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We present a Nonlinear Model Predictive Control (NMPC) algorithm for real-time control of large-scale river networks in delta areas. The algorithm consists of an iterative, finite-horizon optimization of the system over a short-term control horizon. The underlying set of nonlinear internal process models represents relevant physical phenomena such as flow routing in the river network, and the dynamics...
In this paper, a new distributed Kalman filter is proposed for state estimation of systems with acyclic digraph, namely acyclic systems. This method can be applied to a number of large-scale systems including sensor networks and formation flying missions. An acyclic system can be represented by an overlapping block-diagonal state space (OBDSS) model, which requires an extensive communication overhead...
In this paper, a new distributed Kalman filter scheme is proposed to estimate actuator faults for deep space formation flying satellites. The method can also be applied to large-scale systems such as sensor networks and power systems. For a hierarchical large-scale system, the overlapping block-diagonal state space (OBDSS) representation of the system is transformed into our proposed constrained-state...
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