Suresh Manic - Academia.edu (original) (raw)
Papers by Suresh Manic
Sensors, Dec 27, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Mathematical Problems in Engineering
The improvements in computation facility and technology support the development and implementatio... more The improvements in computation facility and technology support the development and implementation of automatic methods for medical data assessment. This study tries to extend a framework for efficiently classifying chest radiographs (X-rays) into normal/COVID-19 class. The proposed framework consists subsequent phases: (i) image resizing, (ii) deep features extraction using a pretrained deep learning method (PDLM), (iii) handcrafted feature extraction, (iv) feature optimization with Brownian Mayfly-Algorithm (BMA), (v) serial integration of optimized features, and (vi) binary classification with 10-fold cross validation. In addition, this work implements two methodologies: (i) performance evaluation of the existing PDLM in the literature and (ii) improving the COVID-19 detection performance of chosen PDLM with this proposal. The experimental investigation of this study authenticates that the effort performed using pretrained VGG16 with SoftMax helped get a classification accuracy o...
Behavioural Neurology
Multimodal medical image fusion is a current technique applied in the applications related to med... more Multimodal medical image fusion is a current technique applied in the applications related to medical field to combine images from the same modality or different modalities to improve the visual content of the image to perform further operations like image segmentation. Biomedical research and medical image analysis highly demand medical image fusion to perform higher level of medical analysis. Multimodal medical fusion assists medical practitioners to visualize the internal organs and tissues. Multimodal medical fusion of brain image helps to medical practitioners to simultaneously visualize hard portion like skull and soft portion like tissue. Brain tumor segmentation can be accurately performed by utilizing the image obtained after multimodal medical image fusion. The area of the tumor can be accurately located with the information obtained from both Positron Emission Tomography and Magnetic Resonance Image in a single fused image. This approach increases the accuracy in diagnosi...
Journal of Engineering Science and Technology, 2016
Most of the real systems exhibit non-linear nature; conventional controllers are not always able ... more Most of the real systems exhibit non-linear nature; conventional controllers are not always able to provide good and acceptable results. This paper presents a hybrid control strategy of Model Predictive Control (MPC) and Fuzzy Logic Control (FLC). The Fuzzy Model Predictive Control (FMPC) approach is developed to control various distillation column models. The performance measures like settling time, peak overshoot, Integral Square Error (ISE) and Integral Absolute Error (IAE) of FMPC is validated with MPC, FLC and conventional multi loop PI controller. The simulation results shows that the FMPC has better performance than other controller on various distillation column models.
International Review on Modelling and Simulations, 2013
Two stage KY converter is a recent invention by K. I. Hwu and Y. T. Yau in the field of non- isol... more Two stage KY converter is a recent invention by K. I. Hwu and Y. T. Yau in the field of non- isolated DC-DC boost converter. This converter produces low output voltage ripple than the conventional converters. In this article an Neuro Fuzzy controller is designed for controlling the converter to yield very low output voltage ripple with fast load transient response and rapid settling time. The results of proposed Neuro Fuzzy controlled two stage KY converter with the digital simulation by Matlab/Simulink® shows reduction in voltage ripple from 200 milli Volts of the existing Fuzzy controlled system to 1.5 milli Volts by the proposed Neuro Fuzzy controlled two stage KY converter. Further the settling time is achieved very fast along with rapid load transient response of the proposed controller which exhibits the load regulation of the proposed system.
Nonlinear system is due to the variation of cross section area correspond to the level system wit... more Nonlinear system is due to the variation of cross section area correspond to the level system with change in shape. Hopper tank, for instance. Controlling the process parameters for nonlinear process is one of the important issues identified in literature. Firstly, Identification of process transfer function is done through the real time implementation experiment and it is applied to a conventional PID (proportional, integral and derivative) controller. Followed by tuning method has been proposed including Cohen-Coon (C-C), Ziegler & Nichols (Z-N), Internal Model Control (IMC) and Tyreus & Luyben (T-L) into PID controller. These tuning methods are design using computer simulation in MATLAB under Simulink software and error integral (ISE, IAE, ITAE) has been used as the criterion for comparison. From the result, it is observed that, T-L and Z-N provides better result compared to other methods considered in this study. Keywords— Nonlinear Process; PID Controller; Hopper Tank; Tuning M...
Image thresholding is widely considered to obtain binary image from the gray level image. In this... more Image thresholding is widely considered to obtain binary image from the gray level image. In this article, histogram based multi-level thresholding approach is proposed using Brownian Distribution (BD) based Bat Algorithm (BA). The optimal thresholds for the gray scale images are attained by maximizing Otsu’s between class variance function. The performance of the proposed algorithm is demonstrated by considering six benchmark (512 x 512) images and compared with the existing algorithms such as improved Particle Swarm Optimization (PSO), enhanced Bacterial Foraging Optimization (BFO) and Levy flight Bat Algorithm (LBA). The performance assessment between algorithms is carried using the parameters such as objective function, Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and convergence of algorithms. The result evident, even though the convergence time is large, that BD guided BA provides better performance measure values for most of the images compared with t...
In this research paper, Image segmentation technique based on maximum fuzzy entropy function and ... more In this research paper, Image segmentation technique based on maximum fuzzy entropy function and optimization is applied on Magnetic Resonance (MR) type of brain images to detect various brain malignancy is presented. The proposed method accomplishes image segmentation centered on optimal thresholding of the input malignant MR brain images. The input MRI of malignant brain is classified into two Membership Functions (MF), whose MFs of the fuzzy region is Z-function and S-function. The optimization of fuzzy MFs parameters to identify the proper threshold is obtained by means of an algorithm called Modified Particle Swarm Optimization (MPSO). The maximum fuzzy entropy is considered to be the objective for finding the optimal value among the fuzzy MFs parameter. From the course of various examples, the performance of the proposed MPSO is compared with those using existing entropy-based object segmentation methods and the supremacy of the proposed Modified PSO method is validated. The s...
2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 2017
In process industries, design of optimal PI/PID controller for a chosen process model is the chie... more In process industries, design of optimal PI/PID controller for a chosen process model is the chief task. In this paper, a method is proposed to design the stabilizing controller for the benchmark Two Input Two Output (TITO) process, such as Vinante & Luyben (VL) and Wood & Berry (WB) distillation columns available in the literature. In this paper, optimal controller values for the considered TITO systems are identified with a centralized tuning scheme using the Jaya algorithm (JA). Superiority of JA is validated against the existing methods, such as Bacterial-Foraging (BFO), Firefly-Algorithm (FA), and Teaching-Learning Based Optimization (TLBO). The experimental investigation confirms that, the JA offers superior values of time-domain values and the error values compared with the alternatives. Hence, in future, JA assisted approach can be considered to resolve a diversity of controller design problems existing in the literature.
Article history: Received 12 October 2014 Received in revised form 26 December 2014 Accepted 17 J... more Article history: Received 12 October 2014 Received in revised form 26 December 2014 Accepted 17 January 2015 Available online 28 February 2015
In this technological world development in the field of nanometre technology makes power consumpt... more In this technological world development in the field of nanometre technology makes power consumption of logic gates as minimum as possible. Reversible logic design became the promising technologies gaining greater interest due to less dissipation of heat and low power consumption. In digital systems code conversion is a widely used process for reasons such as enhancing security of data, reducing the complexity of arithmetic operations and thereby reducing the hardware required, dropping the level of switching activity leading to more speed of operation and power saving etc. This paper proposes novel Reversible logic design for code conversion such as Binary to Gray code, Gray to Binary code, BCD to Excess 3 code, Excess 3 to BCD code.
In this paper, bi-level and multi-level thresholding is presented for the standard RGB images usi... more In this paper, bi-level and multi-level thresholding is presented for the standard RGB images using Otsu and a novel Brownian Bat Algorithm (BBA). Maximization of between-class variance is chosen as the objective function during the optimization search. The performance of the proposed BBA is confirmed by considering six benchmark RGB images and compared with the existing bat algorithms such as Traditional Bat Algorithm (TBA) and the Levy flight Bat Algorithm (LBA). The evaluation of performance between the proposed and existing bat algorithms are done using existing constraints such as objective function, Root Mean Squared Error (RMSE), Peak to Signal Ratio (PSNR), Structural Dissimilarity (DSSIM) index, and algorithm convergence. The result evident that proposed BBA offers better values for objective function, RMSE, PSNR and DSSIM, whereas TBA and LBA offers faster convergence compared to BBA.
INTRODUCTION From the recent control literature, one can observe that, heuristic algorithm based ... more INTRODUCTION From the recent control literature, one can observe that, heuristic algorithm based PI/PID controller tuning procedures are widely adopted to find best possibl e controller parameters for Single Input Single Out put (SISO) and Two Input Two Output (TITO) processes because o f its simplicity and model independent nature (Sure sh Manic, K., et al., 2015; Suresh Manic, K., et al., 2015). In chemical industries, most of the significant pro cesses are multivariable in nature. Distillation is one of the separation technique extensively adopted in the petroleum and chemical industries for purification of final products. Due to its industrial significance, the d istillation column is one of the generally chosen i mperative multivariable processes by the researchers (Coelho, L.S. and V.C. Mariani, 2012; Sivakumar, R., and K. Balu, 2010; Sivakumar, R., et al., 2010). The control literature presents the traditional/mod ern approach based design and implementation of the PI/PID con...
This paper presents Continuous Sliding Mode controllers applied to nonlinear high pressure rated ... more This paper presents Continuous Sliding Mode controllers applied to nonlinear high pressure rated modified CSTR system which has been linearized to one operating point. Firstly, the first-order sliding mode control or classical sliding mode control has been discussed, and second-order super twisting control is used to attain robustness properties in the presence of uncertain bounded External disturbances when applied to the system. Later, Terminal Sliding Mode Control and Fast Terminal Sliding Mode Control are presented which result in faster convergence of state variables with respect to initial values of the system. The convergence of state variables to the equilibrium point occurs in finite time. The simulation results show the improved control performances and the properties of continuous Sliding Mode Controllers when applied for maintaining pH control for High Pressure Rated Modified CSTR system where it has unmodelled dynamics as the external bounded disturbance.
This paper presents the regulation of the continuous sliding mode controller applied to an unstab... more This paper presents the regulation of the continuous sliding mode controller applied to an unstable chemical reactor. The temperature of an unstable chemical reactor cannot be easily measured accurately due to its nonlinearities such as thermal runaway, saturation, delay, backlash etc. The nonlinearities which are present in an unstable chemical reactor are taken as unmodeled dynamics also the parametric uncertainties of the system are given as an external bounded disturbance by which robustness can be achieved by sliding mode controller. Further the asymptotical convergence of the system is achieved by making the state variables to reach the equilibrium point even from far away initial points by implementing terminal sliding mode and fast terminal sliding mode. The performance of the controller is shown in a comparative table when combinations of high frequency oscillating disturbance, low frequency oscillating disturbance and a constant disturbance are given to the system
Nature inspired algorithms are widely proposed in the literature to solve a variety of engineerin... more Nature inspired algorithms are widely proposed in the literature to solve a variety of engineering optimization problems. In this article, a novel methodology called Refined Double Search Optimization (RDSO) is proposed to design the PID controller for a class of unstable process models using heuristic algorithms. RDSO is a two stage search scheme, in which the initial search is used to generate a database of all possible controller parameters in search universe ‘U’ and the second search stage is used to identify global optimal value from database. Main advantage of the proposed method is that, it provides the minimum and maximum limit (search boundary) for controller parameters in the search universe ‘U’, which keeps the unstable process in a firm stable region. Three simulated examples are presented to demonstrate the effectiveness of proposed methodology using recent heuristic algorithms such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (P...
In this paper, an investigation has been made to design the best possible Proportional + Integral... more In this paper, an investigation has been made to design the best possible Proportional + Integral + Derivative (PID) controller for the Hopper type tank and Spherical tank system. In order to identify the optimal controller parameters, soft computing schemes, such as Particle Swarm Optimization (PSO), Bacterial Foraging Optimization (BFO), Firefly Algorithm (FA), and Cuckoo Search (CS) are considered. In the proposed work, minimization of a weighted sum of Objective Function (OF) is adopted to guide the soft computing technique based controller design procedure. The qualitative and quantitative analysis is carried out to validate the performance of the considered procedure. The results evident that, the Brownian walk guided algorithms offers better performance compared to the PSO.
Background: The objective is to track the reference model and to develop a control scheme which f... more Background: The objective is to track the reference model and to develop a control scheme which forces the plant dynamics to follow the dynamics of the reference model. The controller so designed forces the error between the plant and the reference states to zero as time tends to infinity and ensuring that the plant output following the reference model output faithfully even in the presence of unmodelled dynamics or disturbances in the actual plant. The servomechanism is also discussed where the system has to track the reference signal in the presence of disturbances for various feedforward Gains. In this paper the spherical tank is taken as the model of the actual plant and using MIT Rule and Lyapunov Approach where the system is adapted.
Human brain is the most complex organ in the body which controls all conscious and unconscious as... more Human brain is the most complex organ in the body which controls all conscious and unconscious aspects of the body. Numerous neurons combine together to make up the brain and gives us the power of speech, imagination and logical thinking. The communication between these neurons create magnetic and electric field that can be measured through an Electroencephalograph. These measured brainwaves consist of component bandwidths categorised based on their frequency. Studies have shown that the presence of these waves in the brainwave depend on the emotional and mental status of the person as well as physical and mental actions that are being carried out. This paper looks into the different aspects of acquiring these brainwaves in real time and conditioning the waves in order to remove unwanted artefacts for digitisation and signal analysis. An in depth study is carried out for obtaining the waves through a data acquisition device DAQ 6009 and the categorisation of the brainwave to differe...
Neurons in the brain communicate through electrical impulses that give rise to both electrical an... more Neurons in the brain communicate through electrical impulses that give rise to both electrical and magnetic fields which are categorized into five different band limits. These waves can be measured outside the skull through an Electroencephalogram. The utilisation of brainwave detection in other areas such as biomedical engineering and gaming industry is yet to be explored. Categorisation of different rhythms of brainwaves and brainwave pattern analysis make it easier to identify the mental status of a person. This research aims to develop a hardware and software that is tested using function generators to simulate the EEG signal from the brain. It is observed that the initial results based on the above that the device performs as expected and hence can be used as brain wave signal measuring device.
Sensors, Dec 27, 2022
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Mathematical Problems in Engineering
The improvements in computation facility and technology support the development and implementatio... more The improvements in computation facility and technology support the development and implementation of automatic methods for medical data assessment. This study tries to extend a framework for efficiently classifying chest radiographs (X-rays) into normal/COVID-19 class. The proposed framework consists subsequent phases: (i) image resizing, (ii) deep features extraction using a pretrained deep learning method (PDLM), (iii) handcrafted feature extraction, (iv) feature optimization with Brownian Mayfly-Algorithm (BMA), (v) serial integration of optimized features, and (vi) binary classification with 10-fold cross validation. In addition, this work implements two methodologies: (i) performance evaluation of the existing PDLM in the literature and (ii) improving the COVID-19 detection performance of chosen PDLM with this proposal. The experimental investigation of this study authenticates that the effort performed using pretrained VGG16 with SoftMax helped get a classification accuracy o...
Behavioural Neurology
Multimodal medical image fusion is a current technique applied in the applications related to med... more Multimodal medical image fusion is a current technique applied in the applications related to medical field to combine images from the same modality or different modalities to improve the visual content of the image to perform further operations like image segmentation. Biomedical research and medical image analysis highly demand medical image fusion to perform higher level of medical analysis. Multimodal medical fusion assists medical practitioners to visualize the internal organs and tissues. Multimodal medical fusion of brain image helps to medical practitioners to simultaneously visualize hard portion like skull and soft portion like tissue. Brain tumor segmentation can be accurately performed by utilizing the image obtained after multimodal medical image fusion. The area of the tumor can be accurately located with the information obtained from both Positron Emission Tomography and Magnetic Resonance Image in a single fused image. This approach increases the accuracy in diagnosi...
Journal of Engineering Science and Technology, 2016
Most of the real systems exhibit non-linear nature; conventional controllers are not always able ... more Most of the real systems exhibit non-linear nature; conventional controllers are not always able to provide good and acceptable results. This paper presents a hybrid control strategy of Model Predictive Control (MPC) and Fuzzy Logic Control (FLC). The Fuzzy Model Predictive Control (FMPC) approach is developed to control various distillation column models. The performance measures like settling time, peak overshoot, Integral Square Error (ISE) and Integral Absolute Error (IAE) of FMPC is validated with MPC, FLC and conventional multi loop PI controller. The simulation results shows that the FMPC has better performance than other controller on various distillation column models.
International Review on Modelling and Simulations, 2013
Two stage KY converter is a recent invention by K. I. Hwu and Y. T. Yau in the field of non- isol... more Two stage KY converter is a recent invention by K. I. Hwu and Y. T. Yau in the field of non- isolated DC-DC boost converter. This converter produces low output voltage ripple than the conventional converters. In this article an Neuro Fuzzy controller is designed for controlling the converter to yield very low output voltage ripple with fast load transient response and rapid settling time. The results of proposed Neuro Fuzzy controlled two stage KY converter with the digital simulation by Matlab/Simulink® shows reduction in voltage ripple from 200 milli Volts of the existing Fuzzy controlled system to 1.5 milli Volts by the proposed Neuro Fuzzy controlled two stage KY converter. Further the settling time is achieved very fast along with rapid load transient response of the proposed controller which exhibits the load regulation of the proposed system.
Nonlinear system is due to the variation of cross section area correspond to the level system wit... more Nonlinear system is due to the variation of cross section area correspond to the level system with change in shape. Hopper tank, for instance. Controlling the process parameters for nonlinear process is one of the important issues identified in literature. Firstly, Identification of process transfer function is done through the real time implementation experiment and it is applied to a conventional PID (proportional, integral and derivative) controller. Followed by tuning method has been proposed including Cohen-Coon (C-C), Ziegler & Nichols (Z-N), Internal Model Control (IMC) and Tyreus & Luyben (T-L) into PID controller. These tuning methods are design using computer simulation in MATLAB under Simulink software and error integral (ISE, IAE, ITAE) has been used as the criterion for comparison. From the result, it is observed that, T-L and Z-N provides better result compared to other methods considered in this study. Keywords— Nonlinear Process; PID Controller; Hopper Tank; Tuning M...
Image thresholding is widely considered to obtain binary image from the gray level image. In this... more Image thresholding is widely considered to obtain binary image from the gray level image. In this article, histogram based multi-level thresholding approach is proposed using Brownian Distribution (BD) based Bat Algorithm (BA). The optimal thresholds for the gray scale images are attained by maximizing Otsu’s between class variance function. The performance of the proposed algorithm is demonstrated by considering six benchmark (512 x 512) images and compared with the existing algorithms such as improved Particle Swarm Optimization (PSO), enhanced Bacterial Foraging Optimization (BFO) and Levy flight Bat Algorithm (LBA). The performance assessment between algorithms is carried using the parameters such as objective function, Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and convergence of algorithms. The result evident, even though the convergence time is large, that BD guided BA provides better performance measure values for most of the images compared with t...
In this research paper, Image segmentation technique based on maximum fuzzy entropy function and ... more In this research paper, Image segmentation technique based on maximum fuzzy entropy function and optimization is applied on Magnetic Resonance (MR) type of brain images to detect various brain malignancy is presented. The proposed method accomplishes image segmentation centered on optimal thresholding of the input malignant MR brain images. The input MRI of malignant brain is classified into two Membership Functions (MF), whose MFs of the fuzzy region is Z-function and S-function. The optimization of fuzzy MFs parameters to identify the proper threshold is obtained by means of an algorithm called Modified Particle Swarm Optimization (MPSO). The maximum fuzzy entropy is considered to be the objective for finding the optimal value among the fuzzy MFs parameter. From the course of various examples, the performance of the proposed MPSO is compared with those using existing entropy-based object segmentation methods and the supremacy of the proposed Modified PSO method is validated. The s...
2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 2017
In process industries, design of optimal PI/PID controller for a chosen process model is the chie... more In process industries, design of optimal PI/PID controller for a chosen process model is the chief task. In this paper, a method is proposed to design the stabilizing controller for the benchmark Two Input Two Output (TITO) process, such as Vinante & Luyben (VL) and Wood & Berry (WB) distillation columns available in the literature. In this paper, optimal controller values for the considered TITO systems are identified with a centralized tuning scheme using the Jaya algorithm (JA). Superiority of JA is validated against the existing methods, such as Bacterial-Foraging (BFO), Firefly-Algorithm (FA), and Teaching-Learning Based Optimization (TLBO). The experimental investigation confirms that, the JA offers superior values of time-domain values and the error values compared with the alternatives. Hence, in future, JA assisted approach can be considered to resolve a diversity of controller design problems existing in the literature.
Article history: Received 12 October 2014 Received in revised form 26 December 2014 Accepted 17 J... more Article history: Received 12 October 2014 Received in revised form 26 December 2014 Accepted 17 January 2015 Available online 28 February 2015
In this technological world development in the field of nanometre technology makes power consumpt... more In this technological world development in the field of nanometre technology makes power consumption of logic gates as minimum as possible. Reversible logic design became the promising technologies gaining greater interest due to less dissipation of heat and low power consumption. In digital systems code conversion is a widely used process for reasons such as enhancing security of data, reducing the complexity of arithmetic operations and thereby reducing the hardware required, dropping the level of switching activity leading to more speed of operation and power saving etc. This paper proposes novel Reversible logic design for code conversion such as Binary to Gray code, Gray to Binary code, BCD to Excess 3 code, Excess 3 to BCD code.
In this paper, bi-level and multi-level thresholding is presented for the standard RGB images usi... more In this paper, bi-level and multi-level thresholding is presented for the standard RGB images using Otsu and a novel Brownian Bat Algorithm (BBA). Maximization of between-class variance is chosen as the objective function during the optimization search. The performance of the proposed BBA is confirmed by considering six benchmark RGB images and compared with the existing bat algorithms such as Traditional Bat Algorithm (TBA) and the Levy flight Bat Algorithm (LBA). The evaluation of performance between the proposed and existing bat algorithms are done using existing constraints such as objective function, Root Mean Squared Error (RMSE), Peak to Signal Ratio (PSNR), Structural Dissimilarity (DSSIM) index, and algorithm convergence. The result evident that proposed BBA offers better values for objective function, RMSE, PSNR and DSSIM, whereas TBA and LBA offers faster convergence compared to BBA.
INTRODUCTION From the recent control literature, one can observe that, heuristic algorithm based ... more INTRODUCTION From the recent control literature, one can observe that, heuristic algorithm based PI/PID controller tuning procedures are widely adopted to find best possibl e controller parameters for Single Input Single Out put (SISO) and Two Input Two Output (TITO) processes because o f its simplicity and model independent nature (Sure sh Manic, K., et al., 2015; Suresh Manic, K., et al., 2015). In chemical industries, most of the significant pro cesses are multivariable in nature. Distillation is one of the separation technique extensively adopted in the petroleum and chemical industries for purification of final products. Due to its industrial significance, the d istillation column is one of the generally chosen i mperative multivariable processes by the researchers (Coelho, L.S. and V.C. Mariani, 2012; Sivakumar, R., and K. Balu, 2010; Sivakumar, R., et al., 2010). The control literature presents the traditional/mod ern approach based design and implementation of the PI/PID con...
This paper presents Continuous Sliding Mode controllers applied to nonlinear high pressure rated ... more This paper presents Continuous Sliding Mode controllers applied to nonlinear high pressure rated modified CSTR system which has been linearized to one operating point. Firstly, the first-order sliding mode control or classical sliding mode control has been discussed, and second-order super twisting control is used to attain robustness properties in the presence of uncertain bounded External disturbances when applied to the system. Later, Terminal Sliding Mode Control and Fast Terminal Sliding Mode Control are presented which result in faster convergence of state variables with respect to initial values of the system. The convergence of state variables to the equilibrium point occurs in finite time. The simulation results show the improved control performances and the properties of continuous Sliding Mode Controllers when applied for maintaining pH control for High Pressure Rated Modified CSTR system where it has unmodelled dynamics as the external bounded disturbance.
This paper presents the regulation of the continuous sliding mode controller applied to an unstab... more This paper presents the regulation of the continuous sliding mode controller applied to an unstable chemical reactor. The temperature of an unstable chemical reactor cannot be easily measured accurately due to its nonlinearities such as thermal runaway, saturation, delay, backlash etc. The nonlinearities which are present in an unstable chemical reactor are taken as unmodeled dynamics also the parametric uncertainties of the system are given as an external bounded disturbance by which robustness can be achieved by sliding mode controller. Further the asymptotical convergence of the system is achieved by making the state variables to reach the equilibrium point even from far away initial points by implementing terminal sliding mode and fast terminal sliding mode. The performance of the controller is shown in a comparative table when combinations of high frequency oscillating disturbance, low frequency oscillating disturbance and a constant disturbance are given to the system
Nature inspired algorithms are widely proposed in the literature to solve a variety of engineerin... more Nature inspired algorithms are widely proposed in the literature to solve a variety of engineering optimization problems. In this article, a novel methodology called Refined Double Search Optimization (RDSO) is proposed to design the PID controller for a class of unstable process models using heuristic algorithms. RDSO is a two stage search scheme, in which the initial search is used to generate a database of all possible controller parameters in search universe ‘U’ and the second search stage is used to identify global optimal value from database. Main advantage of the proposed method is that, it provides the minimum and maximum limit (search boundary) for controller parameters in the search universe ‘U’, which keeps the unstable process in a firm stable region. Three simulated examples are presented to demonstrate the effectiveness of proposed methodology using recent heuristic algorithms such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (P...
In this paper, an investigation has been made to design the best possible Proportional + Integral... more In this paper, an investigation has been made to design the best possible Proportional + Integral + Derivative (PID) controller for the Hopper type tank and Spherical tank system. In order to identify the optimal controller parameters, soft computing schemes, such as Particle Swarm Optimization (PSO), Bacterial Foraging Optimization (BFO), Firefly Algorithm (FA), and Cuckoo Search (CS) are considered. In the proposed work, minimization of a weighted sum of Objective Function (OF) is adopted to guide the soft computing technique based controller design procedure. The qualitative and quantitative analysis is carried out to validate the performance of the considered procedure. The results evident that, the Brownian walk guided algorithms offers better performance compared to the PSO.
Background: The objective is to track the reference model and to develop a control scheme which f... more Background: The objective is to track the reference model and to develop a control scheme which forces the plant dynamics to follow the dynamics of the reference model. The controller so designed forces the error between the plant and the reference states to zero as time tends to infinity and ensuring that the plant output following the reference model output faithfully even in the presence of unmodelled dynamics or disturbances in the actual plant. The servomechanism is also discussed where the system has to track the reference signal in the presence of disturbances for various feedforward Gains. In this paper the spherical tank is taken as the model of the actual plant and using MIT Rule and Lyapunov Approach where the system is adapted.
Human brain is the most complex organ in the body which controls all conscious and unconscious as... more Human brain is the most complex organ in the body which controls all conscious and unconscious aspects of the body. Numerous neurons combine together to make up the brain and gives us the power of speech, imagination and logical thinking. The communication between these neurons create magnetic and electric field that can be measured through an Electroencephalograph. These measured brainwaves consist of component bandwidths categorised based on their frequency. Studies have shown that the presence of these waves in the brainwave depend on the emotional and mental status of the person as well as physical and mental actions that are being carried out. This paper looks into the different aspects of acquiring these brainwaves in real time and conditioning the waves in order to remove unwanted artefacts for digitisation and signal analysis. An in depth study is carried out for obtaining the waves through a data acquisition device DAQ 6009 and the categorisation of the brainwave to differe...
Neurons in the brain communicate through electrical impulses that give rise to both electrical an... more Neurons in the brain communicate through electrical impulses that give rise to both electrical and magnetic fields which are categorized into five different band limits. These waves can be measured outside the skull through an Electroencephalogram. The utilisation of brainwave detection in other areas such as biomedical engineering and gaming industry is yet to be explored. Categorisation of different rhythms of brainwaves and brainwave pattern analysis make it easier to identify the mental status of a person. This research aims to develop a hardware and software that is tested using function generators to simulate the EEG signal from the brain. It is observed that the initial results based on the above that the device performs as expected and hence can be used as brain wave signal measuring device.