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This paper concentrates on synthesizing robust predictive controllers in uncertain models with time‐delay and saturated input. To handle the complexities simultaneously and reach the desired objective, a state‐feedback structure with unknown gains is considered the compensator. Then, to specify the instantaneous values of the regulator's gains, an optimization issue will be derived relying on linear matrix inequality. Accordingly, in uncertain continuous‐time systems with some constraints and time‐delays, the controller's coefficients would be found in an online way from such an optimization. Numerous continuous‐time simulations are numerically performed to reveal the merit and robustness of the suggested methodology over similar techniques. [ABSTRACT FROM AUTHOR]

Robust regulation is predictively investigated in time-delay models including uncertainties, non-zero reference, and disturbance. Hence, to handle the complexities induced because of the time-delays, disturbances, and uncertainties, enhancing the transient performance would be a main control goal. To this purpose, the required transient and steady-state specifications are achieved through an integral control structure with adjustable gains. The constraints on the signals and aims of the control algorithm are also described by some linear matrix inequalities. Guaranteeing the stability, a minimisation procedure is found to specify the predictive controller. Several simulations are performed to establish the effectiveness of the introduced plan in comparison with the similar strategy. [ABSTRACT FROM AUTHOR]

Reference regulation of uncertain systems is investigated in the discrete-time case. Hence, including the uncertainties and constraints, through a prediction-based controller, the set-point following will be robustly fulfilled in a class of uncertain systems. A novel idea is addressed to achieve this goal optimally. Thus the control synthesis is deliberately transformed into an optimisation issue subjected to some matrix inequality. In the real-time implementation, the controller's parameters would be obtained when a minimisation problem is solved. The applicability of the method is evaluated in some examples. The superiority and robustness of the suggested procedure are remarkably validated by comparing it with a similar one. [ABSTRACT FROM AUTHOR]

In this research, based on the integral sliding-mode scheme, a robust composite nonlinear feedback (CNF) control is addressed for time-delayed uncertain systems. Such an uncertain system may contain some complexities like time-varying delays, actuators saturation, and exterior disturbances. Hence, the tracking problem would be solved under the mentioned constraints. Thus, for achieving these goals, the tracking problem is firstly formulated by considering system's limitations. The controller parameters may be determined via a solution for linear matrix inequality. As a result, the CNF tracker law is numerically simulated in some control cases. The simulation outcomes are compared with a similar technique in terms of the transient response, boundedness of the error, and the disturbance rejections. Thus, the findings illustrate the efficiency of the advised CNF control method comparing to the recent technique. [ABSTRACT FROM AUTHOR]

The transient response improvement is the most crucial feature of the composite nonlinear feedback (CNF) controllers. This study proposes a novel CNF tuning method for systems subject to saturation. To achieve the goals, the linear part is optimally obtained via a performance index and the linear matrix inequality (LMI). Then, employing the passivity property, a heuristic way is suggested to adjust the nonlinear term. Thus, the automatic and online features would be the key novelties of this algorithm compared with the offline, trial and error, or nonautomatic ones. Some systems are simulated to evaluate the technique and compare with the existing methods. The outcomes confirm that the proposed tuning yields outstanding improvement concerning the aforementioned systems. [ABSTRACT FROM AUTHOR]

The main focus of this research is on improving the performance of dynamic systems with actuator non‐linearities and time‐varying disturbances. To this end, using the concept of finite‐time stability, a novel observer is presented to estimate the disturbances in systems with input non‐linearities. Then, introducing an innovative sliding manifold, a robust observer‐based technique is derived to guarantee the finite‐time stability of the sliding surface. Hence, the closed‐loop system would be stable in the presence of hard non‐linearities and time‐varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. [ABSTRACT FROM AUTHOR]

The Lyapunov stability theory has been a well-known and powerful method for justifying the solution property and also stability analysis of an equilibrium point in the nonlinear systems. The stability notions may usually be expressed in terms of some norm functions in the conventional Lyapunov stability theory. In this paper, the boundedness and stability concepts would been investigated within a defined set instead of the equilibrium point. Then, based on the measure functions concept, the boundedness and also stability properties of the solution will be extended to develop a modified stability theory in the nonlinear systems. [ABSTRACT FROM AUTHOR]