In this article, a novel control algorithm is developed for a class of nonlinear stochastic systems subject to multiple disturbances, including exogenous dynamic disturbance and general non-Gaussian noise. An observer is designed to estimate the exog...
A hybrid model integrating chaos theory, support vector machine (SVM) and the difference evolution grey wolf optimization (DEGWO) algorithm is developed to analyze and predict dam deformation. Firstly, the chaotic characteristics of the dam deformati...
This paper introduces a novel robust adaptive fault detection and diagnosis (FDD) observer design approach for a class of nonlinear systems with parametric uncertainty, unknown system fault and time-varying internal delays. The conditions for the exi...
Neural networks : the official journal of the International Neural Network Society
May 28, 2022
This paper investigates an adaptive 2-bits-triggered neural control for a class of uncertain nonlinear multi-agent systems (MASs) with full state constraints. Considering the limitations of practical physical devices and operating conditions, MASs ma...
Journal of tissue engineering and regenerative medicine
May 27, 2022
Utilizing recent advances in human induced pluripotent stem cell (hiPSC) technology, nonlinear analysis and machine learning we can create novel tools to evaluate drug-induced cardiotoxicity on human cardiomyocytes. With cardiovascular disease remain...
This paper, with the adaptive backstepping technique, presents a novel fixed-time neural networks leader-follower consensus tracking control scheme for a class of nonaffine nonlinear multiagent systems. The expression of the error system is derived, ...
This article presents an improved guidance law for underactuated marine vessels that compensates cross-track error caused by external disturbances through its sideslip. The proposed guidance law demonstrates improved path-following performance regard...
This article proposes an adaptive neural-network control scheme for a rigid manipulator with input saturation, full-order state constraint, and unmodeled dynamics. An adaptive law is presented to reduce the adverse effect arising from input saturatio...
In this article, direct adaptive actuator failure compensation control is investigated for a class of noncanonical neural-network nonlinear systems whose relative degrees are implicit and parameters are unknown. Both the state tracking and output tra...
This article investigates the asymptotic tracking control problem for full-state-constrained nonlinear systems with unknown time-varying powers. By introducing a nonlinear state-dependent transformation, a continuous bounded scalar function, and lowe...