Noninteracting Adaptive Control of PMSM Using Interval Type-2 Fuzzy Logic Systems

Observer-based adaptive interval type-2 fuzzy control of uncertain MIMO nonlinear systems with unknown asymmetric saturation actuators

“…Rg i j m θ Rg i j and η * i m η i , then by using triangular inequality we have (e) Using (a)-(d), considering ε as a design parameter and [51,52], it can be easily deduced that u and u ε defined respectively in (26) and ( Proof. Consider the following Lyapunov function candidate:…”

“…However, the membership functions of the antecedent parts of fuzzy rules are crisp and should be selected by the expert. Using adaptive type-2 fuzzy/neural systems some useful and effective controllers have been proposed, for example [26][27][28][29][30][31][32][33]. The general idea for these methods is to set the consequent parameters of fuzzy rules free and tune them by adaptive laws derived via Lyapunov synthesis approach.…”

Review of Recent Type-2 Fuzzy Controller Applications

“…IT2 FLCs have been used in AC motors, such as permanent magnet synchronous motors (PMSM) [66] or permanent magnet linear synchronous motor (PMLSM) [67].…”

Adaptive Fuzzy Speed Control for Permanent Magnet Synchronous Motor Servo Systems

“…In [6], to inhibit the impact of load inertia variation, an adaptive control scheme based on the extended state observer was developed, and the relationship between feed-forward compensation gain and system inertia was analyzed. On the other hand, artificial intelligence control methods [12][13][14][15][16] have attracted much attention due to their strong robustness against parameter variations and the virtue of requiring little information from the system model. Combining the advantages of fuzzy control and sliding-mode control, a speed controller with a load torque observer was designed to enhance the robustness against model parameter variations in [12].…”