QRnet: optimal regulator design with LQR-augmented neural networks
In this paper we propose a new computational method for designing optimal regulators for high-dimensional nonlinear systems. The proposed approach leverages physics-informed machine learning to solve high-dimensional Hamilton-Jacobi-Bellman equations arising in optimal feedback control. Concretely, we augment linear quadratic regulators with neural networks to handle nonlinearities. We train the augmented models on data generated without discretizing the state space, enabling application to high-dimensional problems. We use the proposed method to design a candidate optimal regulator for an unstable Burgers' equation, and through this example, demonstrate improved robustness and accuracy compared to existing neural network formulations.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningPhysics-informed machine learningSimilar Papers 제목 키워드 기반
Modeling Dual-Exposure Quad-Bayer Patterns for Joint Denoising and Deblurring
Image degradation caused by noise and blur remains a persistent challenge in imaging systems, stemming from limitations in both hardware and methodology. Single-image solutions face an inherent tradeoff between noise red…
DeblurringDenoisingImage RestorationShifting More Attention to Visual Backbone: Query-modulated Refinement Networks for End-to-End Visual Grounding
Visual grounding focuses on establishing fine-grained alignment between vision and natural language, which has essential applications in multimodal reasoning systems. Existing methods use pre-trained query-agnostic visua…
Multimodal ReasoningVisual GroundingFrom RAG to QA-RAG: Integrating Generative AI for Pharmaceutical Regulatory Compliance Process
Regulatory compliance in the pharmaceutical industry entails navigating through complex and voluminous guidelines, often requiring significant human resources. To address these challenges, our study introduces a chatbot …
ChatbotRAGRetrievalRetrieval-augmented GenerationLet's have a chat with the EU AI Act
As artificial intelligence (AI) regulations evolve and the regulatory landscape develops and becomes more complex, ensuring compliance with ethical guidelines and legal frameworks remains a challenge for AI developers. T…
ChatbotRAGRetrievalRetrieval-augmented GenerationA Simple Algorithm for Solving Ramsey Optimal Policy with Exogenous Forcing Variables
This algorithm extends Ljungqvist and Sargent (2012) algorithm of Stackelberg dynamic game to the case of dynamic stochastic general equilibrium models including exogenous forcing variables. It is based Anderson, Hansen,…