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A new multiobjective power control algorithm is presented in this paper in which power update is accomplished using local information. The algorithm benefits a multiobjective optimization technique the objectives of which are designed in a way to not only minimize the users’ transmit power but also maintain the users’ SIR at an acceptable level, on one hand, and reduce as much possible the SIR fluctuations, on the other hand. The convergence characteristics of the proposed method are investigated both theoretically and with simulations. The results indicates that, compared to other existing power control algorithms, the proposed algorithm has a higher convergence speed while reducing user’s transmit power. Introducing the practical version of the proposed algorithm, it is then compared with two existing algorithms including B-BPSC (FSPC) and MOTDPC. Simulation results show significant improvements in the convergence speed and average consumed power.

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Electromagnetic suspension technology has been developed in recent years due to advantages such as no contact and reduced friction. Of course, ensuring efficiency in these systems requires precise control of the position of the suspended object. Therefore, electromagnetic suspension is considered as a process by control engineers. The dynamics of electromagnetic suspension systems is nonlinear and also include model and parametric uncertainties such as the weight of the suspended object. In this paper, a finite time nonlinear hybrid method is used to stabilize the electromagnetic suspension system. Proof of finite time stability of the proposed method is performed using Lyapunov theory and a relation for calculating the convergence time depends on the controller gains is presented. To ensure the finite time convergence of the system state and output variables, the backstepping algorithm is used and in each step, the finite-time convergence theory is used. The controller designed in this paper is compared with the backsteping method and the superiority of the proposed method in various simulations is shown.

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In this paper, a new adaptive controller based on the barrier function is designed for high-order nonlinear systems with uncertainties in mind. Accordingly, this paper uses a sliding mode controller that can simultaneously create asymptotic convergence and deal with perturbations. The main problems controlling the slip mode can be considered asymptotic convergence, umbrella phenomenon, stimulus saturation, control gain estimation and failure to deal with time-varying uncertainties. In this paper, the terminal slip mode controller is used to deal with the phenomenon of asymptotic convergence and umbrella and the barrier function is used to overcome the uncertainties of time variable. The advantages of the proposed method include the elimination of the Chattering phenomenon, convergence in finite time, compatibility with time-varying uncertainties, no use of estimates and no need for information on the high limit of perturbations. Stability analysis shows that in the proposed controller, the tracking errors approach the convergence region in the zero range and provide faster convergence. Finally, to prove the efficiency of the controller, based on the chaos synchronization theory, we apply the proposed controller to a new 5D hyperchaotic system. The results show that the proposed controller, despite the disturbances applied to the system, provides rapid convergence and eliminates the umbrella phenomenon.