This book focuses on most recent theoretical findings on control issues for active suspension systems. The authors first introduce the theoretical background of active suspension control, then present constrained H control approaches of active suspension systems in the entire frequency domain, focusing on the state feedback and dynamic output feedback controller in the finite frequency domain which people are most sensitive to. The book also contains nonlinear constrained tracking control via terminal sliding-mode control and adaptive robust theory, presenting controller design of active suspensions as well as the reliability control of active suspension systems. The target audience primarily comprises research experts in control theory, but the book may also be beneficial for graduate students alike.

This book describes new tools for front end analog designers, starting with global variation-aware sizing, and extending to novel variation-aware topology design. The tools aid design through automation, but more importantly, they also aid designer insight through automation. We now describe four design tasks, each more general than the previous, and how this book contributes design aids and insight aids to each. The ?rst designer task targeted is global robust sizing. This task is supported by a design tool that does automated, globally reliable, variation-aware s- ing (SANGRIA), and an insight-aiding tool that extracts designer-interpretable whitebox models that relate sizings to circuit performance (CAFFEINE). SANGRIA searches on several levels of problem dif?culty simultaneously, from lower cheap-to-evaluate "exploration" layers to higher full-evaluation "exploitation" layers (structural homotopy). SANGRIAmakes maximal use of circuit simulations by performing scalable data mining on simulation results to choose new candidate designs. CAFFEINE accomplishes its task by tre- ing function induction as a tree-search problem. It constrains its tree search space via a canonical-functional-form grammar, and searches the space with grammatically constrained genetic programming. The second designer task is topology selection/topology design. Topology selection tools must consider a broad variety of topologies such that an app- priate topology is selected, must easily adapt to new semiconductor process nodes, and readily incorporate new topologies. Topology design tools must allow designers to creatively explore new topology ideas as rapidly as possible.

This book describes new tools for front end analog designers, starting with global variation-aware sizing, and extending to novel variation-aware topology design. The tools aid design through automation, but more importantly, they also aid designer insight through automation. We now describe four design tasks, each more general than the previous, and how this book contributes design aids and insight aids to each. The ?rst designer task targeted is global robust sizing. This task is supported by a design tool that does automated, globally reliable, variation-aware s- ing (SANGRIA), and an insight-aiding tool that extracts designer-interpretable whitebox models that relate sizings to circuit performance (CAFFEINE). SANGRIA searches on several levels of problem dif?culty simultaneously, from lower cheap-to-evaluate "exploration" layers to higher full-evaluation "exploitation" layers (structural homotopy). SANGRIAmakes maximal use of circuit simulations by performing scalable data mining on simulation results to choose new candidate designs. CAFFEINE accomplishes its task by tre- ing function induction as a tree-search problem. It constrains its tree search space via a canonical-functional-form grammar, and searches the space with grammatically constrained genetic programming. The second designer task is topology selection/topology design. Topology selection tools must consider a broad variety of topologies such that an app- priate topology is selected, must easily adapt to new semiconductor process nodes, and readily incorporate new topologies. Topology design tools must allow designers to creatively explore new topology ideas as rapidly as possible.