This dissertation concerns the development of reduced complexity controllers for<br />hybrid switched systems. A diverse number of applications from automotive industry, fluid dyna-<br />mics and power systems are treated. Some general open loop optimal and predictive control schemes<br />are proposed. The main motivation behind each method is the reduction of the combinatorics. In<br />this thesis, two main contributions can be distinguished. The first one concerns the optimal control<br />of switched nonlinear systems where an algorithm based on strong variations is proposed and some<br />convergence results proven. The complexity of the scheme is linear in the number of locations, this<br />in conjunction with its simplicity makes it attractive for large scale systems. An example from<br />the automotive industry is treated to further illustrate the tractability of the scheme. The second<br />contribution concerns the development of a hierarchical approach for switched nonlinear systems.<br />At the lower level, feedback controllers are associated to each location and at the higher level a<br />predictive approach with a reduced order parametrization is in force. Based on this methodology,<br />two schemes are developed and successfully tested in respectively fluid stabilisation by actuator<br />switching and voltage stabilization in power systems.