Neuro-adaptive cooperative tracking control of unknown higher-order affine nonlinear systems

Distributed adaptive output feedback tracking control for a class of uncertain nonlinear multi-agent systems

“…For a class of first-order nonlinear multi-agent systems, where nonlinear dynamics was emulated by neural networks, Hou et al (2009) studied the leaderless consensus problem, while Das and Lewis (2010) and Cheng et al (2010) considered the leader-following consensus problem. Zhang and Lewis (2012) and El-Ferik et al (2014) extended the result (Das & Lewis, 2010) to the distributed tracking control problem of general higher order nonlinear systems in the Brunovsky form. Zou et al (2013) applied terminal sliding mode and Chebyshev neural networks to solve the consensus tracking control problem for second-order multi-agent systems in the presence of uncertain dynamics and bounded external disturbances.…”

“…Recently, a series of papers (Cheng, Hou, Tan, Lin, & Zhang, 2010;Das & Lewis, 2010;El-Ferik, Qureshi, & Lewis, 2014;Hou, Cheng, & Tan, 2009;Sarand & Karimi, 2016;Wang, Huang, Wen, & Fan, 2014;Zhang & Lewis, 2012;Zou, Kumar, & Hou, 2013 ) addressed the consensus problem of nonlinear multi-agent systems. For a class of first-order nonlinear multi-agent systems, where nonlinear dynamics was emulated by neural networks, Hou et al (2009) studied the leaderless consensus problem, while Das and Lewis (2010) and Cheng et al (2010) considered the leader-following consensus problem.…”

“…(1) In Zhang and Lewis (2012), El-Ferik et al (2014), Zou et al (2013), Wang et al (2014), Shi and Shen (2015) and Sarand and Karimi (2016), distributed controllers were designed based on a very ideal condition that all relative states between itself and its neighbours are directly measured. However, in this paper, the distributed control law design for each agent does not require relative state information and works with only the relative output information between itself and its neighbours.…”

Cooperative tracking for nonlinear multi-agent systems with hybrid time-delayed protocol

“…Delayed-input approach was employed in [19] to convert the consensus of a sampled-data nonlinear multi-agent system to the stability of a delayed nonlinear system. Adaptive cooperative tracking has been investigated for nonlinear multi-agent systems in [20,21].…”

Robust adaptive feedback linearization control for a class of MIMO uncertain nonlinear systems

“…Neural network (NN) has been proven to a powerful and effective method for controlling uncertain nonlinear systems for their abilities in nonlinear approximation, adaptation, generalization and associative memory and is herein the key technology permeating throughout this thesis. The adaptive neural network control (ANNC) has been shown to be one of the most effective methods for controlling the uncertain nonlinear systems [1][2][3][4]. In the ANNC, neural networks are primarily used as on-line approximators for the unknown nonlinearities due to their inherent approximation capabilities.…”