This study proposes a combination of a fuzzy sliding mode controller (FSMC) with integral-proportion-Derivative switching surface based superconducting magnetic energy storage (SMES) and PID tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. The goal of design is to improve the dynamic response of power systems after load demand changes. In t...

An adaptive variable structure position control for induction motors using field oriented control theory is presented. The proposed sliding-mode control law incorporates an adaptive switching gain to avoid calculating an upper limit of the system uncertainties. The design incorporates a flux estimator that operates on the principle of flux and current observer. The proposed observer is basicall...

the control law (3) does not only improves the transient performance, but also provides smoother outputs. It is important to stress that a better performance can still be achieved with (28) and (30). However, as discussed in Remark IV.1, increasing gains would not only cause more peaks in the outputs, but it might also yield saturation, especially for 2. V. CONCLUSION The tracking control probl...

Abstract We present, analyze, and test locally stabilized space–time finite element methods on fully unstructured simplicial meshes for the numerical solution of tracking parabolic optimal control problems with standard L 2 -regularization.We derive a priori discretization error estimates in terms local mesh-sizes shape-regular meshes. The adaptive version is driven by residual indicators, or, ...

This paper proposes an approach to tune an Adaptive Neuro Fuzzy Inference System (ANFIS) inverse controller using Iterative Learning Control (ILC). The control scheme consists of an ANFIS inverse model and learning control law. Direct ANFIS inverse controller may not guarantee satisfactory response due to different uncertainties associated with operating conditions and noisy training data. In t...