M. Nasir Uddin

FLC-Based DTC Scheme to Improve the Dynamic Performance of an IM Drive

This paper presents a fuzzy logic hysteresis comparator-based direct torque control (DTC) scheme of an induction motor (IM) under varying dynamic conditions. The fuzzy logic controller (FLC) is used to adjust the bandwidth of the torque hysteresis controller in order to reduce the torque and flux ripples and, hence, to improve motor dynamic response. The effects of torque hysteresis bandwidth on the amplitude of torque ripples of an IM are also discussed in this paper. Based on the slopes of motor-estimated torque and stator current, an FLC is designed to select the optimum bandwidth of the torque hysteresis controller. This paper also proposes a simpler algorithm than the conventional trigonometric function-based algorithm to evaluate the sector number (required for DTC scheme) of the stator flux-linkage space vector. The proposed algorithm reduces the computational burden on the microprocessor. In order to test the performance of the proposed FLC-based DTC scheme for IM drive, a complete simulation model is developed using MATLAB/Simulink. The proposed FLC-based DTC scheme is also implemented in real time using DSP board DS1104 for a prototype 1/3 hp motor. The performance of the proposed drive is tested in both simulation and experiment.

Fuzzy logic controller based SEPIC converter of maximum power point tracking

This paper presents a fuzzy logic controller (FLC)-based single-ended primary-inductor converter (SEPIC) for maximum power point tracking (MPPT) operation of a photovoltaic (PV) system. The FLC proposed presents that the convergent distribution of the membership function offers faster response than the symmetrically distributed membership functions. The fuzzy controller for the SEPIC MPPT scheme shows high precision in current transition and keeps the voltage without any changes, in the variable-load case, represented in small steady-state error and small overshoot. The proposed scheme ensures optimal use of PV array and proves its efficacy in variable load conditions, unity, and lagging power factor at the inverter output (load) side. The real-time implementation of the MPPT SEPIC converter is done by a digital signal processor (DSP), i.e., TMS320F28335. The performance of the converter is tested in both simulation and experiment at different operating conditions. The performance of the proposed FLC-based MPPT operation of SEPIC converter is compared to that of the conventional proportional-integral (PI)-based SEPIC converter. The results show that the proposed FLC-based MPPT scheme for SEPIC can accurately track the reference signal and transfer power around 4.8% more than the conventional PI-based system.

FLC Based DTC Scheme to Improve the Dynamic Performance of an IM Drive

This paper presents a fuzzy logic hysteresis comparator-based direct torque control (DTC) scheme of an induction motor (IM) under varying dynamic conditions. The fuzzy logic controller (FLC) is used to adjust the bandwidth of the torque hysteresis controller in order to reduce the torque and flux ripples and, hence, to improve motor dynamic response. The effects of torque hysteresis bandwidth on the amplitude of torque ripples of an IM are also discussed in this paper. Based on the slopes of motor-estimated torque and stator current, an FLC is designed to select the optimum bandwidth of the torque hysteresis controller. This paper also proposes a simpler algorithm than the conventional trigonometric function-based algorithm to evaluate the sector number (required for DTC scheme) of the stator flux-linkage space vector. The proposed algorithm reduces the computational burden on the microprocessor. In order to test the performance of the proposed FLC-based DTC scheme for IM drive, a complete simulation model is developed using MATLAB/Simulink. The proposed FLC-based DTC scheme is also implemented in real time using DSP board DS1104 for a prototype 1/3 hp motor. The performance of the proposed drive is tested in both simulation and experiment.

Online Efficiency Optimization of a Fuzzy Logic Controller Based IPMSM Drive

This paper presents an online loss minimization algorithm (LMA) for a fuzzy logic controller (FLC) based interior permanent magnet synchronous motor (IPMSM) drive to yield high efficiency and high dynamic performance over wide speed range. The loss minimization algorithm is developed based on the motor model. In order to minimize the controllable electrical losses of the motor and thereby maximize the operating efficiency the d-axis armature current is controlled optimally according to the operating speed and load conditions. For vector control purpose, a fuzzy logic controller (FLC) is used as a speed controller which enables the utilization of the reluctance torque to achieve high dynamic performance as well as to operate the motor over a wide speed range. In order to test the performance of the proposed drive in real-time, the complete drive is experimentally implemented using DSP board DS1104 for a prototype laboratory 5 hp motor. The performance of the proposed loss minimization based FLC for IPMSM drive is tested in both simulation and experiment at different operating conditions. A performance comparison of the drive with and without the proposed LMA based FLC is also provided. It is found from the results that the proposed LMA and FLC based drive demonstrates higher efficiency and better dynamic responses over FLC based IPMSM drive without LMA.

A Novel Fuzzy Logic Controller Based Torque and Flux Controls of IPM Synchronous Motor

This paper presents a novel fuzzy logic controller (FLC)-based wide-speed-range operation of interior permanent-magnet synchronous motor (IPMSM) drives. The proposed FLC is designed in such a way that it can simultaneously control both torque and flux of the motor while maintaining current and voltage constraints. Thus, a stand-alone FLC is utilized, whose outputs are d- and q-axis currents. The proposed FLC is designed based on conventional maximum torque per ampere operation below the rated speed and the field-weakening operation above the rated speed. The complete IPMSM drive is experimentally implemented, utilizing dSPACE DSP board DS1104 for a prototype 5-hp motor. The performance of the proposed drive is tested both in simulation and experiment at different operating conditions. The robustness of the controller and its prospective real-time industrial drive application are evidenced by the results.

Development and Implementation of a Simplified Self-Tuned Neuro–Fuzzy-Based IM Drive

A novel simplified self-tuned neuro-fuzzy controller (NFC) for speed control of an induction motor (IM) drive is presented in this paper. The proposed NFC combines fuzzy logic and a four-layer neural network structure. Only speed error is employed as input to the NFC so that the computational burden of the NFC is reduced and it becomes suitable for real-time industrial drive applications. Based on the knowledge of back-propagation algorithm, an unsupervised self-tuning method is developed to adjust membership functions and weights of the proposed NFC so that the performance will be similar to that of the conventional two-input NFC. The complete drive incorporating the proposed self-tuned NFC is experimentally implemented using a digitalsignal-processor board DS-1104 for a laboratory 1/3-hp motor. The effectiveness of the proposed NFC-based vector control of IM drive is tested in both simulation and experiment at different operating conditions. Comparative results show that the simplification of the proposed NFC does not decrease the system performance as compared to the conventional NFC. In order to prove the superiority of the proposed simplified NFC, the performances of the proposed NFC are also compared to those obtained by a conventional proportional-integral controller.

Real-Time Testing of a Fuzzy-Logic-Controller-Based Grid-Connected Photovoltaic Inverter System

This paper presents a novel fuzzy logic controller (FLC) based high performance control of a 3-phase photovoltaic (PV) inverter connected to the grid line. For the proposed control scheme one FLC is used for voltage control and two FLCs are used for current controls. With the aid of the developed inverter model and fuzzy voltage and current control schemes, the digital signal processing (DSP) controller board generates the sinusoidal pulse-width modulated (SPWM) logic signals for the inverter operation which regulates the 50 Hz sinusoidal ac output voltage and current for both standalone and grid-connected modes. A prototype PV grid connected 3-phase inverter controlled with the proposed FLCs is built using the DSP board DS 1104. The proposed fuzzy control strategy demonstrates stable ac output voltage of the inverter satisfactorily during both transient and steady-state conditions including grid and/or load disturbances. Moreover, the inverter is capable of feeding excess power to the grid when the power generation is more than local demand. The developed control system generates only 2.48% and 4.64% of output voltage and current total harmonic distortion (THD), respectively. The output waveform results such as the inverter output voltage, injected current, and the system power flow are presented to validate the effectiveness of the control system.

Self-Tuned NFC and Adaptive Torque Hysteresis-Based DTC Scheme for IM Drive

This paper presents a simplified self-tuned Sugeno-type neuro-fuzzy controller (NFC)-based direct torque control (DTC) scheme for induction motor (IM) drive. A simple tuning algorithm is developed based on the reference and actual acceleration of the motor. The online tuning strategy adjusts the parameters of the consequent layer of the NFC in order to minimize the square of the error between the actual and the reference acceleration of the motor. In a conventional DTC scheme, the band limits of flux and torque hysteresis controllers remain fixed, and hence, the torque and flux ripples are high. In order to minimize the torque ripples of the IM, the hysteresis band limits are adjusted online for the torque hysteresis controller. Thus, the proposed NFC is used to achieve high dynamic performance of the drive, and the variable hysteresis controller is used to reduce the steady-state torque ripple. The proposed NFC-based DTC scheme is successfully implemented in real time using the DSP board DS1104 for a prototype 1-hp squirrel-cage IM. The performance of the proposed drive is tested at different operating conditions in both simulation and experiment. The proposed NFC-based DTC scheme is found superior to the conventional DTC scheme in both steady-state and transient conditions.

Performance Analysis of an FLC Based Online Adaptation of Both Hysteresis and PI Controllers for IPMSM Drive

This paper presents a closed-loop vector control of an interior permanent magnet synchronous motor (IPMSM) drive incorporating two separate fuzzy logic controllers (FLCs). The first one is a Mamdani-type FLC which minimizes the developed torque ripple by varying online the hysteresis band of the PWM current controller. The second one is an FLC-based tuned proportional-integral (PI) controller where the PI controller actually serves as the primary speed controller and its gains are tuned by a novel Sugeno-type FLC. Thus, the limitations of traditional PI controllers are avoided, and the performance of the drive system is 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. Thus, the proposed drive extends the operating speed limits for the motor and enables the appropriate use of the reluctance torque. The proposed IPMSM drive is also implemented in real time using DSP board DS1104 for a laboratory 5 HP motor. A performance comparison of the proposed IPMSM drive with conventional PI controller-based drive is provided. Simulation and experimental results demonstrate the better dynamic response in torque and speed for the proposed drive over a wide speed range.

A Simplified Self-Tuned Neuro-Fuzzy Controller Based Speed Control of an Induction Motor Drive

In this paper a novel and simplified self-tuned neuro-fuzzy controller (NFC) is developed for speed control of an induction motor (IM) drive. The proposed NFC combines fuzzy logic and a four-layer artificial neural network (ANN) scheme. Based on the knowledge of motor control and intelligent algorithms an unsupervised self-tuning method is developed to adjust membership functions and weights of the proposed NFC. Unlike conventional NFCs, which utilize both speed error and its derivative as inputs of NFC for speed control of IM, the input of the proposed NFC is only the speed error. Comparison of results in simulation proves that the simplification of the proposed NFC does not decrease system performance. The proposed NFC has lower computation burden and is easier to implement in practical applications. The complete drive incorporating the proposed self tuned NFC is experimentally implemented using a digital signal processor board DS-1104 for a laboratory 1/3 hp motor. The effectiveness of the proposed NFC based IM drive is tested both in simulation and experiment at different operating conditions.