One of the issues of reliable performance in the power grid is the existence of electromechanical oscillations between interconnected generators. The number of generators participating in each electromechanical oscillation mode and the frequency oscillation depends on the structure and function of the power grid. In this paper, to improve the transient nature of the network and damping electromechanical fluctuations, a decentralized robust adaptive control method based on Dynamic programming has been used to design a stabilizing power system and a complementary static var compensator (SVC) controller. By applying a single line to ground fault in the network, the robustness of the designed control systems is demonstrated. Also, the simulation results of the method used in this paper are compared with controllers whose parameters are adjusted using the PSO algorithm. The simulation results show the superiority of the decentralized robust adaptive control method based on Dynamic programming for the stabilizing design of the power system and the complementary SVC controller. The performance of the control method is tested using the IEEE 16-machine, 68-bus, 5-area is verified with time domain simulation.

A common method for controlling a group of parallel converters in decentralized control strategy structure in an island microgrid, the use is the droop-down characteristics of frequency ω-P and voltage E-Q. However, the problem with using this method is that the reactive power is not properly distributed (in proportion to the capacity of the micronutrients) between the micronutrients, which may lead to overload in the converters. Microgrids may also suffer from Dynamic stability problems such as power fluctuations, which can be increased by switching between active and reactive power control. To avoid this problem, the X / R ratio of transmission lines is an important parameter that should be carefully considered in the design of micronutrient controllers. By linearizing and simplifying conditions, the control system conversion function model becomes a single input-single output system, which is efficient enough to show the relationship between control parameters such as slope of droop characteristics and derivative sentences, virtual impedance, and voltage controllers. Using this model, stability conditions for different parameters are analyzed. Also, to improve power distribution stability, common droop strategies are modified by adjusting the slope as well as adding nonlinear sentence sections. This approach reduces the coupling between active and reactive power control and reduces the dependence of power distribution on grid parameters such as the X / R ratio. To evaluate the reliability of the proposed model, the simulation results in a sample island microgrid in MATLAB software are presented.

This article investigates the problem of simultaneous attitude and vibration control of a flexible spacecraft to perform high precision attitude maneuvers and reduce vibrations caused by the flexible panel excitations in the presence of external disturbances, system uncertainties, and actuator faults. Adaptive integral sliding mode control is used in conjunction with an attitude actuator fault iterative learning observer (based on sliding mode) to develop an active fault tolerant algorithm considering rigid-flexible body Dynamic interactions. The discontinuous structure of fault-tolerant control led to discontinuous commands in the control signal, resulting in chattering. This issue was resolved by introducing an adaptive rule for the sliding surface. Furthermore, the utilization of the sign function in the iterative learning observer for estimating actuator faults has not only enhanced its robustness to external disturbances through a straightforward design, but has also led to a decrease in computing workload. The strain rate feedback control algorithm has been employed with the use of piezoelectric sensor/actuator patches to minimize residual vibrations caused by rigid-flexible body Dynamic interactions and the effect of attitude actuator faults. Lyapunov's law ensures finite-time overall system stability even with fully coupled rigid-flexible nonlinear Dynamics. Numerical simulations demonstrate the performance and advantages of the proposed system compared to other conventional approaches.

A new kind of adaptive Dynamic surface control (DSC) method is proposed in this study to overcome parametric uncertainties of Flexible-Joint (FJ) robots. These uncertainties of FJ robots are transformed into linear expressions of inertial parameters, which are estimated based on the DSC, and the high-order derivatives in DSC are solved by using a first-order filter. The adaptation laws of inertial parameters are designed directly to improve the tracking performance according to the Lyapunov stability analysis. Simulation results of a two-link FJ robot show better tracking accuracy against model parametric uncertainties. The used method does not need the aid of Neural Network (NN); it is simpler and calculates faster than the other adaptive methods.

In this paper, the control problem of a finite-time target tracking for an underactuated autonomous submarine is considered in three-dimensional space in the presence of unknown disturbances caused by waves and ocean currents via Dynamic surface control (DSC) method. At first, computational complexities of the backstepping method are greatly reduced by employing the DSC technique. Next, by designing a finite-time controller, it can be demonstrated that system errors converge to a small region containing the origin in a finite time. An adaptive robust controller is employed to compensate for unknown vehicle parameters and uncertain nonlinearities. The stability of the proposed controller is demonstrated by an analysis based on Lyapunov theory. Finally, the tracking performance of the proposed control scheme is simulated by MATLAB software and its effectiveness is shown as well.

This paper designs an adaptive improved Dynamic surface controller for a class of uncertain nonlinear systems in the presence of input hysteresis and uncertain control direction. It is assumed that nonlinear functions in the system Dynamics and parameters of the input nonlinearity are uncertain. At first, uncertain Dynamics of the system is identified by the fuzzy system as a linear approximator. Then, the proposed improved Dynamic surface controller is designed. In the proposed controller, a Nussbaum-type function is used to deal with the uncertain control direction problem. Also, for eliminating the “explosion of complexity” problem in the backstepping approach and sensitivity to the time constant of the filters in the Dynamic surface control approach, a nonlinear tracking differentiator is used to obtain the virtual inputs derivative. Furthermore, by considering the norm of the adjustable parameters as an adaptive parameter, number of adaptive parameters and consequently computational burden are decreased considerably. Stability analysis of the proposed controller guarantees that all of the closed-loop signals are uniformly ultimately bounded. Also, adaptive laws for online tuning of adjustable parameters are proposed based on the Lyapunov method. Simulation results on two numerical and application examples verify the effectiveness and proper performance of the proposed controller.

In this paper, the trajectory tracking control problem for a team of nonholonomic tractor-trailer wheeled mobile robots has been investigated based on the leader-follower strategy in the presence of structural uncertainties and external disturbances. For this purpose, the kinematic and Dynamic equations of the formation of tractor-trailer robots are presented and leader-follower's model is produced by defining the state error vector at first. Then, a nonlinear disturbance observer is designed by using the formation Dynamic model to estimate and compensate the external disturbance and a new model of the system is obtained. In the following, a finite-time Dynamic surface controller has been designed and presented by considering an observer-based model. The proposed scheme ensures closed-loop signals boundedness and fast convergence of tracking errors in a limited time. Furthermore, the parametric uncertainties are estimated by using a fuzzy adaptive estimator with a great accuracy. Finally, the finite time stability of the closed-loop control system is proved by Lyapunov theory and the effectiveness of proposed algorithm is shown by simulations.

In this paper, a general elastoplastic-damage constitutive model considering the effect of strain rate has been developed. The derivation of this model has been cast into the irreversible thermoDynamics with internal variables within thefundamentals of Continuum Damage Mechanics (CDM). The rate effect has been involved as an additional term intothe plastic yield surface (Dynamic plastic yield surface). Therefore, the plastic surface has been presented in thecategory of Consistency– type model in which the rate of state variables is considered as independent state variables. The damage has been assumed as a tensor type variable and based on the energy equivalence hypothesis the damageevolution has been developed. The proposed model has been validated for both rate-independent and rate-dependentdeformation. For this manner, the generalized trapezoidal stress integration algorithm of the model has been explainedand the model has been implemented into user-defined subroutines (UMAT and VUMAT) in the finite elementprogram ABAQUS. The results of numerical simulation, statically and Dynamically, have been compared to theexperimental results of three aluminum and two steel alloys. Also, the results of simulation for shear and doublenotchedtests have been compared to their experiments. By comparing the predicted results with experimental data, the capability and validity of the model have been verified.

This paper discusses the flight control strategy based on Adaptive Dynamic Inversion (ADI) with two-time-scale separation for airplane. Because of nonlinear behavior of flight Dynamics, the flight control problem is a rather important and complex issue. In addition to traditional methods, e.g., classic controller, Dynamic inversion methods, fuzzy and neural networks have been used. After reviewing these methods, Combination Adaptive Dynamic inversion Method is designed. In this structure, the control system attempts to track the angle of attack, the sideslip angle and the roll angle in wind frame (m, a, b). Six degree-of-freedom nonlinear equations of motion are considered for tracking the input commands. Dynamic inversion technique needs an exact and accurate flight Dynamics, and to avoid this problem, we use an adaptive controller. Two-timescale based system Dynamics are divided into slow outer variables and fast inner variables. Adaptive controller and Dynamic inversion algorithm are used in inner and outer loops, respectively. The performance of the proposed method compares with Full Dynamic Inversion (DI) method. Simulation results demonstrated the efficacy of Adaptive Dynamic Inversion controller.

This paper deals with the modeling and control of a continuous-How fermentation process for the production of alcohol The Dynamic behavior of fermentors has been developed from mass balance and leads to nonlinear differential equations. Based on the proposed model, two computer algorithms are provided to control output alcohol concentration at the desired value by input flow rate manipulation. The first algorithm is based on a conventional PID (Proportional-Integral-Derivative), in which its parameters are determined in a trial and error procedure. The second algorithm is based on optimal controllers. In this way, the difference between output alcohol concentration and desired value is minimized by flow rate manipulation. Minimization (optimization) is done based on the MARQUARDT procedure. The advantages of this method over the conventional PID controller are its higher speed and lack of overshoot.