Improved direct torque control using Kalman filter: application to a doubly-fed machine

Direct Torque Control (DTC) has been extensively researched and applied during the last two decades. However, it has only first been applied to the Brushless Doubly Fed Reluctance Machine (BDFRM) a few years ago in its basic form inheriting its intrinsic flux estimation problems that propagate throughout the algorithm and hence compromise the DTC performance. In this paper, we propose the use of Kalman Filter (KF) as an alternative to improve the estimation and consequently the control performance of the DTC. The KF is designed around a nominal model, but is shown to be reliable over the whole operating range of the BDFRM. Moreover, we use a modified robust exact differentiator based on Sliding Mode (SM) techniques to calculate the angular velocity from an angular position encoder. Computer simulations are meticulously designed to take into account real-world physical constraints and thus show illustrative supporting results as expected from an experimental setup

Assessment of flywheel energy storage for spacecraft power systems

The feasibility of inertial energy storage in a spacecraft power system is evaluated on the basis of a conceptual integrated design that encompasses a composite rotor, magnetic suspension, and a permanent magnet (PM) motor/generator for a 3-kW orbital average payload at a bus distribution voltage of 250 volts dc. The conceptual design, which evolved at the Goddard Space Flight Center (GSFC), is referred to as a Mechanical Capacitor. The baseline power system configuration selected is a series system employing peak-power-tracking for a Low Earth-Orbiting application. Power processing, required in the motor/generator, provides a potential alternative configurations that can only be achieved in systems with electrochemical energy storage by the addition of power processing components. One such alternative configuration provides for peak-power-tracking of the solar array and still maintains a regulated bus, without the expense of additional power processing components. Precise speed control of the two counterrotating wheels is required to reduce interaction with the attitude control system (ACS) or alternatively, used to perform attitude control functions. Critical technologies identified are those pertaining to the energy storage element and are prioritized as composite wheel development, magnetic suspension, motor/generator, containment, and momentum control. Comparison with a 3-kW, 250-Vdc power system using either NiCd or NiH2 for energy storage results in a system in which inertial energy storage offers potential advantages in lifetime, operating temperature, voltage regulation, energy density, charge control, and overall system weight reduction

Low-cost, high-resolution, fault-robust position and speed estimation for PMSM drives operating in safety-critical systems

In this paper it is shown how to obtain a low-cost, high-resolution and fault-robust position sensing system for permanent magnet synchronous motor drives operating in safety-critical systems, by combining high-frequency signal injection with binary Hall-effect sensors. It is shown that the position error signal obtained via high-frequency signal injection can be merged easily into the quantization-harmonic-decoupling vector tracking observer used to process the Hall-effect sensor signals. The resulting algorithm provides accurate, high-resolution estimates of speed and position throughout the entire speed range; compared to state-of-the-art drives using Hall-effect sensors alone, the low speed performance is greatly improved in healthy conditions and also following position sensor faults. It is envisaged that such a sensing system can be successfully used in applications requiring IEC 61508 SIL 3 or ISO 26262 ASIL D compliance, due to its extremely high mean time to failure and to the very fast recovery of the drive following Hall-effect sensor faults at low speeds. Extensive simulation and experimental results are provided on a 3.7 kW permanent magnet drive

Competence Amelioration of PMBLDC Motor using LQR- PID, Kalman Filter- PID and LQG Based on Kalman Filter-PID optimal Controllers for disturbance attenuation

In this paper, modeling, simulation and performance analysis of the permanent magnet brushless direct current (PMBLDC) motor using classical controller (PID Controller) and optimal controllers ( Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) optimal Controllers Based on Kalman Filter) for disturbance attenuation and noise suppression is presented. The applications of the permanent magnet brushless direct current (PMBLDC) motor are increasing day by day. In order to have proper utilization of these motors and to control them effectively it is important to have proper mathematical modeling of these motors. Similarly effective control these motors are also essential to have successful application of the devices across multiple domains. This paper handles both these important aspects. A mathematical model has been derived to represent permanent magnet brushless direct current (PMBLDC) motor model to study the stability and performance. In order to maintain the stability and to achieve the best performance by reducing disturbance attenuation and noise suppression, the three optimal controllers are developed in this paper. the system performance simulation of these optimal controllers with PID controller is presented using MATLAB program to control the modeled permanent magnet brushless direct current (PMBLDC) motor for disturbance attenuation and noise suppression.. The simulation results show that and Linear Quadratic Gaussian (LQG) Based on Kalman Filter with PID controller  provides best as compared to PID controller, Linear Quadratic Regulator (LQR) with PID controller and Kalman Filter with PID controller

Linear motor motion control using a learning feedforward controller

The design and realization of an online learning motion controller for a linear motor is presented, and its usefulness is evaluated. The controller consists of two components: (1) a model-based feedback component, and (2) a learning feedforward component. The feedback component is designed on the basis of a simple second-order linear model, which is known to have structural errors. In the design, an emphasis is placed on robustness. The learning feedforward component is a neural-network-based controller, comprised of a one-hidden-layer structure with second-order B-spline basis functions. Simulations and experimental evaluations show that, with little effort, a high-performance motion system can be obtained with this approach

Type 1 versus type 2 fuzzy logic speed controllers for brushless dc motors

This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2FLC exhibited better performance than T1FLC

Life buoy

A lifebuoy such as figure 1, or we can call as ring buoy, lifering, lifesaver, life donut, life preserver or lifebelt, also known as a "perry buoy", or "kisby ring". The "kisby ring", or sometimes will be call "Kisbie ring", is thought to be named after Thomas Kisbee (1792–1877) who was a British naval officer. Lifebuoy is a lifesaving buoy designed to save someone in the water. It also can provide buoyancy and prevent drowning. To improve aid rescue at night, mostly lifebuoys are fitted with one or more seawater-activated lights