Cascaded Nonlinear Adaptive Predictive Control based Adaptive Flux Observer of Induction Motor

Abstract

This paper present a new advanced control algorithm based on continuous minimization of predicted tracking errors, to achieve torque, rotor speed and rotor flux amplitude tracking objectives. This algorithm called a new Adaptive Nonlinear Predictive Control to induction motor drive uses a combination of the adaptive observer for rotor flux and Cascaded Nonlinear Predictive Control technique. The variables to be controlled are the rotor speed and the rotor flux norm, required to implement the predictive control algorithm is estimated by flux observer. The parameters identified adaptively are stator and rotor resistance which vary with motor temperature using the adaptive rotor flux observer. A stability of the proposed adaptive flux observer will be proved by the Lyapunov's theorem. Simulations are carried out in order to show the effectiveness of the drive and the robustness to parameters variations.

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“…The objective of the CNPC is to realize a synchronized control of the three variables (speed, flux, and torque) with two loops. Each loop is designed with a generalized predictive controller [21], as shown in Figure 5. First, an external loop controls the speed; then, the inner loop controls other variables [16], [21].…”

“…The quadratic cost function J to be minimized is defined in a finite time of prediction (t+ τr) by, (7) Employing Taylor series expansion for the output vector y(t) and for the reference output vector yr(t). The cost function in ( 7) can be simplified as [17], [21] The optimal control vector u(t) is given by [21],…”

“…Design of the external loop controller The external loop is a simple predictive controller that controls the speed ωm by generating the optimal torque Te * . The optimal control law is deduced from the cancellation of the tracking error defined by [21], (10) Where, and…”

“…To get rid of FOC problems many non-linear control methods have been introduced such as input-output linearization (IOL), sliding mode control (SMC), and non-linear predictive control (NPC) [20]. The NPC has received particular attention due to its capacity to eliminate the weaknesses of the FOC [21]. The NPC task is to track the reference trajectories of flux and speed.…”