Modeling, plant uncertainties, and fuzzy logic sliding control of gaseous systems

The active control problem of gaseous processes such as primary air atmospheric-suction and forced-draft supply of air for fuel combustion is addressed in this article. The objective is to regulate gas velocity, at particular locations within the system, so that appropriate volume flow rate is achieved. Using modal expansion and treating the high-order modes as unmodeled dynamics, the governing law of momentum conservation reduces to a finite set of ordinary differential equations. Due to variations of the gas properties with operating conditions, there exists parametric uncertainty in the obtained reduced-order model. Moreover, inclusion of the fan characteristic and actuator dynamics introduces additional uncertainty and nonlinearity in the model. To avoid relying on estimation of parameters that vary with operating conditions or on conservative bounds on the uncertainty, the proposed controller has variable structure with adaptive switched gain. A fuzzy-logic-based inference engine realizes the adaptive law that tunes the switched gain to the smallest value that verifies the sliding condition. In effect, this novel design reduces the tendency and magnitude of chattering, a drawback of conventional sliding control. The fuzzy logic sliding controller is tested on a prototype air-handling unit. Compared with PI control, a standard for such applications, the advocated controller overshoots less to square-wave and tracks accurately, in the steady-state higher order inputs. Further experimental investigation demonstrates robustness to structured and unstructured uncertainty