Optimal-tuning PID control for industrial systems

Three optimal-tuning PID controller design schemes are presented for industrial control systems in this paper. They are time-domain optimal-tuning PID control, frequency-domain optimal-tuning PID control and multiobjective optimal-tuning PID control. These schemes can provide optimal PID parameters so that the desired system specifications are satisfied even in case where the system dynamics are time variant or the system operating points change. They are applied to three industrial systems, a hydraulic position control system, a rotary hydraulic speed control system and a gasifier, respectively.     

Optimal-tuning nonlinear PID control of hydraulic systems

An optimal-tuning nonlinear PID controller design strategy is proposed for hydraulic systems. After an analysis of these systems, an analytic physical dynamical model with dead-zone nonlinearity is derived. A nonlinear PID control scheme with the inverse of the dead zone is introduced to overcome the dead zone in the hydraulic systems. An optimal PID controller is designed to satisfy some desired time-domain performance requirements. Using an estimated process model, the optimal-tuning PID control provides optimal PID parameters even when the process dynamics are time variant. This strategy is implemented in an environment composed of dSPACE, MATLAB, SIMULINK and Real-Time Workshop. The performance of the controller is demonstrated on a hydraulic position control test rig.     

模糊PID控制器在自适应巡航控制系统中的应用

车辆的油门控制算法是自适应巡航控制系统(ACC：Adaptive Cruise Control)中的核心算法之一。这里采用的模糊PID算法(Fuzzy PID)是对常用的两输入单输出模糊控制算法的改进。通过使用Matlab／Simulink建立车辆动力学模型和控制器模型,对控制器的性能进行了仿真分析,验证了算法的合理性。     

Incremental Q-learning strategy for adaptive PID control of mobile robots

Expert and intelligent systems are being developed to control many technological systems including mobile robots. However, the PID (Proportional-Integral-Derivative) controller is a fast low-level control strategy widely used in many control engineering tasks. Classic control theory has contributed with different tuning methods to obtain the gains of PID controllers for specific operation conditions. Nevertheless, when the system is not fully known and the operative conditions are variable and not previously known, classical techniques are not entirely suitable for the PID tuning. To overcome these drawbacks many adaptive approaches have been arisen, mainly from the field of artificial intelligent. In this work, we propose an incremental Q-learning strategy for adaptive PID control. In order to improve the learning efficiency we define a temporal memory into the learning process. While the memory remains invariant, a non-uniform specialization process is carried out generating new limited subspaces of learning. An implementation on a real mobile robot demonstrates the applicability of the proposed approach for a real-time simultaneous tuning of multiples adaptive PID controllers for a real system operating under variable conditions in a real environment.     

强制循环蒸发系统的非线性自适应解耦PID控制

本文结合现场的实际过程数据,首先应用能量平衡建立了强制循环蒸发过程的动态模型.针对该过程的多变量、非线性以及强耦合特性,在常规增量式PID控制器的基础上提出基于神经网络与多模型切换的非线性自适应解耦PID控制策略.该控制器是由线性自适应解耦PID控制器和基于神经网络的非线性自适应解耦PID控制器以及切换机构组成.其中线性自适应解耦PID控制器可以保证系统的稳定,而基于神经网络的非线性自适应解耦PID控制器则可以有效地提高系统的性能.上述过程的PID参数是通过广义预测的方法得到,最后通过仿真表明,上述控制方法不仅消除了回路间的耦合,在稳定生产的同时提高了蒸发的效率.     

飞机纵向运动模型参考反推自适应PID控制

为克服飞行控制系统设计中传统增益规划方案的缺点,提出一类飞机纵向运动模型参考反推自适应PID控制方案,并给出了该方案的具体设计过程和跟踪性能改善方法．理论分析和数值仿真结果表明．该方案兼具反推自适应控制和PID控制的优点．即：无需知道被控对象的精确数学模型,控制器结构简单,鲁棒性强,在不增大控制增益的前提下具有良好的跟踪性能．     

Decentralized adaptive control: structural conditions for stability

Decentralized adaptive control schemes are presented for a class of large-scale interconnected systems. These schemes have the advantage that in addition to the standard assumption about the uncertainty of the subsystems, the strength of interconnection is assumed unknown. Provided certain structural constraints are satisfied, the adaptation gains automatically adjust to levels that assure stability of the overall system. Simulations of a spring-coupled dual pendulum showed that for high interconnection strengths, the proposed algorithm exhibits better tracking performance than existing algorithms     

磁悬浮系统的模糊自适应PID控制

针对磁悬浮系统开环不稳定、强烈非线性等特性,结合PID控制和模糊控制的优点,提出一种改进的模糊自适应PID控制方法(IFPID).将微分环节从模糊控制器中剥离出来,只对比例和积分参数进行模糊整定.设计时采用非线性模糊化,利用S-函数建立磁悬浮系统的非线性模型并进行仿真.仿真结果表明,IFPID控制系统的抗干扰和适应参数变化的能力都优于常规PID控制,具有较好的动态特性和稳定性.     

磁悬浮自适应控制

以自适应PID结构针对磁悬浮系统设计非线性控制器，并在磁悬浮球装置上进行了试验，结果证实这种控制器具有完全的鲁棒性、良好的参数适应性，设计方法也有广泛的适用性。     

基于自适应模糊PID的UCAV姿态控制

针对UCAV刚体六自由度模型非线性强耦合的特点,结合专家经验设计了一种自适应模糊PID姿态控制方法。利用小扰动原理对UCAV非线性模型线性化,得到了纵向和横侧向通道的状态空间表达式,实现了纵向和横侧向通道的解耦。针对纵向通道的俯仰角和速度以及横侧向通道的滚转角对设计的自适应模糊PID控制器进行了仿真验证,结果表明该控制器具有较快的响应速度和较高的稳定性,能够有效控制UCAV实现预期姿态。     

铁路防尘自动喷洒系统的模糊自适应PID控制研究

针对大滞后、非线性的自动喷洒试验系统,进行了模糊自适应整定参数的PID控制策略研究.对运煤车防尘自动喷洒系统进行了分析;设计了模糊自适应PID控制器;在MATLAB语言环境下编写仿真控制程序.仿真运行结果表明控制方案的有效性和正确性.     

自适应PID的薄壁筒体TIG焊接熔透控制研究

在薄壁筒体环缝焊接中,工艺参数以及坡口尺寸的波动都会导致焊接熔透状态的变化。为保证稳定的熔透,需要对焊接熔透状态进行实时检测和控制。针对薄壁筒体环缝TIG焊,建立了基于视觉传感的直接传感法,获取了清晰的熔池背面图像,经图像处理得到了满足熔透要求的熔池背面熔宽范围,并通过自整定PID控制器调节焊接速度,对熔透状态进行自适应控制。结果表明,该方法对熔透状态信号提取可靠,基本消除了熔透状态间接传感法的控制盲区。     

小型无人机纵向姿态模糊自适应PID控制与仿真

针对某小型实验无人机智能自主飞行的要求,提出了一种无人机纵向姿态的模糊控制方法,设计了模糊自适应PID控制器,可有效实现该无人机的纵向姿态控制和纵向航迹跟踪.仿真结果表明,所设计的模糊自适应PID控制器较传统的PID控制器具有更好的控制性能,其响应快、超调小、精度高,而且鲁棒性和自适应能力也较强,可满足自主飞行的要求.     

基于PLC的中央空调模糊自适应PID监控系统

针对中央空调系统存在非线性、不确定性和干扰性等问题,提出了利用MATLAB实现模糊自适应PID控制,并对系统进行了编程仿真实验。仿真结果表明,将该方法应用在中央空调系统中是可行的,但是MATLAB不能与现场设备进行直接数据通信。因此将MATLAB和PLC控制相结合,利用OPC技术实现MATLAB和PLC之间的动态数据交换,达到智能控制的目的。     

Optimal-tuning PID controller design in the frequency domain with application to a rotary hydraulic system

In this paper a new PID controller design scheme that uses optimisation in the frequency domain is proposed for industrial process control. An optimal-tuning PID controller is designed to satisfy a set of frequency-domain performance requirements: gain margin, phase margin, crossover frequency and steady-state error. Using an estimated process frequency response, the method can provide optimal PID parameters even in cases where the process dynamics are time variant. This scheme is demonstrated through its application to a rotary hydraulic system and its performance is compared with six alternative PID tuning rules.     

基于Q学习的供热末端自适应PID控制算法

城市建筑集中供热末端“全开”和“全关”控制方式不仅热舒适性差,也造成了较大热损耗。为改善这一问题,在研究了强化学习的基础上提出基于Q学习PID参数的供热末端流量控制算法。首先分析了散热器等的热动态及传热过程,建立了供热房间热平衡数学模型,然后以PID控制算法为基础,温度偏差为控制器输入,调节阀开度控制量为输出,选择温差变化为智能体奖惩的学习策略,通过Q学习算法对PID参数进行在线自适应整定,最后在集中供热末端流量调节的仿真实验中验证了控制器的调控性能并与传统PID控制结果进行了对比。实验结果表明,基于Q学习的自适应PID流量控制算法能够使室内温度变化和调节阀开度变化更加平缓,且节省约33%的供热量,节能效果较明显。     

规则自适应模糊PID数字电压调节器设计

应用自适应模糊控制理论,结合航空电源发电机控制器系统的实际情况,设计了基于规则自适应模糊PID算法的数字电压调节器系统.介绍了系统的硬件组成和相应规则自适应模糊PID控制器算法的具体实现.该算法克服了不能建立精确的数学模型所带来的弊端,经过验证,该系统具有良好的稳定性和快速的跟踪性,具有一定的现实意义.     

一种模糊自适应PID控制在溶解氧中的应用

针对污水处理过程的非线性、不稳定性和不确定性,将活性污水处理系统非线性数学模型转换为参数有界的变参数正则状态方程,并对系统模型进行了可控性与稳定性分析,提出了一种基于混沌遗传算法优化的模糊自适应PID控制器.通过仿真实验表明:CGA法提高了种群个体的多样性,有效地避免了“早熟”和局部最优现象;优化后的控制器在超调量、上升速度、稳定时间等性能上得到明显改善.     

串联机器人轨迹跟踪控制模糊自适应PID算法的误差修正

提出了一种基于改进PID控制算法的串联机器人轨迹跟踪控制策略,首先采用减聚类的方法和改进的Logistic映射对RBF神经网络进行聚类中心的优化,然后将改进RBF神经网络中的自适应学习机制和自调整能力应用于传统PID控制算法中,对PID控制算法进行最优PID控制参数的选取。仿真实验表明,提出的串联机器人轨迹跟踪控制策略相比较传统PID控制算法,其误差更小,精度更高。     

Non-linear adaptive closed-loop control system for improved efficiency in IoT-blockchain management

IoT network generates a large amount of data. This means that the monitoring and control of these networks and the transfer of packets from the IoT network to the server can cause communications to collapse. On the other hand, due to the large volume of data stored in the databases the monitoring of the IoT network needs very powerful servers to have a high degree of efficiency. This paper presents a novel adaptive closed-loop control system and speed up searches model to improve the monitor and control efficiency in IoT networks, specially those which are based in blockchain. The non linear control model under consideration includes a new way to evaluate the optimal number of blocks that should be at the queue of the miners’ network in order to make the process efficient through the use of queuing theory. Also, a new system to speed up searches is presented by using hashmaps, which makes the monitoring process faster, reliable and efficient. The efficiency of the presented approach is illustrated by a numerical case study.