A Dynamic S-Procedure for Dynamic Uncertainties

Modeling metabolic networks including gene expression and uncertainties

Constraint based methods, such as the Flux Balance Analysis, are widely used to model cellular growth processes without relying on extensive information on the regulatory features. The regulation is instead substituted by an optimization problem usually aiming at maximal biomass accumulation. A recent extension to these methods called the dynamic enzyme-cost Flux Balance Analysis (deFBA) is a fully dynamic modeling method allowing for the prediction of necessary enzyme levels under changing environmental conditions. However, this method was designed for deterministic settings in which all dyna…

基于积分二次约束的动态不确定性下的输出反馈模型预测控制

Output-feedback model predictive control under dynamic uncertainties using integral quadratic constraints

本文提出一种基于IQC的输出反馈管道MPC方案，通过联合设计鲁棒动态控制器与估计器并凸化峰峰值鲁棒估计问题，实现对动态不确定性系统的递推可行控制与稳定性保证。

输入到状态安全回步：具有不匹配不确定性的鲁棒安全关键控制

Input-to-State Safe Backstepping: Robust Safety-Critical Control with Unmatched Uncertainties

本文提出了一种针对具有不匹配不确定性的非线性系统，通过构造输入到状态安全框架和最优衰减约束前馈，实现鲁棒安全关键控制的方法，并通过倒立摆和四旋翼实验验证。

具有非线性动态不确定性的量子系统的鲁棒稳定性

Robust Stability of Quantum Systems with Nonlinear Dynamic Uncertainties

本文研究了具有非线性动态不确定性的量子系统鲁棒稳定性问题，提出严格有界实条件作为鲁棒稳定性判据，并应用于光学参量放大器的鲁棒稳定性分析。

针对具有椭球型有界不确定性的线性系统的结合主动学习的自适应鲁棒跟踪控制

Adaptive robust tracking control with active learning for linear systems with ellipsoidal bounded uncertainties

针对参数和扰动为椭球型有界的线性系统，提出结合主动学习的自适应鲁棒跟踪控制，通过递推集成员估计学习不确定性，以二阶锥规划构造优化控制律，仿真验证其性能优于固定椭球集控制。

Dynamic Pricing and Energy Management Strategy for EV Charging Stations under Uncertainties

This paper presents a dynamic pricing and energy management framework for electric vehicle (EV) charging service providers. To set the charging prices, the service providers faces three uncertainties: the volatility of wholesale electricity price, intermittent renewable energy generation, and spatial-temporal EV charging demand. The main objective of our work here is to help charging service providers to improve their total profits while enhancing customer satisfaction and maintaining power grid stability, taking into account those uncertainties. We employ a linear regression model to estimate…

Safe Multi-Agent Interaction through Robust Control Barrier Functions with Learned Uncertainties

Robots operating in real world settings must navigate and maintain safety while interacting with many heterogeneous agents and obstacles. Multi-Agent Control Barrier Functions (CBF) have emerged as a computationally efficient tool to guarantee safety in multi-agent environments, but they assume perfect knowledge of both the robot dynamics and other agents' dynamics. While knowledge of the robot's dynamics might be reasonably well known, the heterogeneity of agents in real-world environments means there will always be considerable uncertainty in our prediction of other agents' dynamics. This wo…

An Operator-Theoretic Approach to Robust Event-Triggered Control of Network Systems with Frequency-Domain Uncertainties

In this paper, we study the robustness of the event-triggered consensus algorithms against frequency-domain uncertainties. It is revealed that the sampling errors resulted by event triggering are essentially images of linear finite-gain $\mathcal{L}_2$-stable operators acting on the consensus errors of the sampled states and the event-triggered mechanism is equivalent to a negative feedback loop introduced additionally to the feedback system. In virtue of this, the robust consensus problem of the event-triggered network systems subject to additive dynamic uncertainties and network multiplicati…

形式语言理论最优路径规划以容纳摊销不确定性和动态效应

Formal-language-theoretic Optimal Path Planning For Accommodation of Amortized Uncertainties and Dynamic Effects

提出基于形式语言定量测度理论的全局最优路径规划方法，通过引入概率不可控转移建模不确定性，并采用无搜索组合优化最大化概率正则语言测度，实现机器人导航中目标到达概率最大化与障碍碰撞概率最小化。