Performance & Analysis of Fuzzy Logic Controller Based Induction Motor Drive System Using Simulink

Variable speed drives are growing and varying. Drives expanse depend on progress in different part of science like power system, microelectronic, control methods and so on. In this paper, the motor drive system comprises a voltage source inverter-fed induction motor (VSIM): namely a three-phase voltage source inverter and the induction motor. The squirrel-cage induction motor voltage equations are based on an orthogonal d-q reference-rotating frame where the co-ordinates rotate with the controlled source frequency. The paper presents a novel fuzzy logic controller for high performance induction motor drive system. The inputs to the fuzzy logic controller are the linguistic variables of speed error and change of speed error, while the output is change in switching control frequency of the voltage source inverter. In this paper a comparison between fuzzy logic controller and traditional PI controllers are presented. The results validate the robustness and effectiveness of the proposed fuzzy logic controller for high performance of induction motor drive. Simulink software that comes along with MATLAB was used to simulate the proposed model

Performance analysis of interior permanent magnet synchronous motor (IPMSM) drive system using different speed controllers

The present research is indicating that the Permanent magnet motor drive could become serious competitor to the induction motor drive for servo application. Further, with the evolution of permanent magnet materials and control technology, the Permanent Magnet Synchronous Motor (PMSM) has become a pronounced choice for low and mid power applications such as computer peripheral equipments, robotics, adjustable speed drives and electric vehicles due to its special features like high power density, high torque/inertia ratio, high operating efficiency, variable speed operation, reliability, and low cost etc. Here we deals with the detailed modeling of an IPMSM drive system with Hybrid PI-Fuzzy logic controller (PI-FLC) as speed controller and Adaptive Hysteresis Current Controller as torque controller by controlling the current components of torque.In this thesis we deals with a simulation for speed control and improvement in the performance of a closed loop vector controlled IPMSM drive which employ two loops for better speed tracking and fast dynamic response during transient as well as steady state conditions by controlling the torque component of current. The outer loop employ Hybrid PIFuzzy logic controller (PI-FLC) while inner loop as Adaptive Hysteresis Band Current Controller (AHBCC) designed to reduce the torque ripple. Despite proportional plus Integral (PI) controller are usually preferred as speed controller due to its fixed gain (Kp) and Integral time constant (Ki), the performance of PI controller are affected by parameters variations, speed change and load disturbances in PMSM, due to which it results to unsatisfied operation under transient conditions. The drawbacks of PI controller are minimized using fuzzy logic controller (FLC). So for this a fuzzy control technique is also designed using mamdani type, triangular based 5x5 MFs and selecting the superior functionalities of PI and FLC, a Hybrid PI-FLC designed for effective speed control under transient and steady state condition.The complete viability of above mentioned integrated control strategy is implemented and tested in the MATLAB/Simulink environment and a performance comparison of proposed drive system with conventional PI, fuzzy logic controller and Hybrid PI-Fuzzy Logic Controller integrated separately as speed controller in terms of steady state and transient analysis with fixed step, variable step load and variable speed condition has been presented. Beside this a detailed comparative study of AHBCC is also done with Conventional Hysteresis Current Control(CHCC) scheme. The simulation circuits parameters for IPMSM, inverter, speed and current controllers of the drive system are given in Appendix-A

Fuzzy logic based online adaptation of current and speed controllers for improved performance of IPMSM drive

Precise torque and speed control of electric motors is a key issue in industries for variable speed drives (VSD). Over the years the induction motors have been widely utilized in industries for VSD applications. However, induction motor has some significant drawbacks like low efficiency, lagging power factor, asynchronous speed, low torque density etc. Nowadays the interior permanent magnet synchronous motor (IPMSM) is becoming popular for high performance variable speed drive (HPVSD) due to its high torque-current ratio, large power-weight ratio, high efficiency, high power factor, low noise and robustness as compared to conventional induction and other ac motors. Smooth torque response, fast and precise speed response, quick recovery of torque and speed from any disturbance and parameter insensitivity, robustness in variable speed domain and maintenance free operations are the main concerns for HPVSD. This work proposes a closed loop vector control of an IPMSM drive incorporating two separate fuzzy logic controllers (FLCs). Among them one FLC is designed. to minimize the developed torque ripple by varying online the hysteresis band of the PWM current controller. Another Sugeno type FLC is used to tune the gains of a proportional-integral (PI) controller where the PI controller actually serves as the primary speed controller. Thus, the limitations of traditional PI controllers will be avoided and the performance of the drive system can be improved. A flux controller is also incorporated in such a way that both torque and flux of the motor can be controlled while maintaining current and voltage constraints. The flux controller is designed based on maximum-torque- per-ampere (MTPA) operation below the rated speed and flux weakening operation above the rated speed. Thus, the proposed drive extends the operating speed limits for the motor and enables the effective use of the reluctance torque. In order to verify the performance of the proposed IPMSM drive, first a simulation model is developed using Matlab/Simulink. Then the complete IPMSM drive has been implemented in real-time using digital signal processor (DSP) controller board DS1104 for a laboratory 5 HP motor. The effectiveness of the proposed drive is verified both in simulation and experiment at different operating conditions. In this regard, a performance comparison of the proposed FLC based tuned PI and adapted hysteresis controllers based drive with the conventional PI and fixed bandwidth hysteresis controllers based drive is provided. These comparison results demonstrate the better dynamic response in torque and speed for the proposed IPMSM drive over a wide speed range

Induction Motor Performance Improvement using Super Twisting SMC and Twelve Sector DTC

Induction motor (IM) direct torque control (DTC) is prone to a number of weaknesses, including uncertainty, external disturbances, and non-linear dynamics. Hysteresis controllers are used in the inner loops of this control method, whereas traditional proportional-integral (PI) controllers are used in the outer loop. A high-performance torque and speed system is consequently needed to assure a stable and reliable command that can tolerate such unsettled effects. This paper treats the design of a robust sensorless twelve-sector DTC of a three-phase IM. The speed controller is conceived based on high-order super-twisting sliding mode control with integral action (iSTSMC). The goal is to decrease the flux, torque, the current ripples that constitute the major conventional DTC drawbacks. The phase current ripples have been effectively reduced from 76.92% to 45.30% with a difference of 31.62%. A robust adaptive flux and speed observer-based fuzzy logic mechanism are inserted to get rid of the mechanical sensor. Satisfactory results have been got through simulations in MATLAB/Simulink under load disturbance. In comparison to a conventional six-sector DTC, the suggested technique has a higher performance and lower distortion rate

To develop an efficient variable speed compressor motor system

This research presents a proposed new method of improving the energy efficiency of a Variable Speed Drive (VSD) for induction motors. The principles of VSD are reviewed with emphasis on the efficiency and power losses associated with the operation of the variable speed compressor motor drive, particularly at low speed operation.The efficiency of induction motor when operated at rated speed and load torque is high. However at low load operation, application of the induction motor at rated flux will cause the iron losses to increase excessively, hence its efficiency will reduce dramatically. To improve this efficiency, it is essential to obtain the flux level that minimizes the total motor losses. This technique is known as an efficiency or energy optimization control method. In practice, typical of the compressor load does not require high dynamic response, therefore improvement of the efficiency optimization control that is proposed in this research is based on scalar control model.In this research, development of a new neural network controller for efficiency optimization control is proposed. The controller is designed to generate both voltage and frequency reference signals imultaneously. To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. The simulation of the proposed controller for variable speed compressor is presented. The results obtained clearly show that the efficiency at low speed is significant increased. Besides that the speed of the motor can be maintained. Furthermore, the controller is also robust to the motor parameters variation. The simulation results are also verified by experiment

An improved artificial dendrite cell algorithm for abnormal signal detection

In dendrite cell algorithm (DCA), the abnormality of a data point is determined by comparing the multi-context antigen value (MCAV) with anomaly threshold. The limitation of the existing threshold is that the value needs to be determined before mining based on previous information and the existing MCAV is inefficient when exposed to extreme values. This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. This paper proposed an improved anomaly threshold solution for DCA using the statistical cumulative sum (CUSUM) with the aim to improve its detection capability. In the proposed approach, the MCAV were normalized with upper CUSUM and the new anomaly threshold was calculated during run time by considering the acceptance value and min MCAV. From the experiments towards 12 benchmark and two outbreak datasets, the improved DCA is proven to have a better detection result than its previous version in terms of sensitivity, specificity, false detection rate and accuracy

Simulation of Three-Phase Induction Motor Control Using Fuzzy Logic Controller

A fuzzy logic controller has been developed and simulated on an indirect vector control of an induction motor (IVCIM) drive system. The objective of the indirect vector control is to convert the three-phase induction motor into a linear device where the torque and the flux in the motor can be controlled independently. The induction motor is fed by a current-controlled PWM inverter. The proposed fuzzy speed controller block in a vector controlled drive system observes the pattern of the speed loop error signal and correspondingly updates its output, so that the actual speed matches the command speed. The design of the fuzzy controller starts with identifying the inputs, performing the membership functions for the two inputs of the FLC and ends at manipulating the final command signal to the current regulator which triggers the inverter.The fuzzy logic toolbox has been used to build the fuzzy inference system (FIS) which is the dynamo of the fuzzy logic controller. The proposed FLC controller has been designed to meet the speed tracking requirements under a step change in speed and load changes. The proposed FLC drive dynamic performance has been investigated and tested under different operating conditions by simulation in the SimulinMMatlab software environment. In order to prove the superiority of the FLC, a conventional PI controller based IM drive system has also been simulated. The simulation results obtained have proved the very good performance and robustness of the proposed FLC. It is concluded that the proposed fuzzy logic controller has shown superior performances over the conventional PI controller