Department of Electrical and Electronics Engineering

Permanent URI for this collectionhttp://localhost:4000/handle/123456789/1925

Browse

Filters

2014 - 20175

Settings

Author: search.filters.author.Mishra, PuneetSubject: search.filters.subject.Controller tuning

Search Results

Now showing 1 - 5 of 5
  • No Thumbnail Available
    Item
    Comparative study of some optimization techniques applied to DC motor control
    (IEEE, 2014) Mishra, Puneet
    Traditional tuning techniques for classical Proportional-Integral-Derivative (PID) controller suffer from many disadvantages like non-customized performance measure and insufficient process information. For the past two decades nature inspired optimization algorithms are efficiently being implemented for tuning of PID controllers. In this paper, four optimization methods namely Genetic Algorithm (GA), Accelerated Particle Swarm Optimization (APSO), Differential Evolution (DE) and Cuckoo Search (CS) are studied and used to optimize the controller gains of a Proportional-Integral (PI) controller for set point tracking in speed control of a DC motor by minimizing Integral Time Absolute Error (ITAE). Hardware validation of the efficiency of above mentioned optimization algorithms is studied and presented. The plant under study is a DC motor control module (MS15) from M/S LJ CREATE™. M/S National Instruments (NI) based software and hardware components i.e. LabVIEW™ and its add-ons toolkit and data acquisition (DAQ) card has been utilized for the closed loop control in real time. The system identification is done in LabVIEW™ and then offline performance optimization is carried out in MATLAB™. The tuned gains are further used to study the run time performances in LabVIEW™ environment. This is done because MATLAB™ has very good optimization tools and on the other hand LABVIEW™ makes the measurement very easy. From the results obtained it can be clearly inferred that CS algorithm outperformed other algorithms studied in this paper, particularly in disturbance rejection.
  • No Thumbnail Available
    Item
    Optimization of PID controller with first order noise filter
    (IEEE, 2015) Mishra, Puneet
    Measurement noise is one of the most widely and frequently experienced problems of an industrial working environment. The effects of measurement noise can be reduced by filtering the measurement signal. The aim of the current work is to explore (a) the optimum location of filter in the control loop and (b) the controller tuning in presence of measurement noise. In the present work, two locations are considered for placing the first order noise filter. One, in the feedback path after the sensor and, other cascaded with the derivative term. The controller and filter parameters were tuned using Particle Swarm Optimization (PSO) technique for a combined performance criterion composed of Maximum Overshoot and Integral Absolute Error (IAE). For studying the effectiveness of the proposed scheme, two simulations and a hardware based experiment on a speed control of a DC motor are considered. Based on these investigations, it can be concluded that the filter located in feedback path gives better performance as compared to the filter cascaded with the derivative term in a noisy environment.
  • No Thumbnail Available
    Item
    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.
  • No Thumbnail Available
    Item
    Stiction combating intelligent controller tuning: A comparative study
    (IEEE, 2015) Mishra, Puneet
    This paper investigates the effects of different controller tuning approaches on an intelligent controller, namely Stiction Combating Intelligent Controller (SCIC) earlier developed by the authors. The SCIC controller is inherently a variable gain fuzzy Proportional-Integral (PI) controller based on Takagi-Sugeno model and was specifically designed to handle the stiction nonlinearity in a control loop in presence of a sticky pneumatic control valve. Three different tuning methods, viz. Ziegler-Nichols, Tyreus-Luyben and Direct synthesis (DS) tuning approach, which are extensively employed in process industries to tune Proportional-Integral-Derivative controllers, are tested in this work to find the gains of SCIC and PI controller. The performance of both, SCIC and PI controllers, are rigorously evaluated experimentally on a laboratory scale nonlinear flow process for setpoint tracking, disturbance rejection, and robustness testing. Based on extensive experimental analysis it can be concluded that the SCIC controller tuned using DS approach performed best for almost all cases.
  • No Thumbnail Available
    Item
    A comparative study for flow control using SCIC and NPIC controllers
    (IEEE, 2017) Mishra, Puneet
    Flow control is essentially a very important part of the process control industries. The flow control loops often employ pneumatic control valves as the final control element. These control valves suffer from various nonlinearities and stiction is most common of these. Due to stiction effect in the pneumatic control valves, the commonly used proportional-integral-derivative (PID) controller introduces limit cycles in the flow control loops, which essentially deteriorates the productivity of the industrial environment. To curb such non sinusoidal oscillations in these control loops, recently two novel controllers have been proposed namely, Stiction Combating Intelligent Controller (SCIC) and Nonlinear Proportional Integral Controller (NPIC). These two controllers have been earlier thoroughly evaluated for flow control studies and are claimed to be very efficient for curbing the limit cycle behavior in the control loops. However, a comparative study between them is missing for the same, which would fill the void existing at present. This paper addresses the same issue and a comparative study between the two controllers is performed and presented in this paper for the setpoint tracking, disturbance rejection and parametric uncertainty problems.