Self-adaptive PID controller of microwave drying rotary device tuning on-line by genetic algorithms

The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.

Adaptive control of parallel manipulators via fuzzy-neural network algorithm

This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms （FNNA）. With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric uncertainties are eliminated. FNNA is used to handle model uncertainties and external disturbances. In the proposed control scheme, we consider modifying the weight of fuzzy rules and present these rules to a MIMO system of parallel manipulators with more than three degrees-of-freedom （DoF）. The algorithm has the advantage of not requiring the inverse of the Jacobian matrix especially for the low DoF parallel manipulators. The validity of the control scheme is shown through numerical simulations of a 6-RPS parallel manipulator with three DoF.

Adaptive Robust Control for A Class of Nonlinear Systems with Unknown Uncertainties

The problem of robust stabilization for nonlinear systems with partially known uncertainties is considered in this paper. The required information about uncertainties in the system is merely that the uncertainties are bounded, but the upper bounds are incompletely known. This paper can be viewed as an extension of the work in reference [1]. To compensate the uncertainties, an adaptive robust controller based on Lyapunov method is proposed and the design algorithm is also suggested. Compared with some previous controllers which can only ensure ultimate uniform boundedness of the systems, the controller given in the paper can make sure that the obtained closed-loop system is asymptotically stable in the large. Simulations show that the method presented is available and effective.

Optimization of digital multi-beamforming for space-based ADS-B using distributed cooperative coevolution with an adaptive grouping strategy

Space-based Automatic Dependent Surveillance-Broadcast(ADS-B)technology can eliminate the blind spots of terrestrial ADS-B systems because of its global coverage capability.However,the space-based ADS-B system faces new problems such as extremely low Signal-toNoise Ratio(SNR)and serious co-channel interference,which result in long update intervals.To minimize the position message update interval at an update probability of 95%with full coverage constraint,this paper presents an optimization model of digital multi-beamforming for space-based ADS-B.Then,a coevolution method DECCG_A&A is proposed to enhance the optimization efficiency by using an improved adaptive grouping strategy.The strategy is based on the locations of uncovered areas and the aircraft density under the coverage of each beam.Simulation results show that the update interval can be effectively controlled to be below 8 seconds compared with other existing methods,and DECCG_A&A is superior in convergence to the Genetic Algorithm(GA)as well as the coevolution algorithms using other grouping strategies.Overall,the proposed optimization model and method can significantly reduce the update interval,thus improving the surveillance performance of space-based ADS-B for air traffic control.

爆胎车辆动力学分析及模糊PID控制优化策略研究

车辆通过控制系统提高行驶的稳定性,但在爆胎时容易导致车辆行驶失去稳定性,从而造成车辆发生侧翻现象。为改善车辆动力学控制系统输出效果,建立了车辆轮胎动力学模型。引用模糊比例-积分-微分(PID)控制器,给出了模糊PID控制器输出参数与误差和误差变化率的关系图。提出人群搜索算法,利用人群搜索算法迭代搜索原理对模糊PID控制器参数进行寻优。以车辆2种行驶路况为例,利用Matlab软件对爆胎车辆的稳定性进行仿真,比较和分析爆胎车辆优化控制系统的输出效果。结果显示:采用模糊PID控制系统,爆胎车辆产生的偏航角、俯仰角加速度和侧倾角加速度较大。采用人群搜索算法优化模糊PID控制系统,爆胎车辆产生的偏航角、俯仰角加速度和侧倾角加速度较小。爆胎车辆采用人群搜索算法优化后的模糊PID控制器,不仅响应速度快,而且行驶的稳定性较好。

基于自适应模糊PID算法的锂电池组双层均衡控制

为提高电池重组时的均衡效率,在传统Buck-Boost均衡拓扑电路的基础上,设计了一种锂电池组双层均衡拓扑电路。组内采用Buck-Boost电路均衡,组间利用双向反激变压器进行均衡。均衡控制策略采用自适应模糊PID算法,以电池荷电状态(state of charge, SOC)为均衡变量,利用模糊控制算法对PID参数进行调节,缩短了均衡时间,提高了均衡效率。在Matlab/Simulink中搭建了锂电池组双层均衡拓扑电路和自适应模糊PID控制算法模型。实验结果表明:在不同工作状态下,所提出的电池组均衡拓扑及其控制策略将均衡时间效率平均提高了58.36%,验证了该方案的有效性。

Design of PID controller with incomplete derivation based on ant system algorithm

A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller.

基于改进自适应遗传算法的小径短绳自动打捆机步进电机PID控制

为提高小径短绳自动打捆机步进电机的控制精度,在分析经典遗传算法和经典自适应遗传算法的基础上,引入进化代数和个体适应值排名来指导自适应交叉率和自适应变异率,设计了一个基于改进自适应遗传算法的PID控制器,以削弱进化过程中优良参数的退化现象。MATLAB仿真结果表明,改进的自适应遗传PID提高了收敛精度,并具有更快的收敛速度。针对步进电机的实际测试结果表明,与经典遗传算法相比,改进的自适应遗传PID调整时间更短、超调量更低。

基于遗传算法前馈PID控制的电液伺服泵控系统性能研究

电液伺服泵控技术在液压支架、采煤机、掘进机、挖掘机等煤矿装备中得到了广泛应用,但在复杂工况下,其动作响应性和准确性受到较大影响,需进一步提高。在数学模型的基础上建立了关键部件仿真模型和系统模型,提出了基于遗传算法的前馈PID控制策略。利用MATLAB软件进行仿真,结果显示,阶跃压力信号响应曲线的稳态误差为0.1 MPa、响应时间为0.5 s,正弦压力信号跟随曲线的最大误差为0.02 MPa,较经典PID控制缩短了响应时间,降低了误差,整体性能得到提升。

模糊自适应PID对保险粉合成pH值的控制研究

保险粉合成过程pH值控制存在非线性、时滞性、不确定性问题,采用常规PID控制结合人工控制的方式无法实现参数自调整,对pH值的控制很难达到预期效果,为此,提出了模糊自适应PID控制方法。介绍了保险粉合成原理及反应方程式,分析酸碱中和pH值控制并确定系统的传递函数,设计了模糊自适应PID控制器,通过Matlab/Simulink进行仿真分析,并进行了实验验证,结果表明:模糊自适应PID控制与常规PID控制相比,具有超调量小、调节时间短、抗干扰能力强等优点,实现了对pH值的有效控制。

Simulation research on control algorithm of differential pressure casting process

To improve the precision of the filling pressure curve of differential pressure casting controlled with PID controller,the model of differential pressure casting process is established and two pressure-difference control systems using PID algorithm and Dahlin algorithm are separately designed in MATLAB. The scheduled pressure curves controlled with PID algorithm and Dahlin algorithm,respectively,are comparatively simulated in MATLAB. The simulated pressure curves obtained show that the control precision with Dahlin algorithm is higher than that with PID algorithm in the differential pressure casting process,and it was further verified by production practice.

基于自适应模糊PID的连续管作业机注入头速度控制研究

连续管作业机工作过程中起/下管速度控制主要依赖手动调节注入头泵的排量、马达压力等。为解决操作复杂、自动化程度低等问题,将连续管作业机注入头液压系统简化为闭式泵控马达系统,将传统手动控制方式改进为自动控制方式。分析泵控马达系统的工作原理,在AMESim中构建泵控马达系统的液压仿真模型;利用MATLAB/Simulink设计出AMESim仿真模型的PID及自适应模糊PID控制模型,从而构成整个系统的闭环控制联合仿真平台。采用PID算法及自适应模糊PID控制算法对系统响应进行仿真分析。结果表明:采用自适应模糊PID控制方式后,液压模型的响应速度更快、无超调和滞后现象、稳态误差更小,泵控马达系统具有良好的动态特性。

火电厂湿法烟气脱硫PH值模糊自适应PID控制

火电厂SO2的排放一直都是大气污染防治的重点,电厂脱硫系统的脱硫效率越高则排放出的气体越清洁,脱硫系统浆液池中浆液的PH值是影响脱硫过程中的关键要素。针对浆液PH值非线性,滞后性及大惯性的特点,论文提出了一种对浆液PH值的模糊自适应PID控制方法,对PID参数根据检测量的变化进行动态修正,实现自适应调节。对PID和模糊PID控制在Matlab/simulink内建模仿真,通过对两种响应曲线对比分析,可得出模糊自适应PID控制系统的振荡大小和及振荡次数、超调量、调整时间及系统的稳定性都优于传统PID控制,系统整体的控制性能都有明显的提升。

中频加热电源模糊自适应PID控制系统的设计与实现

针对中频感应加热电源控制系统存在着严重的非线性、参数时变性以及滞后性和惯性缺陷,同时考虑采用常规PID控制很难取得较好的控制效果,设计了一种模糊自适应PID控制系统。该系统结合模糊控制和常规PID控制两种算法的优势,利用模糊控制在线性整定和修改PID的控制参数,较好地解决了系统的存在问题,获得了良好的动态性能和静态性能。在分析模糊自适应PID控制算法的基础上,详细介绍了模糊化处理、模糊控制规则建立表以及模糊判决和决策表等,分别给出了模糊自适应PID控制参数在线整定程序流程,上位机程序的设计方法,系统硬件组成和工作原理,以及主要部件特性等。通过对系统MATLAB仿真分析,其结果表明:该系统与常规PID控制相比较,具有控制精度高、响应速度快、稳定性好的特点,明显改善了中频感应加热电源的控制效果,具有一定的推广价值。

洁净空调冷水阀门一阶惯性滞后PID独立控制方法

冷水阀门一阶惯性控制偏差项造成洁净空调温湿度控制效果较差。为此,提出洁净空调冷水阀门一阶惯性滞后PID独立控制方法。该方法在考虑室内环境基本信息的条件下,建立环境与冷水阀的一阶惯性滞后模型;计算室内洁净空调温湿度新风量,将其作为洁净空调冷水阀门的温湿度独立控制的约束;利用自适应免疫遗传算法优化PID控制器参数,以此为依据实现洁净空调冷水阀门温湿度的独立控制。实验结果表明,该方法控制效果较好、节能率较高。

铝型材数控加工中心的电气自适应PID控制研究

针对机械谐振、非线性摩擦等因素对铝型材数控加工中心的电气伺服系统运动控制精度的影响,研究铝型材数控加工中心的电气自适应PID控制。首先,分别建立铝型材数控加工中心电气伺服系统的电机环节与传动环节的数学模型,并根据模型设计PID控制器。然后,采用遗传算法整定控制器参数,形成自适应PID控制结构,从而实现铝型材数控加工中心的电气控制。结果表明,该设计方法在加工控制时的最大跟随误差为2.51μm,且对速度换向过程中非线性摩擦引起的跟随误差有抑制作用,证实了该方法的控制性能与自适应调整能力良好。

基于模糊自适应PID的SRM直接转矩控制系统研究

针对传统模糊控制器在控制过程中存在超调量大、控制精度不高以及静差等问题,提出了一种基于优化模糊自适应PID的开关磁阻电机控制方法。利用改进蝙蝠算法对模糊控制器进行优化,以外环模糊自适应PID控制器的输出变量为内环控制系统的参考转矩,送入直接转矩控制系统。仿真结果表明,经过算法优化的模糊自适应PID控制器在动态性能和鲁棒性方面明显优于传统模糊PID控制器,成功克服了模糊控制中存在的稳态误差和抗干扰能力不足的问题,有效解决了系统上升时间和超调之间的矛盾,同时显著减少了电机转矩的脉动。