Md Meftahul Ferdaus | Nanyang Technological University (original) (raw)
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Papers by Md Meftahul Ferdaus
Proceedings of the 31st ACM International Conference on Information & Knowledge Management
Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021
2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2018
Procedia Computer Science, 2018
Information Sciences, 2019
Artificial Intelligence Review, 2018
Journal of Artificial Intelligence and Soft Computing Research, 2019
Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is ... more Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is one of the recent research topics related to the field of autonomous MAVs. Some desiring features of the FW MAV are quick flight, vertical take-off and landing, hovering, and fast turn, and enhanced manoeuvrability contrasted with similar-sized fixed and rotary wing MAVs. Inspired by the FW MAV’s advanced features, a four-wing Nature-inspired (NI) FW MAV is modelled and controlled in this work. The Fuzzy C-Means (FCM) clustering algorithm is utilized to construct the data-driven NIFW MAV model. Being model free, it does not depend on the system dynamics and can incorporate various uncertainties like sensor error, wind gust etc. Furthermore, a Takagi-Sugeno (T-S) fuzzy structure based adaptive fuzzy controller is proposed. The proposed adaptive controller can tune its antecedent and consequent parameters using FCM clustering technique. This controller is employed to control the altitude o...
IEEE Transactions on Fuzzy Systems, 2019
Journal of Zhejiang University-SCIENCE A, 2017
IEEE Transactions on Fuzzy Systems, 2019
International Journal of Electronics and Electrical Engineering, 2014
2015 10th Asian Control Conference (ASCC), 2015
Polymer is obtained by a process called polymerization which is actually a chemical reaction to c... more Polymer is obtained by a process called polymerization which is actually a chemical reaction to combine monomer molecules together. In this work a suitable model and control system was proposed for obtaining the maximum production yield of industrial grade polymer. Significant process parameters specifically system temperature (0C), reaction pressure (bar), and raw materials ratio (%) were selected as process controlling inputs. Differential pressure (DP) obtained from a series of experiments were fitted into a quadratic polynomial model by applying multiple regression analysis. By analyzing the response of three dimensional surface plot, contour plot and soling the regression model equation, the optimal process conditions are obtained. To optimize the interactions among the quadratic polynomial models Center Composite Design (CCD) technique under RSM was used. The results showed the best conditions or the optimized values for initial temperature, system pressure to initiate reaction and monomer gas ratio. Further the maximum predicted value of DP was also obtained at same conditions. At last the trail experiments are evaluated by using the optimum conditions to achieve the higher DP.
ABSTRACT The Padma Multipurpose Bridge Design Project comprises a new fixed crossing of the Padma... more ABSTRACT The Padma Multipurpose Bridge Design Project comprises a new fixed crossing of the Padma River, of approximately 6.15 km long. In order to complement the construction of the Project, it is mandatory to plan and to develop road, railway, transmission and telecommunication networks to connect with the south western part of the country. The main purpose of this study is to harvest energy and assesses the cumulative environmental impact that has been caused by river training, construction and development works. The impacts are classified in few categories-land acquisition and resettlement, transport and economy. Energy harvesting though solar panel and speed breaker is proposed to install for sake of economic and environmental improvement. Here, the probable environmental impacts, both positive and negative are properly analyzed which represents a clear picture of the environmental impact scenario of any multipurpose bridge construction.
IOP Conference Series: Materials Science and Engineering, 2013
IOP Conference Series: Materials Science and Engineering, 2013
IOP Conference Series: Materials Science and Engineering, 2013
IOP Conference Series: Materials Science and Engineering, 2013
Springer, 2019
In recent times, technological advancement boosts the desire of utilizing the autonomous Unmanned... more In recent times, technological advancement boosts the desire of utilizing the autonomous Unmanned Aerial Vehicle (UAV) in both civil and military sectors. Among various UAVs, the ability of rotary wing UAVs (RUAVs) in vertical takeoff and landing, to hover and perform quick maneuvering attract researchers to develop models fully autonomous control framework. The majority of first principle techniques in modeling and controlling RUAV face challenges in incorporating and handling various uncertainties. Recently various fuzzy and neuro-fuzzy based intelligent systems are utilized to enhance the RUAV's modeling and control performance. However, the majority of these fuzzy systems are based on batch learning methods, have static structure, and cannot adapt to rapidly changing environments. The implication of Evolving Intelligent System based model-free data-driven techniques can be a smart option since they can adapt their structure and parameters to cope with sudden changes in the behavior of RUAVs real-time flight. They work in a single pass learning fashion which is suitable for online real-time deployment. In this paper, state of the art of various fuzzy systems from the basic fuzzy system to evolving fuzzy system, their application in a RUAV namely quadcopter with existing limitations, and possible opportunities are analyzed. Besides, a variety of first principle techniques to control the quadcopter, their impediments, and conceivable solution with recently employed evolving fuzzy controllers are reviewed.
Elsevier, 2019
Until now the majority of the neuro and fuzzy modeling and control approaches for rotary wing Unm... more Until now the majority of the neuro and fuzzy modeling and control approaches for rotary wing Unmanned Aerial Vehicles (UAVs), such as the quadrotor, have been based on batch learning techniques, therefore static in structure, and cannot adapt to rapidly changing environments. Implication of Evolving Intelligent System (EIS) based model-free data-driven techniques in fuzzy system are good alternatives, since they are able to evolve both their structure and parameters to cope with sudden changes in behavior, and performs perfectly in a single pass learning mode which is suitable for online real-time deployment. The Metacognitive Scaffolding Learning Machine (McSLM) is seen as a generalized version of EIS since the metacognitive concept enables the what-to-learn, how-to-learn, and when-to-learn scheme, and the scaffolding theory realizes a plug-and-play property which strengthens the online working principle of EISs. This paper proposes a novel online identification scheme, applied to a quadrotor using real-time experimental flight data streams based on McSLM, namely Metacognitive Scaffolding Interval Type 2 Recurrent Fuzzy Neural Network (McSIT2RFNN). Our proposed approach demonstrated significant improvements in both accuracy and complexity against some renowned existing variants of the McSLMs and EISs.
Recently, the quadcopter configuration is becoming prevalent for both civilian and military appli... more Recently, the quadcopter configuration is becoming prevalent for both civilian and military applications, and research is continuing to improve its controllability. However, most the control methodologies depend on accurate system models which are derived from six degrees of freedom nonlinear system dynamics and they generally do not consider realistic outdoor perturbations and uncertainties. As a solution, model-free data-driven system identification and controlling of quadcopter have been refined in this paper. This nonlinear multiple input-multiple output system identification is proliferated using a fuzzy clustering model. The accuracy of the identification is seen to very high. The results of a PID controller used in conjunction with the identified fuzzy model is also presented. The PID controller with the fuzzy identified model is seen to precisely follow the commanded signals.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management
Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021
2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2018
Procedia Computer Science, 2018
Information Sciences, 2019
Artificial Intelligence Review, 2018
Journal of Artificial Intelligence and Soft Computing Research, 2019
Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is ... more Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is one of the recent research topics related to the field of autonomous MAVs. Some desiring features of the FW MAV are quick flight, vertical take-off and landing, hovering, and fast turn, and enhanced manoeuvrability contrasted with similar-sized fixed and rotary wing MAVs. Inspired by the FW MAV’s advanced features, a four-wing Nature-inspired (NI) FW MAV is modelled and controlled in this work. The Fuzzy C-Means (FCM) clustering algorithm is utilized to construct the data-driven NIFW MAV model. Being model free, it does not depend on the system dynamics and can incorporate various uncertainties like sensor error, wind gust etc. Furthermore, a Takagi-Sugeno (T-S) fuzzy structure based adaptive fuzzy controller is proposed. The proposed adaptive controller can tune its antecedent and consequent parameters using FCM clustering technique. This controller is employed to control the altitude o...
IEEE Transactions on Fuzzy Systems, 2019
Journal of Zhejiang University-SCIENCE A, 2017
IEEE Transactions on Fuzzy Systems, 2019
International Journal of Electronics and Electrical Engineering, 2014
2015 10th Asian Control Conference (ASCC), 2015
Polymer is obtained by a process called polymerization which is actually a chemical reaction to c... more Polymer is obtained by a process called polymerization which is actually a chemical reaction to combine monomer molecules together. In this work a suitable model and control system was proposed for obtaining the maximum production yield of industrial grade polymer. Significant process parameters specifically system temperature (0C), reaction pressure (bar), and raw materials ratio (%) were selected as process controlling inputs. Differential pressure (DP) obtained from a series of experiments were fitted into a quadratic polynomial model by applying multiple regression analysis. By analyzing the response of three dimensional surface plot, contour plot and soling the regression model equation, the optimal process conditions are obtained. To optimize the interactions among the quadratic polynomial models Center Composite Design (CCD) technique under RSM was used. The results showed the best conditions or the optimized values for initial temperature, system pressure to initiate reaction and monomer gas ratio. Further the maximum predicted value of DP was also obtained at same conditions. At last the trail experiments are evaluated by using the optimum conditions to achieve the higher DP.
ABSTRACT The Padma Multipurpose Bridge Design Project comprises a new fixed crossing of the Padma... more ABSTRACT The Padma Multipurpose Bridge Design Project comprises a new fixed crossing of the Padma River, of approximately 6.15 km long. In order to complement the construction of the Project, it is mandatory to plan and to develop road, railway, transmission and telecommunication networks to connect with the south western part of the country. The main purpose of this study is to harvest energy and assesses the cumulative environmental impact that has been caused by river training, construction and development works. The impacts are classified in few categories-land acquisition and resettlement, transport and economy. Energy harvesting though solar panel and speed breaker is proposed to install for sake of economic and environmental improvement. Here, the probable environmental impacts, both positive and negative are properly analyzed which represents a clear picture of the environmental impact scenario of any multipurpose bridge construction.
IOP Conference Series: Materials Science and Engineering, 2013
IOP Conference Series: Materials Science and Engineering, 2013
IOP Conference Series: Materials Science and Engineering, 2013
IOP Conference Series: Materials Science and Engineering, 2013
Springer, 2019
In recent times, technological advancement boosts the desire of utilizing the autonomous Unmanned... more In recent times, technological advancement boosts the desire of utilizing the autonomous Unmanned Aerial Vehicle (UAV) in both civil and military sectors. Among various UAVs, the ability of rotary wing UAVs (RUAVs) in vertical takeoff and landing, to hover and perform quick maneuvering attract researchers to develop models fully autonomous control framework. The majority of first principle techniques in modeling and controlling RUAV face challenges in incorporating and handling various uncertainties. Recently various fuzzy and neuro-fuzzy based intelligent systems are utilized to enhance the RUAV's modeling and control performance. However, the majority of these fuzzy systems are based on batch learning methods, have static structure, and cannot adapt to rapidly changing environments. The implication of Evolving Intelligent System based model-free data-driven techniques can be a smart option since they can adapt their structure and parameters to cope with sudden changes in the behavior of RUAVs real-time flight. They work in a single pass learning fashion which is suitable for online real-time deployment. In this paper, state of the art of various fuzzy systems from the basic fuzzy system to evolving fuzzy system, their application in a RUAV namely quadcopter with existing limitations, and possible opportunities are analyzed. Besides, a variety of first principle techniques to control the quadcopter, their impediments, and conceivable solution with recently employed evolving fuzzy controllers are reviewed.
Elsevier, 2019
Until now the majority of the neuro and fuzzy modeling and control approaches for rotary wing Unm... more Until now the majority of the neuro and fuzzy modeling and control approaches for rotary wing Unmanned Aerial Vehicles (UAVs), such as the quadrotor, have been based on batch learning techniques, therefore static in structure, and cannot adapt to rapidly changing environments. Implication of Evolving Intelligent System (EIS) based model-free data-driven techniques in fuzzy system are good alternatives, since they are able to evolve both their structure and parameters to cope with sudden changes in behavior, and performs perfectly in a single pass learning mode which is suitable for online real-time deployment. The Metacognitive Scaffolding Learning Machine (McSLM) is seen as a generalized version of EIS since the metacognitive concept enables the what-to-learn, how-to-learn, and when-to-learn scheme, and the scaffolding theory realizes a plug-and-play property which strengthens the online working principle of EISs. This paper proposes a novel online identification scheme, applied to a quadrotor using real-time experimental flight data streams based on McSLM, namely Metacognitive Scaffolding Interval Type 2 Recurrent Fuzzy Neural Network (McSIT2RFNN). Our proposed approach demonstrated significant improvements in both accuracy and complexity against some renowned existing variants of the McSLMs and EISs.
Recently, the quadcopter configuration is becoming prevalent for both civilian and military appli... more Recently, the quadcopter configuration is becoming prevalent for both civilian and military applications, and research is continuing to improve its controllability. However, most the control methodologies depend on accurate system models which are derived from six degrees of freedom nonlinear system dynamics and they generally do not consider realistic outdoor perturbations and uncertainties. As a solution, model-free data-driven system identification and controlling of quadcopter have been refined in this paper. This nonlinear multiple input-multiple output system identification is proliferated using a fuzzy clustering model. The accuracy of the identification is seen to very high. The results of a PID controller used in conjunction with the identified fuzzy model is also presented. The PID controller with the fuzzy identified model is seen to precisely follow the commanded signals.