Computing control invariant sets of cascade nonlinear systems: Decomposition and distributed computing. (March 2023) - Decardi-Nelson, Benjamin; Liu, Jinfeng
Abstract: In this work, we present a distributed framework based on the graph algorithm for computing control invariant set for nonlinear cascade systems. The proposed algorithm exploits the structure of the interconnections within a process network. First, the overall system is decomposed into several subsystems with overlapping states. Second, the control invariant set for the subsystems are computed in a distributed manner. Finally, an approximation of the control invariant set for the overall system is reconstructed from the subsystem solutions and validated. We demonstrate the efficacy and convergence of the proposed method to the centralized graph-based algorithm using several numerical examples including a six dimensional continuous stirred tank reactor system. Highlights: A distributed computing algorithm for control invariant sets. An efficient approach to construct centralized sets from distributed computing. Two examples illustrating the performance of the algorithm.