Adaptive Control via Neural Output Feedback for a Class of Nonlinear Discrete-Time Systems in a Nested Interconnected Form

An unknown input multiobserver based on a discrete uncoupled multimodel for uncertain nonlinear systems: Experimental validation on a transesterification reactor

In the present paper, an unknown input multiobserver (UIMO) is designed for the state estimation of uncertain non-linear systems. A discrete decoupled state multimodel is exploited to describe the behavior of non-linear systems. A particular transformation of uncertainties to unknown inputs is considered. The LMI approach is used to establish the convergence conditions of the state estimation error. The efficiency of the proposed strategy is emphasized through an illustrative example and a real time application on a semi-batch reactor that lead to good performance in terms of robustness, convergence speed and precision.

Two New Discrete-Time Neurodynamic Algorithms Applied to Online Future Matrix Inversion With Nonsingular or Sometimes-Singular Coefficient

In this paper, a high-precision general discretization formula using six time instants is first proposed to approximate the first-order derivative. Then, such a formula is studied to discretize two continuous-time neurodynamic models, both of which are derived by applying the neurodynamic approaches based on neural networks (i.e., zeroing neurodynamics and gradient neurodynamics). Originating from the general six-instant discretization (6ID) formula, a specific 6ID formula is further presented. Subsequently, two new discrete-time neurodynamic algorithms, i.e., 6ID-type discrete-time zeroing neurodynamic (DTZN) algorithm and 6ID-type discrete-time gradient neurodynamic (DTGN) algorithm, are proposed and investigated for online future matrix inversion (OFMI). In addition to analyzing the usual nonsingular situation of the coefficient, this paper investigates the sometimes-singular situation of the coefficient for OFMI. Finally, two illustrative numerical examples, including an application to the inverse-kinematic control of a PUMA560 robot manipulator, are provided to show respective characteristics and advantages of the proposed 6ID-type DTZN and DTGN algorithms for OFMI in different situations, where the coefficient matrix to be inverted is always-nonsingular or sometimes-singular during time evolution.

Rotation matrix based finite-time attitude synchronization control for spacecraft with external disturbances

This paper investigates the anti-unwinding finite-time attitude synchronization control problem for Spacecraft formation flying with external disturbances. Two finite-time controllers are designed based on rotation matrix and terminal sliding mode method. By designing a novel sliding mode surface, the first controller is developed when the upper bound of the external disturbances can be exactly known. However, this value is not always available in reality. In addition, the direct use of the upper bound of the external disturbances can result in the chattering problem. For the purpose of overcoming the disadvantage of the first controller, a modified control law is proposed, in which the adaptive law is applied to estimate the unknown value online. Theoretical analysis and numerical simulations are presented to demonstrate the validity of the proposed controllers.