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Controller design for continuous dynamical systems is a core algorithmic problem in the design of cyber-physical systems (CPS). When the CPS application is safety critical, additionally we require the controller to have strong correctness guarantees. One approach for this design problem is to use simpler discrete abstraction of the original continuous system, on which known reactive synthesis methods can be used to design the controller. This approach is known as the abstraction-based controller design (ABCD) paradigm. In this thesis, we build ABCD procedures which are faster and more modular compared to the state-of-the-art, and can handle problems which were beyond the scope of the existing techniques. Usually, existing ABCD approaches use state space discretization for computing the abstractions, for which the procedures do not scale well for larger systems. Our first contribution is a multi-layered ABCD algorithm, where we combine coarse abstractions and lazily computed fine abstractions to improve scalability. So far, we only address reach-avoid and safety specifications, for which our prototype tool (called Mascot) showed up to an order of magnitude speedup on standard benchmark examples. Second, we consider the problem of modular design of sound local controllers for a network of local discrete abstractions communicating via discrete/boolean variables and having local specifications. We propose a sound algorithm, where the systems negotiate a pair of local assume-guarantee contracts, in order to synchronize on a set of non-conflicting and correct behaviors. As a by-product, we also obtain a set of local controllers for the systems which ensure simultaneous satisfaction of the local specifications. We show the effectiveness of the our algorithm using a prototype tool (called Agnes) on a set of discrete benchmark examples. Our third contribution is a novel ABCD algorithm for a more expressive model of nonlinear dynamical systems with stochastic disturbances and ω-regular specifications. This part has two ...