Model reference adaptive backstepping control of double star induction machine with extended Kalman sensorless control

Abstract

Introduction. Newly, the design of a controller for speed control of double star induction motor as a research focus. Consequently, backstepping technique is used to recursively construct a stable control law for speed and flux. Nevertheless, this control law coming from backstepping requires the knowledge of speed and flux values; in practice the measurement sensors are expensive and fragile. The novelty of this work consists to propose a control strategy which based on accurate Kalman filter observer that estimates speed, flux and torque. This extended Kalman filter is an optimal state estimator and is usually applied to a dynamic system that involves a random noise environment. Purpose. Apply a backstepping control of double star induction motor based on principle of rotor flux orientation. This approach consists in finding a Lyapunov function that allows deducing a control law and a modified adaptation rule is referred and sufficient conditions for the stability of the command-observer, in contrast to other techniques who use nonlinear principle. Results. The simulation results are shown to illustrate the performance of the proposed scheme under parametric uncertainties by simulation on MATLAB. The obtained results showed the robustness of the sensorless control in front of load and parameters variation of double stator induction motor. The research directions of the model were determined for the subsequent implementation of results with simulation samples.

Adaptive output feedback command filter controlbased on extreme learning machine for nonaffine time delay systems with input saturation

“…where ℵ 0 > ℵ(0) > lim t→∞ ℵ(t) = ℵ ∞ > 0 and ϕ are strictly positive constants. In order to acquire the desired performance, let e 0 = ℵ(t)P (z 1 (t)) (11) where z 1 (t) is the converted error, P (z 1 (t)) = (ι max e z1 − ι min e −z1 )/(e z1 − e −z1 ) is the inverse function.…”

“…Nevertheless, the shortcoming of "explosion of complexity" frequently existed in an adaptive backstepping control cannot be disposed availably, as pointed out by [10][11][12][13]. To overcome the challenges arising from the adaptive backstepping control in the control process, a DSC combined with first order low-pass filter was first put forward by Swaroop D [14].…”

Optimal Fractional Order Proportional Integral Controller for Dual Star Induction Motor Based on Particle Swarm Optimization Algorithm

“…The simpler and effective solutions that exist nowadays in the majority of engineering control applications employ proportional integral derivative (PID) in the regulation loop [13]. On the other hand, lots of nonlinear control laws have been proposed including sliding mode control (SMC) [14,15], synergetic control [16][17][18], predictive control [19], backstepping control [20,21], and high-order SMC techniques [5]. In addition, the response and the speed dynamic of a system can be improved using intelligent techniques, such as fuzzy logic and neural networks [22][23][24].…”

Implementation of a new flux rotor based on model reference adaptive system for sensorless direct torque control modified for induction motor

“…The motor speed for sensorless control can be estimated by different methods [2][3][4][5]. The simplest technique is based on the rotor flux vector coordinates obtained using the induction motor model, based on the slip calculation and angular velocity of rotor flux vector.…”