论文标题
控制阳性系统，其依赖状态的功率定律输入延迟和输入饱和
Control of Positive Systems with an Unknown State-Dependent Power Law Input Delay and Input Saturation
论文作者
论文摘要
本文是由一类带有输入的积极系统的动机，该系统受到未知状态依赖性功率定律延迟和饱和度的影响。例如，生物网络具有非负蛋白浓度态。这些系统中的质量作用动力学导致了幂律行为，而复杂的相互作用会导致信号传播延迟。不完整的网络表征使状态依赖性未知。通过调制蛋白质浓度来操纵网络活动以达到所需的性能受到浓度执行器授权的上限限制。在这里，创新的控制法利用了系统动态来补偿控制域的限制。 Lyapunov稳定性分析表明，闭环系统的参考跟踪误差最终是界限的。与相关文献相比，对人类凝血模型的数值模拟显示出控制器的功效和更好的性能。此示例应用程序采取了针对创伤性凝血病的个性化的，闭环治疗，目前使用开环临床方法具有30％的死亡率。
This paper is motivated by a class of positive systems with an input that is subject to an unknown state-dependent power law delay as well as saturation. For example, biological networks have non-negative protein concentration states. Mass action kinetics in these systems result in power law behavior, while complex interactions cause signal propagation delays. Incomplete network characterization makes delay state-dependence unknown. Manipulating network activity via modulated protein concentrations to attain desired performance is restricted by upper-bounds on concentration actuator authority. Here, an innovative control law exploits system dynamics to compensate for control domain restrictions. A Lyapunov stability analysis establishes that the reference tracking error of the closed-loop system is uniformly ultimately bounded. Numerical simulations on a human coagulation model show controller efficacy and better performance compared to the relevant literature. This example application steps toward personalized, closed-loop treatments for trauma coagulopathy, which currently has 30% mortality with open-loop clinical approaches.
