Adaptive Nonlinear PID Control and Rule-Based Compensation for Systems with Backlash

The control of dynamic nonlinear systems with unknown backlash was considered. By using an efficient approach to estimate the unknown backlash parameters, a rule? based backlash compensator was presented for canceling the effect of backlash. Adaptive nonlinear PID controller together with rule? based backlash compensator was developed and a satisfactory tracking performance was achieved. Simulation results demonstrated the effectiveness of the proposed method.

Novel Approach to Nonlinear PID Parameter Optimization Using Ant Colony Optimization Algorithm

This paper presents an application of an Ant Colony Optimization （ACO） algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorithm, which is based on the behaviour of real ants in nature searching for food. In order to optimize the parameters of the nonlinear PID controller using ACO algorithm, an objective function based on position tracing error was constructed, and elitist strategy was adopted in the improved ACO algorithm. Detailed simulation steps are presented. This nonlinear PID controller using the ACO algorithm has high precision of control and quick response.

Realization of nonlinear PID with feed-forward controller for 3-DOF flight simulator and hardware-in-the-loop simulation

As friction, intrinsic steady-state nonlinearity poses a challenging dilemma to the control system of 3-DOF （three degree of freedom） flight simulator, a novel hybrid control strategy of nonlinear PID （proportionalintegral-derivative） with additional FFC （feed-forward controller） is proposed, and the hardware-in-the-loop simulation results are also given. Based on the description of 3-DOF flight simulator, a novel nonlinear PID theory is well introduced. Then a nonlinear PID controller with additional FFC is designed. Subsequently, the loop structure of 3-DOF flight simulator is also designed. Finally, a series of hardware-in-the-loop simulation experiments are undertaken to verify the feasibility and effectiveness of the proposed nonlinear PID controller with additional FFC for 3-DOF flight simulator.

Globally robust nonlinear PID controllers for robot manipulators with an uncertain Jacobian matrix

Based on a continuous piecewise-differentiable increasing functions vector, a class of robust nonlinear PID (RN-PID) controllers is proposed for setpoint control with uncertain Jacobian matrix. Globally asymptotic stability is guaranteed and only position and joint velocity measurements are required. And stability problem arising from integral action and integrator windup, are consequently resolved. Furthermore, RN-PID controllers can be of effective alternative for anti-integrator-wind-up, the control performance would not be very bad in the presence of rough parameter tuning.

Robust Nonlinear PID Controllers for Anti-windup Design of Robot Manipulators with an Uncertain Jacobian Matrix

至于有不明确的 Jacobian 矩阵的机器人操纵者的笛卡儿的规定，柔韧的非线性的 PID (RN-PID ) 控制器的一个反上发条的计划被建议解决在象 PID 一样控制系统从不可分的行动和综合者终结产生的实际问题。当位置和联合速度大小仅仅被要求时， Asymptotic 稳定性被保证；靠近环的系统也由于对不可分的行动起作用的限制被保证的结果的坚韧性。特别与另外的反上发条的途径相比，建议算法为反上发条的设计更简单、更有效。

平面并联机器人离线PID控制优化研究

为了使平面并联机器人在闭环控制系统中具有更稳定的控制性能。对此,这里构建了平面五杆并联机器人动力学模型及其控制系统模型,给出了控制系统的增益矢量p。对机器人系统模型进行离线PID控制优化,通过控制增益来设计控制系统中的增益矢量p,从而实现非线性单目标动态优化(NLMODOP)。在NLMODOP中加入动态约束,采用带约束处理机制的差分进化(DE)算法求解平面并联机器人的非线性规划问题,进而处理不稳定的动态优化。对机器人模型中的五个连杆进行仿真实验,并对有无DE算法控制的仿真结果进行了比较。结果表明:相比于无DE算法,采用DE算法下的机器人系统模型的连杆跟踪位移基本无跟踪误差。说明基于差分进化算法的平面并联机器人离线PID控制优化具有较好的控制精度和跟踪性能。

基于改进鲸鱼算法优化PID的转速控制

当汽轮机转速发生偏差时,需要操作员手动整定PID参数使转速达到稳定,但控制效果不佳且调节时间长,针对这一问题提出了一种改进的鲸鱼优化算法优化PID参数控制转速,通过引入反向学习策略和非线性收敛因子,在一台3MW的汽轮机的组态仿真中进行实验对比。结果表明:与鲸鱼算法、粒子群算法相比,改进鲸鱼算法寻优效果更好,进而有效地达到对汽轮机转速的控制。

基于FA-PID算法的电动舵机多非线性系统研究

针对制导炮弹电动舵机常规建模时常将各部分视为线性环节,且采用传统三闭环PID算法无法解决复杂非线性系统的高频响、低超调等问题。本研究充分考虑了舵机系统内部的电机、死区齿隙与LuGre摩擦等非线性环节,搭建了电动舵机的多非线性控制系统,根据舵偏角运动方向的非单一性,设计了电机的正反转逻辑换相判别模块,并在电动舵机的位置环中引入了模糊自适应PID(FA-PID)智能算法。结果表明:采用FA-PID算法相比于传统PID控制对小角度位置响应的延迟时间下降了约0.49%,上升时间下降了约6.91%,峰值时间下降了约39.94%,稳态误差下降了约94.44%,且进一步通过小角度方波/正弦位置跟踪研究同样可以得出该算法的快速性与鲁棒性。

电液执行器非线性PID控制优化仿真研究

为了提高电液执行器运动轨迹的跟踪精度,提出了一种非线性比例-积分-微分(PID)控制优化方法,通过仿真检验优化后的控制系统输出结果,构建了电液系统数学模型。对传统PID控制参数进行改进,设计了一种非线性PID控制方法。引用粒子群算法并进行改进,利用改进粒子群算法迭代搜索原理对非线性PID控制器参数进行在线调整,最终得到电液执行器最优控制参数值,使电液执行器具有更好的抗负载干扰能力。以电液执行器不同工况为例,利用Matlab软件对电液执行器运动轨迹进行仿真,比较空载和负载条件下输出结果。结果显示:在空载条件下,分别采用PID控制、非线性PID控制和优化非线性PID控制方法,电液执行器运动轨迹输出误差均较小,相差不大。在负载条件下,优化非线性PID控制方法明显优于PID控制和非线性PID控制方法,相比之下使用优化非线性PID控制方法,电液执行器运动轨迹输出误差较小。采用改进粒子群算法优化非线性PID控制方法,使电液执行器能够抑制负载工况的干扰,具有较高的跟踪精度。

基于改进WOA参数优化的反应釜PID控制器

为了解决工业中传统PID控制算法对于大时滞、非线性系统较难取得良好的控制效果的问题,提出一种基于改进鲸鱼优化算法(IWOA)的PID控制器整定算法。该算法考虑均衡算法的探查以及开发能力,引入非线性收敛因子;为了提高算法的勘察能力,避免陷入局部最优的情况,引入正余弦扰动因子改进位置更新策略;最后以化工反应中反应釜温度为被控对象,对其PID控制器进行参数自整定实验,并将结果与WOA算法、Z-N整定算法、PSO算法进行对比,验证了IWOA算法在优化PID控制器工程上的优越性。

Unified Control Theory from PID to ACPID

To address the challenge of achieving unified control across diverse nonlinear systems, a comprehensive control theory spanning from PID (Proportional-Integral-Derivative) to ACPID (Auto-Coupling PID) has been proposed. The primary concept is to unify all intricate factors, including internal dynamics and external bounded disturbance, into a single total disturbance. This enables the mapping of various nonlinear systems onto a linear disturbance system. Based on the theory of PID control and the characteristic equation of a critically damping system, Zeng’s stabilization rules (ZSR) and an ACPID control force based on a single speed factor have been designed. ACPID control theory is both simple and practical, with significant scientific significance and application value in the field of control engineering.

基于自学习非线性PID的音圈电机精密定位系统

基于音圈电机的精密宏微气浮运动系统,是一种能克服接触摩擦和行程限制的新型精密定位系统。针对系统中用于精密定位的音圈电机受到内外扰动从而影响系统最终定位精度的问题,在建立起音圈电机数学模型的基础上,设计了基于反正弦函数的自学习非线性PID控制器,利用自学习算法对非线性增益函数的增益系数进行实时调整。完成算法设计与仿真后,在搭建的系统平台分别进行了微动台短行程定位和宏微动台的长行程定位实验。仿真和实验结果表明,与传统PID控制器相比较,自学习非线性PID控制器的使用有效提高了系统的鲁棒性和定位精度,系统对位置指令响应迅速无超调,控制精度达到了亚微米级。

Nonlinear Decoupling PID Control Using Neural Networks and Multiple Models

For a class of complex industrial processes with strong nonlinearity, serious coupling and uncertainty, a nonlinear decoupling proportional-integral-differential （PID） controller is proposed, which consists of a traditional PID controller, a decoupling compensator and a feedforward compensator for the unmodeled dynamics. The parameters of such controller is selected based on the generalized minimum variance control law. The unmodeled dynamics is estimated and compensated by neural networks, a switching mechanism is introduced to improve tracking performance, then a nonlinear decoupling PID control algorithm is proposed. All signals in such switching system are globally bounded and the tracking error is convergent. Simulations show effectiveness of the algorithm.

Development of nonlinear disturbance observer based control and nonlinear PID： A personal note

This paper gives an overview of early development of nonlinear disturbance observer design technique and the disturbance observer based control （DOBC） design. Some critical points raised in the development of the methods have been reviewed and discussed which are still relevant for many researchers or practitioners who are interested in this method. The review is followed by the development of a new type of nonlinear PID controller for a robotic manipulator and its experimental tests. It is shown that, under a number of assumptions, the DOBC consisting of a predictive control method and a nonlinear disturbance observer could reduce to a nonlinear PID with special features. Experimental results show that, compared with the predictive control method, the developed controller significantly improves performance robustness against uncertainty and friction. This paper may trigger further research and interests in the development of DOBC and related methods, and building up more understanding between this group of control methods with comparable ones （particularly control methods with integral action）.

基于非线性PID的微电网虚拟同步发电机控制

为解决传统虚拟同步发电机(VSG:Virtual Synchronous Generator)电压电流双闭环控制的抗扰动性能差,受系统参数变化及各种不确定影响较大等问题,在建立微电网VSG转动惯量自适应控制模型的基础上,采用一种基于跟踪微分器的非线性PID(Proportion Integration Differentiation)实现电压外环和电流内环的控制,并根据输出信号的反馈值实时调节系统动态响应,从而达到稳定输出的效果。通过仿真验证了基于非线性PID的微电网虚拟同步发电机双闭环控制的正确性和有效性。

Nonlinear system PID-type multi-step predictive control

A compound neural network was constructed during the process of identification and multi-step prediction. Under the PID-type long-range predictive cost function, the control signal was calculated based on gradient algorithm. The nonlinear controller’s structure was similar to the conventional PID controller. The parameters of this controller were tuned by using a local recurrent neural network on-line. The controller has a better effect than the conventional PID controller. Simulation study shows the effectiveness and good performance.

水轮机调节系统的自耦PID控制方法

针对含死区环节和机械时滞的水轮机调节系统,研究了一种基于自耦PID控制理论的控制方法。首先,将带死区环节的时滞水轮机调节系统中时滞、死区非线性因素、不确定性以及外部扰动定义为总扰动,再通过引入虚拟控制量,将其等价映射为一个外环二阶线性扰动系统与一个内环一阶线性扰动系统的双闭环系统;其次,针对外环设计基于速度因子的自耦PD控制器,内环设计基于速度因子的自耦PI控制器;最后,在复频域分析了闭环控制系统的鲁棒稳定性和抗扰动鲁棒性。仿真结果表明,所设计的控制器在不同工况下控制效果不仅具有良好的抗扰动鲁棒性,而且具有良好的动态品质和稳态性能。

变转速泵控液压缸系统的多模型自适应PID控制

变转速泵控液压缸系统转速或负载大范围变动导致的液压系统参量非线性变化,可使基于线性模型设计的控制系统出现控制参数不合理、精度不稳定,甚至控制失稳等问题,本文通过分析典型变转速泵控液压缸系统的状态空间,提出了一种多模型自适应PID(Multi-model adaptive PID,MMA-PID)控制方法。该方法根据系统压力的改变引起的油液体积弹性模量的非线性变化,用多个线性子模型分别描述系统行为,并针对每个子模型,单独设计一个合理的控制器。控制过程中,通过卡尔曼滤波器分别估计各个子模型的输出权重系数,并将所有子模型控制输出加权融合作为系统最终的控制输入。仿真和实验结果表明,在工况大范围变化时,多模型自适应PID控制相较于传统的PID控制,能更好的适应系统参量的非线性变化,具有更好的控制效果和动态性能。

基于改进粒子群优化算法的四旋翼PID参数整定研究

PID控制算法是目前应用最广泛的四旋翼控制算法。但目前传统工业控制中的PID参数整定设置方法难以给出合适的参数导致无人机控制精度低且鲁棒性差。采用粒子群优化算法(PSO)可对PID参数进行优化。针对基本PSO存在的收敛速度慢、收敛精度低、易过早收敛等缺陷,该文在传统粒子群算法基础上提出,非线性权重;非对称学习因子;柯西变异;改进PSO算法用于PID参数整定中。仿真结果表明,该文所提出的改进粒子群算法在PID参数整定中的效果优于传统PSO算法,且鲁棒性强。

基于BP神经网络辨识的预测滤波PID控制

针对复杂非线性系统采用常规PID控制性能不好的问题,通过BP神经网络构建系统输出量的辨识器,在目标函数中加入优化参数的增量约束项,提出可克服算法病态的牛顿法,并用其在线学习BP神经网络的连接权,根据增量式预测滤波PID控制,推导了PID控制参数应满足的线性不等式约束条件,将PID控制参数的优化归结为线性不等式约束的最优化问题。综上研究提出基于BP神经网络辨识的在线优化参数预测滤波PID控制。仿真研究说明,因算法具有在线优化PID控制参数和预测控制性能,故提出的智能PID控制算法与常规PID控制相比,具有更优的性能。