Faculty Publications

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Publications by NITK Faculty

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    Towards a better understanding and analysis of controlled delay (CoDel) algorithm by using fluid modelling
    (Institution of Engineering and Technology journals@theiet.org, 2019) Patil, S.D.; Tahiliani, M.P.
    In this study, a modified fluid model is proposed to understand the design of controlled delay (CoDel) algorithm for active queue management (AQM) and analyse its sensitivity to parameter settings. CoDel significantly differs from other AQM algorithms because it operates at the head of the queue and adopts a deterministic packet drop strategy, unlike other algorithms that operate at the tail and adopt a probabilistic packet drop strategy. The correctness of the proposed fluid model is verified by comparing its results with those obtained from ns-2. Subsequently, using the model developed in this study, the authors analyse the performance of CoDel algorithm by changing its internal parameters and modifying its control law. They highlight the role of the internal parameters and control law on the ability of the CoDel algorithm to control queue delay. Their analysis shows that the CoDel algorithm is sensitive to its parameter settings and that its control law requires minor modifications to gain a better control over the queue delay. © The Institution of Engineering and Technology 2018.
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    Model-based, Distributed, and Cooperative Control of Planar Serial-link Manipulators
    (Institute of Control, Robotics and Systems, 2021) Soumya, S.; Guruprasad, K.R.
    In this paper, we propose a novel distributed control scheme for a planar serial-link manipulator with revolute joints. The control scheme is based on the conventional model-based nonlinear control scheme that achieves linearization by feedback. A dedicated controller controls each joint of the manipulator, as in the case of the decentralized manipulator control scheme. However, in the proposed control scheme, the joint-level controllers communicate and cooperate to account for the nonlinear dynamic coupling between the links. The proposed control scheme can achieve the performance level of that of the model-based nonlinear control scheme, and at the same time, reduce the computational lead-time by distributing the computational load associated with the control law among the joint-level controllers. We design a distributed cooperative control law for a three-link planar manipulator and demonstrate its trajectory tracking performance using simulation experiments. © 2020, ICROS, KIEE and Springer.
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    Design and performance comparison of interconnection and damping assignment passivity-based control for vibration suppression in active suspension systems
    (SAGE Publications Inc., 2021) Sistla, P.; Figarado, S.; Chemmangat, K.; Manjarekar, N.S.; Kallu Valappil, G.
    This study presents the design of interconnection and damping assignment passivity-based control for active suspension systems. It is well known that interconnection and damping assignment passivity-based control’s design methodology is based on the physical properties of the system where the kinetic and potential energy profiles are shaped, and asymptotic stability is achieved by damping injection. Based on the choice of control variables, special cases of the control law are derived, and tuning of the control law with the physical meaning of the variables is demonstrated along with their simulation results. The proposed control law is experimentally validated on a scaled model of a quarter-car active suspension system with different road profiles, varying load conditions, and noise and delay in the sensor measurements and actuator respectively. The results are compared with that of an uncontrolled system with linear quadratic regulator and sliding mode control. © The Author(s) 2020.
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    ARIMA-PID: container auto scaling based on predictive analysis and control theory
    (Springer, 2024) Joshi, N.S.; Raghuwanshi, R.; Agarwal, Y.M.; Annappa, B.; Sachin, D.N.
    Containerization has become a widely popular virtualization mechanism alongside Virtual Machines (VMs) to deploy applications and services in the cloud. Containers form the backbone of the modern architectures around microservices and provide a lightweight virtualization mechanism for IoT and Edge systems. Elasticity is one of the key requirements of modern applications with various constraints ranging from Service Level Agreements (SLA) to optimization of resource utilization, cost management, etc. Auto Scaling is a technique used to attain elasticity by scaling the number of containers or resources. This work introduces a novel mechanism for auto-scaling containers in cloud environments, addressing the key elasticity requirement in modern applications. The proposed mechanism combines predictive analysis using the Auto-Regressive Integrated Moving Average (ARIMA) model and control theory utilizing the Proportional-Integral-Derivative (PID) controller. The major contributions of this work include the development of the ARIMA-PID algorithm for forecasting resource utilization and maintaining desired levels, comparing ARIMA-PID with existing threshold mechanisms, and demonstrating its superior performance in terms of CPU utilization and average response times. Experimental results showcase improvements of approximately 10% in CPU utilization and 30%. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.