Department of Electrical and Electronics Engineering

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Subject: search.filters.subject.Fuzzy logic controller

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Now showing 1 - 10 of 19
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    An improved nonlinear deloading approach based on the fuzzy controller for wind turbine generators in an islanded microgrid
    (Elsevier, 2023-11) Mishra, Puneet; Mathur, Hitesh Datt
    The wind turbine generators (WTG’s) incapability of primary frequency support during system contingencies due to its decoupled nature from the system frequency causes profound integration and stability issues. The present study focuses on resolving such issues by enabling the WTGs to participate in long-term frequency support under the derated operation of WTGs. The deloading operation of WTGs can provide a specific reserve power margin by reducing its rotor speed, which can be utilized during system contingencies. In literature, linear and quadratic deloading techniques have been proposed but these fail to replicate the nonlinear characteristics of the WTG accurately, thereby making deloading ineffective. To effectively implement the deloading, this work uses a more-accurate higher-order Newton’s interpolation polynomial (HNIP), to cope with the highly nonlinear characteristics of WTG. The proposed deloading approach is also augmented with a fuzzy-based intelligent supplementary control structure to handle the inherent and incorporated nonlinearities in WTG. The microgrid system, consisting of a conventional energy source with WTG, has been considered as system under investigation. The integral time absolute error for step wind profile and variable speed wind profile was found to be improved by 97.65% and 97.29%, respectively, with the proposed novel deloading technique with fuzzy-PID compared to PID. Further, to ensure the implementation viability of the proposed control scheme, real-time validation of the same is carried out on OPAL-RT 4510, having a Xilinx Kintex-7 FPGA board. It was found that for all the scenarios considered for real-time digital simulation purposes, the results unerringly matched with MATLAB/Simulink.
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    Comparative study of some optimization techniques applied to Jacketed CSTR control
    (IEEE, 2015-09) Mishra, Puneet
    In this paper, the performance of four optimization techniques i.e. Grey Wolf Optimizer (GWO), Backtracking Search Algorithm (BSA), Differential Evolution (DE), and Bat Algorithm (BA) have been investigated for optimizing the scaling factors of fuzzy proportional-integral controller (FPIC). Jacketed continuous stirred tank reactor (CSTR) has been considered for step set-point and trajectory tracking of reactor temperature. The present work has been simulated in LabVIEW™. The performance of aforementioned algorithms has been evaluated by comparing the cost function Integral of Absolute Error for step set-point and trajectory tracking. On the basis of simulation results, it can be inferred that, GWO outperformed other optimization algorithms for all considered cases.
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    A fractional order fuzzy PID controller for binary distillation column control
    (Elsevier, 2015-12) Mishra, Puneet
    Expert and intelligent control schemes have recently emerged out as a promising solution with robustness which can efficiently deal with the nonlinearities, along with various types of modelling uncertainties, present in different real world systems e.g. binary distillation column. This paper is an attempt to propose an intelligent control system which takes the form of a fractional order fuzzy proportional–integral–derivative (FOFPID) controller which is investigated as a solution to deal with the complex dynamic nature of the distillation column. The FOFPID controller is an extension of an existing formula based self tuning fuzzy proportional integral controller structure, which varies its gains at run time in accordance with the instantaneous error and rate of change of error. The FOFPID controller is a Takagi–Sugeno (TS) model based fuzzy adaptive controller comprising of non-integer order of integration and differentiation operators used in the controller. It has been observed that inclusion of non-integer order of the integration and differentiation operators made the controller scheme more robust. For the performance evaluation of the proposed scheme, the performance of FOFPID controller is compared with that of its integer order counterpart, a fuzzy proportional–integral–derivative (FPID) controller. The parameters of both the controllers were optimized for minimum integral of absolute error (IAE) using a bio-inspired global optimization algorithm, genetic algorithm (GA). Intensive LabVIEWۛ simulation studies were performed which included setpoint tracking with and without uncertainties, disturbance rejection, and noise suppression investigations. For testing the parameter uncertainty handling capability of the proposed controller, uncertain and time varying relative volatility and uncertain tray hydraulic constant were applied. Also, for the disturbance rejection studies, intensive simulations were conducted, which included two most common causes of disturbance i.e. variation in feed composition and variation in feed flow rate. All the simulation investigations clearly suggested that FOFPID controller provided superior performance over FPID controller for each case study i.e. setpoint tracking, disturbance rejection, noise suppression and parameter uncertainties.
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    A Novel Augmented Fractional-Order Fuzzy Controller for Enhanced Robustness in Nonlinear and Uncertain Systems with Optimal Actuator Exertion
    (Springer, 2021-03) Mishra, Puneet
    An appropriate balance between the controller’s performance and its robustness is a complex design challenge. In order to enhance the control system performance, vigorous and rapid variations in controller output are often employed; however, this poses a critical challenge for practical implementations of the control schemes, as it may affect the actuator badly and may reduce its lifetime. To handle this issue, the current work presents an innovative control structure that aims to strike an apt balance between the control output variability while maintaining the desired control performance. The proposed control scheme exploits the abilities of fuzzy logic to cope with uncertainties in the system and along with the use of fractional calculus to enhance the control performance. Further, to evaluate the performance of the proposed improved fractional-order fuzzy controller (IFOFC), extensive simulation studies have been carried out on a multi-input–multi-output nonlinear system for a wide variety of test scenarios. An exhaustive comparative study with an inline state-of-art controller, i.e., fractional-order fuzzy PID (FOFPID) controller has also been carried out on two interesting performance measures. These performance measures include integral of time-weighted absolute error (ITAE) and another measure which corresponds to undesirable variations in the controller output, i.e., integral of the absolute change of torque (IACT). Based on the detailed simulation studies, it was found that the proposed control structure provides a fair balance between controller output aggression and control performance and also completely outperformed the FOFPID controller, even under large parametric variations.
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    Automatic Generation Control of Multi Area Interconnected Hydro-Thermal Power System with HVDC Links
    (IAES, 2012) Mathur, Hitesh Datt
    This paper investigates the effects of HVDC link in parallel with HVAC link on automatic generation control (AGC) problem for a multi area power system taking into consideration system parameter v ariations. A fuzzy logic controller is proposed for four area power system i nterconnected via parallel HVAC/HVDC transmission link which is also referred as asynchronous tie- lines. The linear model of HVAC/HVDC link is develope d and the system responses to sudden load change are studied. The si mulation studies are carried out for a four area interconnected thermal power system. Suitable solution for automatic generation control problem o f four area electrical power system is obtained by means of improving the dynamic performance of power system under study. Robustness of controll er is also checked by varying parameters. Simulation results indicate tha t the scheme works well. The dynamic analyses have been done with and withou t HVDC link using fuzzy logic controller in Matlab-Simulink. Further a comparison between the two is presented and it has been shown that the per formance of the proposed scheme is superior in terms of overshoot and settli ng time
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    Frequency stabilization using fuzzy logic based controller for multi-area power system in deregulated environment
    (CSIRO, 2008-03) Mathur, Hitesh Datt
    In this paper, a fuzzy logic controller is proposed for load frequency control problem of electrical power system. The fuzzy controller is constructed as a set of control rules and the control signal is directly deduced from the knowledge base and the fuzzy inference. The study has been designed for a two area interconnected power system. A comparison among a conventional proportional integral (PI) controller, some other fuzzy gain scheduling controllers and the proposed fuzzy controller is presented and it has been shown that proposed controller can generate the best dynamic response following a step load change. Robustness of proposed controller is achieved by analyzing the system response with varying system parameters.
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    Power frequency balance in multi-generation smart grid system with V2G option
    (IEEE, 2015) Mathur, Hitesh Datt
    In smart grid scenario, penetration of large scale renewable energy sources are increasing rapidly. This causes uncertainty among various power system parameters, mainly frequency in interconnected power system. When automatic generation control (AGC) is not sufficient to manage balance between demand and supply, battery energy storage is considered a viable option for short term active power support in order to bring frequency back to normal. In energy storage possibilities, super conducting magnetic energy storage, ultra-capacitor etc. are primarily discussed. This paper focuses on integrated model of vehicle to grid (V2G) and wind power as an alternative to supply instant power to regulate frequency when system is subjected to sudden perturbation. GA (Genetic algorithm) optimized fuzzy logic controller is used to intelligently suppress frequency and tie-line power oscillations. Results obtained are comprehensively presented and discussed in achieving power-frequency balance. MATLAB/Simulink is used for the simulation purpose
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    Two Stage Optimized Fuzzy Controlled Multi-Area System for AGC in Smart Grid Age
    (Elsevier, 2015) Mathur, Hitesh Datt
    A model of two area deregulated power system with automatic generation control (AGC) is developed. Two conventional control strategies, integral controller optimized by Genetic Algorithm (GA) and Proportional derivative integral (PID) controller tuned with Ziegler-Nichols (ZN), have been compared with proposed two step GA optimized fuzzy logic controller (FLC). In proposed controller, first step optimization is carried out for range optimization with uniform scaling of membership functions of input and output variables and in second step, scaling and gain parameters of FLC are optimized. The proposed control scheme shows the better dynamic response following a step load change with combination of PoolCo and bilateral contracts in deregulated environment.
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    Wind power inertial support for inter-area oscillations suppression with fuzzy controller in varying load conditions
    (IEEE, 2013) Mathur, Hitesh Datt
    Wind power is emerging renewable energy technology in the recent power system scenario and can be developed as viable options for electricity generation in future. The wind power generation system does not provide inertia and isolates from the grid during disturbances but this possibility will be mitigated if wind power generators also contribute to system inertia. This paper analyses the participation of a doubly fed induction generator based wind turbine in inertial support for reducing frequency and tie-line power oscillations. The proposed control scheme with fuzzy logic uses frequency deviations to provide fast active power support, which arrests the fall in frequency and tie-line power during transient conditions. The simulation studies have been conducted in a two-area interconnected power system in restructured environment to demonstrate the contribution of the doubly fed induction generator in inter-area oscillation suppression.
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    Power–frequency balance with superconducting magnetic energy storage using optimized intelligent controller
    (Energetika, 2014) Mathur, Hitesh Datt
    This paper presents an optimized design of the fuzzy logic controller (FLC) for the two-area interconnected power system to regulate the frequency deviation and power deviations when subjected to change in load. The developed power system model apart from having conventional sources also has a superconducting magnetic energy storage (SMES) unit which is capable of storing electric energy and releases it as per system requirements. SMES is used to support short-term active power in order to maintain power–frequency balance in the system under test. This two-area power system considered comprises reheat thermal and hydro units of the same capacity in each area. In the proposed control scheme, optimization of the FLC is carried out in four different steps: the first step is for optimization of the range of input and output variables, the second one for membership functions, the third and fourth steps for rule base and rule weight optimization, respectively. Genetic algorithm (GA) is used for the proposed step-by-step optimization process. Comparing the other methods available in literature, the proposed method is found more effective in achieving optimal results. Simulation results are also tabulated as a comparative performance in view of the main performance indices, i. e. settling time and peak undershoot