To improve the nonlinear approximating ability of cerebellar model articulation controller(CMAC), by introducing the Gauss basis functions and the similarity measure based addressing scheme, a new kind of fuzzy CMAC...To improve the nonlinear approximating ability of cerebellar model articulation controller(CMAC), by introducing the Gauss basis functions and the similarity measure based addressing scheme, a new kind of fuzzy CMAC with Gauss basis functions(GFCMAC) was presented. Moreover, based upon the improvement of the self organizing feature map algorithm of Kohonen, the structural self organizing algorithm for GFCMAC(SOGFCMAC) was proposed. Simulation results show that adopting the Gauss basis functions and fuzzy techniques can remarkably improve the nonlinear approximating capacity of CMAC. Compared with the traditional CMAC,CMAC with general basis functions and fuzzy CMAC(FCMAC), SOGFCMAC has the obvious advantages in the aspects of the convergent speed, approximating accuracy and structural self organizing.展开更多
The adaptive fault-tolerant control scheme of dynamic nonlinear system based on the credit assigned fuzzy CMAC neural network is presented. The proposed learning approach uses the learned times of addressed hypercubes...The adaptive fault-tolerant control scheme of dynamic nonlinear system based on the credit assigned fuzzy CMAC neural network is presented. The proposed learning approach uses the learned times of addressed hypercubes as the credibility, the amounts of correcting errors are proportional to the inversion of the learned times of addressed hypercubes. With this idea, the learning speed can indeed be improved. Based on the improved CMAC learning approach and using the sliding control technique, the effective control law reconfiguration strategy is presented. The system stability and performance are analyzed under failure scenarios. The numerical simulation demonstrates the effectiveness of the improved CMAC algorithm and the proposed fault-tolerant controller.展开更多
Soft sensor is attractive in dealing with online product quality measurement by virtue of other easily measured variables. In AMOCO PTA (purified terephthalic acid) production process, the unavailability of real-time ...Soft sensor is attractive in dealing with online product quality measurement by virtue of other easily measured variables. In AMOCO PTA (purified terephthalic acid) production process, the unavailability of real-time measurement of 4-CBA makes it impossible for timely adjustment and thereby influences the product quality and the plant economy benefit. In this paper, a kind of FCMAC (fuzzy cerebellar model articulation controller) method is presented to solve the online measurement problem. Different from the conventional CMAC (cerebellar model articulation controller) networks, which has inferior smoothing ability because of its table look-up based technology. Integrating fuzzy model into CMAC networks, it becomes more accurate in functional mapping without weakening its generalization ability. Numerical example and industrial application results show the method proposed here is satisfactory and feasible.展开更多
Based on the fuzzy CMAC (FCMAC) neural networks (NNs), the theory of feedback linearization (FL), and the simplified bank to turn (BTT) missile control design model, a robust adaptive BTT missile autopilot design m...Based on the fuzzy CMAC (FCMAC) neural networks (NNs), the theory of feedback linearization (FL), and the simplified bank to turn (BTT) missile control design model, a robust adaptive BTT missile autopilot design method is presented. First, based on the simplified BTT missile model for control design, a nonlinear feedback control law which depends on the accurate model of the controlled plant is obtained using the theory of FL. Secondly, based on the nominal BTT missile control design model, the FCMAC NNs are introduced to improve further the estimation accuracy of the BTT missile control design model in a online way, and a robustifying portion is included in the control law to suppress the effect of the NNs approximation errors on the missile system. A stability proof is given strictly in the sense of Lyapunov. Its shown that all the signals in the closed loop BTT missile system are uniformly ultimately bounded (UUB). The control law is valid throughout the entire flight envelope of the BTT missile and is fit for real time control due to the advantages of the FCMAC NNs. Simulation results have shown the rightness and effectiveness of the designed autopilot.展开更多
文摘To improve the nonlinear approximating ability of cerebellar model articulation controller(CMAC), by introducing the Gauss basis functions and the similarity measure based addressing scheme, a new kind of fuzzy CMAC with Gauss basis functions(GFCMAC) was presented. Moreover, based upon the improvement of the self organizing feature map algorithm of Kohonen, the structural self organizing algorithm for GFCMAC(SOGFCMAC) was proposed. Simulation results show that adopting the Gauss basis functions and fuzzy techniques can remarkably improve the nonlinear approximating capacity of CMAC. Compared with the traditional CMAC,CMAC with general basis functions and fuzzy CMAC(FCMAC), SOGFCMAC has the obvious advantages in the aspects of the convergent speed, approximating accuracy and structural self organizing.
基金The Natural Science Foundation of Jiangsu Province (BK200402)Key Project of Chinese Ministry of Education(105088)
文摘The adaptive fault-tolerant control scheme of dynamic nonlinear system based on the credit assigned fuzzy CMAC neural network is presented. The proposed learning approach uses the learned times of addressed hypercubes as the credibility, the amounts of correcting errors are proportional to the inversion of the learned times of addressed hypercubes. With this idea, the learning speed can indeed be improved. Based on the improved CMAC learning approach and using the sliding control technique, the effective control law reconfiguration strategy is presented. The system stability and performance are analyzed under failure scenarios. The numerical simulation demonstrates the effectiveness of the improved CMAC algorithm and the proposed fault-tolerant controller.
基金Supported by the special Funds for Major State Basic Research Program of China (973 Program) (No. 2002CB312200) the 863 Hi-Tech. Research and Development Program of China (No. 2001AA413130, No.2002AA412110)the Key Technologies R&D Programme of China (No. 2001BA201A04).
文摘Soft sensor is attractive in dealing with online product quality measurement by virtue of other easily measured variables. In AMOCO PTA (purified terephthalic acid) production process, the unavailability of real-time measurement of 4-CBA makes it impossible for timely adjustment and thereby influences the product quality and the plant economy benefit. In this paper, a kind of FCMAC (fuzzy cerebellar model articulation controller) method is presented to solve the online measurement problem. Different from the conventional CMAC (cerebellar model articulation controller) networks, which has inferior smoothing ability because of its table look-up based technology. Integrating fuzzy model into CMAC networks, it becomes more accurate in functional mapping without weakening its generalization ability. Numerical example and industrial application results show the method proposed here is satisfactory and feasible.
文摘Based on the fuzzy CMAC (FCMAC) neural networks (NNs), the theory of feedback linearization (FL), and the simplified bank to turn (BTT) missile control design model, a robust adaptive BTT missile autopilot design method is presented. First, based on the simplified BTT missile model for control design, a nonlinear feedback control law which depends on the accurate model of the controlled plant is obtained using the theory of FL. Secondly, based on the nominal BTT missile control design model, the FCMAC NNs are introduced to improve further the estimation accuracy of the BTT missile control design model in a online way, and a robustifying portion is included in the control law to suppress the effect of the NNs approximation errors on the missile system. A stability proof is given strictly in the sense of Lyapunov. Its shown that all the signals in the closed loop BTT missile system are uniformly ultimately bounded (UUB). The control law is valid throughout the entire flight envelope of the BTT missile and is fit for real time control due to the advantages of the FCMAC NNs. Simulation results have shown the rightness and effectiveness of the designed autopilot.
