| 1. |
- Abdalmoaty, Mohamed, et al.
(författare)
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Measures and LMIs for optimal control of piecewise-affine systems
- 2013
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Ingår i: 2013 European Control Conference, ECC 2013. - : IEEE. - 9783033039629 ; , s. 3173-3178
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Konferensbidrag (refereegranskat)abstract
- This paper considers the class of deterministic continuous-time optimal control problems (OCPs) with piecewise-affine (PWA) vector field, polynomial Lagrangian and semialgebraic input and state constraints. The OCP is first relaxed as an infinite-dimensional linear program (LP) over a space of occupation measures. This LP is then approached by an asymptotically converging hierarchy of linear matrix inequality (LMI) relaxations. The relaxed dual of the original LP returns a polynomial approximation of the value function that solves the Hamilton-Jacobi-Bellman (HJB) equation of the OCP. Based on this polynomial approximation, a suboptimal policy is developed to construct a state feedback in a sample-and-hold manner. The results show that the suboptimal policy succeeds in providing a suboptimal state feedback law that drives the system relatively close to the optimal trajectories and respects the given constraints.
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| 2. |
- Abdalmoaty, Mohamed Rasheed, 1986-, et al.
(författare)
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Consistent Estimators of Stochastic MIMO Wiener Models based on Suboptimal Predictors
- 2018
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Ingår i: 2018 IEEE Conference on Decision and Control (CDC). - : IEEE. - 9781538613955 - 9781538613948 - 9781538613962 ; , s. 3842-3847
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Konferensbidrag (refereegranskat)abstract
- We consider a parameter estimation problem in a general class of stochastic multiple-inputs multiple-outputs Wiener models, where the likelihood function is, in general, analytically intractable. When the output signal is a scalar independent stochastic process, the likelihood function of the parameters is given by a product of scalar integrals. In this case, numerical integration may be efficiently used to approximately solve the maximum likelihood problem. Otherwise, the likelihood function is given by a challenging multidimensional integral. In this contribution, we argue that by ignoring the temporal and spatial dependence of the stochastic disturbances, a computationally attractive estimator based on a suboptimal predictor can be constructed by evaluating scalar integrals regardless of the number of outputs. Under some conditions, the convergence of the resulting estimators can be established and consistency is achieved under certain identifiability hypothesis. We highlight the relationship between the resulting estimators and a recently proposed prediction error method estimator. We also remark that the method can be used for a wider class of stochastic nonlinear models. The performance of the method is demonstrated by a numerical simulation example using a 2-inputs 2-outputs model with 9 parameters.
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| 3. |
- Abdalmoaty, Mohamed R. H., 1986-, et al.
(författare)
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Identification of Non-Linear Differential-Algebraic Equation Models with Process Disturbances
- 2021
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Ingår i: 2021 60th IEEE Conference on Decision and Control (CDC). - : IEEE. - 9781665436595 - 9781665436588 - 9781665436601 ; , s. 2300-2305
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Konferensbidrag (refereegranskat)abstract
- Differential-algebraic equations (DAEs) arise naturally as a result of equation-based object-oriented modeling. In many cases, these models contain unknown parameters that have to be estimated using experimental data. However, often the system is subject to unknown disturbances which, if not taken into account in the estimation, can severely affect the model's accuracy. For non-linear state-space models, particle filter methods have been developed to tackle this issue. Unfortunately, applying such methods to non-linear DAEs requires a transformation into a state-space form, which is particularly difficult to obtain for models with process disturbances. In this paper, we propose a simulation-based prediction error method that can be used for non-linear DAEs where disturbances are modeled as continuous-time stochastic processes. To the authors' best knowledge, there are no general methods successfully dealing with parameter estimation for this type of model. One of the challenges in particle filtering methods are random variations in the minimized cost function due to the nature of the algorithm. In our approach, a similar phenomenon occurs and we explicitly consider how to sample the underlying continuous process to mitigate this problem. The method is illustrated numerically on a pendulum example. The results suggest that the method is able to deliver consistent estimates.
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| 4. |
- Abdalmoaty, Mohamed, 1986-, et al.
(författare)
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Simulated Pseudo Maximum Likelihood Identification of Nonlinear Models
- 2017
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Ingår i: The 20th IFAC World Congress. - : Elsevier. ; 50:1, s. 14058-14063
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Konferensbidrag (refereegranskat)abstract
- Nonlinear stochastic parametric models are widely used in various fields. However, for these models, the problem of maximum likelihood identification is very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the analytically intractable likelihood function and compute either the maximum likelihood or a Bayesian estimator. These methods, albeit asymptotically optimal, are computationally expensive. In this contribution, we present a simulation-based pseudo likelihood estimator for nonlinear stochastic models. It relies only on the first two moments of the model, which are easy to approximate using Monte-Carlo simulations on the model. The resulting estimator is consistent and asymptotically normal. We show that the pseudo maximum likelihood estimator, based on a multivariate normal family, solves a prediction error minimization problem using a parameterized norm and an implicit linear predictor. In the light of this interpretation, we compare with the predictor defined by an ensemble Kalman filter. Although not identical, simulations indicate a close relationship. The performance of the simulated pseudo maximum likelihood method is illustrated in three examples. They include a challenging state-space model of dimension 100 with one output and 2 unknown parameters, as well as an application-motivated model with 5 states, 2 outputs and 5 unknown parameters.
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| 5. |
- Ahmed, J., et al.
(författare)
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Automated diagnostic of virtualized service performance degradation
- 2018
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Ingår i: Proceedings 2018 IEEE/IFIP Network Operations and Management Symposium, NOMS 2018. - New York : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1-9
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Konferensbidrag (refereegranskat)abstract
- Service assurance for cloud applications is a challenging task and is an active area of research for academia and industry. One promising approach is to utilize machine learning for service quality prediction and fault detection so that suitable mitigation actions can be executed. In our previous work, we have shown how to predict service-level metrics in real-time just from operational data gathered at the server side. This gives the service provider early indications on whether the platform can support the current load demand. This paper provides the logical next step where we extend our work by proposing an automated detection and diagnostic capability for the performance faults manifesting themselves in cloud and datacenter environments. This is a crucial task to maintain the smooth operation of running services and minimizing downtime. We demonstrate the effectiveness of our approach which exploits the interpretative capabilities of Self- Organizing Maps (SOMs) to automatically detect and localize different performance faults for cloud services.
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| 6. |
- Ahrendt, Wolfgang, 1967, et al.
(författare)
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TriCo—Triple Co-piloting of Implementation, Specification and Tests
- 2022
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 13701 LNCS, s. 174-187, s. 174-187
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Konferensbidrag (refereegranskat)abstract
- This white paper presents the vision of a novel methodology for developing safety-critical software, which is inspired by late developments in learning based co-piloting of implementations. The methodology, called TriCo, integrates formal methods with learning based approaches to co-pilot the agile, simultaneous development of three artefacts: implementation, specification, and tests. Whenever the user changes any of these, a TriCo empowered IDE would suggest changes to the other two artefacts in such a way that the three are kept consistent. The user has the final word on whether the changes are accepted, rejected, or modified. In the latter case, consistency will be checked again and re-established. We discuss the emerging trends which put the community in a good position to realise this vision, describe the methodology and workflow, as well as challenges and possible solutions for the realisation of TriCo.
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| 7. |
- Alghamdi, Fayiq, et al.
(författare)
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Computer science teachers perspectives on competencies - A case study in the Kingdom of Saudi Arabia
- 2018
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Ingår i: 11th International Conference on Informatics in Schools: Situation, Evolution and Perspectives, ISSEP 2018, Saint-Petersburg, Russia. - Cham : Springer. - 9783030027490 ; , s. 129-140
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Konferensbidrag (refereegranskat)abstract
- The Kingdom of Saudi Arabia (KSA) has recently adopted the Saudi Teaching Competencies Standard (STCS). This paper tries to answer how these competencies are achieved, how they are maintained, and what support exists to support teaching CS competently in the KSA. This paper presents the results of an investigation of teacher awareness of, and attitudes to, the STCS in the Kingdom. Through the study reported here, we address an urgent need in the Kingdom to understand teacher preparedness in terms of CS teaching competencies. The study draws on interviews with ten CS teachers in five different cities in the KSA. A thematic coding analysis approach was used. This study explores the CS teaching competencies held by teachers in three areas of CS teaching, focusing on connection to society, professional practice and professional development. The results of the study highlight the CS teaching competencies that CS teachers feel they currently grasp well in the KSA. By enhancing awareness of what teachers currently do well we contribute to the adjustment and improvement of the STCS and help to build a program which addresses the current in-service training needs of CS teachers. The outcomes also help to raise awareness of the challenges of implementing the Computer Education curriculum in KSA schools.
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| 8. |
- Amilon, Jesper, et al.
(författare)
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Automatic Program Instrumentation for Automatic Verification
- 2023
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Ingår i: Computer Aided Verification. - Cham : Springer Nature. ; , s. 281-304, s. 281-304
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Konferensbidrag (refereegranskat)abstract
- In deductive verification and software model checking, dealing with certain specification language constructs can be problematic when the back-end solver is not sufficiently powerful or lacks the required theories. One way to deal with this is to transform, for verification purposes, the program to an equivalent one not using the problematic constructs, and to reason about its correctness instead. In this paper, we propose instrumentation as a unifying verification paradigm that subsumes various existing ad-hoc approaches, has a clear formal correctness criterion, can be applied automatically, and can transfer back witnesses and counterexamples. We illustrate our approach on the automated verification of programs that involve quantification and aggregation operations over arrays, such as the maximum value or sum of the elements in a given segment of the array, which are known to be difficult to reason about automatically. We implement our approach in the MonoCera tool, which is tailored to the verification of programs with aggregation, and evaluate it on example programs, including SV-COMP programs.
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