Robust ultimately boundedness control of uncertain delayed systems under time-varying reference and external disturbance.

In the set-point following, the asymptotic property of the stability would disappear in the presence of time-varying references and disturbances. Hence, the boundedness of state variables is an essential issue in the regulation. To this aim, in light of time-varying references and disturbed signals, a robust integral policy is systematically developed to achieve the control aim in the uncertain equations with delay. Utilizing linear matrix inequality, a guideline is suggested for guaranteeing the boundedness of the solutions in uncertain systems with delays. Then, the gains of the control law are computed from a minimization. Although the boundedness is ultimately obtained in the perturbed case, the asymptotic stability would also be deduced for the nominal systems. The findings are numerically evaluated in some simulations. The favorability of the proposed integral method is shown in comparison to the traditional control strategies.

Robust tracking composite nonlinear feedback controller design for time-delay uncertain systems in the presence of input saturation.

In this study, a robust control technique is investigated for the reference tracking of uncertain time-delayed systems in the existence of the actuator saturation. Due to emerging of some control complexities, as well as the input limitations, time-varying delay, uncertainty, and external disturbance, such a tracking goal would be realized through suitable design of the composite nonlinear feedback (CNF) controller. Thus, considering the mentioned limitations, a Lyapunov-based procedure is used to determine the control law. Then, the parameters of the CNF input are derived by using the solution of a linear matrix inequality (LMI) problem. The planned tracking idea is numerically implemented in two uncertain control systems. Some performance characteristics (i.e., the tracking error, boundedness, and transient responses) are compared with similar ones. Accordingly, the simulations illustrate the efficiency of the suggested control procedure over the existing CNF approaches.

A model predictive scheme to integral controller design for uncertain LTI systems with nonzero reference.

A model predictive method is developed to tune an integral controller for uncertain systems subjected to constrained input signals. For this purpose, a stabilizing integral controller is firstly designed for linear time-invariant (LTI) systems with polytopic uncertainty. The integral controller gains can be determined via a feasible solution of a linear matrix inequality (LMI). Then, a predictive control is incorporated into the integral controller synthesis through an optimization problem subjected to some LMI constraints. The suggested control is successfully applied to a typical uncertain system and an uncertain chemical reactor. The effectiveness of the proposed technique will be shown in comparison with other control methods.