PALS-Based Analysis of an Airplane Multirate Control System in Real-Time Maude

Distributed cyber-physical systems (DCPS) are pervasive in areas such as aeronautics and ground transportation systems, including the case of distributed hybrid systems. DCPS design and verification is quite challenging because of asynchronous communication, network delays, and clock skews. Furthermore, their model checking verification typically becomes unfeasible due to the huge state space explosion caused by the system's concurrency. The PALS ("physically asynchronous, logically synchronous") methodology has been proposed to reduce the design and verification of a DCPS to the much simpler task of designing and verifying its underlying synchronous version. The original PALS methodology assumes a single logical period, but Multirate PALS extends it to deal with multirate DCPS in which components may operate with different logical periods. This paper shows how Multirate PALS can be applied to formally verify a nontrivial multirate DCPS. We use Real-Time Maude to formally specify a multirate distributed hybrid system consisting of an airplane maneuvered by a pilot who turns the airplane according to a specified angle through a distributed control system. Our formal analysis revealed that the original design was ineffective in achieving a smooth turning maneuver, and led to a redesign of the system that satisfies the desired correctness properties. This shows that the Multirate PALS methodology is not only effective for formal DCPS verification, but can also be used effectively in the DCPS design process, even before properties are verified.Comment: In Proceedings FTSCS 2012, arXiv:1212.657

Cinnamons: A Computation Model Underlying Control Network Programming

We give the easily recognizable name "cinnamon" and "cinnamon programming" to a new computation model intended to form a theoretical foundation for Control Network Programming (CNP). CNP has established itself as a programming paradigm combining declarative and imperative features, built-in search engine, powerful tools for search control that allow easy, intuitive, visual development of heuristic, nondeterministic, and randomized solutions. We define rigorously the syntax and semantics of the new model of computation, at the same time trying to keep clear the intuition behind and to include enough examples. The purposely simplified theoretical model is then compared to both WHILE-programs (thus demonstrating its Turing-completeness), and the "real" CNP. Finally, future research possibilities are mentioned that would eventually extend the cinnamon programming into the directions of nondeterminism, randomness, and fuzziness.Comment: 7th Intl Conf. on Computer Science, Engineering & Applications (ICCSEA 2017) September 23~24, 2017, Copenhagen, Denmar

Exponential Separation of Quantum and Classical Online Space Complexity

Although quantum algorithms realizing an exponential time speed-up over the best known classical algorithms exist, no quantum algorithm is known performing computation using less space resources than classical algorithms. In this paper, we study, for the first time explicitly, space-bounded quantum algorithms for computational problems where the input is given not as a whole, but bit by bit. We show that there exist such problems that a quantum computer can solve using exponentially less work space than a classical computer. More precisely, we introduce a very natural and simple model of a space-bounded quantum online machine and prove an exponential separation of classical and quantum online space complexity, in the bounded-error setting and for a total language. The language we consider is inspired by a communication problem (the set intersection function) that Buhrman, Cleve and Wigderson used to show an almost quadratic separation of quantum and classical bounded-error communication complexity. We prove that, in the framework of online space complexity, the separation becomes exponential.Comment: 13 pages. v3: minor change

Generalized Hybrid Evolutionary Algorithm Framework with a Mutation Operator Requiring no Adaptation

This paper presents a generalized hybrid evolutionary optimization structure that not only combines both nondeterministic and deterministic algorithms on their individual merits and distinct advantages, but also offers behaviors of the three originating classes of evolutionary algorithms (EAs). In addition, a robust mutation operator is developed in place of the necessity of mutation adaptation, based on the mutation properties of binary-coded individuals in a genetic algorithm. The behaviour of this mutation operator is examined in full and its performance is compared with adaptive mutations. The results show that the new mutation operator outperforms adaptive mutation operators while reducing complications of extra adaptive parameters in an EA representation

A critical evaluation of deterministic methods in size optimisation of reliable and cost effective standalone Hybrid renewable energy systems

Reliability of a hybrid renewable energy system (HRES) strongly depends on various uncertainties affecting the amount of power produced by the system. In the design of systems subject to uncertainties, both deterministic and nondeterministic design approaches can be adopted. In a deterministic design approach, the designer considers the presence of uncertainties and incorporates them indirectly into the design by applying safety factors. It is assumed that, by employing suitable safety factors and considering worst-case-scenarios, reliable systems can be designed. In fact, the multi-objective optimisation problem with two objectives of reliability and cost is reduced to a single-objective optimisation problem with the objective of cost only. In this paper the competence of deterministic design methods in size optimisation of reliable standalone wind-PV-battery, wind-PV-diesel and wind-PV-battery-diesel configurations is examined. For each configuration, first, using different values of safety factors, the optimal size of the system components which minimises the system cost is found deterministically. Then, for each case, using a Monte Carlo simulation, the effect of safety factors on the reliability and the cost are investigated. In performing reliability analysis, several reliability measures, namely, unmet load, blackout durations (total, maximum and average) and mean time between failures are considered. It is shown that the traditional methods of considering the effect of uncertainties in deterministic designs such as design for an autonomy period and employing safety factors have either little or unpredictable impact on the actual reliability of the designed wind-PV-battery configuration. In the case of wind-PV-diesel and wind-PV-battery-diesel configurations it is shown that, while using a high-enough margin of safety in sizing diesel generator leads to reliable systems, the optimum value for this margin of safety leading to a cost-effective system cannot be quantified without employing probabilistic methods of analysis. It is also shown that deterministic cost analysis yields inaccurate results for all of the investigated configurations