The practical applications of chaotic systems are gaining more dimensions every day. In this paper, a new 3D chaotic system is presented with three nonlinear terms and unique strong chaotic behavior. For the initial evaluation of the behavior of the innovative chaotic system, analyses related to equilibrium points, sensitivity, stability, Lyapunov exponent, and bifurcation have been carried out, and its strong attractor manner has been well shown. The practical realization of the designed system is shown by its circuit implementation through the use of electronic elements and Kirchhoff’s laws. To show the performance of the innovative system in practical applications, first a synchronization technique inspired by non-linear and active approaches has been designed, and then by using the innovative chaotic system in the masking technique, a new information encryption method has been derived. The results obtained from the masking based on the innovative chaotic system and the designed synchronization technique show the high functionality of the derivative encryption method.

This paper indicates the use of explicit nonlinear model predictive control method to prevent and control of compressor surge using extended Greitzer model. To encompass the effects of fast transients, nonlinear extended Greitzer model is considered for modelling and control of the compressor system. This model covers the effects of different parts, especially the compressor system pipeline, as the most important factor in the occurrence and acceleration of the surge. Also, the mathematical description of the flow dynamic of compression system is derived in the presence of close-coupled valve (CCV) as the most commonly used actuator. For controlling the compressor system surge instability, explicit nonlinear model predictive control (NMPC) is applied, whose allows efficient online implementation, significantly enlarges the operating region of the compressor and enhances the authority of the control system. Numerical simulations show that the proposed control system is able to meet the desired specifications in avoiding and active control of surge, in the presence of different types of disturbances occurring along the pipeline. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka. Ovo je primjer sažetka.

This paper presents a new robust predictive controller for a special class of continuous-time non-linear systems with uncertainty. These systems have bounded disturbances with unknown upper bound as well as constraints on input states. The controller is designed in the form of an optimization problem of the ‘worst-case’ objective function over an infinite moving horizon. Through this objective function, constraints and uncertainties can be applied explicitly on the controller design, which guarantees the system stability. Next, LMI tool is used to improve the calculation time and complexity. To do this, in order to find the optimum gain for state-feedback, the optimization problem is solved using LMI method in each time step. Finally, to show the efficiency and effectiveness of the proposed algorithm, a surge phenomenon avoidance problem in centrifugal compressors is solved.

This paper signifies a tube model predictive control for discrete time uncertain nonlinear systems in the presence of bounded disturbances. The problem of obtaining robustness against parametric uncertainty is renewed to the problem of grasping robustness against additional bounded disturbance. The nominal control law is achieved through the same computational burden as that of standard MPC with guaranteed stability. Also, ancillary control law is accomplished by H∞ control approach to stabilize the states despite parametric uncertainty and disturbances. A simulation example is exploited to show the effectiveness and applicability of the method.