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21.
A General Robust MPC Design for the State‐Space Model: Application to Paper Machine Process 下载免费PDF全文
Applying model predictive control (MPC) in some cases such as complicated process dynamics and/or rapid sampling leads us to poorly numerically conditioned solutions and heavy computational load. Furthermore, there is always mismatch in a model that describes a real process. Therefore, in this paper in order to prevail over the mentioned difficulties, we design a robust MPC using the Laguerre orthonormal basis in order to speed up the convergence at the same time with lower computation adding an extra parameter “a” in MPC. In addition, the Kalman state estimator is included in the prediction model and accordingly the MPC design is related to the Kalman estimator parameters as well as the error of estimations which helps the controller react faster against unmeasured disturbances. Tuning the parameters of the Kalman estimator as well as MPC is another achievement of this paper which guarantees the robustness of the system against the model mismatch and measurement noise. The sensitivity function at low frequency is minimized to tune the MPC parameters since the lower the magnitude of the sensitivity function at low frequency the better command tracking and disturbance rejection results. The integral absolute error (IAE) and peak of the sensitivity are used as constraints in optimization procedure to ensure the stability and robustness of the controlled process. The performance of the controller is examined via the controlling level of a Tank and paper machine processes. 相似文献
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Emad Shihab Akinori Ihara Yasutaka Kamei Walid M. Ibrahim Masao Ohira Bram Adams Ahmed E. Hassan Ken-ichi Matsumoto 《Empirical Software Engineering》2013,18(5):1005-1042
Bug fixing accounts for a large amount of the software maintenance resources. Generally, bugs are reported, fixed, verified and closed. However, in some cases bugs have to be re-opened. Re-opened bugs increase maintenance costs, degrade the overall user-perceived quality of the software and lead to unnecessary rework by busy practitioners. In this paper, we study and predict re-opened bugs through a case study on three large open source projects—namely Eclipse, Apache and OpenOffice. We structure our study along four dimensions: (1) the work habits dimension (e.g., the weekday on which the bug was initially closed), (2) the bug report dimension (e.g., the component in which the bug was found) (3) the bug fix dimension (e.g., the amount of time it took to perform the initial fix) and (4) the team dimension (e.g., the experience of the bug fixer). We build decision trees using the aforementioned factors that aim to predict re-opened bugs. We perform top node analysis to determine which factors are the most important indicators of whether or not a bug will be re-opened. Our study shows that the comment text and last status of the bug when it is initially closed are the most important factors related to whether or not a bug will be re-opened. Using a combination of these dimensions, we can build explainable prediction models that can achieve a precision between 52.1–78.6 % and a recall in the range of 70.5–94.1 % when predicting whether a bug will be re-opened. We find that the factors that best indicate which bugs might be re-opened vary based on the project. The comment text is the most important factor for the Eclipse and OpenOffice projects, while the last status is the most important one for Apache. These factors should be closely examined in order to reduce maintenance cost due to re-opened bugs. 相似文献
25.
The position control system of an electro-hydraulic actuator system (EHAS) is investigated in this paper. The EHAS is developed by taking into consideration the nonlinearities of the system: the friction and the internal leakage. A variable load that simulates a realistic load in robotic excavator is taken as the trajectory reference. A method of control strategy that is implemented by employing a fuzzy logic controller (FLC) whose parameters are optimized using particle swarm optimization (PSO) is proposed. The scaling factors of the fuzzy inference system are tuned to obtain the optimal values which yield the best system performance. The simulation results show that the FLC is able to track the trajectory reference accurately for a range of values of orifice opening. Beyond that range, the orifice opening may introduce chattering, which the FLC alone is not sufficient to overcome. The PSO optimized FLC can reduce the chattering significantly. This result justifies the implementation of the proposed method in position control of EHAS. 相似文献
26.
Anas El Husseini Abdallah M’Hamed Bachar El Hassan Mounir Mokhtari 《Personal and Ubiquitous Computing》2013,17(5):1013-1023
In smart environments, pervasive computing contributes in improving daily life activities for dependent people by providing personalized services. Nevertheless, those environments do not guarantee a satisfactory level for protecting the user privacy and ensuring the trust between communicating entities. In this study, we propose a trust evaluation model based on user past and present behavior. This model is associated with a lightweight authentication key agreement protocol (Elliptic Curve-based Simple Authentication Key Agreement). The aim is to enable the communicating entities to establish a level of trust and then succeed in a mutual authentication using a scheme suitable for low-resource devices in smart environments. An innovation in our trust model is that it uses an accurate approach to calculate trust in different situations and includes a human-based feature for trust feedback, which is user rating. Finally, we tested and implemented our scheme on Android mobile phones in a smart environment dedicated for handicapped people. 相似文献
27.
Zerrik El Hassan Ghafrani Fatima 《International Journal of Control, Automation and Systems》2009,7(2):297-304
The aim of this paper is to deal with an output controllability problem. It consists in driving the state of a distributed
parabolic system toward a state between two prescribed functions on a boundary subregion of the system evolution domain with
minimum energy control. Two necessary conditions are derived. The first one is formulated in terms of subdifferential associated
with a minimized functional. The second one is formulated as a system of equations for arguments of the Lagrange systems.
Numerical illustrations show the efficiency of the second approach and lead to some conjectures.
Recommended by Editorial Board member Fumitoshi Matsuno under the direction of Editor Jae Weon Choi.
Zerrik El Hassan is a Professor at the university Moulay Ismail of Meknes in Morocco. He was an Assistant Professor in the faculty of sciences
of Meknes and researcher at the university of Perpignan (France). He got his doctorat d etat in system regional analysis (1993)
at the University Mohammed V of Rabat, Morocco. Professor Zerrik wrote many papers and books in the area of systems analysis
and control. Now he is the Head of the research team MACS (Modeling Analysis and Control of Systems) at the university Moulay
Ismail of Meknes in Morocco.
Ghafrani Fatima is a Researcher at team MACS at the University Moulay Ismail of Meknes in Morocco. She wrote many papers in the area of systems
analysis and control. 相似文献
28.
Hatim Lahza Hassan Khosravi Gianluca Demartini 《Journal of Computer Assisted Learning》2023,39(1):94-112
Background
The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored.Objectives
To contribute to filling this gap, this study explores how students engage with learnersourcing tasks across a range of course and assessment designs.Methods
We conducted an exploratory study on trace data of 1279 students across three courses, originating from the use of a learnersourcing environment under different assessment designs. We employed a new methodology from the learning analytics (LA) field that aims to represent students' behaviour through two theoretically-derived latent constructs: learning tactics and the learning strategies built upon them.Results
The study's results demonstrate students use different tactics and strategies, highlight the association of learnersourcing contexts with the identified learning tactics and strategies, indicate a significant association between the strategies and performance and contribute to the employed method's generalisability by applying it to a new context.Implications
This study provides an example of how learning analytics methods can be employed towards the development of effective learnersourcing systems and, more broadly, technological educational solutions that support learner-centred and data-driven learning at scale. Findings should inform best practices for integrating learnersourcing activities into course design and shed light on the relevance of tactics and strategies to support teachers in making informed pedagogical decisions. 相似文献29.
Hassan Md Rafiul Ismail Walaa N Chowdhury Ahmad Hossain Sharara Huda Shamsul Hassan Mohammad Mehedi 《The Journal of supercomputing》2022,78(7):10250-10274
The Journal of Supercomputing - This paper designs and develops a computational intelligence-based framework using convolutional neural network (CNN) and genetic algorithm (GA) to detect COVID-19... 相似文献
30.
Data available in software engineering for many applications contains variability and it is not possible to say which variable helps in the process of the prediction. Most of the work present in software defect prediction is focused on the selection of best prediction techniques. For this purpose, deep learning and ensemble models have shown promising results. In contrast, there are very few researches that deals with cleaning the training data and selection of best parameter values from the data. Sometimes data available for training the models have high variability and this variability may cause a decrease in model accuracy. To deal with this problem we used the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) for selection of the best variables to train the model. A simple ANN model with one input, one output and two hidden layers was used for the training instead of a very deep and complex model. AIC and BIC values are calculated and combination for minimum AIC and BIC values to be selected for the best model. At first, variables were narrowed down to a smaller number using correlation values. Then subsets for all the possible variable combinations were formed. In the end, an artificial neural network (ANN) model was trained for each subset and the best model was selected on the basis of the smallest AIC and BIC value. It was found that combination of only two variables’ ns and entropy are best for software defect prediction as it gives minimum AIC and BIC values. While, nm and npt is the worst combination and gives maximum AIC and BIC values. 相似文献