A new approach to the design of a fuzzy sliding mode controller

Fuzzy Sliding Mode Control of a Ball Screw Driven Stage

“…It is obvious that the tracking precision is at least 50% better than that of in conventional sliding mode control (Liang &, 2003).…”

“…By appropriate tuning the parameters of fuzzy controller, a high performance controller can be obtained and no further information about uncertainties of the system will be needed. It is worth to point out that because the fuzzy controller is constructed on sliding mode controller which is robust, the stability of fuzzy controller would be guaranteed (Liang &, 2003). …”

“…Lee et al developed a sliding mode controller based on fuzzy variable boundary layer with a control gain and boundary layer thickness as design parameters (Lee et al, 2001). Liang et al proposed a two input single output (TISO) fuzzy sliding mode controller (FSMC) by developing complementary sliding mode controller (CSMC) (Liang &, 2003). Mihajlov et al applied a sliding mode controller enhanced by fuzzy PI controller to an electro-hydraulic positioning system, whose model includes internal friction (Mihajlov1 et al, 2002).…”

“…In following chapter, the phenomena of backlash and friction are introduced firstly and then Canudas friction model (Canudas et al, 1995) is used to capture the frictional behaviors in a ball screw driven stage. Conventional sliding mode control with boundary layer, complementary sliding mode control and TISO fuzzy sliding mode control (Liang &, 2003) are applied to this dynamic system for the purpose of the compensation of friction effects. Finally the performances of various controllers are evaluated in the sense of submicrometer positioning, tracking accuracy and control input to the system.…”

Position Location Technique in Wireless Sensor Network Using Rapid Prototyping Algorithm

“…The challenge here is to prospect others approaches offering more realistic models taking into account these constraints and particularly parameters approximation problem. Introduced by Zadeh (Zadeh, 1965) in 1965, fuzzy logic concept has been widely applied in different applications such as control and identification process, pattern recognition, graphics analysis and synthesis and robotics (Bezdek, 1981;Dave, 1990;Liang, 2003;Huang, 2003;Lei, 2001) and satisfactory results have been obtained. In contrast, few researches have been directed towards development of fuzzy logic-based approaches for localization in WSN, even if they present advantages in terms of robustness in spite of noise or other sensor failures, ability to handle non-linearity without degradation and the use of linguistic adjectives and relations similar to a natural language for interpretability.…”