Design of Adaptive Alpha-Beta-Gamma Filters with Fuzzy Systems

The α β γ filter is an efficient estimation scheme for the motion control. According to the estimated position, velocity and acceleration signals which are provided by the α β γ filters, motion objects will be able to result in an excellent control. However, the estimation performance heavily depends on the parameters α , β and γ . This paper presents a fuzzy logic system to develop an adaptive α β γ filter. In the proposed method, the parameters α , β and γ can be real-time adjusted by fuzzy systems to meet some specifications. The simulation results demonstrate that the adaptive α β γ filters are capable of tracking the desired signals accurately and, at the same time, reducing the noise disturbance remarkably. When compared with evolution algorithm based estimation schemes proposed in earlier literatures, the newly proposed method seems to be promising in the practical applications.