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Model predictive control (MPC) is an advanced control design used in many industries worldwide. An MPC selects control actions which are optimal with respect to a given performance metric as well as any physically-motivated constraints. MPC has therefore gained significant research attention over the past several decades. Advances in MPC continue to unlock its potential to solve a wide variety of practical issues. This book presents some of the state-of-the-art in MPC design from theoretical and applications perspectives. It covers a broad spectrum of MPC application areas, reviewing applications as diverse as air conditioning, pharmaceutical manufacturing, mineral column flotation, actuator faults, and hydraulic fracturing, while also highlighting recent theoretical advancements in control technology that integrate it with data-driven models, zone tracking, or process safety and cybersecurity. Both centralized and distributed MPC formulations are presented. The purpose of this book is to assemble a collection of current research in MPC that handles practically-motivated theoretical issues as well as recent MPC applications, with the aim of highlighting the significant potential benefits of new MPC theory and design.

receding horizon control --- optimal control --- predictive control

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This work addresses inverse dynamic games, which generalize the inverse problem of optimal control, and where the aim is to identify cost functions based on observed optimal trajectories. The identified cost functions can describe individual behavior in cooperative systems, e.g. human behavior in human-machine haptic shared control scenarios.

Electrical engineering --- optimale Regelung --- dynamische Spieltheorie --- kooperative Systeme --- Identifikation --- optimal control --- dynamic game theory --- cooperative systems --- identification

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In Networked Control Systems (NCS), components of a control loop are connected by data networks that may introduce time-varying delays and packet losses into the system, which can severly degrade control performance. Hence, this book presents the newly developed S-LQG (Sequence-Based Linear Quadratic Gaussian) controller that combines the sequence-based control method with the well-known LQG approach to stochastic optimal control in order to compensate for the network-induced effects.

Paketverluste --- Networked Control Systems (NCS) --- sequence-based control --- Optimale Regelung --- Sequenzbasierte Regelung --- optimal control --- packet losses --- time delays --- Vernetzte Regelungssysteme (NCS) --- Zeitverzögerungen

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According to the National Research Council, the use of embedded systems throughout society could well overtake previous milestones in the information revolution. Mechatronics is the synergistic combination of electronic, mechanical engineering, controls, software and systems engineering in the design of processes and products. Mechatronic systems put “intelligence” into physical systems. Embedded sensors/actuators/processors are integral parts of mechatronic systems. The implementation of mechatronic systems is consistently on the rise. However, manufacturers are working hard to reduce the implementation cost of these systems while trying avoid compromising product quality. One way of addressing these conflicting objectives is through new automatic control methods, virtual sensing/estimation, and new innovative hardware topologies.

independent-wheel drive --- steering assistance --- nonlinear system --- active disturbance rejection control --- smooth road feeling --- city bus transport --- electric vehicles --- electrification --- software tool --- planning --- control --- charging management --- simulation --- analysis --- energy management --- hybrid electric vehicle --- powertrain electrification --- equivalent consumption minimization --- supercharging --- hardware-in-the-loop experiments --- driving force distribution --- decentralized traction system --- 4WD electric vehicle --- energy efficiency --- traction control --- efficiency optimization --- air mobility --- fuel cell hybrid aircraft --- stochastic optimal control --- drift counteraction optimal control --- normal force estimation --- unbiased minimum variance estimation --- controller output observer --- youla parameterization --- adaptive cruise control --- automated driving --- energy-saving --- fuel-saving --- optimal control --- passenger comfort --- new energy vehicles --- speed prediction --- macroscopic traffic model --- traffic big-data --- deep learning --- vehicle lateral dynamic and control --- unresolved issues --- application of speed prediction --- electric vehicle --- hybrid vehicle --- lithium ion --- ultracapacitor --- battery aging --- EHB --- EMB --- EWB --- system modeling --- bond graph --- optimization --- control design --- Youla parameterization --- robust control --- nonlinear optimization --- brake-by-wire --- actuator --- electro-mechanical brake --- electronic wedge brake --- electro-hydraulic brake --- n/a

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Mathematical optimization --- Structural optimization --- Mathematical optimization. --- Structural optimization. --- linear programming --- gradient descent --- optimal control --- optimization --- process optimization --- Optimal structural design --- Optimization, Structural --- Optimization of structural systems --- Optimum design of structures --- Optimum structural design --- Optimum structures --- Structures, Optimum design of --- Structural design --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis