Stabilization of Discrete-Time Interconnected Systems Under Control Constraints

Decentralized state feedback and near optimal adaptive neural network control of interconnected nonlinear discrete-time systems

“…Let the unknown nonlinearities in each subsystem be approximated by a NN whose weight update is provided by (9). Then there exist a set of control gains i K and filtered error coefficients i , associated with the given control inputs (7) such that the filtered error ) (k r i as well as the NN…”

“…In the recent years, there has been a great interest in the decentralized control of interconnected nonlinear systems using neural networks (NNs) [1][2][3][4][5][6][7][8]. In large-scale systems such as power systems, the feedback delays degrade the controller performance thus necessitating more decentralized control techniques.…”

“…In large-scale systems such as power systems, the feedback delays degrade the controller performance thus necessitating more decentralized control techniques. The decentralized state feedback control effort has focused mainly on nonlinear continuous-time systems [1][2][3][4][5] and limited effort in discrete-time case [6][7][8].…”

“…1 ) ( x g ). In [7][8], a stabilizing robust controller is proposed by assuming the dynamics are known beforehand. Therefore, the NNs are not utilized in the controller design.…”

“…The interconnected terms are also considered unknown as opposed to [7] [8]. A single NN is used to approximate the control gain matrix ) (x g as well as the subsystem internal dynamics ) (x f for each subsystem.…”