It takes the average reader 5 hours and 8 minutes to read Output Feedback Reinforcement Learning Control for Linear Systems by Syed Ali Asad Rizvi
Assuming a reading speed of 250 words per minute. Learn more
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.
Output Feedback Reinforcement Learning Control for Linear Systems by Syed Ali Asad Rizvi is 304 pages long, and a total of 77,216 words.
This makes it 103% the length of the average book. It also has 94% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 7 hours and 1 minute to read Output Feedback Reinforcement Learning Control for Linear Systems aloud.
Output Feedback Reinforcement Learning Control for Linear Systems is suitable for students ages 12 and up.
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