Publications Scientifiques

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Modern artificial intelligence technics for unmanned aerial vehicles path planning and control
(2025) Zamoum, Yasmine; Baiche, Karim; Benkeddad, Youcef; Bouzida, Brahim
Unmanned aerial vehicles (UAVs) require effective path planning algorithms to navigate through complex environments. This study investigates the application of Deep Q-learning and Dyna Q-learning methods for UAV path planning and incorporates fuzzy logic for enhanced control. Deep Q-learning, a reinforcement learning technique, employs a deep neural network to approximate Q-values, allowing the UAV to improve its path planning capabilities by maximizing cumulative rewards. Conversely, Dyna Q-learning leverages simulated scenarios to update Q- values, refining the UAV’s decision-making process and adaptability to dynamic environments. Additionally, fuzzy logic control is integrated to manage UAV movements along the planned path. This control system uses linguistic variables and fuzzy rules to handle uncertainties and imprecise information, enabling real-time adjustments to speed, altitude, and heading for accurate path following and obstacle avoidance. The research evaluates the effectiveness of these methods individually, with a focus on model-free learning in a gradual training approach, and compares their performance in terms of path planning accuracy, adaptability, and obstacle avoidance. The paper contributes to a deeper understanding of UAV path planning techniques and their practical applications in various scenarios.
Multivariate nuisance alarm management in chemical processes
(Elsevier, 2021) Kaced, Radhia; Kouadri, Abdelmalek; Baiche, Karim; Bensmail, Abderazak
Alarm systems are of vital importance in the safe and effective functioning of industrial plants, yet they frequently suffer from too many nuisance alarms (alarm overloading). It is necessary to intelligently enhance existing alarm systems and supply accurate information for the operators. Nowadays, process variables are more correlated and complicated. This correlation structure can be used as a basis to manage alarms efficiently. Hence, multivariate approaches are more appropriate. Designing a system aimed at reducing nuisance alarms is an essential phase to guarantee the reliable operation of a plant. Due to the definition of alarm limits, the problem of false alarms is inevitable in multivariate methods. In this paper, the conventional Principal Component Analysis (PCA) is applied to extract the sum of squared prediction error (SPE) known as the statistic and the Hotelling statistic. These statistics are used separately as alarm indicators where their control limits are duly modified. Consequently, for each statistic, a nonlinear combination of alarm duration and alarm deviation, is additionally exploited as a new requirement to activate an alarm or not. The resulting new index is fed to a delay timer with a defined parameter . The implementation of this technique resulted in a significant reduction in the severity of alarm overloading. Historical data collected from the cement rotary kiln operating under healthy conditions are employed to adequately build the PCA model and extract the proposed alarming indexes. Then, various testing data sets, covering different types of faults occurring in the cement process, are used to assess the performance of the developed method. In comparison with the conventional PCA technique, alarms are better managed nd almost nuisance alarms are suppressed. The proposed method is more robust to false alarms and more sensitive to fault detection
Designing alarm system using modified generalized delay-timer
(Elsevier, 2019) Kaced, Radhia; Kouadri, Abdelmalek; Baiche, Karim
Alarm systems are of crucial importance in ensuring safety and efficiency of industrial installations. In practice, alarm systems are not properly designed or given the attention they deserve; their performance is unsatisfactory. The main role of alarms is to inform the operator of any incident in the plant. Regrettably, most occurred alarms are false and nuisance. To avoid this, industrial community developed techniques like deadbands, filters and delay-timers. Delay-timer is largely exercised in industry. This article presents a new concept for designing a Generalized delay-timer. out of n consecutive samples is not the only condition to activate an alarm, we will use additional setpoints to rise or clear an alarm. Three performance indicators namely, False Alarm Rate (), Missed Alarm Rate () and Average Alarm Delay () are computed for the proposed method. At the end, the modified Generalized delay-timer method is examined and compared with the Generalized delay-timer using a simulation and industrial case studies The obtained results show that alarm system performance is improved and even optimized using the modified Generalized delay-timer

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