Sharif Digital Repository

This paper addresses the design of an observer-based adaptive fuzzy controller for a class of uncertain non-strict nonlinear systems subject to time-delays, unknown direction, input saturation, and output constraint. The Barrier Lyapunov Function (BLF) has been utilized to keep the system output inside the desired bounds. The state and input delays have been handled by using the Lyapunov–Krasovskii function and including an integral compensator term in the controller, respectively. A state observer has been designed to estimate the unmeasured states. The Lipschitz condition for proving boundedness of the estimated states has been relaxed. The Nussbaum gain function has been exploited to deal... 

Ignoring actuator dynamics in control of rigid manipulators can in practice result in performance degradation or loss of system stability. However, consideration of actuator dynamics usually requires measurement of robot joint torques. This paper addresses motion tracking control of an n-DOF rigid robot by taking into account its actuator dynamics. Joint torque measurement is avoided by using an adaptive observer. The backstepping technique is adopted to develop a dynamically smooth adaptive nonlinear controller dealing with uncertainties in manipulator and actuator dynamics. Semi-global convergence of motion tracking errors as well as torque estimation error are proven without any...