Edward reyland (4 Ergebnisse)

Taschenbuch. Zustand: Neu. Neuware - Understand vehicle dynamics from the tire contact patch to integrated chassis control. Modern Vehicle Dynamics provides a rigorous, practical treatment of the forces, models, calculations, and control methods that govern the behavior of modern road vehicles. >>Inside, readers will explore: >- Longitudinal dynamics, road loads, traction, acceleration, and energy - Braking dynamics, brake-force distribution, wheel-slip behavior, and antilock control - Steady-state and transient handling, stability, and driver response - Steering geometry, compliance, power assistance, rear steering, and steer-by-wire - Suspension kinematics, chassis load paths, wheel rates, ride, and vibration - Longitudinal and lateral load transfer, roll, pitch, wheel lift, and rollover - Aerodynamic forces, vehicle attitude, crosswinds, and active aerodynamics - Vehicle modeling, numerical simulation, parameter identification, verification, and validation - State estimation and electronic stability control - Semi-active and active suspension and roll-control systems - Electric and hybrid vehicle dynamics, regenerative limits, and brake blending - Torque vectoring, control allocation, and integrated chassis control The book combines derivations, worked examples, engineering calculations, figures, tables, review questions, numerical practice problems, and complete worked solutions, making it suitable for structured university courses as well as independent professional study. Special attention is given to model boundaries, calculation auditing, verification, and engineering application. Readers learn not only how to obtain a numerical result, but how to understand the assumptions behind a model, recognize its limitations, and determine what evidence is needed before trusting its predictions. Written for mechanical and automotive engineering students, vehicle-dynamics engineers, chassis and controls engineers, simulation engineers, and vehicle-integration professionals, Modern Vehicle Dynamics provides a connected framework for understanding classical vehicle behavior and the increasingly integrated control systems used in modern vehicles. Build the models. Trace the forces. Audit the calculations. Understand how the complete vehicle responds. …

Taschenbuch. Zustand: Neu. Neuware - HANDBOOK OF AI ENGINEERING AND AGENTIC AIBuilding an impressive AI prototype is easier than ever. Engineering an AI system that stays reliable, secure, measurable, and economical in production is a much harder problem.Handbook of AI Engineering and Agentic AI is a rigorous, engineering-first guide to building intelligent systems that move beyond promising demos and perform dependably under real-world conditions. Prompts go brittle. Retrieval misses critical evidence. Structured outputs fail validation. Agents lose state, repeat actions, or exceed intended boundaries. This handbook develops the engineering principles and practical methods needed to address those failures systematically.Inside, you will learn how to: - Understand foundation-model behavior, context limits, decoding, caching, and cost trade-offs.- Engineer prompts, structured outputs, and tool interfaces for dependable applications.- Build retrieval-augmented systems using chunking, hybrid retrieval, reranking, and advanced retrieval architectures.- Decide when retrieval, fine-tuning, or both are appropriate-and evaluate results using evidence rather than intuition.- Design evaluation systems for quality, groundedness, robustness, safety, and cost.- Build agentic systems that plan, use tools, maintain memory, recover from failures, and incorporate human oversight.- Design multi-agent architectures in which specialized agents coordinate complex workflows.- Apply security controls, guardrails, observability, and failure management to production systems.- Optimize latency and cost while deploying and governing systems at scale.Agentic AI receives substantial treatment throughout the handbook. Rather than reducing agents to simple prompt loops, the book examines planning, task decomposition, memory, state management, tool use, reflection, permission boundaries, failure recovery, and coordination between specialized agents-the engineering mechanisms required for controlled autonomy.Each chapter combines learning objectives, first-principles explanations, worked examples, practice problems with worked solutions, and concise summaries, making the book suitable for structured study or professional reference.Written for AI engineers, machine-learning engineers, software engineers, architects, technical leads, and advanced computing students, the handbook assumes basic code literacy and systems thinking, not a machine-learning research background.The focus is not on temporary interfaces or short-lived tricks, but on the durable engineering principles behind intelligent systems that can be evaluated, secured, scaled, and operated with confidence.…

Taschenbuch. Zustand: Neu. Neuware.

Taschenbuch. Zustand: Neu. Neuware.