• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.161-167
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• 2001

This paper presents an approach to nonlinear engine idle controller and intake manifold absolute pressure(MAP) observer based on mean torque production model. A stable engine idle speed is important in that the unstable engine Idle mode can make engine to drooping or stall state. A sliding fuzzy controller has been designed to control engine idle speed under load disturbance. A sliding observer is also developed to estimate the intake manifold absolute pressure and compared with the actual MAP sensor value. The sliding mode observer has shown good robustness and good tracking performance. The inputs of sliding fuzzy controller are the errors of rpm and MAP. The output is a duty cycle(DC) for driving a idle speed control valve(ISCV).

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.113-118
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• 2010

This paper proposed an ECAM (Electronic cam) control system which has simple and general structure. The proposed cam controller adopted the linear and polynomial curve-fitting method to generates a smooth cam profile curve function. Smooth motion trajectory of master actuator guarantees the good performance of slave motion and has an important effect on the interpolation quality of ECAM. The auto-tuning PID velocity controller was applied to overcome the uncertainties in ECAM, and the gains of the controller are updated continuously to ensure the consistency of system performance under varying working conditions. The robustness of system against the varying load torque disturbances and noises is guaranteed by using the load torque disturbance observer to suppress the disturbance on master actuator. The velocity compensator was applied to compensate the degradation of performance of slave motion caused from the varying driving speed of master motion. The stability and validity of the proposed ECAM control system was verified by simulation results.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.127-134
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• 2008

In this paper, we propose a robust adaptive backstepping control of induction motors with uncertainties using nonlinear disturbance observer(NDO). The proposed NDO is applied to estimate the time-varying lumped uncertainty which are derived from unknown motor parameters and load torque, but NDO error does not converge to zero since the derivate of lumped uncertainty is not zero. Then the fuzzy neural network(FNN) is presented to estimate the NDO error such that the rotor speed to converge to a small neighborhood of the desired trajectory. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer. Simulation results are provided to verify the effectiveness of the proposed approach.