Understanding Smart Sensors - Nomads.usp

162 Understanding Smart SensorsControlcommands(Referenceinputs)FuzzyknowledgebaseandinferencemechanismFuzzifierDefuzzifierMeasurementsControl actionsSensorsProcessProcessoutputs(a)SignalprocessorMonitoringsystemFuzzytuning andadaptationSensorsControlinputsLow-level crispcontrollersProcessProcessoutputs(b)Figure 7.9 (a) Low-level direct control and (b) high-level tuning/adaptive control in fuzzylogic control system. (After: [19].)include online and offline tuning of the controller parameters, online adaptationof the low-level controller, and self-organization and dynamic restructuringof the control system.7.6.1 Observers for SensingObservers, or algorithms that correct for variations from physical models,are increasingly being used in more complex systems such as motor controlsand automotive engine controls. A discrete time domain representation ofan observer in a motor control system is shown in Figure 7.10 [20]. InFigure 7.10, the intent is to compute the best-estimated value for velocity fromthe measured position of the rotor. In Figure 7.10, u is the input voltage, A is amatrix representing the motor’s dynamics, B is the input vector, D is a vectorthat shows which of the system variables is the output (position), X is the statevariablevector that includes two components: position and velocity, Z is the