基于观测器的联合输出反馈鲁棒制导与控制漏斗综合
Joint Observer-Based Output-Feedback Robust Guidance and Control Funnel Synthesis
- William E. Boeing Department of Aeronautics and Astronautics, University of Washington（华盛顿大学航空航天系）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
提出联合制导与鲁棒观测器输出反馈综合框架，协同设计参考轨迹、观测器及增益，用LMI和prox-SCP求解，仿真验证鲁棒跟踪与约束满足。
AI中文摘要：
针对受有界过程扰动和测量噪声影响的离散时间非线性系统，开发了一种联合制导与鲁棒基于观测器的输出反馈综合框架。该方法协同设计了参考轨迹、时变Luenberger观测器和基于观测器的线性输出反馈增益，以及耦合的椭球漏斗，用于证明跟踪误差和估计误差的条件不变界。非线性残差通过由局部Lipschitz常数参数化的增量二次约束（QCs）进行界定，这些常数通过采样方法估计。耦合稳定性条件被表述为线性矩阵不等式（LMI）替代形式，并通过使用半定规划（SDP）的带近端正则化的序列凸规划（prox-SCP）求解。在持续传感器噪声和系统扰动下对独轮车模型的仿真表明，相对于联合设计的参考轨迹，实现了鲁棒跟踪和漏斗认证的约束满足。
英文摘要：
A joint guidance and robust observer-based output-feedback synthesis framework is developed for discrete-time nonlinear systems subject to bounded process disturbances and measurement noise. The method co-designs a reference trajectory, time-varying Luenberger observer and observer-based linear output-feedback gains, and coupled ellipsoidal funnels that certify conditioned-invariant bounds on tracking and estimation errors. Nonlinear residuals are bounded by incremental quadratic constraints (QCs) parameterized by local Lipschitz constants, estimated via sampling approaches. The coupled stability conditions are formulated as linear matrix inequality (LMI) surrogates and solved using sequential convex programming with proximal regularization (prox-SCP) via semidefinite programming (SDP). Simulations of a unicycle model under persistent sensory noise and system disturbances demonstrate robust tracking and funnel-certified constraint satisfaction with respect to the jointly designed reference trajectory.
