Output Feedback Reinforcement Learning Control for Linear Systems
Produktnummer:
18ea15ddff55b64a84ae6aa1310e653bd4
| Autor: | Lin, Zongli Rizvi, Syed Ali Asad |
|---|---|
| Themengebiete: | Adaptive Dynamic Programming Model-Free Control Model-Free Control Algorithms Multi-Agent Synchronization Optimal Tracking Control Reinforcement Learning Reinforcement Learning Algorithms |
| Veröffentlichungsdatum: | 30.11.2022 |
| EAN: | 9783031158575 |
| Sprache: | Englisch |
| Seitenzahl: | 294 |
| Produktart: | Gebunden |
| Verlag: | Springer International Publishing |
Produktinformationen "Output Feedback Reinforcement Learning Control for Linear Systems"
This monograph explores the analysis and design of model-free optimal control systems based on reinforcement learning (RL) theory, presenting new methods that overcome recent challenges faced by RL. New developments in the design of sensor data efficient RL algorithms are demonstrated that not only reduce the requirement of sensors by means of output feedback, but also ensure optimality and stability guarantees. A variety of practical challenges are considered, including disturbance rejection, control constraints, and communication delays. Ideas from game theory are incorporated to solve output feedback disturbance rejection problems, and the concepts of low gain feedback control are employed to develop RL controllers that achieve global stability under control constraints.Output Feedback Reinforcement Learning Control for Linear Systems will be a valuable reference for graduate students, control theorists working on optimal control systems, engineers, and applied mathematicians.
Sie möchten lieber vor Ort einkaufen?
Sie haben Fragen zu diesem oder anderen Produkten oder möchten einfach gerne analog im Laden stöbern? Wir sind gerne für Sie da und beraten Sie auch telefonisch.
Juristische Fachbuchhandlung
Georg Blendl
Parcellistraße 5 (Maxburg)
8033 München
Montag - Freitag: 8:15 -18 Uhr
Samstags geschlossen