This book provides a thorough and fresh treatment of the control of innovative variable-geometry vehicle suspension systems. A deep survey on the topic, which covers the varying types of existing variable-geometry suspension solutions, introduces the study. The book discusses three important aspects of the subject:

• robust control design;

• nonlinear system analysis; and

• integration of learning and control methods.

The importance of variable-geometry suspensions and the effectiveness of design methods implemented in the autonomous...

This book offers a thorough introduction to the basics and scientific and technological innovations involved in the modern study of reinforcement-learning-based feedback control. The authors address a wide variety of systems including work on nonlinear, networked, multi-agent and multi-player systems.

A concise description of classical reinforcement learning (RL), the basics of optimal control with dynamic programming and network control architectures, and a brief introduction to typical algorithms build the foundation for the remainder of the book. Extensive...

Control of Autonomous Aerial Vehicles is an edited book that provides a single-volume snapshot on the state of the art in the field of control theory applied to the design of autonomous unmanned aerial vehicles (UAVs), aka “drones”, employed in a variety of applications. The homogeneous structure allows the reader to transition seamlessly through results in guidance, navigation, and control of UAVs, according to the canonical classification of the main components of a UAV’s autopilot.

Each chapter has been written to assist graduate students and practitioners in the...

This book provides a summary of the essential knowledge and working processes involved with control of rotating equipment including:

• machine characteristics;
• overall control strategies;
• detailed design; and
• best practices.

Emphasis is placed on the role of pumps and compressors as part of the overall process flow rather than treating them in isolation as this tends to optimize energy efficiency.

Readers are made aware of the critical roles of rotating equipment and are given a good...

Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games develops its specific learning techniques, motivated by application to autonomous driving and microgrid systems, with breadth and depth: integral reinforcement learning (RL) achieves model-free control without system estimation compared with system identification methods and their inevitable estimation errors; novel inverse RL methods fill a gap that will help them to attract readers interested in finding data-driven model-free solutions for inverse optimization and optimal control, imitation...

This book provides models and methods for the optimal management of electrical vehicles through an interdisciplinary approach that brings together knowledge from the sectors of transportation, manufacturing and smart grids.

Optimization of Electric-Vehicle Charging explores several optimization models for the scheduling of electric vehicles in a smart grid. Both discrete-time and discrete-event approaches are considered to minimize tardiness, charging and production costs, on the basis of information like release time, due date, deadline, energy request, and availability...