TY - GEN
T1 - Performance Analysis of Fuzzy Proportional-Derivative Control Systems
AU - Li, Huaidong
AU - Malki, Heidar
AU - Chen, Guanrong
PY - 1994/4/6
Y1 - 1994/4/6
N2 - This paper analyzes the performance of a fuzzy proportional-derivative (PD) controller in comparison with the conventional PD controller. The design of the fuzzy PD controller follows the structure of the conventional digital PD controller, with additional fuzzy logic control rules. The resulting controller, therefore, has the same linear structure as that of the conventional digital PD controller, except that both the proportional and the derivative parts have non-constant gains. The fuzzy proportional and derivative gains are nonlinear functions of the control-input signals and hence have a self-Tuning control capability. Thus, the proposed fuzzy PD controller preserves the simple linear structure of the conventional PD controller yet enhances its adaptive control capability. In. computer simulations, a set of linear systems, with or without time-delays, were used to test the performance of the fuzzy PD controller in [4], and a set of nonlinear systems are used to test the performance of the fuzzy PD controller in this paper. The performance has been compared to the conventional PD controller for the same linear and nonlinear systems. Computer simulation results have demonstrated the advantages of the fuzzy PD controller, particularly if the system to be controlled is nonlinear.
AB - This paper analyzes the performance of a fuzzy proportional-derivative (PD) controller in comparison with the conventional PD controller. The design of the fuzzy PD controller follows the structure of the conventional digital PD controller, with additional fuzzy logic control rules. The resulting controller, therefore, has the same linear structure as that of the conventional digital PD controller, except that both the proportional and the derivative parts have non-constant gains. The fuzzy proportional and derivative gains are nonlinear functions of the control-input signals and hence have a self-Tuning control capability. Thus, the proposed fuzzy PD controller preserves the simple linear structure of the conventional PD controller yet enhances its adaptive control capability. In. computer simulations, a set of linear systems, with or without time-delays, were used to test the performance of the fuzzy PD controller in [4], and a set of nonlinear systems are used to test the performance of the fuzzy PD controller in this paper. The performance has been compared to the conventional PD controller for the same linear and nonlinear systems. Computer simulation results have demonstrated the advantages of the fuzzy PD controller, particularly if the system to be controlled is nonlinear.
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U2 - 10.1145/326619.326679
DO - 10.1145/326619.326679
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 0897916476
T3 - Proceedings of the ACM Symposium on Applied Computing
SP - 115
EP - 119
BT - SAC '94: Proceedings of the 1994 ACM symposium on Applied computing
PB - Association for Computing Machinery
T2 - 1994 ACM Symposium on Applied Computing, SAC 1994
Y2 - 6 March 1994 through 8 March 1994
ER -