论文标题
令人满意的控制设计框架，具有安全性和性能保证在干扰下的受限系统
A Satisficing Control Design Framework with Safety and Performance Guarantees for Constrained Systems under Disturbances
论文作者
论文摘要
本文介绍了一种安全的强大政策迭代（SR-PI）算法，以使用满意（足够）的性能和安全保证来设计控制器。这与没有安全认证的基于标准的基于PI的控制设计方法相反。它还远离现有的安全控制设计方法，这些方法可以进行刻薄的优化，因此是近视的。安全保证需要满足控制屏障功能（CBF），这可能与绩效驱动的Lyapunov解决方案相抵触，以解决PI的每次迭代中出现的Bellman方程。因此，需要进行新的开发，以便在PI的每次迭代中稳健地证明改进的政策的安全性。拟议的SR-PI算法在每次迭代时都会使用安全保证（由强大的CBF提供）统一性能保证（由Bellman不平等提供）。 Bellman的不平等类似于令人满意的决策框架，并在与安全发生冲突时以志向级别的态度参数。在每次迭代时，都优化了这种愿望水平，以最大程度地减少表现的牺牲。结果表明，在SR-PI的每次迭代中获得的介绍的满足控制策略可确保强大的安全性和性能。当与安全没有冲突时，还可以保证稳定的稳定性。正方形（SOS）程序的总和用于实现所提出的SR-PI算法。最后，进行数值模拟以说明提出的满足控制框架。
This paper presents a safe robust policy iteration (SR-PI) algorithm to design controllers with satisficing (good enough) performance and safety guarantee. This is in contrast to standard PI-based control design methods with no safety certification. It also moves away from existing safe control design approaches that perform pointwise optimization and are thus myopic. Safety assurance requires satisfying a control barrier function (CBF), which might be in conflict with the performance-driven Lyapunov solution to the Bellman equation arising in each iteration of the PI. Therefore, a new development is required to robustly certify the safety of an improved policy at each iteration of the PI. The proposed SR-PI algorithm unifies performance guarantee (provided by a Bellman inequality) with safety guarantee (provided by a robust CBF) at each iteration. The Bellman inequality resembles the satisficing decision making framework and parameterizes the sacrifice on the performance with an aspiration level when there is a conflict with safety. This aspiration level is optimized at each iteration to minimize the sacrifice on the performance. It is shown that the presented satisficing control policies obtained at each iteration of the SR-PI guarantees robust safety and performance. Robust stability is also guaranteed when there is no conflict with safety. Sum of squares (SOS) program is employed to implement the proposed SR-PI algorithm iteratively. Finally, numerical simulations are carried out to illustrate the proposed satisficing control framework.
