对于大规模的具有伪凸目标函数的二次规划问题，本文提出一种分解算法。
This paper proposes a decomposition algorithm for large scale quadratic programming with a pseudoconvex objective function.
对PWA模型的状态区域进一步的细化凸划分，以增加找到分段二次lyapunov函数的可能性，减低闭环系统稳定性分析的保守性。
Further convex partitioning of the state's regions increases the possibility of finding the piece-wise quadratic Lyapunov functions, which reduces the conservativeness of the stability analysis.
对PWA模型的状态区域进一步的细化凸划分，以增加找到分段二次lyapunov函数的可能性，减低闭环系统稳定性分析的保守性。
Further convex partitioning of the state's regions increases the possibility of finding the piece-wise quadratic Lyapunov functions, which reduces the conservativeness of the stability analysis.
应用推荐