Model predictive control strategy of a medium hybrid electric vehicle

The intense coupled and nonlinear behaviors were observed on the tall long span tower line systems which were under the icing and wind loads in heavy icing areas. A set of stiffness equations of insulator, conductor and boundary conditions was deduced. Taking the ±800 kV UHV DC transmission line from Xiangjiaba to Shanghai as an example, the simplified numerical model of transmission tower, conductor, insulator and constraint was developed. The long span transmission tower line system models under seven loads conditions were analyzed by static nonlinear methods. It was found that the P Δ effect of tower components was small when the covered ice was uniformly distributed. The unbalanced wire loads on the tower would lead to twist effect when the covered ice was uneven distributed. The axial forces, moments at restraint nodes and the longest cantilever member were greatly affected by the P Δ effect, under which the unfavorable effect on the structure should be considered.     

Research of UD2UU with human simulated intelligent control for a double inverted pendulum

Double pendulum has four equilibrium points (down down, down up, up down, and up up). Twelve transfer actions and eight spin actions can be formed with these equilibrium points. One of the transfer action, up down to up up (UD2UU) with human simulated intelligent control (HSIC) theory based on sensor motor intelligent schema is studied. Control system designed by HSIC has following advantages: hierarchic control architecture with multi controller and multi control mode; hybrid control law combining close loop and open loop control as well as positive feedback and negative feedback control; associating schema based on characteristic model which takes charge of switch between each control mode. The design process of HSIC controller for UD2UU is discussed. The real time control results demonstrate the validation of the proposed theory and method.     

Predictive Control Approach for Active Power Filter Based on Neural Networks

In this paper, a predictive control approach using neural networks for active power filter is proposed. The control system of active power filter using this method make using of the internal model control technology based on neural networks, meanwhile, to solve its questions such as lag because of calculating using neural networks, a predictive model based on neural networks is introduced. Simulation analysis shows that this control approach can compensate the lag of system and take advantage of self-adaptive characteristic of neural networks. Good result can be obtained.     

Robust adaptive control for nonlinear chaotic systems

Tracking control of a nonlinear uncertain Chua's chaotic system is studied. With coordinate transform, Chua's chaotic system is transformed to a general form of a strict feedback control system. Combining the backstepping method with robust control technology, an adaptive parameter control law for a robust output feedback control scheme is developed for output tracking of nonlinear unknown systems. It is shown that the derived robust adaptive controller based on Lyapunov stability theory can guarantee global uniformly bounded ultimate property for all states of the closed loop system, and lead to tracking error decreasing at exponential speed. The simulation results show the effectiveness of the proposed approach.     

Control strategy and parameters optimization outsourcing production inventory system under uncertainty

This paper proposes a control strategy for the optimal control of the outsourcing production inventory system based on production point and production batch. The statistical probability distribution is used to describe the uncertainty of the production capacity of cooperative enterprises and the transportation time. The optimization model of the control parameters is developed with random production capacity for cooperative enterprises and random transportation time in order to minimize the holding cost,setup cost as well as the cost of production capacity waste. A simulation-based control parameters optimization algorithm is designed to solve the proposed model. The control strategy of production inventory system and the control parameters optimization algorithm proposed are validated by an example. We analyze the influence of the variation of the production point and production batch to the performance of the outsourcing production inventory system.     

An Excitative Control in Operating Process for Synchronous Motor

Aimed at the excitative control for synchronous motor, based on main adjust for power factor and aided adjust for power angle,a kind of new control strategy is presented in this paper. In the steady running,the excitation current will be adjusted in keep. power factor constant,and in dynamic running,it will be calibrated by means of power angle when the disturbance happened.For specified object,the improved algorithm of artificial intelligence controller is also presented in the paper,the simulation result shows that the control algorithm is satisfactory.     

模糊控制系统的垂直切换判决算法分析

针对模糊控制系统中切换时延较长和切换次数较多的问题,研究了一种基于模糊控制系统的垂直切换判决算法。在基于信号强度判决时将RSS作为门限值,提高系统判决能力;同时,将网络参数和服务类型作为判决因素,结合层次分析法引入并行的模糊控制系统,缩短了切换判决的时间、选择适合用户的最佳网络,做出垂直切换。仿真结果表明,该算法减少了切换次数,降低了切换时延,增强了系统的性能。与传统的切换算法相比较,该算法对切换的判决因素考虑的更全面,兼顾了用户终端的使用环境及成本问题,有效地保证了网络的服务质量。     

PID Control for Multivariable System Based on Ameliorative RBF Neural Networks

Aiming at systems which are of characteristics of multi-input and multi-output, nonlinearity and time-variation in the industrial control fields, this paper presents a intelligent PID control method based on ameliorative RBF neural networks, which constructs RBF neural networks identifier on-line and identifies a controlled object on-line by means of adopting the nearest neighbor-clustering algorithm, and adjusts parameters of PID controller on-line and realizes decoupiing control of multivariable, nonlinear and time-variation system. The simulation result indicates that the controller can get parameters which are optimal under some control law, it makes the decoupled system, compared to the PID control method based on the conventional RBF neural networks, has perfect dynamic and static performances, possesses the advantages of high precision, quick response speed and is of great adaptability and robustness.     

The Algorithm of Pole-Assignment Self Tuning Robust Control

An control algorithm with goed robustness has been developed,based on the combination of poletassignment self- tuning control algorithm with robust estimation and control al-gorithms,while the input signal and process parameters are varied on a large scale. The design of controller based on presented algorithm is simple,with good robustness for parameter changes and a strong ability for overcoming determined disturbance.The simulating research results proved the ef-fectiveness of the pole- assienment self-tuning robust control algorithm.     

The predictive control of an incremental model based on tracking error

An algorithm of incremental model predictive control is proposed to solve a class of industrial production process real-time tracking problems. The basic idea is to establish a predictive model by adopting speed response on the basis of tracking error, and realize the optimization of the second time performance by using the soft constraint of the increment of control quantity and the online rolling optimization method. The theoretical analysis and Matlab simulation results show that the control algorithm can obtain good tracking performance, smooth dynamic response of the controlled object and strong robustness of the closed-loop system.     

A Kind of Synthetical Fuzzy Control System of Carburization

Carburization is a complex manufacturing process with serious disturbance and time delay,which is multi-variable and uncertain.It is difficult to set up an exact mathematic model.Moreover,by means of conventional control methods and experience,satisfying control result can't be obtained.In this paper,according to the characteristic of controlled-object,Fuzzy control method has been chosen to design a Fuzzy-PI controller and a mixed-PID Fuzzy controller.The result of simulation shows that the robust performance and control result of the new Fuzzy controllers is better than the conventional PID controller.The overshoot is smaller.It is helpful to improve the quality of carburizing workpieces.     

Improvement Methods of Fuzzy Control with Intelligent Integration

Fuzzy controller can achieve satisfactory dynamic performance even for complicated process without mathematical model of the process.Its main imperfection is the existence of steady state error and ultimate oscillatory in the process output. This limits its application area. How to eliminate the steady state error while keep its good dynamic performance has been paid much attention. The strategy to introduce integral function to the conventional fuzzy control system is put forward in this paper to overcome the above problem. After expound two key factors on introducing integral action,an intelligent integral algorithm has been employed,and two methods on introduction of the intelligent integral to the fuzzy control system are proposed. Their characteristics and applied situations are summarized.     

Rapid Prototype Control of Hydraulic Automatic Transmission System Based on dSPACE

dSPACE is a prototype development and real-time control testing platform which is based on MATLAB/Simulink software. By establishing mathematic model of hydraulic automatic transmission system, the shift rules are achieved. A testing platform for hydraulic automatic transmission system is developed whose control software is programmed by simulink and using the dSPACE as the centre controller. The experiment of electric throttle control and power performance matching control of hydraulic automatic transmission system is carried out. the result shows that well matching performance of hydraulic automatic transmission system can be realizedby using the control strategy proposed in this paper, it provides a fast and efficient approach for researching and developing the hydraulic automatic transmission system.     

Design of a Motion Control System of Confocal Scanning Laser Microscope

A confocal scanning laser microscope is presented. Its motion control system is built with the DSP - based motion controller. The system worked on a double CPU structure that includes industrial control computer and motion controller, the system adopt friendly man - machine interface In the design of software. The systems tasks are divided into real - time tasks and no - real - time tasks. The lower computer deals with the real - time tasks such as position control and velocity control and the upper computer is used to deal with the non - real - time tasks. The system structure of con-focal scanning laser microscope and the constitute of motion control system as well as the software is introduced .     

Robust Adaptive Control Based on On-line Identification to Multi-parameters

In system controlled,Sampling these parameters and with parameters for controller in time, it is an object to adaptive control. The article presents a scheme that the structure parameters on it's model and model parameters is robust identified by on line, while to optimal of algorithm on adaptive control is fulfilled. In control scheme, method of intelligent identifying to the structure parameters(levels of model) and algorithm of robust pole placement are introduced also It is advancer for already mentioned scheme. Whole scheme presents new model on adaptive control.     

Adaptive Iterative Learning Control of Nonlinear Systems with Unknown Control Direction

An adaptive iterative learning control scheme is proposed for a class of mismatched nonlinear systems with periodic uncertainties and unknown control directions. The control algorithm has the following three features;the control method does not need control direction information; the periodic uncertainties are learned online by a learning control method; and the algorithm can deal with mismatched uncertainties. The proposed method can achieve asymptotical convergence along a learning repetition horizon. A simulation example is provided can demonstrate the effectiveness and feasibility of the control strategy.     

The Adaptive Robust Control Based On Synthetical Algorithm

An adaptive robust control based on synthetical algorithm was presented in this paper. The main character is to put the expert knowledge into parameter identification to realize the robust estimation, and combine the generalised minimum variance control with the pole assignment control for improving the robustness of the controller. Numerical simulation has proved that the control scheme suggested by authors quite prevailed over the general adaptive controller in control effects.     

THE OVERLAPPING DECOMPOSITION DECENTRALIZED CONTRAL FOR GENERATOR''S EXCITER/GOVERNOR SYSTEMS

In this paper the generator's exciter/governor system are decomposed by using the overlapping decomposition method, and an overlapping decomposition decentralized control (ODDC) system is designed for the exciter /governor systems. In or.dar to enhance the dynamic qualities of the decentralized control system, the concept of the second feedback system is introduced to modify the first feedback gain matrix on the condition of the structure of the original decentralized control system maintaining unchanged. The practical decentralized control system design and its; simulation results show that this method greatly improves the control effect of the ODDC system and also holds all the advantages of the ODDC system. Besides, this paper indicates that it is a simple and effective method to control excitor/governor system by overlapping decomposition decentralized control strategy.     

The design of torque dynamic sliding mode controller in permanent magnet synchronous generator for wind turbine

Permanent magnet synchronous generator for wind turbine is a multivariable nonlinear system with strong coupling. Considering the influence of the volatile parameters of the generator on the performance of vector control, the torque dynamic sliding-mode control strategy is further studied. The proposed first order dynamic sliding-mode control strategy reduces the chattering by using a new switch function constituted with derivative element. With the dynamic sliding-mode controller in the power outer loop, the PMSG vector control system shows excellent robustness and insensitivity to the parameters and disturbance, which is confirmed by simulation.