基于Bode''''s integrals的PID控制器的设计及其仿真

该文为一类稳定的最小相位控制对象提出一种新的PID控制器的参数整定方法。它是基于Bode’s integrals可以给出最小相位稳定系统的幅值与相位的关系，从而运用bode’s integrals近似表示控制对象G（jw）的幅值和相位的微分，然后将该简化结果用于PID控制器的设计中，从而得到新的控制器参数整定方法。该文中PID控制器的设计要求是，调整控制对象的Nyquist曲线在给定频率处的斜率，以提高闭环系统性能。最后，通过在matlab中对一类稳定的最小相位系统的计算机仿真例子比较，可以显示出该方法的优越性。     

New methodology for analytical and optimal design of fuzzy PIDcontrollers

Describes a methodology for the systematic design of fuzzy PID controllers based on theoretical fuzzy analysis and, genetic-based optimization. An important feature of the proposed controller is its simple structure. It uses a one-input fuzzy inference with three rules and at most six tuning parameters. A closed-form solution for the control action is defined in terms of the nonlinear tuning parameters. The nonlinear proportional gain is explicitly derived in the error domain. A conservative design strategy is proposed for realizing a guaranteed-PID-performance (GPP) fuzzy controller. This strategy suggests that a fuzzy PID controller should be able to produce a linear function from its nonlinearity tuning of the system. The proposed PID system is able to produce a close approximation of a linear function for approximating the GPP system. This GPP system, incorporated with a genetic solver for the optimization, will provide the performance no worse than the corresponding linear controller with respect to the specific performance criteria. Two indexes, linearity approximation index (LAI) and nonlinearity variation index (NVI), are suggested for evaluating the nonlinear design of fuzzy controllers. The proposed control system has been applied to several first-order, second-order, and fifth-order processes. Simulation results show that the proposed fuzzy PID controller produces superior control performance to the conventional PID controllers, particularly in handling nonlinearities due to time delay and saturation     

An Intelligent Design for a PID Controller for Nonlinear Systems

The proportional integral derivative (PID) controller is the most frequently used controller design for industrial applications because of its favorable response and simplicity of adjustment. However, PID manual tuning is traditionally based on engineering experience, and adjusting nonlinear or unknown systems is extremely difficult. In promoting an intelligent controller design theory that can be applied to the control of various systems, this paper proposes a nonlinear control design method that involves determining the optimal solution and obtaining the transfer function of an unknown system by using sequential quadratic programming. In addition, this paper presents a case study of an induction motor V/F speed control to demonstrate the effectiveness of the proposed method based on MATLAB simulation. The results prove that the design of the proposed intelligent PID controller is more robust than traditional controller designs.     

基于Maclaurin 展开的PID 设计与无模型自整定

针对自衡对象,提出一种基于期望模型的PID自整定方法,该方法无需被控对象的数学模型.利用Maclaurin展开技术,给出了PID控制器的整定公式;并通过开环阶跃响应,实现了PID控制器的无模型自整定.仿真结果表明,利用该自整定方法所得的PID能有效地提高高阶被控对象的系统性能;即使在噪声环境下,该方法仍具有很好的鲁棒性.     

Nonlinear CSTR control system design using an artificial bee colony algorithm

This paper proposes a novel controller design method based on using artificial bee colony (ABC) algorithms for an unstable nonlinear continuously stirred tank reactor (CSTR) chemical system. Such CSTR process is highly nonlinear and its dynamic is significantly dominated by system parameters. It is a good challenge to access the controller design performance when the controller is applied in the CSTR control system. The commonly used proportional–integral-derivative (PID) controller is taken into account in this study, and tuning three PID control gains is carried out by the artificial bee colony algorithm. With the use of the optimal ABC algorithm, PID controller gains can be derived suitably by means of minimizing the cost function given in advance. Finally, several control operations are provided to confirm the feasibility and effectiveness of the proposed method. We also discuss the influence of algorithm initial conditions on the control performance with many different tests.     

NEW TUNING METHOD FOR PID CONTROL OF A PLANT WITH UNDER‐DAMPED RESPONSE

In this paper, a tuning formula is derived for PID control of plants with under‐damped step responses. The under‐damped systems are modeled by second‐order plus dead time transfer functions. To derive the tuning rule, the dominant pole assignment method was applied to design the PID controllers for a variety of plant models. Then, the correlation between the controller parameters and the parameters of the models was found and the tuning formula derived. Several simulation examples are given to demonstrate the effectiveness and robustness of this formula.     

Robust self-tuning PID controller for nonlinear systems

In this paper, we propose a robust self-tuning PID controller suitable for nonlinear systems. The control system employs a preload relay (P_Relay) in series with a PID controller. The P_Relay ensures a high gain to yield a robust performance. However, it also incurs a chattering phenomenon. In this paper, instead of viewing the chattering as an undesirable yet inevitable feature, we use it as a naturally occurring signal for tuning and re-tuning the PID controller as the operating regime digresses. No other explicit input signal is required. Once the PID controller is tuned for a particular operating point, the relay may be disabled and chattering ceases correspondingly. However, it is invoked when there is a change in setpoint to another operating regime. In this way, the approach is also applicable to time-varying systems as the PID tuning can be continuous, based on the latest set of chattering characteristics. Analysis is provided on the stability properties of the control scheme. Simulation results for the level control of fluid in a spherical tank using the scheme are also presented.     

Quantitative design and analysis of fuzzy proportional-integralderivative control a step towards autotuning

In this paper, a thorough mathematical analysis is proposed for designing and tuning fuzzy proportional-integral-derivative (FZ-PID) control in order to achieve a better performance and simpler design. The quantitative model of FZ-PID, derived for the mathematical analysis and gain design, consists of a nonlinear relay and a nonlinear proportional-integral-derivative (PID) controller. This nonlinear model can be treated as of a PID nature around the equilibrium state under certain approximations. Through direct comparison with the conventional PID control, the connection between the scaling gains and the control actions is expressed in an explicit mathematical form. This theoretical analysis reveals that FZ-PID leads to more damping and hence less oscillation than do its conventional counterparts. This could be one of the reasons why fuzzy logic control can achieve a robust performance. A less coupled gain structure is further proposed to decouple the influence of the scaling gains and to disclose the major contribution of each gain to the different aspects of the control performance. Consequently, the systematic design and tuning method of the conventional PID control can be applied to the initial gain design and the fine tuning of the FZ-PID control. The simulation results confirm the effectiveness of the method proposed. This research is actually an important step towards the possible autotuning of the fuzzy controller.     

新型模糊PID控制及在HVAC系统的应用

为了推广模糊控制器在非线性系统中的应用,提出一种利用PID控制器的参数优化和调节模糊控制器的新型设计方法.通过模糊控制器的结构分析建立与PID控制之间的精确解析关系之后提出基于PID控制增益因子的模糊控制器设计算法,然后利用改进的变论域思想进一步优化模糊控制器设计参数.将其应用于暖通空调(HVAC)系统的节能控制中并与常规PID控制器相比较,仿真和实验结果表明这种模糊控制器具有超调量小、跟踪迅速、鲁棒性强等优越的控制性能.     

非线性PID控制器研究——比例分量的非线性方法

研究了基于比例控制分量非线性方法合成的新型非线性PID控制器(简记为:NPID-PCA).该控制器将比例控制分量表示为误差信号的非线性函数,并通过三个独立非线性函数构造合成PID控制器。由于比例控制分量具有最简的非线性特征,因此该类控制器在设计上更为简洁,非线性在控制作用方面的物理意义更为明确.采用样条函数[7]生成非线性作用曲线,用户可以通过图形化交互方式直观地实现非线性设计.通过与文献中的控制实例比较,本文提出的新型非线性PID控制器可以实现更为优良的控制性能指标,包括对带有时延或死区的被控对象.     

Robust optimization-based multi-loop PID controller tuning: A new tool and its industrial application

Modern process plants are highly integrated and as a result, decentralized PID control loops are often strongly interactive. The iterative SISO tuning approach currently used in industry is not only time consuming, but does also not achieve optimal performance of the inherently multivariable control system. This paper describes a method and a software tool that allows control engineers/technicians to calculate optimal PID controller settings for multi-loop process systems. It requires the identification of a full dynamic model of the multivariable system, and uses constrained nonlinear optimization techniques to find the controller parameters. The solution is tailored to the specific control system and PID algorithm to be used. The methodology has been successfully applied in many industrial advanced control projects. The tuning results that have been achieved for interacting PID control loops in the stabilizing section of an industrial Gasoline Treatment Unit as well as a Diesel Desulfurization plant are presented.     

非线性PID控制器参数优化方法

分析了非线性PID控制器各部分参数对于误差的理想变化过程,构造出一种非线性PID控制器;整定参数较多时,传统的参数优化方法容易产生振荡和较大的超调量,在分析量子粒子群算法（QPSO）的基础上,引入了随机选择最优个体的思想,提出使用改进的量子粒子群算法（GQPSO）优化非线性PID控制器参数。将改进量子粒子群算法与量子粒子群算法、粒子群算法通过benchmark测试函数进行了比较。最后,通过典型传递函数实例,分别使用Z-N、PSO、QPSO方法和改进的量子粒子群算法进行了PID控制器参数优化设计,并对结果进行了分析。     

Stabilising PID tuning for a class of fourth-order integrating nonminimum-phase systems

Fed-batch fermentation processes are commonly used in bioprocessing industry. A fed-batch fermentation process often exhibits integrating/unstable type of dynamics with multiple right-half plane zeros. A class of fourth-order integrating model can be used to adequately represent such a complex dynamics of the fed-batch fermentation process. In this paper, rigorous stability analysis of proportional-integral-derivative (PID) controller based on the Routh-Hurwitz criteria for the fourth-order integrating system is presented. A set of all stabilising PID controller parameter regions is established. Based on these stabilising regions, a general PID controller tuning procedure is proposed for the fourth-order integrating system with two right-half plane zeros. Numerical study shows that based on the proposed tuning procedure, a low-order PID controller can outperform a fifth-order optimal LQG controller in terms of servo and regulatory controls.     

基于强化学习的参数自整定及优化算法

传统PID控制算法在非线性时滞系统的应用中,存在参数整定及性能优化过程繁琐、控制效果不理想的问题。针对该问题,提出了一种基于强化学习的控制器参数自整定及优化算法。该算法引入系统动态性能指标计算奖励函数,通过学习周期性阶跃响应的经验数据,无需辨识被控对象模型的具体数据,即可实现控制器参数的在线自整定及优化。以水箱液位控制系统为实验对象,对不同类型的PID控制器使用该算法进行参数整定及优化的对比实验。实验结果表明,相比于传统的参数整定方法,所提出的算法能省去繁琐的人工调参过程,有效优化控制器参数,减少被控量的超调量,提升控制器动态响应性能。     

具有PID反馈增益的自主水下航行器反步法变深控制

本文针对海底地形测绘时自主水下航行器(autonomous underwater vehicle,AUV)的变深控制问题,提出具有PID增益调节的AUV深度控制方法,基于反馈增益的反步法设计控制器,避免了采用传统反步法导致控制器中存在虚拟控制量的高阶导数问题;基于李雅普诺夫稳定性理论设计控制器参数消除了部分非线性项,得到的控制器的线性部分为状态变量的线性组合,具有PID控制器参数调节的形式;针对存在建模不精确、外界干扰和测量噪声时的闭环系统鲁棒性进行分析,保证了误差系统在扰动作用时的一致最终有界性.最后通过仿真实验验证了本文设计的控制器的有效性.     

基于RBF网络自整定PID控制的应用研究

经典PID的控制参数难以精确整定，且依赖于对象的数学模型，故自适应性较差，很难适应具有非线性、时变不确定性的被控对象，控制精度难以保证。该文对纯滞后工业对象提出了一种基于RBF神经网络PID参数自整定的控制方法，采用将RLS算法和梯度法相融合的新型学习算法，并将这种控制方法与PID控制器相结合应用于纯滞后工业对象中，克服了不确定性对控制对象性能的不利影响，解决了传统PID控制鲁棒性差，及需要预先知道受控对象精确数学模型的问题。仿真结果表明了该方法的鲁棒性和跟踪性能均优于传统PID控制方法。     

Fuzzy neural networks for tuning PID controller for plants withunderdamped responses

In this paper, the fuzzy neural network (FNN) for tuning proportional-integral-derivative (PID) controller for plants with underdamped step responses is proposed. The underdamped systems are modeled by second-order-plus-dead-time transfer functions. For deriving the FNN, the dominant pole assignment method is applied to design the PID controllers for a batch of test plant models that represent the plants with underdamped responses. Then, a fuzzy neural modeling method is utilized to identify the relationship between the parameters that characterize the plant dynamics and the controller parameters. We then utilize the obtained FNN to tune the PID controller for plants with underdamped responses. Several simulation examples are given to demonstrate the effectiveness and robustness of the FNN obtained     

基于BP神经网络的PID控制器在温控系统中的应用

工业中的温控对象普遍具有大时滞、非线性和时变性等特点,采用传统的PID控制器难以取得满意的效果。基于BP神经网络的PID控制器具有逼近任意非线性函数的能力,能实现对PID控制器的参数Kp,KI,KD的实时在线整定,使系统具有更好的鲁棒性和自适应性,其输出也可以通过在线调整达到预期的控制精度,适用于温控系统。实验结果表明,该控制器具有抗干扰能力强、鲁棒性好等特点。     

Discrete-time fractional-order PID controller: Definition,tuning, digital realization and some applications

In some of the complicated control problems we have to use the controllers that apply nonlocal operators to the error signal to generate the control. Currently, the most famous controller with nonlocal operators is the fractional-order PID (FOPID). Commonly, after tuning the parameters of FOPID controller, its transfer function is discretized (for realization purposes) using the so-called generating function. This discretization is the origin of some errors and unexpected results in feedback systems. It may even happen that the controller obtained by discretizing a FOPID controller works worse than a directly-tuned discrete-time classical PID controller. Moreover, FOPID controllers cannot directly be applied to the processes modeled by, e.g., the ARMA or ARMAX model. The aim of this paper is to propose a discrete-time version of the FOPID controller and discuss on its properties and applications. Similar to the FOPID controller, the proposed structure applies nonlocal operators (with adjustable memory length) to the error signal. Two methods for tuning the parameters of the proposed controller are developed and it is shown that the proposed controller has the capacity of solving complicated control problems.