ABSTRACT
This paper presents a two-loop control framework for robotic manipulator systems subject to state constraints and input saturation, which effectively integrates planning and control strategies. Namely, a stability controller is designed in the inner loop to address uncertainties and nonlinearities; an optimization-based generator is constructed in the outer loop to ensure that state and input constraints are obeyed while concurrently minimizing the convergence time. Furthermore, to dramatically the computational burden, the optimization-based generator in the outer loop is switched to a direct model-based generator when the tracking errors are sufficiently small. In this way, both a high tracking accuracy and fast dynamic response are obtained for constrained robotic manipulator systems with considerably lower computational burden. The superiority and effectiveness of the proposed structure are illustrated through comparative simulations and experiments.
ABSTRACT
This research studies the problem of fault detection observer design for two-dimensional (2-D) continuous-time nonlinear systems in Takagi-Sugeno (T-S) form. Finite frequency (FF) specifications are used to design the observers, which makes observer designing different from previously proposed 2-D detection observers. Faults and disturbances are considered to be dominated in two different FF domain intervals. Fault sensitivity and disturbance robustness are measured by two FF performance indices, respectively. The aim of this paper is to design fault detection observers such that the residual error system has the sensitivity to faults and the desired robustness to disturbances. Sufficient conditions for the existence of a desired fault detection fuzzy observer are established in terms of linear matrix inequalities (LMIs). Simulation results indicate that faults can be detected effectively using the proposed method.
