This study presents a robust nonsingular terminal sliding-mode control (RNTSMC) system to achieve finite time tracking control (FTTC) for the rotor position in the axial direction of a nonlinear thrust active magnetic bearing (TAMB) system. Compared with conventional sliding-mode control (SMC) with linear sliding surface, terminal sliding-mode control (TSMC) with nonlinear terminal sliding surface provides faster, finite time convergence, and higher control precision. In this study, first, the operating principles and dynamic model of the TAMB system using a linearized electromagnetic force model are introduced. Then, the TSMC system is designed for the TAMB to achieve FTTC. Moreover, in order to overcome the singularity problem of the TSMC, a nonsingular terminal sliding-mode control (NTSMC) system is proposed. Furthermore, since the control characteristics of the TAMB are highly nonlinear and time-varying, the RNTSMC system with a recurrent Hermite neural network (RHNN) uncertainty estimator is proposed to improve the control performance and increase the robustness of the TAMB control system. Using the proposed RNTSMC system, the bound of the lumped uncertainty of the TAMB is not required to be known in advance. Finally, some experimental results for the tracking of various reference trajectories demonstrate the validity of the proposed RNTSMC for practical TAMB applications.
"Answering this question will significantly enrich the control theory of the offshore platform, which is the second motivation of this paper. Since sliding mode control is an efficient control method to enhance the system robustness against parameter perturbations and unmodeled dynamic uncertainties , , it has a wide range of applications in various areas, such as micromanipulator , magnetic bearing systems , offshore container crane , and offshore platforms . In this paper, we develop a novel sliding mode control scheme for an offshore steel jacket platform subjected to nonlinear self-excited wave force and parameter perturbations. "
[Show abstract][Hide abstract] ABSTRACT: This paper is concerned with active control for an offshore steel jacket platform subjected to wave-induced force and parameter perturbations. An uncertain dynamic model for the offshore platform is first established, where uncertainties not only on the natural frequency and the damping ratio of both the offshore platform and the active tuned mass damper (TMD) but also on the damping and stiffness of the TMD are considered. Then, by intentionally introducing a proper time delay into the control channel, a novel sliding mode control scheme is proposed. This scheme uses information about mixed current and delayed states. It is shown through simulation results that this scheme is more effective in both improving the control performance and reducing control force of the offshore platform than some existing ones, such as delay-free sliding mode control, nonlinear control, dynamic output feedback control, and delayed dynamic output feedback control. Furthermore, it is shown that the introduced time delay in this scheme can take values in different ranges while the corresponding control performance of the offshore platform is almost at the same level.
IEEE Transactions on Control Systems Technology 09/2014; 22(5):1769-1783. DOI:10.1109/TCST.2013.2293401 · 2.47 Impact Factor
"A continuous finite-time control scheme for rigid robotic manipulators using a new form of terminal sliding modes was proposed in . For the sake of achieving finite-time tracking control for the rotor position in the axial direction of a nonlinear thrust active magnetic bearing system, the robust non-singular TSMC was given in . However, the conventional TSMC methods are not the best in the convergence time, the primary reason is that the convergence speed of the nonlinear sliding mode is slower than the linear sliding mode when the state variables are close to the equilibrium points. "
[Show abstract][Hide abstract] ABSTRACT: A synthesis control method is proposed to perform the position and attitude tracking control of the dynamical model of a small quadrotor unmanned aerial vehicle (UAV), where the dynamical model is underactuated, highly-coupled and nonlinear. Firstly, the dynamical model is divided into a fully actuated subsystem and an underactuated subsystem. Secondly, a controller of the fully actuated subsystem is designed through a novel robust terminal sliding mode control (TSMC) algorithm, which is utilized to guarantee all state variables converge to their desired values in short time, the convergence time is so small that the state variables are acted as time invariants in the underactuated subsystem, and, a controller of the underactuated subsystem is designed via sliding mode control (SMC), in addition, the stabilities of the subsystems are demonstrated by Lyapunov theory, respectively. Lastly, in order to demonstrate the robustness of the proposed control method, the aerodynamic forces and moments and air drag taken as external disturbances are taken into account, the obtained simulation results show that the synthesis control method has good performance in terms of position and attitude tracking when faced with external disturbances.
ISA Transactions 05/2014; 53(3). DOI:10.1016/j.isatra.2014.01.004 · 2.98 Impact Factor
"In addition, AMBs being very fast electromagnetic devices, major realtime constraints have to be considered when designing an appropriate control system. Control of magnetic levitation systems, are the subject of numerous publications owing to their industrial importance (see e.g –, , , –, , , ), which rely on a wide array of modern control techniques. What makes this control problem hard stems mainly from its complex model. "
[Show abstract][Hide abstract] ABSTRACT: The newly introduced model-free control is applied to the stabilization of an active magnetic bearing, which is a most important industrial device. Experimental results are compared to those obtained via other control techniques, showing at least on-par performance with this very straightforward approach, which is moreover quite easy to implement.
52nd IEEE Conference on Decision and Control, Florence, Italie; 12/2013
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