Robust Control Barrier and Control Lyapunov Functions with Fixed-Time Convergence Guarantees
Robust Control Barrier and Control Lyapunov Functions with Fixed-Time Convergence Guarantees
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DOI：
10.23919/acc50511.2021.9482751
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发表时间：
2020-04
期刊：
影响因子：
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通讯作者：
Kunal Garg;Dimitra Panagou
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文献类型：
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作者：
Kunal Garg;Dimitra Panagou
研究了一类一般的非线性控制仿射动力系统在加性扰动和状态估计误差作用下的控制综合问题。我们强制静态和动态安全集的向前不变性，并在输入约束存在的情况下，在用户定义的时间内收敛到给定的目标集。我们使用控制屏障函数(CBF)和固定时间控制Lyapunov函数(FxT-CLF)的鲁棒变体来在系统动力学中加入一类加性扰动和状态估计误差。为了解决基本的约束控制问题，我们建立了一个二次规划，并使用所提出的鲁棒CBF-FxT-CLF条件来计算控制输入。我们在一个涉及多个欠驱动海洋航行器的数值案例研究中展示了所提出的方法的有效性。
This paper studies control synthesis for a general class of nonlinear, control-affine dynamical systems under additive disturbances and state-estimation errors. We enforce forward invariance of static and dynamic safe sets and convergence to a given goal set within a user-defined time in the presence of input constraints. We use robust variants of control barrier functions (CBF) and fixed-time control Lyapunov functions (FxT-CLF) to incorporate a class of additive disturbances in the system dynamics, and state-estimation errors. To solve the underlying constrained control problem, we formulate a quadratic program and use the proposed robust CBF-FxT-CLF conditions to compute the control input. We showcase the efficacy of the proposed method on a numerical case study involving multiple underactuated marine vehicles.