Finite time command filtered adaptive fuzzy control for a twin roll inclined casting system

This paper, the adaptive fuzzy control problem for finite-time command filtering is studied at the twin roll inclined casting system. An explosion of complexity caused by a differential surge can be avoided by constructing adaptive fuzzy controller combined with command filtering and backstepping schemes. The designed adaptive fuzzy controller ensures simultaneously the stability and tracking performance of the closed-loop system in a limited time, and the tracking error converges in a small neighborhood of the origin. Eventually, a simulation example is given to verify the effectiveness of the proposed scheme

Finite time command filtered adaptive fuzzy control for a twin roll inclined casting system

This paper, the adaptive fuzzy control problem for finite-time command filtering is studied at the twin roll inclined casting system. An explosion of complexity caused by a differential surge can be avoided by constructing adaptive fuzzy controller combined with command filtering and backstepping schemes. The designed adaptive fuzzy controller ensures simultaneously the stability and tracking performance of the closed-loop system in a limited time, and the tracking error converges in a small neighborhood of the origin. Eventually, a simulation example is given to verify the effectiveness of the proposed scheme

Globally Intelligent Adaptive Finite-/Fixed- Time Tracking Control for Strict-Feedback Nonlinear Systems via Composite Learning Approaches

This article focuses on the globally composite adaptive law-based intelligent finite-/fixed- time (FnT/FxT) tracking control issue for a family of uncertain strict-feedback nonlinear systems. First, intelligent approximators with new composite updating laws are developed to model uncertain nonlinear terms, which encompass prediction errors to enhance intelligent approximators' learning behaviors and fewer online learning parameters to diminish computational burden. Then, a novel smooth switching function coupled with robust controllers is designed to pull system states back when the transients are out of the approximators' active domain. After that, a modified FnT/FxT backstepping technique is constructed to render output to follow the reference trajectory, and an adaptive law is employed to alleviate the impact of external disturbances. It is theoretically confirmed that the proposed control strategies ensure globally FnT/FxT boundedness of all the closed-loop variables. Finally, the validity of theoretical results is testified via a simulation case.Comment: 6 pages,12 figure

Unknown dynamics estimator-based output-feedback control for nonlinear pure-feedback systems

Most existing adaptive control designs for nonlinear pure-feedback systems have been derived based on backstepping or dynamic surface control (DSC) methods, requiring full system states to be measurable. The neural networks (NNs) or fuzzy logic systems (FLSs) used to accommodate uncertainties also impose demanding computational cost and sluggish convergence. To address these issues, this paper proposes a new output-feedback control for uncertain pure-feedback systems without using backstepping and function approximator. A coordinate transform is first used to represent the pure-feedback system in a canonical form to evade using the backstepping or DSC scheme. Then the Levant's differentiator is used to reconstruct the unknown states of the derived canonical system. Finally, a new unknown system dynamics estimator with only one tuning parameter is developed to compensate for the lumped unknown dynamics in the feedback control. This leads to an alternative, simple approximation-free control method for pure-feedback systems, where only the system output needs to be measured. The stability of the closed-loop control system, including the unknown dynamics estimator and the feedback control is proved. Comparative simulations and experiments based on a PMSM test-rig are carried out to test and validate the effectiveness of the proposed method

Backstepping with virtual filtered command: Application to a 2D autonomous Vehicle

Through this work a deep understanding of the backstepping control technique is sought when applied over non-affine systems. It is shown that in this case appears the necessity to bound the value of internal states and that a modification over standard backstepping is mandatory. The principal goal of this study is to evaluate the effects of finite frequency filters, and the effects of saturation affecting intermediate states and control actions, in the tracking performance when using the command filtered backstepping. Some relations that bind the controller gains to maintain performance appear naturally. Finally simulations over a 2D steering robot model are given to illustrate the found results.Peer ReviewedPostprint (author’s final draft

Online optimisation-based backstepping control design with application to quadrotor

In backstepping implementation, the derivatives of virtual control signals are required at each step. This study provides a novel way to solve this problem by combining online optimisation with backstepping design in an outer and inner loop manner. The properties of differential flatness and the B-spline polynomial function are exploited to transform the optimal control problem into a computationally efficient form. The optimisation process generates not only the optimised states but also their finite order derivatives which can be used to analytically calculate the derivatives of virtual control signal required in backstepping design. In addition, the online optimisation repeatedly performed in a receding horizon fashion can also realise local motion planning for obstacle avoidance. The stability of the receding horizon control scheme is analysed via Lyapunov method which is guaranteed by adding a parametrised terminal condition in the online optimisation. Numerical simulations and flight experiments of a quadrotor unmanned air vehicle are given to demonstrate the effectiveness of the proposed composite control method

Barrier Lyapunov function-based adaptive fuzzy attitude tracking control for rigid satellite with input delay and output constraint

This paper investigates the adaptive attitude tracking problem for the rigid satellite involving output constraint, input saturation, input time delay, and external disturbance by integrating barrier Lyapunov function (BLF) and prescribed performance control (PPC). In contrast to the existing approaches, the input delay is addressed by Pade approximation, and the actual control input concerning saturation is obtained by utilizing an auxiliary variable that simplifies the controller design with respect to mean value methods or Nussbaum function-based strategies. Due to the implementation of the BLF control, together with an interval notion-based PPC strategy, not only the system output but also the transformed error produced by PPC are constrained. An adaptive fuzzy controller is then constructed and the predesigned constraints for system output and the transformed error will not be violated. In addition, a smooth switch term is imported into the controller such that the finite time convergence for all error variables is guaranteed for a certain case while the singularity problem is avoided. Finally, simulations are provided to show the effectiveness and potential of the proposed new design techniques