Backstepping is a nonlinear control design tool for underactuated systems. Backstepping is used for output stabilization or tracking using feedback similarly to feedback linearization. In feedback linearization the stabilizing controller is designed entirely for a virtual input which is then mapped back to the physical input by completely canceling nonlinearities. In backstepping the system is ...

This paper presents an adaptive backstepping sliding mode tracking control method for underactuated unmanned surface vehicle. The controller is designed by combining and technology. virtual law used to replace the strategy of position error, transformed into velocity control, which can effectively avoid input saturation singular value problem existing in design traditional law. neural shunt mod...

This paper considers the position tracking problem of a magnetic levitation system in the presence of uncertainties of physical parameters. The dynamic surface control (DSC) technique is modified and applied to the system under study, to overcome the problem of “explosion of terms” associated with the backstepping design procedure. Input-to-state stability (ISS) property is ensured by the robus...

In this paper, a novel one-step backstepping design scheme for an adaptive output feedback control of uncertain nonlinear system with a higher order relative degree and nonparametric uncertainties is proposed. The proposed method can design an output feedback based adaptive controller through a backstepping of only one step even when the controlled system has a higher order relative degree. Cop...

In this paper, a direct adaptive fuzzy tracking control scheme is presented for a class of stochastic uncertain nonlinear systems with unknown dead-zone input. A direct adaptive fuzzy tracking controller is developed by using the backstepping approach. It is proved that the design scheme ensures that all the error variables are bounded in probability while the mean square tracking error becomes...

This paper proposes a high-precision intelligent adaptive backstepping control system (HPIABCS) for the position control of permanent-magnet synchronous motor (PMSM) servo drive. The HPIABCS incorporates an ideal backstepping controller, a dynamic recurrent-fuzzy-wavelet-neural-network (DRFWNN) uncertainty observer and a robust H∞ controller. First, a backstepping position controller is designe...

In this paper, a direct adaptive fuzzy tracking control scheme is presented for a class of stochastic nonaffine uncertain nonlinear systems with unknown dead-zone input. Based on the first-type fuzzy logic system’s online approximation capability, a direct adaptive fuzzy tracking controller is developed by using the backstepping approach. It is proved that the design scheme ensures that all the...

This paper presents a new design of adaptive fuzzy variable structure control to solve the traditional problem of model reference adaptive control (MRAC) for a class of single-input, single-output minimum-phase uncertain nonlinear systems via backstepping. Instead of taking the tedious coordinate transformation and yielding a "hard" high-gain controller, we introduce smooth B-spline-type member...

In this paper, robust adaptive neural network control is investigated for a class of multi-input-multi-output (MIMO) pure-feedback nonlinear system with unknown nonlinearities. The unknown nonlinearities could be come from unmodeled dynamics, modeling errors, or nonlinear time-varying uncertainties. Based on the backstepping design technique and the universal approximation property of the neura...

In this paper, an adaptive backstepping controller is proposed for the position tracking of a mechanical system driven by an induction motor (IM). The mechanical system is a single link fixed on the shaft of the induction motor. The backstepping methodology provides a simpler design procedure for a adaptive control scheme than the model reference adaptive control method, which is demonstrated i...