enablers. In this paper, we propose a hierarchical wireless network architecture for building automation and control systems and a protocol to manage it. We implement gradient based routing (for collecting data) and label switching table (for disseminating configuration commands), thereby supporting upstream and downstream data flows across the network.

ACM/IEEE Second International Conference on Cyber-Physical Systems, Chicago, IL, April 12-14, 2011

Abstract: We propose a methodology, and its embodiment into a design flow, to realize execution platforms for high-performance building applications. This is an example of a class of cyber-physical systems where a network of sensors, controllers, and actuators must be designed under physical spatial constraints to implement various types of signal processing and control tasks. In our approach, the applications are specified using the dataflow model of computation while the building dictates the physical constraints, including the position of sensors and actuators. We present a rigorous formulation of the design-space exploration problem and we propose to solve it by progressing through a sequence of refinement steps from specification to detailed implementation. Two key steps are the synthesis of the computation platform and the synthesis of the communication network. Combined, they allow us to automatically derive an optimal implementation through the selection and composition of processing and networking elements from given technology libraries. We demonstrate the applicability of our approach by comparing it to the manual design of a given case study: the real-time estimation of building occupancy using a network of video cameras.

PDF

@inproceedings{Leonardi:2011:SDE:2007337.2007445,
author = {Leonardi, Francesco and Pinto, Alessandro and Carloni, Luca P.},
title = {Synthesis of Distributed Execution Platforms for Cyber-Physical Systems with Applications to High-Performance Buildings},
booktitle = {Proceedings of the 2011 IEEE/ACM Second International Conference on Cyber-Physical Systems},
series = {ICCPS ’11},
year = {2011},
isbn = {978-0-7695-4361-1},
pages = {215–224},
numpages = {10},
url = {http://dx.doi.org/10.1109/ICCPS.2011.23},
doi = {http://dx.doi.org/10.1109/ICCPS.2011.23},
acmid = {2007445},
publisher = {IEEE Computer Society},
address = {Washington, DC, USA},
keywords = {Cyber-Physical Systems, CAD, Sythesis},
}

Abstract: In this paper we present an approach to control a vehicle in a hostile environment with obstacles and moving adversaries. The vehicle is required to satisfy a mission objective expressed as a temporal logic specification over a set of properties satisfied at regions of a partitioned environment. To solve this problem, we model the movements of adversaries in between regions of the environment as Poisson processes. Furthermore, we assume that the time it takes for the vehicle to traverse in between two facets of each region is exponentially distributed, and we obtain the rate of this exponential distribution from a simulator of the environment. We capture the motion of the vehicle and the vehicle updates of adversaries distributions as a Markov Decision Process. Using tools in probabilistic Computational Tree Logic, we find a control strategy for the vehicle that maximizes the probability of accomplishing the mission objective. We demonstrate our approach with illustrative case studies.

PDF

@article{journals/corr/abs-1103-4065,
added-at = {2011-12-05T00:00:00.000+0100},
author = {Cizelj, Igor and Ding, Xu Chu and Lahijanian, Morteza and Pinto, Alessandro and Belta, Calin},
biburl = {http://www.bibsonomy.org/bibtex/2968193be417389e99862122e7267e741/dblp},
ee = {http://arxiv.org/abs/1103.4065},
interhash = {d05d077cdc5b4a0b230c14292706dcbb},
intrahash = {968193be417389e99862122e7267e741},
journal = {CoRR},
keywords = {dblp},
timestamp = {2011-12-05T00:00:00.000+0100},
title = {Probabilistically Safe Vehicle Control in a Hostile Environment},
url = {http://dblp.uni-trier.de/db/journals/corr/corr1103.html#abs-1103-4065},
volume = {abs/1103.4065},
year = 2011
}

Abstract:We propose a system-level design flow for building automation and control (BAC) systems. The input to the design flow is a high level description of the control algorithms given in a model-based environment such as Simulink. The input specification is translated into an intermediate format, and then automatically refined into a distributed implementation. Refinement includes optimal mapping of the functional specification on a set of computation and communication resources, and software synthesis, which generates code for each component in the mapped design while guaranteeing semantic equivalence with the original specification. Experiments with a temperature control system are presented to illustrate the flow.

PDF

@inproceedings{conf/rtss/YangPSZ10,
added-at = {2011-06-13T00:00:00.000+0200},
author = {Yang, Yang and Pinto, Alessandro and Sangiovanni-Vincentelli, Alberto L. and Zhu, Qi},
biburl = {http://www.bibsonomy.org/bibtex/244b6454bd3369136bac830df77bd5f13/dblp},
booktitle = {RTSS},
crossref = {conf/rtss/2010},
ee = {http://dx.doi.org/10.1109/RTSS.2010.26},
interhash = {806f6f5d0f4549050db3071689debc3c},
intrahash = {44b6454bd3369136bac830df77bd5f13},
isbn = {978-0-7695-4298-0},
keywords = {dblp},
pages = {105-116},
publisher = {IEEE Computer Society},
timestamp = {2011-06-13T00:00:00.000+0200},
title = {A Design Flow for Building Automation and Control Systems.},
url = {http://dblp.uni-trier.de/db/conf/rtss/rtss2010.html#YangPSZ10},
year = 2010
}

Allerton Conference 2010

Abstract: We motivate the need for a cyber-physical system analysis and design tool that embraces uncertainty as key characteristic of these type of systems. We outline the features that such tool should provide and we present a prototype implementation. The challenges faced during its development go beyond the sheer complexity of analyzing large Markov Models. We close the paper with some examples of analysis of uncertain systems.

PDF

@inproceedings{MbdusPintoAllerton2010,
author = {Alessandro Pinto and Sudha Krishnamurthy},
title = {Developing design tools for uncertain systems in an industrial setting},
booktitle = {Allerton},
month = {September},
year = {2010}
}

Abstract: Hybrid systems are a useful abstraction for systems that have a combination of discrete and continuous dynamics. For typical examples of hybrid systems, there can be various sources of stochasticity. The source of stochasticity can be in the dynamics of the continuous states, the probabilistic switching between various modes of the system and the probabilistic resetting of the continuous state after switches. Such systems can be mathematically modeled by Discrete Time Stochastic Hybrid Systems (DTSHS). If the uncertainty in the initial condition of the stochastic hybrid system is specified by a probability distribution, it is useful to compute the probability distribution of the state of the system for some time in the future. This would allow one to quantify the probability of the system to be in an undesired or unsafe set. Such computations can be useful for probabilistic verification and validation of systems. In this paper, we discuss state space models for DTSHS and present computational methods to propagate probability distributions for DTSHS.

PDF
@inproceedings{ShsMathewAllerton2010,
author = {George Mathew and Alessandro Pinto},
title = {Markov modeling of Stochastic Hybrid Systems},
booktitle = {Allerton},
month = {September},
year = {2010}
}