The practical environment settings are always dynamic and unpredictable. And the adaptive solution is deteriorated seriously unless we can accurately determine when the filter's adaptation actually converges. In t...
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ISBN:
(纸本)9781424403417
The practical environment settings are always dynamic and unpredictable. And the adaptive solution is deteriorated seriously unless we can accurately determine when the filter's adaptation actually converges. In this paper, based on the principle of orthogonality, a scheme is proposed for sharply judging the iteration's convergence to obtain the optimal estimation in practically unknown stationary or nonstationary circumstances. The discriminant obtained through the estimated mean-square values of the desired, output and error signals at each iteration cycle, can be updated according to the varying characteristics of the actual input signal. Cases of both computer simulations and real applications are studied to validate its effectiveness in stationary and nonstationary environments.
The riding comfort and handling safety of vehicle are regarded as control aims. With the nonlinearity of the road-vehicle system, an adjustable fuzzy control algorithm which fuzzy control rule table can be obtained wi...
详细信息
ISBN:
(纸本)0780381254
The riding comfort and handling safety of vehicle are regarded as control aims. With the nonlinearity of the road-vehicle system, an adjustable fuzzy control algorithm which fuzzy control rule table can be obtained with the numerical calculation is advanced. Because the algorithm can adjust the rectification factor of fuzzy controller with the Least Means Squares (lms) method, it not only can reflect the advantage of fuzzy logic in nonlinearity system but also can improve the disadvantage of common fuzzy control method strongly depending on the experience. For two degree-of-freedom (DOF) vehicle model,. the simulation of vehicle performance in road signal is studied, its results show the adjustable fuzzy controller can reduce the acceleration of the sprung mass by a factor of 20. According to the experiment study of vehicle model, the results further prove that the algorithm can effectively control the vibration of vehicle system.
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