Emotional Fuzzy Sliding-Mode Control for Unknown Nonlinear Systems

[[abstract]]The brain emotional learning model can be implemented with a simple hardware and processor; however, the learning model cannot model the qualitative aspects of human knowledge. To solve this problem, a fuzzy-based emotional learning model (FELM) with structure and parameter learning is proposed. The membership functions and fuzzy rules can be learned through the derived learning scheme. Further, an emotional fuzzy sliding-mode control (EFSMC) system, which does not need the plant model, is proposed for unknown nonlinear systems. The EFSMC system is applied to an inverted pendulum and a chaotic synchronization. The simulation results with the use of EFSMC system demonstrate the feasibility of FELM learning procedure. The main contributions of this paper are (1) the FELM varies its structure dynamically with a simple computation; (2) the parameter learning imitates the role of emotions in mammalians brain; (3) by combining the advantage of nonsingular terminal sliding-mode control, the EFSMC system provides very high precision and finite-time control performance; (4) the system analysis is given in the sense of the gradient descent method.[[notice]]補正完

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

Development and implementation of various speed controllers for wide speed range operation of IPMSM drive / by Md Muminul Islam Chy.

Despite many advantageous features of interior permanent magnet synchronous motor (IPMSM), the precise speed control of an IPMSM drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinearity present in the electromagnetic developed torque due to magnetic saturation of the rotor core particularly, at high speeds (above rated speed). Fast and accurate response, quick recovery of speed from any disturbances and insensitivity to parameter variations are some of the important characteristics of high performance drive system used in robotics, rolling mills, traction and spindle drives. The conventional controllers such as PI, PID are sensitive to plant parameter variations and load disturbance. For the purpose of obtaining high dynamic performance, recently researchers developed several non-linear as well as intelligent controllers. Most of the reported works on controller design of IPMSM took an assumption of d-axis stator current (i[subscript d]) equal to zero in order to simplify the development of the controller. However, with this assumption it is not possible to control the motor above the rated speed and the reluctance torque of IPMSM can not be utilized efficiently. Furthermore, this assumption leads to an erroneous result for motor at all operating conditions. In this thesis, some controllers are developed for the IPMSM drive system incorporating the flux-weakening technique in order to control the motor above the rated speed. A detailed analysis of the flux control based on various operating regions is also provided in this thesis. In order to get the optimum efficiency, an adaptive backstepping based nonlinear control scheme incorporating flux control for an IPM synchronous motor drive is taken into account at the design stage of the controller. Thus, the proposed adaptive nonlinear backstepping controller is capable of conserving the system robustness and stability against all mechanical parameters variation and external load torque disturbance. To ensure stability the controller is designed based on Lyapunov's stability theory. A novel fuzzy logic controller (FLC) including both torque and flux control is also developed in this work. The proposed FLC overcomes the unknown and nonlinear uncertainties of the drive and controls the motor over a wide speed range. For further improvement of the FLC structure, the membership function of the controller is tuned online. An integral part of this work is directed to develop an adaptive-network based fuzzy interference system (ANFIS) based neuro fuzzy logic controller. In this work, an adaptive tuning algorithm is also developed to adjust the membership function and consequent parameters. In order to verify the effectiveness of the proposed IPMSM drive, at first simulation model is developed using Matlab/Simulink. Then the complete IPMSM drive incorporating various control algorithms have been successfully implemented using digital signal processor (DSP) controller board-DSI104 for a laboratory 5 hp motor. The effectiveness of the proposed drive is verified both in simulation and experiment at different operating conditions. The results show the robustness of the drive and it's potentiality to apply for real-time industrial drive application. This thesis also provides through knowledge about development and various speed real-time applications of controllers for IPMSM drive, which will be useful for researchers and practicing engineers

A New Synergetic Scheme Control of Electric Vehicle Propelled by Six-phase Permanent Magnet Synchronous Motor

Electric Vehicles (EVs) are a promising al- ternative to conventional vehicles powered by internal combustion motors, offering the possibility of reduc- ing CO2, pollutants, and noise emissions. As known, the control of such an electric vehicle takes into ac- count several phenomena governing its behavior, which is a complicated problem because of the non-linearities, unmeasured disturbance, and parameters uncertainty of this system. This problem is one of the important challenges facing controller designers. Various control techniques have been proposed to enhance Ev’s perfor- mance. On this basis, in this research, a new synergetic scheme of electric vehicles propelled by Six-Phase Per- manent Magnet Synchronous Motor (PMSMs) is de- veloped. The synthesis of the proposed Synergetic Con- troller (SC) is based on the selection of four-manifolds of stator current of PMSMs. The SC provides fast response, asymptotic stability of the closed-loop sys- tem in wide range operating condition, and decrease the size of modeled system. Also, the principal fea- ture of SC is that it supports parameters variation. Furthermore, to illustrate the improvements and the performances of the proposed controller, a compari- son study between various nonlinear controllers such as Integral Action in Sliding Mode (ISMC), Super Twist- ing Sliding Mode (STSM), using a dynamic model of the lightweight vehicle under New European Driv- ing Cycle (NEDC) was done. The obtained simula- tion results under several operating conditions show the efficiency and superiority of the proposed control compared with nonlinear controllers; also, it demon- strates the feasibility of the proposed control approach for real system

Speed sensorless and MPPT control of IPM synchronous generator for wind energy conversion system

The popularity of renewable energy has experienced significant growth recently due to the foreseeable exhaustion of conventional fossil fuel power generation methods and increasing realization of the adverse effects that conventional fossil fuel power generation has on the environment. Among the renewable energy sources, wind power generation is rapidly becoming competitive with conventional fossil fuel sources. The wind turbines in the market have a variety of innovative concepts, with proven technology for both generators and power electronics interfaces. Recently, variable-speed permanent magnet synchronous generator (PMSG) based wind energy conversion systems (WECS) is becoming more attractive in comparison to the fixed-speed WECS. In the variable-speed generation system, the wind turbine can be operated at maximum power operating points over a wide speed range by adjusting the shaft speed optimally. This thesis presents both wind and rotor speed sensorless control for the direct-drive interior permanent magnet synchronous generator (IPMSG) with maximum power point tracking (MPPT) algorithm. The proposed method, without requiring the knowledge of wind speed, air density or turbine parameters, generates optimum speed command for speed control loop of vector controlled machine side converter. The MPPT algorithm based on perturbation and observation uses only estimated active power as its input to track peak output power points in accordance with wind speed change and incorporates proposed sensorless control to transfer maximum dc-link power from generator. In this work for the IPMSG, the rotor position and speed are estimated based on model reference adaptive system. Additionally, it incorporates flux weakening controller (FWC) for wide operating speed range at various wind speed and other disturbances. Matlab/Simulink based simulation model of the proposed sensorless MPPT control of IPMSG based WECS is built to verify the effectiveness of the system. The MPPT controller has been tested for variable wind speed conditions. The performance of the proposed WECS is also compared with the conventional control of WECS system. The proposed IPMSG based WECS incorporating the MPPT and sensorless algorithms is successfully implemented in real-time using the digital signal processor (DSP) board DS1104 for a laboratory 5 hp machine. A 5 hp DC motor is used as wind turbine to drive the IPMSG. The speed tracking performance and maximum power transfer capability of the proposed WECS are verified by both simulation and experimental results at different speed conditions

Power quality improvement utilizing photovoltaic generation connected to a weak grid

Microgrid research and development in the past decades have been one of the most popular topics. Similarly, the photovoltaic generation has been surging among renewable generation in the past few years, thanks to the availability, affordability, technology maturity of the PV panels and the PV inverter in the general market. Unfortunately, quite often, the PV installations are connected to weak grids and may have been considered as the culprit of poor power quality affecting other loads in particular sensitive loads connected to the same point of common coupling (PCC). This paper is intended to demystify the renewable generation, and turns the negative perception into positive revelation of the superiority of PV generation to the power quality improvement in a microgrid system. The main objective of this work is to develop a control method for the PV inverter so that the power quality at the PCC will be improved under various disturbances. The method is to control the reactive current based on utilizing the grid current to counteract the negative impact of the disturbances. The proposed control method is verified in PSIM platform. Promising results have been obtaine

Robust predictive tracking control for a class of nonlinear systems

A robust predictive tracking control (RPTC) approach is developed in this paper to deal with a class of nonlinear SISO systems. To improve the control performance, the RPTC architecture mainly consists of a robust fuzzy PID (RFPID)-based control module and a robust PI grey model (RPIGM)-based prediction module. The RFPID functions as the main control unit to drive the system to desired goals. The control gains are online optimized by neural network-based fuzzy tuners. Meanwhile using grey and neural network theories, the RPIGM is designed with two tasks: to forecast the future system output which is fed to the RFPID to optimize the controller parameters ahead of time; and to estimate the impacts of noises and disturbances on the system performance in order to create properly a compensating control signal. Furthermore, a fuzzy grey cognitive map (FGCM)-based decision tool is built to regulate the RPIGM prediction step size to maximize the control efforts. Convergences of both the predictor and controller are theoretically guaranteed by Lyapunov stability conditions. The effectiveness of the proposed RPTC approach has been proved through real-time experiments on a nonlinear SISO system

Induction Motors

AC motors play a major role in modern industrial applications. Squirrel-cage induction motors (SCIMs) are probably the most frequently used when compared to other AC motors because of their low cost, ruggedness, and low maintenance. The material presented in this book is organized into four sections, covering the applications and structural properties of induction motors (IMs), fault detection and diagnostics, control strategies, and the more recently developed topology based on the multiphase (more than three phases) induction motors. This material should be of specific interest to engineers and researchers who are engaged in the modeling, design, and implementation of control algorithms applied to induction motors and, more generally, to readers broadly interested in nonlinear control, health condition monitoring, and fault diagnosis