Kamran Zeb

Performance of adaptive PI based on fuzzy logic for Indirect Vector Control Induction Motor drive

A Novel Adaptive PI based on Fuzzy Logic Reasoning (FLR) is presented in this paper for Indirect Vector Control (IVC) three phase Induction Motor (IM). The main objective is to achieve fast dynamic response and robustness for speed variation, parameter uncertainties, load disturbances, electrical faults perturbations, and to acquire maximum torque and efficiency. The d-q modeling of the IM in synchronously rotating reference frame and Space Vector Pulse Width Modulation (SVPWM) employed in power inverter are carried out in Matlab/Simulink. Both PI and Adaptive PI based on FLR are analyzed, designed, and simulated for IVC IM drive system. Furthermore, the critical and analytical assessment of the aforesaid designed control methodology provides robust and faster response with low overshoot, rise, and settling time for the load disturbances, parameter uncertainties, speed variation, and electrical faults perturbation of IVC IM drive system, compared to prior works.

Control of DC link voltage for grid interfaced DFIG using Adaptive Sliding Mode & Fuzzy based on Levenberg-Marquardt algorithm during symmetrical fault

Enhancement of fault ride through capability of Doubly Fed Induction Generator (DFIG) is demanding issue in developed countries. In this paper crowbar circuit is implemented for limitation of fault current while the Adaptive Sliding Mode Controller (ASMC) & Adaptive Fuzzy controller (AFC) based on Levenberg-Marquardt algorithm is proposed to enhance fault ride through capability. The Adaptive controller is used to control DC link voltage during normal and faulty condition. The result of controlled DC link voltage with ASMC & AFC is critically and analytically compared with the conventional tuned PI controller. The test bench model is IEEE 5 bus system composed of 9MW DFIG interfaced with 120kv grid.

Fault tolerant speed regulation of Induction Motor using Artifical Neural Network

This paper successfully develops and investigates the implementation of Artificial Neural Network (ANN) based robust speed control strategy for Indirect Vector Control (IVC) three phase Induction Motor (IM) drive. The IM is modeled in terms of dq in synchronously rotating reference frame for IVC in Matlab/Simulink. The main purpose of the proposed design is to accomplish robustness for load disturbances, speed variation, parameter uncertainties, and electrical faults. The performance of aforesaid control technique is compared with that of conventional tuned PI control scheme. Simulation results of the ANN guarantee effectiveness and robustness regarding overshoot, undershoot, rise time, fall time and chattering for different operating condition in comparison to traditional PI control scheme.

Environment Control System for Livestock Sheds Using Fuzzy Logic Technique

In Pakistan, 70% of the population lives in villages, where the source of income depends upon agriculture, livestock, and poultry sheds. In order to produce maximum meat, milk and other products one should have to focus on the growth of the animals. There are some crucial factors like the temperature, humidity level and suitable air flow in the shed to remove waste gasses. These factors are monitored by using Mamdani model based upon fuzzy logic technique to improve growth of animals. The main objective of this research is to design a controller and check out its simulation results to produce the most suitable results for the environment control of livestock sheds. The output parameters to control these inputs are Water sprinkler (Ws), Exhaust fan (Exf) and Auto Curtains (A.C). In this research, we focused on the Mamdani method in fuzzy logic to design fuzzy logic controller (FLC) to control the environmental parameters of a live stock shed in order to provide the most suitable conditions for the growth of animals.

Siding Mode Control for PMSG based Wind Energy Conversion System connected to the grid

This paper presents a non-linear Sliding Mode Control (SMC) strategy based on continuous switching law for large-power (10MW) Permanent Magnet Synchronous Generator (PMSG) based Wind-Energy Conversion System (WECS). The WECS model consists of a wind turbine, PMSG, rectifier fed boost converter, PWM inverter and the filter. The controller is used to maintain the DC-link voltage constant and to generate controlled active and reactive power for grid. For verification of validity of proposed control scheme and model, the proposed systems dynamic model is simulated in MATLAB/Simulink. SMC has the promising features of: fast switching, insensitivity to parameter uncertainty, disturbance rejection quality, and more robustness than the conventional linear controllers. The proposed continuous control compelled the states trajectories of the system onto the surface in error space (sliding surface) for the system behavior to obtain design specifications. Simulation results demonstrate that the proposed SMC is effective and gives superior performance than conventionally tuned PI controller.

An adaptive controller scheme implemented on multiple links VSC-HVDC for effective damping of low frequency power oscillations

Inter-area power oscillation damping is of fundamental importance in todays era of sophisticated and highly complex power system. The present paper demonstrates a practical solution obtaining satisfactory performance in damping power system oscillations utilizing the flexible Voltage Source Converter-High Voltage Direct Current (HVDC-VSC) transmission technology in an optimal combination with a Power Oscillation Damping (POD) controller such as Nonlinear Autoregressive Moving Average (NARMA-L2), utilizing active power modulation technique. The primary focus of the control scheme is to improve the damping of lightly damped or even unstable modes of the interconnected AC/DC power system through modal identification and estimation techniques. The performance of aforesaid control technique is compared with that of conventionally tuned PI control scheme. The designed control scheme guarantees stability margins through eigenvalue analysis and non-linear time domain simulations during symmetrical and asymmetrical faults. The software platform under which the various simulation scenarios were implemented is MATLAB/Simulink.

Indirect Vector Control of Induction Motor using Adaptive Sliding Mode Controller

This paper presents an implementation of Adaptive Sliding Mode Controller (ASMC) based robust speed control strategy for Indirect Vector Control (IVC) three phase Induction Motor (IM) drive. The software platform for modelling of IM in the synchronous rotating frame of reference for IVC is Matlab/Simulink. The primary focus of the proposed controller is to accomplish robustness for electrical faults perturbations, load disturbances, speed variation, and parameter uncertainties. The performance of the proposed control technique is compared with that of the conventionally tuned PI control scheme. The Simulation results of the ASMC guarantee effectiveness and robustness regarding overshoot, undershoot, rise time, fall time, and chattering for different operating conditions compared to the traditional PI control scheme.