分层控制架构的契约理论

分层控制架构的协同设计

Co-designing a Layered Control Architecture

针对复杂工程系统中分层控制架构（LCA）缺乏系统设计理论的问题，提出线性时不变被控对象的两层LCA协同设计框架，可在帕累托前沿上权衡速度、精度等最优性维度，通过数值示例验证了权衡效果。

基于深度可达性分析和分层控制架构的信号时间逻辑验证与综合

Signal Temporal Logic Evaluation and Synthesis Using Deep Reachability Analysis and Layered Control Architecture

本文提出了一种基于深度可达性分析和分层控制架构的信号时间逻辑验证与综合框架，通过高效计算后向可达管和结合混合整数线性规划与模型预测控制，实现安全可靠的任务执行。

约束线性系统的分层多速率控制

Layered Multirate Control of Constrained Linear Systems

针对约束线性系统的分层控制问题，提出一种基于离散时间仿真函数的分层多速率控制方法，通过约束传播与简化设计保证高低层约束满足，在运动规划避障中验证了有效性。

A Layered Architecture for Active Perception: Image Classification using Deep Reinforcement Learning

We propose a planning and perception mechanism for a robot (agent), that can only observe the underlying environment partially, in order to solve an image classification problem. A three-layer architecture is suggested that consists of a meta-layer that decides the intermediate goals, an action-layer that selects local actions as the agent navigates towards a goal, and a classification-layer that evaluates the reward and makes a prediction. We design and implement these layers using deep reinforcement learning. A generalized policy gradient algorithm is utilized to learn the parameters of thes…

Diversity-enabled sweet spots in layered architectures and speed-accuracy trade-offs in sensorimotor control

Nervous systems sense, communicate, compute and actuate movement using distributed components with severe trade-offs in speed, accuracy, sparsity, noise and saturation. Nevertheless, brains achieve remarkably fast, accurate, and robust control performance due to a highly effective layered control architecture. Here we introduce a driving task to study how a mountain biker mitigates the immediate disturbance of trail bumps and responds to changes in trail direction. We manipulated the time delays and accuracy of the control input from the wheel as a surrogate for manipulating the characteristic…

使用时间分层架构优化注意力与认知控制成本

Optimizing Attention and Cognitive Control Costs Using Temporally-Layered Architectures

针对现有强化学习框架重性能轻效率的问题，提出DB-MDP约束智能体决策数与计算能耗，并设计受生物启发的TLA架构，在保持性能的同时显著降低计算成本，为相关研究建立基准。

Temporally Layered Architecture for Adaptive, Distributed and Continuous Control

We present temporally layered architecture (TLA), a biologically inspired system for temporally adaptive distributed control. TLA layers a fast and a slow controller together to achieve temporal abstraction that allows each layer to focus on a different time-scale. Our design is biologically inspired and draws on the architecture of the human brain which executes actions at different timescales depending on the environment's demands. Such distributed control design is widespread across biological systems because it increases survivability and accuracy in certain and uncertain environments. We …

分布鲁棒模仿学习：用于可验证自主性的分层控制架构

Distributionally Robust Imitation Learning: Layered Control Architecture for Certifiable Autonomy

本文提出分布鲁棒模仿策略架构，通过整合泰勒级数模仿学习和ℓ₁-分布鲁棒自适应控制，解决分布偏移问题，实现可验证的自主性。

基于Actor-Critic学习的分层控制策略中规划与跟踪的协调

Coordinating Planning and Tracking in Layered Control Policies via Actor-Critic Learning

提出一种基于强化学习的actor-critic算法，联合训练分层控制中的规划器与跟踪控制器，通过对偶网络协调二者，实现可解释策略，并在LQR下证明收敛，在非线性独轮车模型上验证有效性。

用于混合系统鲁棒镇定的分层非线性模型预测控制

Layered Nonlinear Model Predictive Control for Robust Stabilization of Hybrid Systems

针对非线性混合系统滚动时域优化难以实时求解的问题，提出高低层分层MPC架构，并通过跟踪误差管建立重算速度与鲁棒性的联系。

架构就是你所需要的一切：面向鲁棒人形机器人运动的多样性赋能甜点

Architecture Is All You Need: Diversity-Enabled Sweet Spots for Robust Humanoid Locomotion

本文提出由高速本体感知稳定器与低速紧凑感知策略组成的 LCA，并采用两阶段训练，证明架构上的时间尺度分离可显著提升人形机器人在复杂地形中的运动鲁棒性。