Aircraft Electric Anti-skid Braking System Based on Fuzzy-PID Controller with Parameter Self-adjustment Feature

The principle of electric braking system is analyzed and an anti-skid braking system based on the slip rate control is proposed.The fuzzy-PID controller with parameter self-adjustment feature is designed for the anti-skid braking system.The dynamic model of aircraft ground braking is established in the simulation environment of MATLAB/SIMULINK,and simulation results of dry runway and wet runway are presented.The results show that the fuzzy-PID controller with parameter self-adjustment feature for the electric anti-skid braking system keeps working in the state of stability and the brake efficiencies are increased to 93%on dry runway and 82%on wet runway respectively.

Design Method for the Magnetic Bearing Control System with Fuzzy-PID Approach

The five degree freedom magnetic bearing is researched and its structure and working principles are introduced also. Based on the fuzzy control technology, combining fuzzy algorithm and PID control method, identifying the transition process mode of the online system to get the PID parameters＇ self-adjusting, the magnetic beating system＇s Fuzzy-PID nonlinear controller is designed by analyzing the system control demands. The Fuzzy-PID nonlinear controller can deal with the magnetic bearing system＇ s open loop instability and strong nonlinearity, and the approach could improve the system＇s rapidity, adaptability, stability and dynamic characteristics. Comparative analysis and experiments are conducted between linear PID and nonlinear fuzzy- PID control methods, the results show that the fuzzy-PID controller is better, and the five-freedom magnetic bearing＇ s rotary precision experiments are conducted by the fuzzy-PID controller, it satisfies the control rotary precision demands and realizes the hearing＇s steady floating and rotating.

Performance analysis of semi-active cab’s hydraulic system of the vibratory roller using optimal fuzzy-PID control

In order to evaluate the performance of semi-active cab’s hydraulic mounts(SHM)of the off-road vibratory roller with the optimal fuzzy-PID(proportional integral derivative)control,a nonlinear dynamic model of the vehicle interacting with off-road terrains is established based on Matlab/Simulink software.The weighted root-mean-square(RMS)acceleration responses of the driver’s seat heave and the cab’s pitch angle are chosen as objective functions.The SHM is then optimized and analyzed via the optimal fuzzy-PID control under different operation conditions.The simulations results show that the driver’s ride comfort and the cab shaking are greatly affected by the off-road terrains under various operating conditions of the vehicle,especially at the speed from 8 to 12 km/h on a very poor terrain surface of Grenville soil ground under the vehicle travelling.With SHM using the optimal fuzzy-PID control,the driver’s ride comfort and the cab shaking are clearly improved under various operation conditions of the vehicle,particularly at the speed from 6 to 7 km/h of the vehicle traveling.

Implementation of Fuzzy-PID in Smart Car Control

An unmanued smart car control system and the fuzzy-PID control algorithm are produced.A design scheme of fuzzy-PID controller is put forward.The simulation analysis from matlab indicated that the dynamic performance of fuzzy-PID control algorithm is better than that of usual PID.Experimental result of smart car show that it can follow the black guid line well and fast-stable complete running the whole trip.

OPTIMIZED REVERSIBLE ARITHMETIC LOGIC UNITS

Arithmetic Logic Unit(ALU) as one of the main parts of any computing hardware plays an important role in digital computers. In quantum computers which can be realized by reversible logics and circuits, reversible ALUs should be designed. In this paper, we proposed three different designs for reversible 1-bit ALUs using our proposed 3×3 and 4×4 reversible gates called MEB3 and MEB4(Moallem Ehsanpour Bolhasani) gates, respectively. The first proposed reversible ALU consists of six logical operations. The second proposed ALU consists of eight operations, two arithmetic, and six logical operations. And finally, the third proposed ALU consists of sixteen operations, four arithmetic operations, and twelve logical operations. Our proposed ALUs can be used to construct efficient quantum computers in nanotechnology, because the proposed designs are better than the existing designs in terms of quantum cost, constant input, reversible gates used, hardware complexity, and functions generated.

A New Coordinated Fuzzy-PID Controller for Power System Considering Electric Vehicles

With penetration growing of renewable energy sources which integrated into power system have caused problems on grid stability. Electric Vehicles (EV) are one of the renewable energy sources that can bring significant impacts to power system during their charging and discharging operations. This article established a model of single machine infinite bus (SMIB) power system considering EV as a case study of load disturbance for power system oscillation. The objective of this research is to enhance stability and overcome the drawbacks of traditional control algorithms such as power system stabilizer (PSS), PID controller and fuzzy logic controller (FLC). The implementation’s effect of FLC parallel with PID controller (Fuzzy-PID) has been shown in this paper. The speed deviation (?ω) and electrical power (Pe) are the important factors to be taken into consideration without EV (only change in mechanical torque), EV with change in the mechanical torque and sudden plug-in EV. The obtained result by nonlinear simulation using Matlab/Simulink of a SMIB power system with EV has shown the effectiveness of using (Fuzzy-PID) against all disturbances.

基于模型预测控制的多能源微网仿射优化调度

受源荷日前预测误差较大的影响,多能源微网存在优化调度方案变化范围较大,且难有足够的不确定性应对裕度的问题。为解决上述问题,提出一种基于模型预测控制的多能源微网仿射优化调度方法。首先,通过不断更新预测信息以保证源荷预测精度。在此基础上,采用仿射算法表征源荷预测的不确定性。然后,将仿射优化调度模型嵌入滚动优化中,并在每次滚动优化中求解仿射优化调度模型。最后,仿真结果验证了所提方法能够有效降低优化调度方案的保守性与提高不确定性应对能力。

A Mode-Switching Motion Control System for Reactive Interaction and Surface Following Using Industrial Robots

This work proposes a sensor-based control system for fully automated object detection and exploration(surface following) with a redundant industrial robot. The control system utilizes both offline and online trajectory planning for reactive interaction with objects of different shapes and color using RGBD vision and proximity/contact sensors feedback where no prior knowledge of the objects is available. The RGB-D sensor is used to collect raw 3D information of the environment. The data is then processed to segment an object of interest in the scene. In order to completely explore the object, a coverage path planning technique is proposed using a dynamic 3D occupancy grid method to generate a primary(offline) trajectory. However, RGB-D sensors are very sensitive to lighting and provide only limited accuracy on the depth measurements. Therefore, the coverage path planning is then further assisted by a real-time adaptive path planning using a fuzzy self-tuning proportional integral derivative(PID)controller. The latter allows the robot to dynamically update the 3D model by a specially designed instrumented compliant wrist and adapt to the surfaces it approaches or touches. A modeswitching scheme is also proposed to efficiently integrate and smoothly switch between the interaction modes under certain conditions. Experimental results using a CRS-F3 manipulator equipped with a custom-built compliant wrist demonstrate the feasibility and performance of the proposed method.

Application of Fuzzy Logic Controller to Level Control of Twin-Roll Strip Casting

An intelligent fuzzy-PID controller consisting of fuzzy logic controller and PID controller was developed to control the molten steel level of twin-roll strip caster.Additionally,a feedforward differential PID controller was used for stopper position control in order to avoid differential kick.It is proved by simulation that the proposed intelligent controller is able to obtain zero steady state error asymptotically and the control system is robust due to its fuggy behavior of the controller.

Kolmogorov-Chaitin Complexity of Digital Controller Implementations

The complexity of linear, fixed-point arithmetic digital controllers is investigated from a Kolmogorov-Chaitin perspective. Based on the idea of Kolmogorov-Chaitin complexity, practical measures of complexity are developed for statespace realizations, parallel and cascade realizations, and for a newly proposed generalized implicit state-space realization. The complexity of solutions to a restricted complexity controller benchmark problem is investigated using this measure. The results show that from a Kolmogorov-Chaitin viewpoint, higher-order controllers with a shorter word-length may have lower complexity and better performance, than lower-order controllers with longer word-length.

THEORETICAL AND EXPERIMENTAL STUDY ON THE PRESSURE AND VACUUM CONTINUOUS CONTROL SYSTEM BASED ON HYBRID PUMP

A novel pressure and vacuum continuous control system, which adopts a hybrid pump as pressure and vacuum source, is presented. The mathematical model of the system is developed. The theoretical simulation and analysis on the system are implemented in order to study the relationships among the characteristics, parameters and working points of the system. The experimental investigations on the system characteristics are presented with the adoption ofa fuzzy-PID controller. The simulation and experimental results indicate that the pressure and vacuum continuous control system based on hybrid pump has good dynamic and static performance, strong robustness and satisfactory adaptability to various system parameters. According to the results, system can successfully gain high accuracy and fast response signal. Also, the mathematical model of system is also testified by the experimental results.

Adaptive nonlinear model predictive control design of a flexible-link manipulator with uncertain parameters

This paper presents a novel adaptive nonlinear model predictive control design for trajectory tracking of flexible-link manipulators consisting of feedback linearization, linear model predictive control, and unscented Kalman filtering. Reducing the nonlinear system to a linear system by feedback linearization simplifies the optimization problem of the model predictive controller significantly, which, however, is no longer linear in the presence of parameter uncertainties and can potentially lead to an undesired dynamical behaviour. An unscented Kalman filter is used to approximate the dynamics of the prediction model by an online parameter estimation, which leads to an adaptation of the optimization problem in each time step and thus to a better prediction and an improved input action. Finally, a detailed fuzzy-arithmetic analysis is performed in order to quantify the effect of the uncertainties on the control structure and to derive robustness assessments. The control structure is applied to a serial manipulator with two flexible links containing uncertain model parameters and acting in three-dimensional space.

Intelligent PID Control of Pneumatic Rotary Actuator Angle Servo-System

In order to solve the problems that make the orientation of pneumatic rotary actuator inaccurate, a newly intelligent PID control algorithm is proposed. Pneumatic rotary actuator angle servo-system uses electropneumatic proportional valve as control device, which changes the pressure of cavity and then pushes the actuator to revolve to the expected position. Using intelligent PID control algorithm, several special methods were put forward to overcome the connatural shortcomings of pneumatic system and make the rotary actuator track the expected value timely and accurately. Experimental results have shown that by using this intelligent algorithm, the performance index of system was improved greatly.

Position Control of Single Pneumatic Muscle Actuator

The PID, fuzzy, self-organized fuzzy and self-organized fuzzy-PID controllers are adopted in the position control of single pneumatic muscle actuator. Experiments show that the self-organized fuzzy-PID is obviously effective for the position control of single pneumatic muscle actuator, which can realize precision within 0.3 mm and withstand 18?N variable load plus about 36?N fixed load. It is relatively precise and robust.

Measurement and AFPS control of molten steel level in strip casting

The measurement and control of the molten steel level are studied, which affect the quality of strip surface in strip casting. A system of molten steel measurement with a CCD (Charge Coupled Devices) sensor is designed, real-time measured data are given and its precision is analyzed. The level fluctuation model is derived, and an adaptive fuzzy-PID controller with supervisory control (AFPS) is proposed. The stability of the system is proved using Lyapunov theorem, and the simulation results are given when the model, the casting speed and the roll gap change. It is suggested that this kind of coupled nonlinear and time varying system is stable and robust using the designed AFPS controller.

Wind Turbine Speed Compound Control of a New-Type Wind-Electric Hybrid Power Pumping Unit

Because the load of the oil beam pumping unit driven by pure electric motor changes sharply during operation,the power of the driving motor does not match and the energy efficiency is low.In this paper,a new type of wind-driven hydro-motor hybrid power system is proposed.The motor and the hydraulic motor are jointly driven,and the energy is recovered by a hydraulic pump with controllable displacement,so that the speed of the driving motor is relatively stable.In order to control the fan speed and keep up with the drastic changes of the outside wind speed,a control strategy of hybrid power system based on wind speed feed-forward compensation is proposed.Through simulation and experimental results,the following conclusions can be drawn:to begin with,the mathematic model is proved to be effective;next,simulation studies show that the proposed feed-forward control method can improve the response rate as well as reduce the response lag.This research can be a reference for the application of the feed-forward control method on the hybrid power system of beam pumping unit.system.

基于FPGA高速浮点控制算法的设计架构与应用

为满足控制系统对高速处理、高精度运算的需求,提出一种基于现场可编程门阵列(FPGA)的高速浮点控制算法的设计架构。利用System Generator工具设计浮点控制算法并生成其IP核;VHDL编写模/数(A/D)、数/模(D/A)转换芯片的驱动逻辑;而后顶层中按照时序逻辑关系连接各模块;最终在FPGA中实现硬件控制。将算法设计架构应用在快速反射镜的闭环控制中,实验结果表明:单精度浮点格式的PID算法执行时间为2~3个采样周期,整个控制算法最快执行仅需10个时钟周期,闭环控制周期为6.55μs。实验验证了提出的算法设计架构具有可行性;该架构设计的控制器具有高速的处理性能和高精度的控制效果。

大林算法在氨汽化温度控制系统中的应用研究

针对某合成氨工艺液氨汽化过程的大滞后特性,研究了大林控制算法的基本原理和适用性。通过对现场生产数据进行辨识获得被控对象数学模型,利用西门子S7系列PLC控制平台,编制了基于大林算法的液氨汽化温度控制程序,并在仿真实验中取得了良好的控制效果,对工程实际应用具有良好的参考意义。

基于模糊神经网络PID控制的双向DC/DC变换器

为提高交错并联双向DC/DC变换器的动态性能与抗干扰能力,提出一种基于模糊神经网络PID的控制方法.建立并联交错双向DC/DC变换器的小信号数学模型,得到输出电压与电感电流的传递函数;设计模糊神经网络PID控制器,应用到变换器双闭环控制的电压外环.仿真结果表明:与模糊PID控制、RBF神经网络PID控制相比,Buck模式下,模糊神经网络PID控制下的变换器输出电压达到稳态的时间为15 ms,超调量为1%,加入扰动后30 ms即可恢复稳态;Boost模式下的仿真结果与Buck模式相似,证明了模糊神经网络PID控制方法的优越性和有效性.

基于Arduino与Processing互动编程的特种仓库智能测控系统设计

基于Arduino与Processing互动编程方式进行特种仓库智能测控系统设计。该系统以Arduino为主控单元,利用各种传感器实时采集库区火情、烟雾、温度、湿度、有害气体浓度等关键参数;采用中位值平均滤波法对参数进行处理,并根据库内参数发出相应控制信号,作用于对应节点设备,实现自动控制。同时,保留人工干预措施,仓库管理人员可以根据库内环境参数做出相应的管控措施。所设计系统是集常规监测、自动控制、无人值班等功能于一体的智能化系统,对弹药、危险品、生化物品等高危物品的存储有一定的借鉴意义。