Robust Adaptive Backstepping Control Research Articles

Indirect adaptive tracking control of a nonholonomic mobile robot via neural networks

This paper presents the design and implementation of a novel adaptive trajectory tracking controller for a nonholonomic wheeled mobile robot (WMR) with unknown parameters and uncertain dynamics. The learning ability of neural networks is used to design a robust adaptive backstepping controller that does not require the knowledge of the robot dynamics. The kinematic controller gains are tuned on-line to minimize the velocity error and improve the trajectory tracking characteristics. The performance of the proposed control algorithm is verified and compared with the classical backstepping controller through simulation and experiments on a commercial mobile robot platform.

Robust adaptive backstepping control for a class of uncertain nonlinear systems based on disturbance observers

In this paper, a novel robust adaptive control scheme for a class of uncertain nonlinear systems is proposed using disturbance observer and backstepping method. Firstly, a disturbance observer is developed using radial basis function (RBF) neural network. The parameter updated law of the RBF neural network is given for monitoring subsystem disturbance well. The robust adaptive control scheme is then presented with backstepping method based on the designed disturbance observer. Semiglobal uniform ultimate boundedness (SGUUB) of all signals in the closed-loop uncertain nonlinear system is achieved. The closed-loop system stability analysis shows that semiglobal uniform boundedness of all signals is guaranteed by appropriately choosing design parameters. Finally, two examples are taken to illustrate the effectiveness of the proposed control scheme.

ADAPTIVE BACKSTEPPING CONTROL OF A PIEZO-POSITIONING MECHANISM WITH HYSTERESIS

Piezo-positioning mechanisms are often used in high-precision positioning applications. Due to their materials, nonlinear hysteretic behavior is commonly observed in such mechanisms and can be described by a LuGre model. In this paper, we develop two robust adaptive backstepping control algorithms for piezo-positioning mechanisms. In the first scheme, we take the structure of the LuGre model into account in the controller design, if the parameters of the model are known. A nonlinear observer is designed to estimate the hysteresis force. In the second scheme, there is no apriori information required from these parameters and thus they can be allowed totally uncertain. In this case, the LuGre model is divided into two parts. While the unknown parameters of one part are incorporated with unknown system parameters for estimation, the effect of the other part is treated as a bounded disturbance. An update law is used to estimate the bound involving this partial hysteresis effect and the external load. For both schemes, it is shown that not only global stability is guaranteed by the proposed controller, but also both transient and asymptotic performances are quantified as explicit functions of the design parameters so that designers can tune the design parameters in an explicit way to obtain the required closed loop behavior.

3749 ロバスト適応バックステッピング制御の磁気浮上システムへの適用(G10-3 運動および振動の制御,G10 機械力学・計測制御)

It is very important to confirm the robust performance of the existing control scheme through experiments because several problems which might not satisfy the assumptions imposed on the controlled system are in hiding in practical applications. In this paper, we verify the effectiveness of the proposed robust adaptive backstepping control through experiment of a magnetic levitation system with uncertain nonlinearities.

Adaptive Backstepping Control of a Class of Uncertain Nonlinear Systems With Unknown Backlash-Like Hysteresis

In this note, we consider the same class of systems as in a previous paper, i.e., a class of uncertain dynamic nonlinear systems preceded by unknown backlash-like hysteresis nonlinearities, where the hysteresis is modeled by a differential equation, in the presence of bounded external disturbances. By using backstepping technique, robust adaptive backstepping control algorithms are developed. Unlike some existing control schemes for systems with hysteresis, the developed backstepping controllers do not require the uncertain parameters within known intervals. Also, no knowledge is assumed on the bound of the disturbance-like term, a combination of the external disturbances and a term separated from the hysteresis model. It is shown that the proposed controllers not only can guarantee global stability, but also transient performance.

Robust Adaptive Backstepping Control Based on High-Gain Feedback and Its Application to a CSTR Control

In this paper, we propose a robust adaptive control for uncertain nonlinear systems via backstepping procedure based on high gain feedback strategy. It is shown that one can design a stable adaptive control system provided that the uncertain nonlinearities can be evaluated by an unknown constant and a known nonlinear function which give upper bounds of uncertainties. The effectiveness of the proposed methods is demonstrated by a simulation for a CSTR model.