Perturbed cooperative-state feedback strategy for model predictive networked control of interconnected systems. (January 2018) - Tran, Tri; Ha, Q.P.
Abstract: A perturbed cooperative-state feedback (PSF) strategy is presented for the control of interconnected systems in this paper. The subsystems of an interconnected system can exchange data via the communication network that has multiple connection topologies. The PSF strategy can resolve both issues, the sensor data losses and the communication network breaks, thanks to the two components of the control including a cooperative-state feedback and a perturbation variable, e.g., u i = K ij x j + w i . The PSF is implemented in a decentralized model predictive control scheme with a stability constraint and a non-monotonic storage function ( Δ V ( x ( k ) ) ≥ 0 ), derived from the dissipative systems theory. Numerical simulation for the automatic generation control problem in power systems is studied to illustrate the effectiveness of the presented PSF strategy. Abstract : Graphical abstract: The Partially Decentralized MPC with PSF Strategy provides a comparable control performance to the Centralized MPC for the Automatic Generation Control (AGC) of power systems. Abstract : Highlights: Perturbed cooperative-state feedback (PSF) strategy for the control of interconnected systems having flexible communication network topology. Partially Decentralized Model Predictive Control (DeMPC) with a dissipation-based constraint employing the PSF strategy, applying to the Automatic Generation Control (AGC) of power systems. Intermittent data losses are dealt with in real time, right after every data loss incident. The real-time approach is less conservative than the static approach which assumes the worst case scenario of data losses in the design. The dissipation-based constraint method is novel. The stabilization in this method is achieved and characterized by a relaxed non-monotonic Lyapunov function.