In this paper, formation control based on the virtual structure for the non-holonomic mobile robot system with two models of certain and uncertain kinematic equations is discussed. First, the formation equations of a certain model are calculated and then it is proved that it is possible to create a geometric shape and maintain that state by using the sliding model control theory for any two moving mobile robots. Then, after deriving the formation equations of the uncertain model, a sliding model controller is designed that is able to control the uncertain model provided that the uncertainty range of the kinematic equation is present. For each design, the stability of the system is guaranteed using the Lyapunov stability theorem. Finally, in order to compare the performance of the designed controllers, a pre-designed back-stepping controller is introduced and the results will be presented in the form of simulations. The simulation results show the effective performance of the designed controllers.

In this paper, a fractional order backstepping type of fast terminal sliding mode controller is proposed for controlling a micro-electro-mechanical triaxial gyroscope with parameter uncertainty and internal and external disturbances. To compensate uncertainties and also incoming disturbances to the system used combination of sliding mode and backstepping robust nonlinear controllers. In the proposed approach, the sliding surface is selected in the form of fractional order. To increase the speed of convergence the system states to equilibrium points or the error to zero, the fast terminal sliding mode controller is used. The globally stability of the closed loop system will prove by Lyapunov stability theorem. Also in addition to the above proposal controller, a fractional order backstepping sliding mode controller designed and implemented for the gyroscope system. In order to evaluate the performance of designed controllers, these controllers compared with backstepping sliding mode controller and the backstepping fast terminal sliding mode controller. The results shown that the proposed controller has a faster transient response than the other controllers. Another advantage of the proposed controller is simplicity designed and implemented, increase system stability and acceptable tracking than the other controllers. Also unlike the other two controllers the chattering phenomenon completely removed in the fractional order designed controllers.

In this paper, a dynamic sliding mode controller with fractional order sliding surface based on backstepping algorithm is designed and presented for controlling performance of a micro-electro-mechanical triaxial gyroscope. To compensate uncertainties and incoming disturbances to the system, a sliding mode controller is used. In order to increase the degree of freedom and further robustness of the controller, the sliding surface is selected as fractional order form. Using dynamic sliding mode controller in addition to the increasing the performance of controller, cause to reduce the chattering phenomenon in the input control signal. Using the backstepping approach as a very powerful design tool for nonlinear systems, makes the designed controller more robust against incoming disturbances to the system. Asymptotic stability of the closed loop system will be proven by Lyapunov stability theorem. At the end of the design, in order to efficacious reduce the chattering phenomenon in the control signal, fuzzy control theory for control the boundary layer and also adaptive method for online estimating the upper bound of uncertainty are used. In order to evaluate performance of the designed controller, this controller is compared with two other sliding mode controllers. Simulation results show that the proposed controller have a much less chattering phenomenon in control signal, increasing system stability, reducing the rise time and better tracking.

In this paper, an intelligent neural network controller is designed that can balance a quadrotor. After comparing the two types of independent reverse controllers and PID in the simulation environment, their differences are stored as data in the software. By specifying the input data of the controller and the target data and using the feedforward neural network architecture and a Narx architecture, intelligent controllers are designed and the obtained results are shown in several stability detection diagrams. The obtained results show that the equilibrium and vertical flight control are quite acceptable. Finally, the results are tested in a practical model on a real vertical plane. In the practical model, due to the limited amount of training data, the performance of Narx network is much more appropriate than the performance of the feed network. In fact, the complexity of the Narx recursion algorithm helps to interpret the complex dynamic behavior of the system well despite the low data. The disadvantage of this type of network is its very complex hardware implementation, which requires a much more powerful processor and memory to run on the controllers.

This paper compares spacecraft attitude control in the presence of disturbance torque using an adaptive backstepping controller and an extended state observer-based backstepping controller. Firstly, the adaptive backstepping controller is designed, in which the unknown parameters in a specific disturbance model are estimated using an adaptive law so that the closed-loop system is stable. Afterward, the backstepping control based on the extended state observer is designed. In this approach, the standard backstepping controller is initially designed, and then disturbances with a completely unknown model are estimated by the extended state observer, and the disturbance is rejected by applying the feed-forward law. The simulation results for two different disturbance models show that the backstepping controller based on the extended state observer demonstrates very good results compared to the adaptive backstepping controller when no disturbance information is available. This is for the reason that the extended state observer estimates the uncertainties more accurately.

The present paper proves chaos phenomenon for a range of parameters in attitude dynamic of a satellite and designs an appropriate nonlinear controller, while ensuring optimal system performance, the controller guarantees control of a chaotic state. As the dynamic equations of a three-axis satellite are defined as a nonlinear non-autonomous system, a technique is offered for calculating the Lyapunov exponents of such systems that may express the system’s chaotic state. Using the technique, the chaotic behavior of a system is proved within a range of parameters. Then a back-stepping sliding mode controller is proposed based on the desired performance and the closed-loop system stability is proved based on the Lyapunov’s theorem. Moreover, converting the system into a compatible form with the conditions of the Melnikov theorem using this analytical method ensures removing chaos phenomenon in the controlled system. Calculating Lyapunov exponents of the closed system confirms this issue. Finally, the simulation results obtained from the proposed controlling actions for different work fields are presented

Al-Ahmad as acritical thinker that attitude critical view and attention to the selfish identity challanged the West and the Westernization and ultimately rejecting it, expressed the idea of "Return to the Self". Al-Ahmad for the treatment of retardation and release of the community from domination of the West, points its attention to two important factors: internal and external. retardation and Gharbzadegi (infatuation with the West) in his thought imphy process in different political, economic, social and cultural aspects. Accordingly, he, on the one hand attends to the problem of Gharbzadegi (infatuation with the West) and on the other hand to the problem of Intellectual. "Return to the Self" is his solution for the treatment of illness of retardation and escape from the problems of society. Return to Self means return to system of values, culture, relgion and idea of self: Islam. Consequently, he wants to reform of intellectual and clergy and come these to the scene and creating links between the two main intellectual agents in Iranian society.

In this paper, an intelligent integral Back-step controller is used to control the position of the quadrotor. Using a new strong particle swarm optimization algorithm, the optimal system response is Achieved by changing constant design values in the controller. Then, the optimal path for the quadrotor is designed using the algorithmic method of particle swarm and considering the predetermined obstacles in the three-dimensional environment, which ensures safety flight. Also, the shortest path between the origin and destination as the optimal path is determined. Finally, the path generated by the algorithm as the optimal path of planning. Thus, in addition to optimizing the control parameters in the controller, the quadrotor path is also optimized using the algorithm to minimize energy consumption from source to destination. Finally, by simulating the system in MATLAB environment, the system response to the desired input in a limited time was plotted and investigated.

This paper examines the various methods of applying no slip boundary condition on a fixed and rotary cylinder in the lattice Boltzmann framework. For this purpose, five methods of bounce back, LYMLS, QYMLS, LBFL and QBFL are chosen. The main challenge in all of these methods is how to calculate and interpolate the unknown distribution functions at the points around the boundary points. Results show that in the stable conditions (Re=20 and Re=40), the maximum error of calculation of the separation angle is 6.7 % and it is related to the bounce back method, while in the stable conditions, a significant difference cannot be seen between the bounce back and other methods. Also, the LBFL method has the most error in calculating the separation length (6% for Re=20 and 8.82 % for Re=40). By increasing the Reynolds number and increasing the rotational velocity, the bounce back method differs in the prediction of the lift and drag coefficients respect to other methods; so that there is a difference in the lift coefficient in the early times, t*> 7.78 for the conditions of k=0.2 and Re=200, between the bounce back and other methods, however with increasing time, this difference reduces, whereas the three methods of LYMLS, LBFL and QYMLS continue to produce similar results. Investigations show that the choice of the single release time τ has a serious effect on the convergence of the stated methods, so that the two methods of the QYMLS and QBFL have a smaller convergence limit.