The Experts below are selected from a list of 165549 Experts worldwide ranked by ideXlab platform
Rohit Ramachandran - One of the best experts on this subject based on the ideXlab platform.
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a systematic framework for onsite design and implementation of a control system in a continuous tablet manufacturing process
Computers & Chemical Engineering, 2014Co-Authors: Ravendra Singh, Abhishek Sahay, Fernando J Muzzio, Marianthi G Ierapetritou, Rohit RamachandranAbstract:Abstract A novel manufacturing strategy based on continuous processing integrated with online/inline monitoring tools coupled with an advanced control system is highly desired for efficient Quality by Design (QbD)-based pharmaceutical manufacturing. A control system ensures the predefined end product quality, satisfies the high regulatory constraints, facilitates real time release of the product, and optimizes the resources. In this work, a systematic framework for the onsite design and implementation of the control system in continuous tablet manufacturing process has been developed. The framework includes a generic methodology and supporting tools through which the control system can be designed at the manufacturing site and can be implemented for closed-loop operation. The control framework has different novel features such as the option to run the plant in closed-loop (MPC/PID), open-loop and Simulation Mode. NIR sensor, an online prediction tool, a PAT data management tool, and a control platform have been used to close the control loop.
Macedo Nuno - One of the best experts on this subject based on the ideXlab platform.
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Simulation under Arbitrary Temporal Logic Constraints
'Open Publishing Association', 2019Co-Authors: Brunel Julien, Chemouil David, Cunha Alcino, Macedo NunoAbstract:Most Model checkers provide a useful Simulation Mode, that allows users to explore the set of possible behaviours by interactively picking at each state which event to execute next. Traditionally this Simulation Mode cannot take into consideration additional temporal logic constraints, such as arbitrary fairness restrictions, substantially reducing its usability for debugging the Modelled system behaviour. Similarly, when a specification is false, even if all its counter-examples combined also form a set of behaviours, most Model checkers only present one of them to the user, providing little or no mechanism to explore alternatives. In this paper, we present a simple on-the-fly verification technique to allow the user to explore the behaviours that satisfy an arbitrary temporal logic specification, with an interactive process akin to Simulation. This technique enables a unified interface for simulating the Modelled system and exploring its counter-examples. The technique is formalised in the framework of state/event linear temporal logic and a proof of concept was implemented in an event-based variant of the Electrum framework.Comment: In Proceedings F-IDE 2019, arXiv:1912.0961
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Simulation under arbitrary temporal logic constraints
HAL CCSD, 2019Co-Authors: Brunel Julien, Chemouil David, Cunha Alcino, Macedo NunoAbstract:International audienceMost Model checkers provide a useful Simulation Mode, that allows users to explore the set of possible behaviours by interactively picking at each state which event to execute next. Traditionally this Simulation Mode can not take into consideration additional temporal logic constraints, such as arbitrary fairness restrictions, substantially reducing its usability for debugging the Modelled system behaviour. Similarly, when a specification is false, even if all its counterexamples combined also form a set of behaviours, most Model checkers only present one of them to the user, providing little or no mechanism to explore alternatives. In this paper, we present a simple on-the-fly verification technique to allow the user to explore the behaviours that satisfy an arbitrary temporal logic specification, with an interactive process akin to Simulation. This technique enables a unified interface for simulating the Modelled system and exploring its counterexamples. The technique is formalised in the framework of state/event linear temporal logic and a proof of concept was implemented in an event-based variant of the Electrum framework
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Simulation under arbitrary temporal logic constraints
'Open Publishing Association', 2019Co-Authors: Brunel Julien, Chemouil David, Cunha Alcino, Macedo NunoAbstract:Most Model checkers provide a useful Simulation Mode, that allows users to explore the set of possible behaviours by interactively picking at each state which event to execute next. Traditionally this Simulation Mode cannot take into consideration additional temporal logic constraints, such as arbitrary fairness restrictions, substantially reducing its usability for debugging the Modelled system behaviour. Similarly, when a specification is false, even if all its counter-examples combined also form a set of behaviours, most Model checkers only present one of them to the user, providing little or no mechanism to explore alternatives. In this paper, we present a simple on-the-fly verification technique to allow the user to explore the behaviours that satisfy an arbitrary temporal logic specification, with an interactive process akin to Simulation. This technique enables a unified interface for simulating the Modelled system and exploring its counter-examples. The technique is formalised in the framework of state/event linear temporal logic and a proof of concept was implemented in an event-based variant of the Electrum framework.This work is financed by the ERDF - European Regional Development Fund - through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 - and by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia, within project POCI-01- 0145-FEDER-016826, and the French Research Agency project FORMEDICIS ANR-16-CE25-0007. The third author was also supported by the FCT sabbatical grant with reference SFRH/BSAB/143106/2018
Wang Xiaohua - One of the best experts on this subject based on the ideXlab platform.
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networked Modeling Simulation platform based on concept of cloud computing cloud Simulation platform
Computer Simulation, 2009Co-Authors: Wang XiaohuaAbstract:Based on the research fruits of Simulation Grid [1], a networked Modeling Simulation platform was put forward based on the concept of cloud computing, then its research background, connotation, features and infrastructure were discussed, and the finished research of the related key technologies and typical application demonstration system were introduced. The primary research and practice show that: the "Cloud Simulation" platform can improve the capability of Simulation grid in sharing, collaborating, fault-tolerating and migrating multi-granularity resources on demand by multi-user, which establishes a new Modeling and Simulation Mode—"Cloud Simulation". Finally, the future work of cloud Simulation platform was given.
Ravendra Singh - One of the best experts on this subject based on the ideXlab platform.
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a systematic framework for onsite design and implementation of a control system in a continuous tablet manufacturing process
Computers & Chemical Engineering, 2014Co-Authors: Ravendra Singh, Abhishek Sahay, Fernando J Muzzio, Marianthi G Ierapetritou, Rohit RamachandranAbstract:Abstract A novel manufacturing strategy based on continuous processing integrated with online/inline monitoring tools coupled with an advanced control system is highly desired for efficient Quality by Design (QbD)-based pharmaceutical manufacturing. A control system ensures the predefined end product quality, satisfies the high regulatory constraints, facilitates real time release of the product, and optimizes the resources. In this work, a systematic framework for the onsite design and implementation of the control system in continuous tablet manufacturing process has been developed. The framework includes a generic methodology and supporting tools through which the control system can be designed at the manufacturing site and can be implemented for closed-loop operation. The control framework has different novel features such as the option to run the plant in closed-loop (MPC/PID), open-loop and Simulation Mode. NIR sensor, an online prediction tool, a PAT data management tool, and a control platform have been used to close the control loop.
Mohd. Fua'ad Rahmat - One of the best experts on this subject based on the ideXlab platform.
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feed forward linear quadratic controller design for an industrial electro hydraulic actuator system with servo valve
International Journal on Smart Sensing and Intelligent Systems, 2013Co-Authors: J Micheal, Mohd. Fua'ad Rahmat, Abdul N Wahab, W K LaiAbstract:Electro-hydraulic servo actuator (EHA) system consists of several dynamic parts which are widely used in motion control application. These dynamic parts need to be controlled to determine direction of the motion. In this research paper, system identification technique is used for system Modeling and the Model of the system is estimated by using parameter estimation technique. This process started with collection of input and output data from experimental procedure. The data collected is used for Model estimation and Auto Regressive with eXogeneous input (ARX) Model is chosen as Model structure of the system. Based on the input and output data of the system, best fit criterion and correlation analysis of the residual is analyzed to determine the adequate Model to represent the EHA system. Once the Model is obtained, discrete PID and feed forward plus Linear Quadratic Regulator (LQR) controller is developed to improve the performance and position tracking performance of EHA system. In order to verify these controllers, it is applied to the real time system and the performance of the system is monitored. The result obtained shows that the output of the system in Simulation Mode and experimental works is almost similar for both controllers. The output of the system also tracked the input given successfully. Finally, by comparing the best tuning output from these two different controllers, feed forward plus LQR controller proved to give a better output performance than the classical discrete PID controller by minimize the phase lag and reduce disturbance effect in the system
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pid controller design for an industrial hydraulic actuator with servo system
Student Conference on Research and Development, 2010Co-Authors: Md S Rozali, Mohd. Fua'ad Rahmat, Abdul N Wahab, Rozaimi GhazaliAbstract:Electro-hydraulic system (EHS) consists of several dynamic parts which are widely used in motion control application. These dynamic parts need to be controlled to determine direction of the motion. Mathematical Model of EHS is required in order to design a controller for the system. In this paper, system identification technique is used for system Modeling. Model of the system is estimated by using System Identification Toolbox in Matlab. This process began with collection of input and output data from experimental works. The data collected is used for Model estimation. Auto Regressive with eXogeneous input (ARX) Model is chosen as Model structure of the system. Based on the input and output data of the system, best fit criterion and correlation analysis of the residual is analyze to determine the adequate Model for representing the EHS system. By using Ziegler-Nichols tuning method, PID controller is designed for the Model chosen through Simulation in Simulink. In order to verify this controller, it is applied to the real time system and the performance of the system is monitored. The result obtained shows that the output of the system with controller in Simulation Mode and experimental works is almost similar. The output of the system also tracked the input given successfully.
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Modeling and controller design of an electro-hydraulic actuator system
American Journal of Applied Sciences, 2010Co-Authors: Mohd. Fua'ad Rahmat, Sahazati Md. Rozali, N A Wahab, Kamaruzaman JusoffAbstract:Problem statement: Electro-hydraulic actuators are widely used in motion control application. Its valve needs to be controlled to determine direction of the motion. Mathematical Modeling is a description of a system in terms of equations. It can be divided into two parts; physical Modeling and system identification. The objective of this study was to obtain mathematical Model of an electro-hydraulic system using system identification technique by estimating Model using System Identification Toolbox in MATLAB. Approach: Experimental works were done to collect input and output data for Model estimation and ARX Model was chosen as Model structure of the system. The best Model was accepted based on the best fit criterion and residuals analysis of autocorrelation and cross correlation of the system input and output. PID controller was designed for the Model through Simulation in SIMULINK. The controller is tuning by Ziegler-Nichols method. The Simulation work was verified by applying the controller to the real system to achieve the best performance of the system. Results: The result showed that the output of the system with controller in Simulation Mode and experimental works were improved and almost similar. Conclusion/Recommendations: The designed PID controller can be applied to the electro-hydraulic system either in Simulation or real-time Mode. The self-tuning or automatic tuning controller could be developed in future work to increase the reliability of the PID controller.
