Titlebook: Innovative Techniques and Applications of Modelling, Identification and Control; Selected and Expande Quanmin Zhu,Jing Na,Xing Wu Book 2018

Priapism

,Hopfield Neural Network Identification and Adaptive Control for Bouc–Wen Hysteresis System,space equation and a new HNN is designed to identify the coefficients. Finally, an adaptive controller is proposed and the stability is guaranteed by a Lyapunov function candidate. Simulation results verify the effectiveness of the proposed identification and adaptive control approach.

Mammal

CRAMP

Adaptive Parameter Identification and Control for Servo System with Input Saturation,kened using the proposed method. Moreover, several adaptive parameters are adopted to suppress the effect of saturation when the limited input affects the system tracking performance. Finally, simulations are conducted to verify the effectiveness of the proposed method.

伪善

Diastole

Dynamic Modeling and Modal Analysis of RV Reducer,he lumped parameter method. The natural frequency of the system is then obtained by solving the free-vibration equation. The vibration mode of the first eight natural frequencies is summed up by using the induction method. The paper provides specific theoretical basis for the design and application of RV reducer.

拱形大桥

进取心

DECRY

The Application of Data-Level Fusion Algorithm Based on Adaptive-Weighted and Support Degree in Intre stable. The accuracy of data fusion directly determines the precision and quality of greenhouse intelligent control. The experimental results show that the fusion result adopting the proposed method of this paper is superior to the result of traditional average-estimation fusion and data fusion based on support degree.

Commodious

使高兴

Improved NSGA-II Algorithm for Multi-objective Scheduling Problem in Hybrid Flow Shop,he AP clustering mechanism. We compare the proposed algorithm and compare it with the state-of-the-art solutions. The numerical result shows that the proposed MODADE algorithm outperforms others in terms of the algorithm convergence, the number, and distribution of Pareto solutions.