Multilayer feedforward networks are universal approximators
Neural Networks
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Brief paper: On the V-stability of complex dynamical networks
Automatica (Journal of IFAC)
Brief paper: Distributed nonlinear control algorithms for network consensus
Automatica (Journal of IFAC)
Brief paper: On pinning synchronization of complex dynamical networks
Automatica (Journal of IFAC)
Cooperative Control of Dynamical Systems: Applications to Autonomous Vehicles
Cooperative Control of Dynamical Systems: Applications to Autonomous Vehicles
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Automatica (Journal of IFAC)
Multilayer neural-net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
Adaptive neural control of uncertain MIMO nonlinear systems
IEEE Transactions on Neural Networks
Adaptive cooperative tracking control of higher-order nonlinear systems with unknown dynamics
Automatica (Journal of IFAC)
Adaptive consensus of multi-agents in networks with jointly connected topologies
Automatica (Journal of IFAC)
Quasi-synchronization of delayed coupled networks with non-identical discontinuous nodes
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Robust cooperative tracking for multiple non-identical second-order nonlinear systems
Automatica (Journal of IFAC)
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
Robust control for a specific class of non-minimum phase dynamical networks
Journal of Computer and Systems Sciences International
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This paper is concerned with synchronization of distributed node dynamics to a prescribed target or control node dynamics. A design method is presented for adaptive synchronization controllers for distributed systems having non-identical unknown nonlinear dynamics, and for a target dynamics to be tracked that is also nonlinear and unknown. The development is for strongly connected digraph communication structures. A Lyapunov technique is presented for designing a robust adaptive synchronization control protocol. The proper selection of the Lyapunov function is the key to ensuring that the resulting control laws thus found are implementable in a distributed fashion. Lyapunov functions are defined in terms of a local neighborhood tracking synchronization error and the Frobenius norm. The resulting protocol consists of a linear protocol and a nonlinear control term with adaptive update law at each node. Singular value analysis is used. It is shown that the singular values of certain key matrices are intimately related to structural properties of the graph.