Papers by Debasis Acharya
Optimal rule based fuzzy-PI controller for core power control of nuclear reactor
Annals of Nuclear Energy
An Adaptive Chaotic Search Class Topper Optimization Algorithm to Design Optimal PI-ID Controller for Artificial Ventilation System
Lecture notes in networks and systems, 2023
Optimal membership function based fuzzy proportional–integral controller for power control of molten salt breeder reactor core
Progress in Nuclear Energy, Jul 1, 2023
A New Quantum-Class Topper Optimization Based Fractional Order Proportional Integral Power System Stabilizer Design to Damp Out Low Frequency Oscillations in Power Systems
Oscillation with low frequency in grid is a serious issue in power sector. It may effect on perfo... more Oscillation with low frequency in grid is a serious issue in power sector. It may effect on performance of the system and even can cause power collapse. To stabilize such oscillation, power system stabilizer (PSS) is used. In this paper, a new quantum class topper based (QCTO) based fractional order proportional integral (FOPI) power system stabilizer (PSS) is proposed to control such oscillations. The parameters of the stabilizer are tuned using QCTO. Integral time square error (ITSE) is chosen as the performance index to design the stabilizer. It is implemented with IEEE type exciter and one machine infinite bus (OMIB). In this paper, two type of exciter such as IEEE type DC1 and IEEE type ST1 excited has been considered for OMIB system. The performance of QCTO based FOPI is compared with QCTO based PI, PID stabilizers. To check the effectiveness of the designed stabilizers, comparative analysis is done with some existing results.
Swarm optimization approach to design PID controller for artificially ventilated human respiratory system
Computer Methods and Programs in Biomedicine, 2021
BACKGROUND AND OBJECTIVE An artificially ventilated human respiratory system is used to help brea... more BACKGROUND AND OBJECTIVE An artificially ventilated human respiratory system is used to help breathing of a patient with respiratory problem. The level of oxygen is maintained stable by controlling the airway pressure in the lungs mechanism with the help of medical ventilator. For pressure control in a ventilator, the airway pressure in lungs mechanism is controlled by a motor driven piston mechanism. The optimal setting of controller parameters of a respiratory ventilator system depends on many factors of a patient such as physical condition of patient, need of oxygen, age of a patient etc. Therefore, computer operated algorithm based artificial ventilation system becomes most popular for its better performance, efficiency, and easy control mechanism. In this paper, a simple swarm optimization based controller design approach is systematically verified to design suitable controller for pressure controlled artificially ventilated human respiratory system. A modified constricted class topper optimization (C-CTO) algorithm is proposed for tuning the controller in an artificial ventilator system. METHODS A pressure controlled ventilation (PCV) model has been considered. A proportional-integral-derivative (PID) controller structure is considered for the PCV. Three different optimization approach (Particle swarm optimization (PSO), class topper optimization (CTO) and a modified constricted class topper optimization (C-CTO)) are verified one by one for the purpose of tuning PID controller for PVC system. RESULTS The performances of swarm based controller in PCV system for three different cases are examined in terms of settling times and maximum overshoot of the system. CONCLUSIONS The swarm based optimization approach is improving the dynamic response of pressure control artificially ventilated human respiratory system. In this paper, a simple piston-motor driven lung mechanism is applied to verify the swarm based approach, but this approach can further be checked in the future for more complex human lungs artificially ventilated system.
An Optimizer to Tune Fractional-Order Power System Stabilizer for Synchronous Generator Considering Governor Effect and Exciter Voltage Fluctuation
Journal of Control, Automation and Electrical Systems, Dec 14, 2022
A Modified Constricted Quantum Class Topper Optimization Algorithm for Tuning FOPI Stabilizer for One Machine Infinite Bus System
An oscillation with frequency of low range in the grid is damped out with power system stabilizer... more An oscillation with frequency of low range in the grid is damped out with power system stabilizer (PSS). The conventional PSS will not provide the flexible operation in real power system. In this paper, a fractional order PI (FOPI) along with wash-out filter is used for one machine infinite bus (OMIB) system. The stabilizer gains are optimized by a modified constricted quantum class topper optimization (CQCTO) algorithm. Integral time square of speed deviation (ITSSD) is taken as the fitness function. It is verified for one machine infinite bus (OMIB) system with IEEE DC-1 type exciter. The comparison of CQCTO-FOPI is presented with class topper optimization (CTO)-FOPI stabilizers and existing results.
An Optimized Tilted Controller for Core Relative Power Control of Nuclear Reactor
2022 4th International Conference on Energy, Power and Environment (ICEPE), Apr 29, 2022
Scientific Reports, Dec 14, 2022
Computational techniques are widely used to solve complex optimization problems in different fiel... more Computational techniques are widely used to solve complex optimization problems in different fields such as engineering, finance, biology, and so on. In this paper, the Human Conception Optimizer (HCO) is proposed as a novel metaheuristic algorithm to solve any optimization problems. The idea of this algorithm is based on some biological principles of the human conception process, such as the selective nature of cervical gel in the female reproductive system to allow only healthy sperm cells into the cervix, the guidance nature of mucus gel to help sperm track a genital tracking path towards the egg in the Fallopian tube, the asymmetric nature of flagellar movement which allows sperm cells to move in the reproductive system, the sperm hyperactivation process to make them able to fertilize an egg. Thus, the strategies pursued by the sperm in searching for the egg in the Fallopian tube are modeled mathematically. The best sperm which will meet the position of the egg will be the solution of the algorithm. The performance of the proposed HCO algorithm is examined with a set of basic benchmark test functions called IEEE CEC-2005 and IEEE CEC-2020. A comparative study is also performed between the HCO algorithm and other available algorithms. The significance of the results is verified with statistical test methods. To validate the proposed HCO algorithm, two real-world engineering optimization problems are examined. For this purpose, a complex 14 over-current relay based IEEE 8 bus distribution system is considered. With the proposed algorithm, an improvement of 50% to 60% in total relay operating times is observed comparing with some existing results for the same system. Another engineering problem of designing an optimal proportional integral derivative (PID) controller for a blower driven patient hose mechanical ventilator (MV) is examined. A significant improvement in terms of response time, settling time is observed in the MV system by comparing with existing results.
Extended Kalman filter state estimation–based nonlinear explicit model predictive control design for blood glucose regulation of type 1 diabetic patient
Medical & Biological Engineering & Computing, Mar 10, 2022
The computational burden of iterative online optimization-based model predictive control (MPC) pr... more The computational burden of iterative online optimization-based model predictive control (MPC) process is solved by adapting off-line optimization-based nonlinear explicit model predictive control (NEMPC). In this paper, the application of NEMPC is verified to regulate blood glucose level in type 1 diabetes mellitus (T1DM) patients. The objective of glucose regulation is to avoid hyperglycemia (> 180 mg/dl) and hypoglycemia (< 50 mg/dl) by maintaining glucose level in the range of 70 to 180 mg/dl. It helps to avoid time complexity of iterative process during solution of optimization stage in MPC. In the nonlinear T1DM model, only the state dynamic of sugar is measurable with low complexity and high cost among other states of the model. Therefore, an extended Kalman filter (EKF) is used developed to estimate unavailable states. The information of the estimated states are used to develop the proposed control approach for the T1DM patients. The simulation results of the NEMPC along with EKF-based state estimator for T1DM model shows the regulation of blood glucose-level (BGL) within 70 to 180 mg/dl within 120 min. The robustness of the proposed scheme is also verified under the change in parameters and food disturbance. The control variability grid analysis (CVGA) of NEMPC for 50 numbers of virtual T1DM patients under random parametric changes and meal disturbances shows the avoidance of hypoglycemia and hyperglycemia in type 1 diabetic patients. The proposed control method is simple, robust and efficient to regulate glucose level in T1DM patients. Extended Kalman filter state estimator based nonlinear explicit model predictive control for blood glucose regulation in Type 1 diabetic patients.
Particle Swarm Optimization based PID-Controller Design for Volume Control of Artificial Ventilation System
2020 IEEE Calcutta Conference (CALCON), Feb 1, 2020
Artificial ventilation has become a necessary means for medical purposes. With an increase in the... more Artificial ventilation has become a necessary means for medical purposes. With an increase in the reliability of such devices, the need for designing a proper controller is growing. The main purpose of this paper is to design a particle swarm optimization (PSO) based PID-controller to control the volume of the artificial ventilation systems. PSO algorithm is used to tune the gains of the PID controller. It aims at improving the dynamic stability of an artificial ventilation system. A step signal is considered as the desired signal for the system which acts as a reference signal for the controller. With the optimum parameters of the designed controller, the dynamic stability of the volume control ventilation system is improved.
An efficient optimizer for optimal overcurrent relay coordination in power distribution system
Expert Systems With Applications, Aug 1, 2022
An enhanced human conception optimization algorithm based optimal 2-DoF-PID controller for Artificial Respiratory Ventilation System
2023 IEEE Guwahati Subsection Conference (GCON)
Scientific Reports
In order to improve the pressure tracking response of an artificial ventilator system, a novel pr... more In order to improve the pressure tracking response of an artificial ventilator system, a novel proportional integral derivative (PID) controller is designed in the present work by utilizing an optimal rule-based fuzzy inference system (FIS) with a reshaped class-topper optimization algorithm (RCTO), which is named as (Fuzzy-PID). Firstly, a patient-hose blower-driven artificial ventilator model is considered, and the transfer function model is established. The ventilator is assumed to operate in pressure control mode. Then, a fuzzy-PID control structure is formulated such that the error and change in error between the desired airway pressure and actual airway pressure of the ventilator are set as inputs to the FIS. The gains of the PID controller (proportional gain, derivative gain, and integral gain) are set as outputs of the FIS. A reshaped class topper optimization algorithm (RCTO) is developed to optimize rules of the FIS to establish optimal coordination among the input and out...
An Improved DV-Hop Localization Algorithm based on Human Conception Optimization with Time Varying Acceleration Coefficients for Wireless Sensor Network
Wireless Sensor Network (WSN) is widely used in a variety of practical applications. WSN may be u... more Wireless Sensor Network (WSN) is widely used in a variety of practical applications. WSN may be used to sense objects, gather information, analyze it, and then transmit it again. The significance of optimization techniques is crucial for the accurate and reliable estimation of the sensor nodes’ location. The positioning accuracy of traditional DV-Hop localization algorithm is not entirely satisfactory instead of it is quite simple, stabilized, feasible, and requires less hardware. Thus to enhance the positioning accuracy without increasing the hardware cost of a sensor node, this article provides an improved DV-Hop localization algorithm using Human Conception Optimization (HCO). The proposed method adds a parameter to alter the anchor nodes' hop size. Furthermore, it is analyzed with traditional DV-Hop, IDV-Hop algorithm, DV-Hop based PSO, and DV-Hop based CTO. The simulation results support the conclusion that, the proposed algorithm performs better than the competing algorith...
An Optimizer to Tune Fractional-Order Power System Stabilizer for Synchronous Generator Considering Governor Effect and Exciter Voltage Fluctuation
Journal of Control, Automation and Electrical Systems
An optimal internal model proportional integral controller to improve pressure tracking profile of artificial ventilator
Medical & Biological Engineering & Computing
An efficient optimizer for optimal overcurrent relay coordination in power distribution system
Expert Systems with Applications, 2022
Scientific Reports
Computational techniques are widely used to solve complex optimization problems in different fiel... more Computational techniques are widely used to solve complex optimization problems in different fields such as engineering, finance, biology, and so on. In this paper, the Human Conception Optimizer (HCO) is proposed as a novel metaheuristic algorithm to solve any optimization problems. The idea of this algorithm is based on some biological principles of the human conception process, such as the selective nature of cervical gel in the female reproductive system to allow only healthy sperm cells into the cervix, the guidance nature of mucus gel to help sperm track a genital tracking path towards the egg in the Fallopian tube, the asymmetric nature of flagellar movement which allows sperm cells to move in the reproductive system, the sperm hyperactivation process to make them able to fertilize an egg. Thus, the strategies pursued by the sperm in searching for the egg in the Fallopian tube are modeled mathematically. The best sperm which will meet the position of the egg will be the solut...
Extended Kalman filter state estimation–based nonlinear explicit model predictive control design for blood glucose regulation of type 1 diabetic patient
Medical & Biological Engineering & Computing, 2022
The computational burden of iterative online optimization-based model predictive control (MPC) pr... more The computational burden of iterative online optimization-based model predictive control (MPC) process is solved by adapting off-line optimization-based nonlinear explicit model predictive control (NEMPC). In this paper, the application of NEMPC is verified to regulate blood glucose level in type 1 diabetes mellitus (T1DM) patients. The objective of glucose regulation is to avoid hyperglycemia (> 180 mg/dl) and hypoglycemia (< 50 mg/dl) by maintaining glucose level in the range of 70 to 180 mg/dl. It helps to avoid time complexity of iterative process during solution of optimization stage in MPC. In the nonlinear T1DM model, only the state dynamic of sugar is measurable with low complexity and high cost among other states of the model. Therefore, an extended Kalman filter (EKF) is used developed to estimate unavailable states. The information of the estimated states are used to develop the proposed control approach for the T1DM patients. The simulation results of the NEMPC along with EKF-based state estimator for T1DM model shows the regulation of blood glucose-level (BGL) within 70 to 180 mg/dl within 120 min. The robustness of the proposed scheme is also verified under the change in parameters and food disturbance. The control variability grid analysis (CVGA) of NEMPC for 50 numbers of virtual T1DM patients under random parametric changes and meal disturbances shows the avoidance of hypoglycemia and hyperglycemia in type 1 diabetic patients. The proposed control method is simple, robust and efficient to regulate glucose level in T1DM patients. Extended Kalman filter state estimator based nonlinear explicit model predictive control for blood glucose regulation in Type 1 diabetic patients.
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Papers by Debasis Acharya