Fuzzy Self-adaptive Proportional Integration Differential Control for Attitude Stabilization of Quadrotor UAV

The technology of attitude control for quadrotor unmanned aerial vehicles(UAVs) is one of the most important UAVs' research areas.In order to achieve a satisfactory operation in quadrotor UAVs having proportional integration differential(PID) controllers,it is necessary to appropriately adjust the controller coefficients which are dependent on dynamic parameters of the quadrotor UAV and any changes in parameters and conditions could affect desired performance of the controller.In this paper,combining with PID control and fuzzy logic control,a kind of fuzzy self-adaptive PID control algorithm for attitude stabilization of the quadrotor UAV was put forward.Firstly,the nonlinear model of six degrees of freedom(6-DOF) for quadrotor UAV is established.Secondly,for obtaining the attitude of quadrotor,attitude data fusion using complementary filtering is applied to improving the measurement accuracy and dynamic performance.Finally,the attitude stabilization control simulation model of the quadrotor UAV is build,and the self-adaptive fuzzy parameter tuning rules for PID attitude controller are given,so as to realize the online self-tuning of the controller parameters.Simulation results show that comparing with the conventional PID controller,this attitude control algorithm of fuzzy self-adaptive PID has a better dynamic response performance.

Adaptive proportional integral differential control based on radial basis function neural network identification of a two-degree-of-freedom closed-chain robot

A closed-chain robot has several advantages over an open-chain robot, such as high mechanical rigidity, high payload, high precision. Accurate trajectory control of a robot is essential in practical-use. This paper presents an adaptive proportional integral differential （PID） control algorithm based on radial basis function （RBF） neural network for trajectory tracking of a two-degree-of-freedom （2-DOF） closed-chain robot. In this scheme, an RBF neural network is used to approximate the unknown nonlinear dynamics of the robot, at the same time, the PID parameters can be adjusted online and the high precision can be obtained. Simulation results show that the control algorithm accurately tracks a 2-DOF closed-chain robot trajectories. The results also indicate that the system robustness and tracking performance are superior to the classic PID method.

Proportion Integration Differentiation(PID)Control Strategy of Belt Sander Based on Fuzzy Algorithm

Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts,a constant force control strategy combining fuzzy control and proportion integration differentiation(PID)was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism.The simulation results showed that compared with the classical PID control strategy,the system adjustment time was shortened by 98.7%,the overshoot was reduced by 5.1%,and the control error was 0.2%-0.5%when the system was stabilized.The optimized fuzzy control system had fast adjustment speeds,precise force control and stability.The experimental analysis of the surface morphology of the machined blade was carried out by the industrial robot abrasive grinding mechanism,and the correctness of the theoretical analysis and the effectiveness of the control strategy were verified.

The Bezier Control Points Method for Solving Delay Differential Equation

In this paper, Bezier surface form is used to find the approximate solution of delay differential equations (DDE’s). By using a recurrence relation and the traditional least square minimization method, the best control points of residual function can be found where those control points determine the approximate solution of DDE. Some examples are given to show efficiency of the proposed method.

A differential control method for the proportional directional valve

For the proportional directional valve controlled by two proportional solenoids, the normal control method(NCM) energizes only one solenoid at a time. The performance of the valve is greatly influenced by the nonlinearity of the proportional solenoid, such as dead zone and low force gain with a small current, and this effect cannot be eliminated by a simple dead-zone current compensation. To avoid this disadvantage, we propose the differential control method(DCM). By employing DCM, the controller outputs differential signals to simultaneously energize both solenoids of the proportional valve, and the operating point is found by analyzing the force output of the two solenoids to make a minimum variation of the current force gain. The comparisons of the valve response characteristics are made between NCM and DCM by nonlinear dynamic simulation and experiments. Simulation and experimental results show that by using DCM, the frequency response of the valve is greatly enhanced, especially when the input is small, which means that the dynamic characteristics of the proportional valve are improved.

A new approach to detecting weak signal in strong noise based on chaos system control

In this paper, a chaos system and proportional differential control are both used to detect the frequency of an unknown signal. In traditional methods the useful signal is obtained through the Duffing equation or other chaotic oscillators. But these methods are too complex because of using a lot of chaos oscillators. In this paper a new method is presented that uses the Rossler equation and proportional differential control to detect a weak signal frequency. Substituting the detected signal frequency into the RSssler equation leads the Rossler phase state to be considerably changed. The chaos state can be controlled through the proportional differential method. Through its phase diagram and spectrum analysis, the unknown frequency is obtained. The simulation results verify that the presented method is feasible and that the detection accuracy is higher than those of other methods.

Active Disturbance Rejection Control for a Multiple-Flexible-Link Manipulator

The control problem of multiple-flexible-link manipulators( MFLMs) is studied in this paper.The dynamic model of MFLM is derived and separated into two-time scale by utilizing the singular perturbation technique. The active disturbance rejection control( ADRC) is adopted to the slow subsystem to track a desired trajectory. The proposed ADRC structure preshapes the desired trajectory by utilizing the tracking differentiator,estimates the disturbance and internal states with an extended state observer,and guarantees a robust performance by combining a feedback controller with a feedforward term. Two types of feedback controllers are designed,proportional derivative( PD) controller and nonlinear PD( NPD) controller. For the fast subsystem,a fast stabilizing control is designed according to the standard linear quadratic regulator approach. Simulations are performed to evaluate the proposed control scheme.Results show that,compared with the traditional PD controller,the ADRC structure based control scheme has smaller overshot and shorter settling time,suppresses vibration quickly,and is robust to the maneuver speed. In general,the control scheme utilizing ADRC structure and NPD feedback controller shows better performance.

Research on the Low-order Control Strategy of the Power System With Time Delay

In this paper, the design problem of the low-order controller is considered for the power system with a fixed time delay. A linear model of the power system with time delay is firstly established. Then the proportional-integral-differential(PID) controller, which is the typical low-order controller, is designed to improve the stability of the power system. The stabilizing region of the PID controller is obtained. The control parameters chosen arbitrarily in the resultant region can ensure the stability of the power system. Finally, based on the stabilizing result, the PID controller satisfying the H∞performance index is designed, which improves the robustness of the whole power system. The main advantage of the proposed method lies in that there is no need to approximate the model of the power system.The method can be further extended to the power system which is more complex.

Stable Transition of Quadruped Rhythmic Motion Using the Tracking Differentiator

Since the quadruped robot possesses predominant environmental adaptability,it is expected to be employed in nature environments. In some situations,such as ice surface and tight space,the quadruped robot is required to lower the height of center of gravity( COG) to enhance the stability and maneuverability. To properly handle these situations,a quadruped controller based on the central pattern generator( CPG) model,the discrete tracking differentiator( TD) and proportional-derivative( PD) sub-controllers is presented. The CPG is used to generate basic rhythmic motion for the quadruped robot. The discrete TD is not only creatively employed to implement the transition between two different rhythmic medium values of the CPG which results in the adjustment of the height of COG of the quadruped robot,but also modified to control the transition duration which enables the quadruped robot to achieve the stable transition. Additionally,two specific PD sub-controllers are constructed to adjust the oscillation amplitude of the CPG,so as to avoid the severe deviation in the transverse direction during transition locomotion. Finally,the controller is validated on a quadruped model. A tunnel with variable height is built for the quadruped model to travel through. The simulation demonstrates the severe deviation without the PD sub-controllers,and the reduced deviation with the PD sub-controllers.

Structure Analysis and Control Optimization on High Speed Lift Platform

Dynamic analysis of scissor hydraulic lift platform has been performed to invest/gate the key factors which determine size and shape of the platfolan. By using MATLAB, the position of hydraulic cylinder has been optimized to reduce jacking force of piston and the whole system. Thus structure deformation decreases which is beneficial to control accuracy. Additionally, a new proportion integration differentiation （PID） control mode based on BP neural network has been developed to improve the stability and accuracy for the pasitio^L control in this system. Compared with existing PID tuning meth~~ls and fuzzy self-adjusted PID controllers, the proposed back propagation （BP） based PID controller can achieve better performance for a wide range of complex processes and realize self-tuning of parameters. It was confirmed that the performance of the lift platform regarding the force variation and position accuracy was greatly enhanced by optimizing of the system both in structure and control. Considerable economic benefit can also be achieved thrangh the application of this intelligent PID system.

Stability Improvement of Power System by Using PI ＆ PD Controller

This paper presents the model of a SVC （Static VAR Compensator） which is controlled externally by a PI （Proportional Integral） ＆ PD （Proportional Differential） controllers for the improvements of voltage stability and damping effect of an on line power system. Both controller parameters has been optimized by using Ziegler-Nichols close loop tuning method. Both single phase and three phase （L-L） faults have been considered in the research. In this paper, a power system network is considered which is simulated in the phasor simulation method ＆ the network is simulated in four steps; without SVC, With SVC but no externally controlled, SVC with PI controller ＆ SVC with PD controller. Simulation result shows that without SVC, the system parameters become unstable during faults. When SVC is imposed in the network, then system parameters become stable. Again, when SVC is controlled externally by PI ＆ PD controllers, then system parameters becomes stable in faster way then without controller. It has been observed that the SVC ratings are only 50 MVA with controllers and 200 MVA without controllers. So, SVC with PI ＆ PD controllers are more effective to enhance the voltage stability and increases power transmission capacity of a power system. The power system oscillations are also reduced with controllers in compared to that of without controllers. So with both controllers the system performance is greatly enhanced.

APPLICATION OF NONLINEAR PID CONTROLLER IN AERODYNAMICS LOADING SYSTEM

The design idea of tracking-differentiator and the nonlinear PID controllerare introduced, the applicable algorithm and its real result for distributed aerodynamicsloading control system are discussed, and the construction of the test & contro1 system arealso presented. The application shows that the nonlinear PID algorithm has the advan-tages of high reliability, short run time and strong stability.

Design of the PLC-based burner Control System

With consideration to the acid gas incinerator burned and the problems identified during its application, renovation program has been proposed. According to the new design, draught burners with automatic control system shall be used to eliminate problems encountered during application of original burner. In addition to implement automatic control of combustion processes, the new system may minimize labor intensity and enhance safety of facilities.

模型信息联合校正型自抗扰控制策略

为解决微电网受到不确定扰动时,会对直-直变换器输出的电能质量产生严重影响的问题,该文提出一种模型信息联合校正型自抗扰控制技术(ADRC-MIR)。在该控制策略中,首先借助串联超前校正的思想,以比例微分校正环节对线性扩张状态观测器的扰动观测传递函数进行修正,使其可实现对总和扰动更精确的跟踪;然后,根据状态空间平均法从被控系统中提取部分模型信息,将其写入修正后的线性扩张状态观测器的系数矩阵并最终构建出ADRC-MIR;随后基于理论推导,给出改进控制器的参数整定公式及其物理意义,并从噪声抑制、扰动抑制及其频域特性等方面指出改进后的控制器可提升控制品质的原因。最后通过对比不同工况下的数值仿真验证所提控制策略的可行性与正确性。

Application of linear active disturbance rejection control for photoelectric tracking system

Dynamic characteristics and tracking precision are studied in the photoelectric tracking system and a linear active disturbance rejection control( LADRC) scheme is proposed for position loop. A current and speed controller is designed by a transfer function model,which is obtained by adaptive differential evolution. Model error,friction and nonlinear factor existing in position loop are treated as ‘disturbance',which is estimated and compensated by generalized proportional integral( GPI)observer. Comparative results are provided to demonstrate the remarkable performance of the proposed method. It turns out that the proposed scheme is successful and has superior features,such as quick dynamic response,low overshoot and high tracking precision. Furthermore,with the proposed method,friction is suppressed effectively.

基于改进麻雀优化PID的波浪补偿控制方法

随着海上风电“十四五”规划的不断推动,在深远海域对兆瓦级大功率海上风机的需求量随之增加,其规模也在不断扩大。但是,在吊运、安装等海上工作过程中,复杂海浪对船舶产生的持续影响导致风机安装的精度和效率大幅下降,甚至会对人员安全以及财产造成重大损失。在深远海域复杂海况下对工程船舶进行有效的波浪补偿,可提供稳定的作业环境以保证精准高效地完成各项工作,因此,本文提出了一种基于改进麻雀优化PID的波浪补偿控制方法并将其应用于Stewart补偿平台。首先,建立波浪补偿平台动力学以及运动学反解模型,并设计正解模型迭代求解算法。随后,使用PID进行波浪补偿控制,并通过麻雀搜索算法优化参数。接着,采用Circle混沌映射对其进行初始化分布,以解决初始化不均匀的问题;并采用动态自适应加权、柯西突变以及反向学习以提升算法全局寻优能力。最后,生成4~6级海况下的某工程船运动数据作为系统输入,利用MATLAB和Simulink软件平台搭建模型进行补偿控制验证,并在Stewart硬件平台上做补偿试验。结果表明,改进麻雀搜索算法具有较快的收敛速度、较高的精度和更好的寻优能力,优化后的PID控制方法更适合用于复杂海况下波浪补偿平台的控制优化,可为大功率海上风机安装的补偿平台控制系统设计提供参考。

Feed-Forward-Like Decoupling Control in Coagulation Bath of Carbon Fiber Precursor

The coagulation bath system of carbon fiber precursor is a complicated and multivariable coupling system. Based on the model of industrial production,the full dynamic decoupling control of the coagulation bath system of carbon fiber precursor is achieved in combination with multivariable feed-forward-like decoupling and proportional-integral-differential( PID) control. Compared with the conventional PID decoupling control,the experiment results show that the proposed method has a better control effect. The use of the controller can achieve complete decoupling of three parameters from coagulation bath system. The method should have great applications.

数控压机伺服控制系统复合控制器I-ABC与PID优化

为了提高数控压机伺服控制系统的控制精度,针对伺服控制系统运行控制过程构建数学模型,在人工蜂群算法基础上融入了云分析模型,之后采用改进人工蜂群算法(Improved Artificial Bee Colony,I-ABC)调节比例-积分-微分(Proportional Integral Differential,PID)参数,建立了一种复合控制方法。研究结果表明:以I-ABC进行PID控制时,可以使幅度差降低到0.4%,相位差基本在-0.54°之内,系统加载精度也获得了明显提升,表现出了更优的跟踪性能。以I-ABC进行PID控制时,能够对多余力起到明显抑制作用,响应速度也获得明显提升,可以有效满足系统的准确控制要求。在系统内加入干扰信号,引入I-ABC实施PID调节可以减小系统超调量,还可以获得更短调节时间,使系统获得更强抗干扰性能。

磁力馈能主动悬架稳定性分析

为了提高车辆行驶平顺性和安全性,提出了一种新型磁力馈能主动悬架,并研究其稳定性。采用BP神经网络PID控制算法(BP-PID)搭建磁力馈能主动悬架控制系统,利用MATLAB/Simulink进行理论仿真。建立B级和C级随机路面,仿真分析不同速度、不同等级下,磁力馈能主动悬架的稳定性。结果表明,相比于被动悬架效果和PID控制的磁力馈能主动悬架效果,采用BP-PID控制可明显提高悬架稳定性。B级随机路面60 km/h时车身垂直加速度改善了45.90%,证明了BP-PID控制的合理性,可有效提升悬架稳定性。

低附着路况条件下车辆横向稳定性控制

针对在冰雪环境下车辆横向稳定控制,为解决在低附着、分布不均的路面情况下车辆对参考轨迹的稳定跟踪问题,设计了基于神经网络调节的模糊PID(Proportional-Integral-Differential)制器,以及基于线性化车辆模型的模型预测控制(MPC:Model Predictive Controll)。以路面附着系数及车辆速度作为输入构建BP(Back-Propagation)神经网络,输出调节系数优化模糊PID控制器控制性能;设计了十自由度模型表征车辆在冰雪环境下的动力学特性,使用MPC实现车辆横向稳定控制。使用CarSim/Simulink进行联合仿真实验,结果表明该控制器能显著提高车辆轨迹跟踪性能。