Many chemical and nonchemical processes exhibit integrating behavior. This paper presents new approach for deriving parameters of proportional-integral-derivative controller for various types of integrating processes. In order to obtain enhanced performance, the controller is augmented by a second order filter. In the process of deriving controller and filter parameters, time delay is approximated by second order Laguerre shift. Analytical tuning rules are derived on the basis of the sensitivity of loop transfer function. With the help of polynomial method, the poles are placed so as to minimize the overshoot in the servo response. A set point filter is also employed to mitigate the overshoot and settling time in servo response. Besides, the set point filter is able to decouple servo and regulatory responses. The proposed method is compared with recently proposed methods. The evaluation is carried out in terms of various performance indices. Investigation of evaluation results reveals that the proposed method offers considerable improvement over the existing methods.
This paper presents a novel technique in designing controller for integrating process with inverse response and time delay. Using Pade’s approximation, the positive zero is approximated to a negative zero by modifying the time delay of process. The polynomial approach is employed for the rearranged process to derive the controller parameters. The tuning parameter is selected based on the value of maximum sensitivity. Set point filtering is employed to reduce the overshoot in servo response. Various bench marking examples are considered to evaluate the proposed method. The evaluation is carried out in terms of various performances.
The fault detection and isolation of generators used in wind turbines gathering interest as to maximize the reliability and avail of distributed energy systems with recent unmatched growth in construction of offshore wind farms. In particular it is interested in performing fault detection and isolation (FDI) of incipient faults affecting the measurements of the three-phase signals (currents) in a controlled DFIG and PMSG. Although different authors have dealt with FDI for sensors in induction machines and in DFIGs, most of them rely on the machine model with constant parameters. However, the parameter uncertainties due to changes in the operating conditions will produce degradation in the performance of such FDI systems. The robust techniques to detect faults are exist but there is a need of extra sensor. This paper proposed a systematic methodology for the design of sensor FDI systems with the following characteristics: i) capable of detecting and isolating incipient additive (bias) faults, ii) robust against changes in the references/disturbances affecting the controlled DFIG and PMSG as well as modeling/parametric uncertainties, iii) residual generation system based on a multi-observer strategy to enhance the isolation process, The designed sensor FDI systems have been validated using measured voltages, as well as simulated data from a controlled DFIG. First the state space models of DFIG and PMSM explained followed by kalman filter introduction and current sensor fault detection using a bank of kalman filter named dedicated Observer Scheme and generalized Observer scheme to detect simultaneous and multiple faults was theorized and simulated using MATLAB simulation tool .The simulation results were summarized with and without Sensor fault.
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