Hybrid Automaton Model and Control of Hybird Systems
β Scribed by Zhang, Wei ;Sun, Youxian
- Publisher
- Curtin University of Technology
- Year
- 2008
- Tongue
- English
- Weight
- 389 KB
- Volume
- 9
- Category
- Article
- ISSN
- 0969-1855
No coin nor oath required. For personal study only.
β¦ Synopsis
Abstract
A hybrid automaton model is proposed in this paper for hybrid systems. The model, with particular emphasis on process control applications, is based on the dynamic features of hybrid systems. It takes into account the discrete dynamics of hybrid systems in particular and can clearly separate the controller from the closedβloop system. The definition of controllability of hybird systems with respect to the marked regions is also given. An analyzing algorithm and sufficient and necessary condition for controllability based on the hybrid automaton model are discussed. At the same time, the property of the loops in the trajectory of the closedβloop plant is studied. Finally, the synthesis scheme for a hybrid controller is given. In this scheme, the controller consists of two parts, the discrete supervisor and the continuous regulator. The closedβloop plant with the controller is stateβcontrollable.
π SIMILAR VOLUMES
## Abstract The control of systems that have sandwiched nonsmooth nonlinearities, such as a deadβzone sandwiched between two dynamic blocks, is addressed. An adaptive inverse control scheme using a hybrid controller structure and a neural network based inverse compensator, is proposed for such syst
## Abstract A hybrid system approach is adopted to study the dynamic behavior of a controlled reverse flow reactor, where the occurrence of flow inversions is caused by a feedback control strategy. With this approach it is analyzed, theoretically and numerically a typical behavior of hybrid systems
## Abstract A constrained minimum variance controller is derived based on a moving horizon approach that explicitly accounts for hard constraints on process variables. A procedure for the performance assessment of constrained model predictive control systems is then developed based on the constrain