In IBVS (image based visual servoing), the error signal in image space should be transformed into the control signal in the input space quickly. To avoid the iterative adjustment and complicated inverse solution of im...In IBVS (image based visual servoing), the error signal in image space should be transformed into the control signal in the input space quickly. To avoid the iterative adjustment and complicated inverse solution of image Jacobian, CMAC (cerebellar model articulation controller) neural network is inserted into visual servo control loop to implement the nonlinear mapping. Two control schemes are used. Simulation results on two schemes are provided, which show a better tracking precision and stability can be achieved using scheme 2.展开更多
The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise m...The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise mathemati- cal model for control. So, a new method for establishing a hydraulic roll bending control system is put forward by cerebellar model articulation controller （CMAC） neural network and proportional-integral-derivative （PID） coupling control strategy. The non-linear relationship between input and output can be achieved by the concept mapping and the actual mapping of CMAC. The simulation results show that, compared with the conventional PID control algo- rithm, the parallel control algorithm can overcome the influence of parameter change of roll bending system on the control performance, thus improve the anti jamming capability of the system greatly, reduce the dependence of con- trol performance on the accuracy of the analytical model, enhance the tracking performance of hydraulic roll bending loop for the hydraulic and roll bending force and increase system response speed. The results indicate that the CMAC-P1D coupling control strategy for hydraulic roll bending system is effective.展开更多
In this paper, an adaptive backstepping fuzzy cerebellar-model-articulation-control neural-networks control （ABFCNC） system for motion/force control of the mobile-manipulator robot （MMR） is proposed. By applying t...In this paper, an adaptive backstepping fuzzy cerebellar-model-articulation-control neural-networks control （ABFCNC） system for motion/force control of the mobile-manipulator robot （MMR） is proposed. By applying the ABFCNC in the tracking-position controller, the unknown dynamics and parameter variation problems of the MMR control system are relaxed. In addition, an adaptive robust compensator is proposed to eliminate uncertainties that consist of approximation errors, uncertain disturbances. Based on the tracking position-ABFCNC design, an adaptive robust control strategy is also developed for the nonholonomicconstraint force of the MMR. The design of adaptive-online learning algorithms is obtained by using the Lyapunov stability theorem. Therefore, the proposed method proves that it not only can guarantee the stability and robustness but also the tracking performances of the MMR control system. The effectiveness and robustness of the proposed control system are verified by comparative simulation results.展开更多
A control algorithm for following robot trajectory with high speed moving is proposed. The controller consists of a linear regulator and a feed-forward compensationitem. A neural network is used and is let to learn th...A control algorithm for following robot trajectory with high speed moving is proposed. The controller consists of a linear regulator and a feed-forward compensationitem. A neural network is used and is let to learn the mapping between the inverse dynamic characteristic of the robot and the driving commands. The experimental system, that includes the PUMA 560 robot, a universal motor controller and a host computer, has proved that the proposed algorithm is very efficient and it has many advantages.展开更多
The real-time fault diagnosis system is very great important for steam turbine generator set due to a serious fault results in a reduced amount of electricity supply in power plant. A novel real-time fault diagnosis s...The real-time fault diagnosis system is very great important for steam turbine generator set due to a serious fault results in a reduced amount of electricity supply in power plant. A novel real-time fault diagnosis system is proposed by using strata hierarchical fuzzy CMAC neural network. A framework of the fault diagnosis system is described. Hierarchical fault diagnostic structure is discussed in detail. The model of a novel fault diagnosis system by using fuzzy CMAC are built and analyzed. A case of the diagnosis is simulated. The results show that the real-time fault diagnostic system is of high accuracy, quick convergence, and high noise rejection. It is also found that this model is feasible in real-time fault diagnosis.展开更多
基金This project is supported by National Natural Science Foundation of China (No.59990470).
文摘In IBVS (image based visual servoing), the error signal in image space should be transformed into the control signal in the input space quickly. To avoid the iterative adjustment and complicated inverse solution of image Jacobian, CMAC (cerebellar model articulation controller) neural network is inserted into visual servo control loop to implement the nonlinear mapping. Two control schemes are used. Simulation results on two schemes are provided, which show a better tracking precision and stability can be achieved using scheme 2.
基金Item Sponsored by National High-Tech Research and Development Program(863Program)of China(2009AA04Z143)Natural Science Foundation of Hebei Province of China(E2006001038)Hebei Provincial Science and Technology Project of China(10212101D)
文摘The hydraulic roll bending control system usually has the dynamic characteristics of nonlinearity, slow time variance and strong outside interference in the roiling process, so it is difficult to establish a precise mathemati- cal model for control. So, a new method for establishing a hydraulic roll bending control system is put forward by cerebellar model articulation controller （CMAC） neural network and proportional-integral-derivative （PID） coupling control strategy. The non-linear relationship between input and output can be achieved by the concept mapping and the actual mapping of CMAC. The simulation results show that, compared with the conventional PID control algo- rithm, the parallel control algorithm can overcome the influence of parameter change of roll bending system on the control performance, thus improve the anti jamming capability of the system greatly, reduce the dependence of con- trol performance on the accuracy of the analytical model, enhance the tracking performance of hydraulic roll bending loop for the hydraulic and roll bending force and increase system response speed. The results indicate that the CMAC-P1D coupling control strategy for hydraulic roll bending system is effective.
基金supported by the National Natural Science Foundation of China(Nos.6117075,60835004)the National High Technology Research and Development Program of China(863 Program)(Nos.2012AA111004,2012AA112312)
文摘In this paper, an adaptive backstepping fuzzy cerebellar-model-articulation-control neural-networks control （ABFCNC） system for motion/force control of the mobile-manipulator robot （MMR） is proposed. By applying the ABFCNC in the tracking-position controller, the unknown dynamics and parameter variation problems of the MMR control system are relaxed. In addition, an adaptive robust compensator is proposed to eliminate uncertainties that consist of approximation errors, uncertain disturbances. Based on the tracking position-ABFCNC design, an adaptive robust control strategy is also developed for the nonholonomicconstraint force of the MMR. The design of adaptive-online learning algorithms is obtained by using the Lyapunov stability theorem. Therefore, the proposed method proves that it not only can guarantee the stability and robustness but also the tracking performances of the MMR control system. The effectiveness and robustness of the proposed control system are verified by comparative simulation results.
文摘A control algorithm for following robot trajectory with high speed moving is proposed. The controller consists of a linear regulator and a feed-forward compensationitem. A neural network is used and is let to learn the mapping between the inverse dynamic characteristic of the robot and the driving commands. The experimental system, that includes the PUMA 560 robot, a universal motor controller and a host computer, has proved that the proposed algorithm is very efficient and it has many advantages.
文摘The real-time fault diagnosis system is very great important for steam turbine generator set due to a serious fault results in a reduced amount of electricity supply in power plant. A novel real-time fault diagnosis system is proposed by using strata hierarchical fuzzy CMAC neural network. A framework of the fault diagnosis system is described. Hierarchical fault diagnostic structure is discussed in detail. The model of a novel fault diagnosis system by using fuzzy CMAC are built and analyzed. A case of the diagnosis is simulated. The results show that the real-time fault diagnostic system is of high accuracy, quick convergence, and high noise rejection. It is also found that this model is feasible in real-time fault diagnosis.
