无需系统模型即可安全追踪路径，适用于动态突变场景。
Reachable Predictive Control: A Novel Control Algorithm for Nonlinear Systems with Unknown Dynamics and its Practical Applications
- 通过局部微扰学习动态，构建可到达状态集
- 保证在任意未知非线性系统中可达性，不依赖先验模型
- 适合动态突变、模型未知的工业控制应用
本文提出一种新型控制算法，可在不掌握系统动力学的情况下，驱动非线性系统沿分段线性轨迹运动。针对系统动力学可能发生突变的关键失效场景，证明了一组状态点在理论上是可到达的。算法首先对当前状态施加小扰动以局部学习系统动态，随后基于所学动态计算出可严格证明可达的状态集合及其最大增长速率边界，并最终合成控制指令，将系统导航至一个确定可到达的状态。该方法不依赖系统先验模型，适用于动态未知或突变的复杂系统控制。
原文摘要 · Abstract (English)
This paper proposes an algorithm capable of driving a system to follow a piecewise linear trajectory without prior knowledge of the system dynamics. Motivated by a critical failure scenario in which a system can experience an abrupt change in its dynamics, we demonstrate that it is possible to follow a set of waypoints comprised of states analytically proven to be reachable despite not knowing the system dynamics. The proposed algorithm first applies small perturbations to locally learn the system dynamics around the current state, then computes the set of states that are provably reachable using the locally learned dynamics and their corresponding maximum growth-rate bounds, and finally synthesizes a control action that navigates the system to a guaranteed reachable state.
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