T-S fuzzy H∞ tracking control of input delayed robotic manipulators

Time delays are often encountered by practical control systems while they are acquiring, processing, communicating, and sending signals. T ime delays may affect the system stability and degrade the control system performance if they are not properly dealt with. T aking the classical robot control problem as an example, the significant effect of time delay on the closed-loop system stability has been highlighted in the bilateral teleoperation, where the communication delay transmitted through a network medium has been received widespread attention and different approaches have been proposed to address this problem (Hokayem and Spong, 2006). In addition, examples like processing delays in visual systems and communication delay between different computers on a single humanoid robot are also main sources that may cause time delays in a robotic control system (Chopra, 2009), and the issue of time delay for robotic systems has been studied through the passivity property . F or systems with time delays, both delay dependent and delay independent control strategies have been extensively studied in recent years, see for example (Xu and Lam, 2008) and references therein. F or the control of nonlinear time delay systems, model based T akagi-Sugeno (T -S) fuzzy control (T anaka and W ang, 2001; F eng, 2006; Lin et al., 2007) is regarded as one of the most effective approach because some of linear control theory can be applied directly . Conditions for designing such kinds of controllers are generally expressed as linear matrix inequalities (LMIs) which can be efficiently solved by using most available software like Matlab LMI T oolbox, or bilinear matrix inequalities (BMIs) which could be transferred to LMIs by using algorithms like iteration algorithm or cone complementar y linearisation algorithm. F rom the theoretical point of view, one of the current focus on the control of time delay systems is to develop less conser vative approaches so that the controller can stabilise the systems or can achieve the defined control performance under bigger time delays.