Chaotic Analysis of Fractional-Order Permanent Magnet Synchronous Generator for Wind Turbine

Fractional-order wind turbine is a strongly coupled non-linear dynamic system. It mainly studies the significant chaos characteristics such as the complex chaotic motion with fractional order varying. According to the mathematical model of the system, the fractional order Lorenz chaotic equation is established by linear affine transformation and time scale transformation. The theory of Lyapunov stability analysis is adopted to deeply study the development process of the system from stable operation to chaotic motion. The correctness of the chaos characteristics of the system is verified.

Synthesis of an Improved Fast Terminal Sliding Mode Controller for Opto-Electronic Observatory in Mobile Vehicle

The paper presents a method of synthesizing the Variable Structure Controller (VSC) based on the Fast Terminal Sliding Mode (FTSM) control for an optoelectronic observatory to eliminate the effects of the vibration and the change of vehicle’s direction. An improved fast terminal sliding surface and a fuzzy saturation function have been proposed to develop the improved fast terminal sliding mode variable structure controller (IFTSM-VSC). Based on the theory of Lyapunov stability, the article has proved that the IFTSM-VSC controller ensures the Line of Sight (LOS) stabilization of the observation devices and ensures the tracking errors converge to zero in finite time. The simulation uses data about the vibration and navigation of the vehicle recorded on some streets and roads. Simulation results in Matlab/Simulink show the effectiveness of the IFTSM-VSC controller.

Improved Control of the Web Winding System Based on a Super-Twisting Observer

The web winding system (WWS) presents a difficult problem at the level of control because of the strong nonlinearities of the models and the effects of internal or external disturbances. To improve the dynamic performance and robustness of the control of WWS, a robust control method based on the first and second order sliding mode algorithm is proposed in this work. The stability of the controllers is proved by the theory of Lyapunov stability using an appropriate switching function. In addition, an observer of super twisting tensions is suggested. The developed method allows a direct estimate "on line" of the tension. Finally, computer simulations are developed to show the performance of the sliding mode control and the proposed nonlinear observer

High gain feedback robust control for flocking of multi-agents system

This paper focuses on the detailed illustration over the feedback robust control of high gain for flocking of the multi-agent system. As for the second-order unknown bounded nonlinear dynamic system, the designed controller has feedback robust control of high gain. Under the action of the leader, the flocking of the multi-agent system established on the basis of high gain feedback robust control can be realized. By employing the theory of Lyapunov stability, it is observed that the velocity error between agents approaches to zero, and no collision occurs between agents. It is further proved by the simulation that the high gain feedback robust control for flocking of multi-agent system can be obtained accordingly. Compared with Qing et al. (2014), high gain feedback robust control for flocking of multi-agent system has better stability.

Force control of an uncertain series elastic actuator system via a fuzzy sliding mode controller and a nonlinear state estimator

Nowadays, series elastic actuators play an important role in actuation technology, especially for mechatronics and robotic applications. In this article, the accurate tracking of output force for a series elastic actuator is investigated. In order to achieve this aim, a novel robust control scheme is developed to overcome friction effects, backlash in the drivetrain, measurement noises (sensor inaccuracy) and uncertainties in the dynamic model. The control scheme consists of a fuzzy sliding mode controller and a nonlinear state estimator. The theory of Lyapunov stability is used for the formulation of the proposed controller and also the fuzzy logic strategy is used for tuning the sliding surface parameter in order to achieve accurate and chattering-free performance. Furthermore, a powerful estimator algorithm, unscented H-infinity filter, is added to the control scheme to improve the robustness of the system. Simulation results, as well as experimental analysis, approved the efficiency of the proposed approach in the presence of uncertainties and disturbances.

Adaptive Fuzzy Sliding Mode Control for a Class of Nonlinear Dynamical Systems

This paper presents a FBFN-based (Fuzzy Basis Function Networks) adaptive sliding mode control algorithm for nonlinear dynamic systems. Firstly, we designed an perfect control law according to the nominal plant. However, there always exists discrepancy between nominal and actual mode, and the FBFN was applied to approximate the uncertainty. After that, the adaptive law was designed to update the parameters of FBFN to alleviate the approximating errors. Based on the theory of Lyapunov stability, the stability of the adaptive controller was given with a sufficient condition. Simulation example was also given to illustrate the effectiveness of the method.