Model reference adaptive synchronization of T–S fuzzy discrete chaotic systems using output tracking control

Discrete time robust control of robot manipulators in the task space using adaptive fuzzy estimator

“…Stability analysis and stabilization of discrete-time T-S fuzzy time-varying delay systems has been studied in [3]. A model reference adaptive control approach for the synchronization of a discretetime chaotic system is using output tracking control has been performed [4]. The important purposes in these researches are the improvement of the control performance and to ensure the system stability at the presence of problems such as uncertainties, nonlinearities, sampling period and discretizing errors.…”

The model reference control for the four-dimensional energy supply-demand system

“…MRC has a wide application in many areas but not in energy systems. For example, see [1] for the control of SIRS models [2] for the control of a Human-Operated Mobile Robot [3] for the control of synchronous machine [4] for the control of a flight system [5] for the control of a flexible launch vehicle [6] for the control of a shunt active-power-filter system [7,8] for the control of time-varying systems [9,10] for the control of chaotic systems.…”

Directly adaptive fuzzy control of discrete-time chaotic systems by least squares algorithm with dead-zone

“…A unified approach to controlling chaos via LMIbased fuzzy control system design was suggested in [23] where the key idea is to use the well-known Takagi-Sugeno (T-S) fuzzy model to represent typical chaos models and then apply some effective fuzzy control techniques. Following the idea of representing chaotic systems via the T-S fuzzy model, some adaptive control methods have been proposed for stabilization or synchronization of discrete-time chaotic systems [24][25][26]. However, the modeling error and unknown disturbances are not considered in [24][25][26].…”

“…Following the idea of representing chaotic systems via the T-S fuzzy model, some adaptive control methods have been proposed for stabilization or synchronization of discrete-time chaotic systems [24][25][26]. However, the modeling error and unknown disturbances are not considered in [24][25][26].…”