A servo system control with time-varying and nonlinear load conditions using type-2 TSK fuzzy neural system

Position tracking of a 3-PSP parallel robot using dynamic growing interval type-2 fuzzy neural control

“…For avoiding high computational cost, instead of iterative Karnik-Mendel algorithm, the method which is introduced in [36] is used to calculate the output of the network.…”

“…for trajectory and joint angle tracking are obtained. To test the efficiency of the proposed controller, the results for the DGIT2FNC are compared with a TSK interval type-2 fuzzy neural controller (TSK IT2FNC) [36] and dynamic growing type-1 fuzzy neural controller (DGT1FNC) [27,28].…”

Harmony search algorithm and Lyapunov theory based hybrid adaptive fuzzy controller for temperature control of air heater system with transport-delay

“…The temperature controller employed to control the temperature of the process at different locations should be able to cope with such variations and unwanted/unforeseeable situations. Researchers, during the last two decades, have continuously proved that the conventional PID type controllers are not suitable for these types of applications [1,[5][6][7] and several research works have corroborated the fact that fuzzy logic controllers (FLCs) possess tremendous potential to find their applications in these fields [8,10,12]. Several researchers are also motivated by the hybrid design methodologies combining fuzzy control theory with genetic algorithm to accommodate the complexities of the system to be controlled [9,13,18,19].…”

Direct inverse control of cable-driven parallel system based on type-2 fuzzy systems

“…The theory and application researches of type-2 fuzzy logic have demonstrated that type-2 fuzzy logic systems can allow us to cope with the different sources of uncertainties, and weaken noisy disturbance, which cannot be appropriately handled by type-1 fuzzy systems [14,18]. Many fuzzy identification and control schemes have been developed for uncertain nonlinear systems, and found extensive applications based on type-2 FLSs, for example, [1,[4][5][6][9][10][11][12][13]16,17,29] and reference therein. The authors in [4] investigated an optimization type-2 fuzzy controller for an autonomous mobile robot and compared with type-1 fuzzy controller.…”

“…Furthermore, we obtain the consequent parameter vector w by solving (7) and (10). Based on the antecedent and consequent parameters of the inverse controllers, the fuzzy rules are listed in Tables 1 and 2.…”