Temperature Control Of Semiconductor Metal-oxide Gas Sensors By Means Of Fuzzy Logic

Abstract

The electrical conductivity of metal-oxide gas sensors depends on the gas atmosphere and on the temperature of the sensor. In order to eliminate this influence, temperature control systems for gassensors were developed as conventionel PID-controller. Problems appears in cases of hard disturbances (i. e. rough gasflows) to fix a temperature point what is justified with the high non linearity of the controlled system. A new concept based on fuzzy logic was developed to gain better temperature stabilization in atmospheres with hard disturbances. This control system was adapted in the laboratory and tested in a real sensor application. The fuzzy system can optimize the system for different disturbances. TRODUCTIONIn the temperature range above 450°C, semiconducting metal-oxide gassensors are suitable for detecting gasconcentrations in the atmosphere surrounding them. The effect of detection is caused by a change in the electrical resistance (R,,,,) of the semiconductor. This signal is amongst the kind and concentration of the gas, primarily strong dependent on the temperature (T) what means R,,,,,= f(gas,T). In order to heat and keep the sensor on a fix temperature point, an electrical heater (Pt) is attached to the back side of the sensor chip. With this heater it is possible to measure the temperature (change of the electrical resistance) as well as to heat the sensor (set an electrical voltage) [3].For applications with a small or constant gasflow, temperature controller based on PID-algorithms show good results to hold a fixed temperature on the sensor. Here the optimization of the control system is performed by linearising the complex mathematical sensor model. But these parameters belong to a fix temperature point with no or only constant (well known) troubles. In cases with rapid and unpredictable changes of the gasflow, especially hard disturbances, the controller can not deal properly with the appearing overshoots and huntings. It is, however, theoreticaly impossible to pursue both improvement in disturbance response characteristics and suppression of overshoot at the same time. The parameter for the controller here, adapted in a long continous try and error proceeding, can not optimize the high nonlinear system. For this reason a fuzzy control system was developed to suppress temperature overshoots caused by different changes in the gasflow [ 11.

Air-Suspended Silicon Micro-Bridge Structures for Metal Oxide- Based Gas Sensing

“…As mentioned earlier, the gas (or vapor) detection technique is primarily based on the change in their electrical resistance of the metal oxide films [2] upon their exposure to the test gas under study. The principal detection process is the change of oxygen concentration at the surface of these sensing metal oxides, caused by the adsorption of the test gas and subsequent heterogeneous catalytic reactions of the gas under study.…”

Fuzzy Logic Transformer DesignAlgorithm (FLTDA)

“…The linguistic concepts like 'Core is large', 'Window size is small', 'Turns per volt to be changed' normally difficult to implement, are incorporated in to the computer in fuzzy approach via membership functions [10,12]. E.g., the implementation of 'Current density' is shown in Figure 1.…”

“…2.3. Inference-scheme [11,12,141 The FLTDA employs Mamadani type individual rule based fuzzy logic inference. This is a process where contribution of each fuzzy logic rule is evaluated.…”