This thesis addresses several synthesis and optimization issues for embedded control systems. Examples of such systems are automotive and avionics systems in which physical processes are controlled by embedded computers through sensor and actuator interfaces. The execution of multiple control applications, spanning several computation and communication components, leads to a complex temporal behavior that affects control quality. The relationship between system timing and control quality is a key issue to consider across the control design and computer implementation phases in an integrated manner. We present such an integrated framework for scheduling, controller synthesis, and quality optimization for distributed embedded control systems. At runtime, an embedded control system may need to adapt to environmental changes that affect its workload and computational capacity. Examples of such changes, which inherently increase the design complexity, are mode changes, component failures, and resource usages of the running control applications. For these three cases, we present trade-offs among control quality, resource usage, and the time complexity of design and runtime algorithms for embedded control systems. The solutions proposed in this thesis have been validated by extensive experiments. The experimental results demonstrate the efficiency and importance of the presented techniques.