Prescribed Performance Tracking Control Research Articles

Robust prescribed performance tracking control for free-floating space manipulators with kinematic and dynamic uncertainty

This paper investigates the task-space prescribed performance tracking control problem of free-floating space manipulators with kinematic and dynamic uncertainty. In order to formulate and solve this prescribed performance tracking problem on SE(3), we first select a suitable tracking error vector and prescribed performance bound which characterizes the minimum convergence rate and maximum overshoot of the tracking error vector. Then, two robust tracking controllers based on the prescribed performance bound are designed to solve the tracking control problem. Compared with the existing work on the guaranteeing prescribed performance control, a linear switching surface is incorporated into the controller design procedure, which makes it easy to cope with kinematic and dynamic uncertainty. A rigorous mathematical stability proof is given. Finally, numerical simulations are presented to demonstrate the effectiveness and robustness of the proposed controller.

Adaptive prescribed performance control of output feedback systems including input unmodeled dynamics

In this paper, an adaptive prescribed performance tracking control scheme is investigated for a class of output feedback nonlinear systems with input unmodeled dynamics based on dynamic surface control method. A transformation with respect to tracking error is introduced to implement prescribed performance tracking control. A novel description based on Lyapunov function for unmodeled dynamics is presented to deal with state unmodeled dynamics. The negative impact of nonlinear input unmodeled dynamics is offset by using a normalization signal. With the aid of Nussbaum function, the unknown control gain sign is effectively handled in the controller design. By the theoretical analysis, not only the signals in the closed-loop system are proved to be semi-globally uniformly ultimately bounded, but also the transient tracking performance can be guaranteed. Two simulation examples are provided to show the effectiveness of the proposed approach.

Adaptive neural prescribed performance tracking control for near space vehicles with input nonlinearity

In this paper, an adaptive neural tracking controller with prescribed performance is developed for near space vehicles (NSVs) with unknown parametric uncertainties, external disturbances and input nonlinearities including input saturation and dead-zone. By placing the right inverse of the dead-zone before the input nonlinearity, the serial input nonlinearity consisting of input saturation and dead-zone can be regarded as an equivalent input saturation which is solved by a common constrained control method. To guarantee the prescribed performance of the closed-loop system including the transient and steady-state performance, the constrained prescribed performance is changed into unconstrained transformation error using error transformed technology. Meanwhile, the radial basis function neural networks (RBFNNs) are adopted to tackle the system uncertainties. Then, using the auxiliary system and backstepping technology, an adaptive tracking control scheme is proposed, and all the closed-loop system signals are proved to be bounded. Finally, extensive simulations are given for the attitude motion of the NSV to illustrate the effectiveness of the developed adaptive neural control scheme.

Observer-based fuzzy adaptive prescribed performance tracking control for nonlinear stochastic systems with input saturation

In this paper, the problem of prescribed performance adaptive fuzzy output feedback control is investigated for a class of single-input and single-output nonlinear stochastic systems with input saturation and unmeasured states. Fuzzy logic systems are used to identify the unknown nonlinear system, the input saturation is approximated by a smooth function, and a fuzzy state observer is designed for estimating the unmeasured states. Based on the backstepping recursive design technique and the predefined performance technique, a new fuzzy adaptive output feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin with the prescribed performance bounds. The simulation example and the comparative results are provided to show the effectiveness of the proposed control approach.