Power Network Regulation Benchmark for Switched-Mode Optimal Control

Adaptive voltage regulation of an inverter-based power distribution network with a class of droop controllers

The voltage received by each customer connected to a power distribution line with local controllers (inverters) is regulated to be within a desired margin through a class of slope-restricted controllers, known conventionally as \emph{droop} controllers. We adapt the design of the droop controllers according to the known bounds of the net power consumption of each customer in each observation time window. A sufficient condition for voltage regulation is provided for each time window, which guides the design of the droop controllers, depending on the properties of the distribution line (line imp…

Cooperative Global Robust Output Regulation for a Class of Nonlinear Multi-Agent Systems by Distributed Event-Triggered Control

This paper studies the event-triggered cooperative global robust output regulation problem for a class of nonlinear multi-agent systems via a distributed internal model design. We show that our problem can be solved practically in the sense that the ultimate bound of the tracking error can be made arbitrarily small by adjusting a design parameter in the proposed event-triggered mechanism. Our result offers a few new features. First, our control law is robust against both external disturbances and parameter uncertainties, which are allowed to belong to some arbitrarily large prescribed compact …

离散时间线性二次调节的最优输出反馈学习控制

Optimal Output Feedback Learning Control for Discrete-Time Linear Quadratic Regulation

本文针对未知离散时间系统的LQR问题，提出一种保证收敛、稳定和最优的广义动态输出反馈学习控制方法，通过等效状态反馈设计、自适应动态规划迭代及无模型稳定性判据求解最优控制增益，并经数值实验验证。

Infinite-Horizon Optimal Control of Switched Boolean Control Networks with Average Cost: An Efficient Graph-Theoretical Approach

This study investigates the infinite-horizon optimal control problem for switched Boolean control networks with an average-cost criterion. A primary challenge of this problem is the prohibitively high computational cost when dealing with large-scale networks. We attempt to develop a more efficient and scalable approach from a graph-theoretical perspective. First, a weighted directed graph structure called the $\textit{optimal state transition graph}$ (OSTG) is established, whose edges encode the optimal action for each one-step transition between states reachable from a given initial state sub…

用于五大湖调控的WLPCM方法

WLPCM Approach for Great Lakes Regulation

本研究提出了水位预测控制模型（WLPCM），结合延迟微分方程与模型预测控制，优化五大湖大坝流量，有效缓解洪水并平衡多方需求。

Designing reactive power control rules for smart inverters using support vector machines

Smart inverters have been advocated as a fast-responding mechanism for voltage regulation in distribution grids. Nevertheless, optimal inverter coordination can be computationally demanding, and preset local control rules are known to be subpar. Leveraging tools from machine learning, the design of customized inverter control rules is posed here as a multi-task learning problem. Each inverter control rule is modeled as a possibly nonlinear function of local and/or remote control inputs. Given the electric coupling, the function outputs interact to yield the feeder voltage profile. Using an app…

利用调节触发有限时间识别的常参数反应扩散PDEs自适应边界控制

Adaptive Boundary Control of Constant-Parameter Reaction-Diffusion PDEs Using Regulation-Triggered Finite-Time Identification

本文提出基于确定性等价的新型自适应边界控制方案，通过事件触发最小二乘识别器实现参数估计的有限时间收敛，针对特定基准问题解决高频率增益未知的挑战。

Frequency-driven market mechanisms for optimal dispatch in power networks

This paper studies real-time bidding mechanisms for economic dispatch and frequency regulation in electrical power networks. We consider a market administered by an independent system operator (ISO) where a group of strategic generators participate in a Bertrand game of competition. Generators bid prices at which they are willing to produce electricity. Each generator aims to maximize their profit, while the ISO seeks to minimize the total generation cost and to regulate the frequency of the system. We consider a continuous-time bidding process coupled with the swing dynamics of the network th…

Power Regulation in High Performance Multicore Processors

This paper presents, implements, and evaluates a power-regulation technique for multicore processors, based on an integral controller with adjustable gain. The gain is designed for wide stability margins, and computed in real time as part of the control law. The tracking performance of the control system is robust with respect to modeling uncertainties and computational errors in the loop. The main challenge of designing such a controller is that the power dissipation of program-workloads varies widely and often cannot be measured accurately; hence extant controllers are either ad hoc or based…