In this paper, we investigate the adaptive output tracking control for fuzzy stochastic parametric strict-feedback systems. To deal with the output tracking problem, we convert it into a stabilization one via the concept of virtual desired variables. Then all the analysis and synthesis are carried out using LMI (linear matrix inequality) technique. Here we emphasize that, due to the specific feature of the strict-feedback systems, the virtual desired variables can be well-defined such that our stochastic adaptive tracking control can be well developed. From the numerical simulations, it is found that the proposed schemes are feasible and the performance is satisfactory.
Hybrid systems are usually consisted of states described partially by continuous variables and partially by discrete variables. In this work, we propose an LMI-based control design for hybrid systems by using fuzzy model-based approach and averaging method. We start with the control-oriented presentation to define the hybrid automata. Then, it is described by a fuzzy model. In light of the concept of pulse-width modulation (PWM) scheme, the crisp fuzzy set is with the value of the duration in an interval. Instead of directly designing the switching sequence for our hybrid systems, the values of the duration are the control signals which need to be designed. Then, the switching sequence for the hybrid systems can be realized by using PWM method.
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