Description :
Hybrid systems are important in applications in real-time software, robotics and automation, mechatronics, aeronautics, air and ground transportation systems, systems biology, process control, and have recently been at the center of intense research activity in the control theory, computer-aided verification, and artificial intelligence communities. In the past several years, methodologies have been developed to model hybrid systems, to analyze their behavior, and to synthesize controllers that guarantee closed-loop safety and performance specifications We will present hybrid automaton models and related modeling approaches. In hybrid controller synthesis, we will treat different control system setups such as game theoretic and optimal control, and we will present recent advances in integrating learning-based approaches into such methods. Finally, we apply the theory in case studies to complex problems such as automated highway systems, air traffic management systems, networks of unmanned vehicles, closing the loop around sensor networks, and systems biology