Enhanced design of cascade control systems for unstable processes with time delay

In this paper, optimal H₂ internal model controller (IMC) is designed for control of unstable cascade processes with time delays. The proposed control structure consists of two controllers in which inner loop controller (secondary controller) is designed using IMC principles. The primary controller (master controller) is designed as a proportional-integral-derivative (PID) in series with a lead-lag filter based on IMC scheme using optimal H₂ minimisation. Selection of tuning parameter is important in any IMC based design and in the present work, maximum sensitivity is used for systematic selection of the primary loop tuning parameter. Simulation studies have been carried out on various unstable cascade processes. The present method provides significant improvement when compared to the recently reported methods in the literature particularly for disturbance rejection. The present method also provides robust closed loop performances for large uncertainties in the process parameters. Quantitative comparison has been carried out by considering integral of absolute error (IAE) and total variation (TV) as performance indices.     

高阶不确定系统的线性串级自抗扰控制

自抗扰控制是我国著名学者韩京清原创的先进控制技术,本文针对自抗扰控制(ADRC)在高阶系统应用中控制器设计和参数整定问题,提出了串级自抗扰控制(CADRC). CADRC把高阶被控对象分解为含确定性部分和含总扰动的低阶部分的串联组合,采用由内环和外环组成的串级控制系统来完成控制.该CADRC方案的内环采用内模控制,外环采用经典ADRC.外环ADRC的被控对象是一个等效的低阶系统,可以采用带宽法进行整定,而内环的内模控制采用高阶低通滤波器进行回路成形设计和参数整定.仿真研究表明,所提出的方法是有效的,具有良好的工程应用前景.     

双馈风力发电机的内模控制器设计

针对双馈风力发电机(DFIG)中普遍存在的功率耦合问题,设计了一种基于内模原理的电流控制器.首先介绍了内模控制(IMC)理论的系统结构,在此基础上推导出双馈风力发电系统的传递函数,并建立基于内模控制的电流内环数学模型;其次,内模控制器的参数整定参考系统的平方积分误差值,其鲁棒稳定性参考M值的大小;最后利用Matlab仿真平台进行了仿真实验.结果表明,该控制器实现了系统有功和无功的充分解耦,并具有较好的稳态和动态性能.     

基于分数阶内模控制的风力机叶片颤振研究

针对风力机叶片颤振系统,提出了一种结合分数阶(Fractional Order)控制与内模控制(Internal Model Control,IMC)的新型颤振控制方法.利用分数阶滤波器设计了分数阶内模控制器,基于闭环动态特性指标,如相位裕量和截止频率,实现对控制器参数的自整定.通过仿真实验对比证明,针对风力机叶片颤振控制,所设计的控制方法优于传统PID、内模PID控制方法,不仅减少了控制参数,而且提高了动态特性和鲁棒性.     

工业过程运行的解耦内模控制方法

工业过程运行控制的目的是实现反映过程整体运行性能的工艺指标. 将常规解耦内模控制(Internal model control, IMC)进行推广, 提出了优化过程运行的解耦IMC方法. 通过对广义解耦内模控制器的设计获得了具有高维解耦能力、鲁棒稳定性和抗干扰能力强的回路设定模型. 该模型能够响应系统的各种不确定性和干扰, 对回路设定值进行调整, 通过控制回路的输出跟踪调整后的设定值, 从而实现期望的工艺指标. 磨矿回路运行的解耦IMC设计实例及仿真验证了所提方法的有效性.     

Robust IMC–PID tuning for cascade control systems with gain and phase margin specifications

In this article, an internal model control plus proportional-integral-derivative (IMC–PID) tuning procedure for cascade control systems is proposed based on the gain and phase margin specifications of the inner and outer loop. The internal model control parameters are adjusted according to the desired frequency response of each loop with a minimum interaction between the inner and outer PID controllers, obtaining a fine tuning and the desired gain and phase margins specifications due to an appropriate selection of the PID controller gains and constants. Given the design specifications for the inner and outer loop, this tuning procedure adjusts the IMC parameter of each controller independently, with no interference between the inner and outer loop obtaining a robust method for cascade controllers with better performance than sequential tuning or other frequency domain-based methods. This technique is accurate and simple, providing a convenient technique for the PID tuning of cascade control systems in different applications such as mechanical, electrical or chemical systems. The proposed tuning method explained in this article provides a flexible tuning procedure in comparison with other tuning procedures because each loop is tuned simultaneously without modifying the robustness characteristics of the inner and outer loop. Several experiments are shown to compare and validate the effectiveness of the proposed tuning procedure over other sequential or cascade tuning methods; some experiments under different conditions are done to test the performance of the proposed tuning technique. For these reasons, a robustness analysis based on sensitivity is shown in this article to analyze the disturbance rejection properties and the relations of the IMC parameters.     

IMC-based iterative learning control for batch processes with uncertain time delay

Based on the internal model control (IMC) structure, an iterative learning control (ILC) scheme is proposed for batch processes with model uncertainties including time delay mismatch. An important merit is that the IMC design for the initial run of the proposed control scheme is independent of the subsequent ILC for realization of perfect tracking. Sufficient conditions to guarantee the convergence of ILC are derived. To facilitate the controller design, a unified controller form is proposed for implementation of both IMC and ILC in the proposed control scheme. Robust tuning constraints of the unified controller are derived in terms of the process uncertainties described in a multiplicative form. To deal with process uncertainties, the unified controller can be monotonically tuned to meet the compromise between tracking performance and control system robust stability. Illustrative examples from the recent literature are performed to demonstrate the effectiveness and merits of the proposed control scheme.     

IMC–PID Design: Analytical Optimization for Performance/Robustness Tradeoff Tuning for Servo/Regulation Mode

This paper addresses the analytical design of a one‐degree‐of‐freedom (1‐DoF) robust proportional–integral–derivative (PID) controller for the servo/regulation mode in line with the enhanced internal model control (IMC) principle based on a first order plus dead time (FOPDT) model. The proposed enhanced IMC–PID can provide acceptable performance both for set‐point tracking and for load disturbance rejection. The design procedure is formulated as a constrained optimization problem, in which the robustness of the system is adequately considered. Therefore, the resulting PID controller gives optimal performance with an exact selected robustness degree. Illustrative examples are given to show the effectiveness and merits of the analytical tuning rules for a wide range of plants.     

基于支持向量机逼近的内模控制系统及应用

针对同步发电机组汽门系统, 文章研究了一种基于支持向量机逼近的内模控制系统. 所研究的控制系统包括两个主要部分: 支持向量机逼近逆控制器、内模框架下的不确定性补偿. 由基于泰勒扩展的输入输出逼近模型计算逆控制律, 并由非线性系统辨识来实现. 同时, 采用一个鲁棒滤波器实现内模框架下的不确定性补偿. 针对汽门系统的仿真实验验证了该控制系统的优良性能.     

Simultaneous automatic tuning of cascade control systems from closed-loop step response data

This study presents a novel automatic tuning method for cascade control systems in which both primary and secondary controllers are tuned simultaneously using a single closed-loop step test. The proposed technique identifies the required process information with the help of B-spline series representation for the step responses. The two proportional–integral–derivative (PID) controllers are then tuned using an internal model control (IMC) approach. Considering the rationale of cascade control, the secondary controller is designed for faster disturbance attenuation. Without requiring an additional experiment, the primary controller is designed based on an identified process model that accurately accounts for inner loop dynamics. Finally, this study includes robustness considerations in the controller tuning process, and develops explicit guidelines for the selection of the IMC tuning parameters, completing the automatic tuning procedure for cascade control systems. The proposed method is robust to measurement noise because of the filtering property of the B-splines, and can provide superior control performance for both set-point tracking and disturbance rejection. Simulation examples demonstrate the effectiveness of the proposed automatic tuning method.     

一种基于支持向量机的内模控制方法

在基于数据的基础上,采用SVM回归理论建立系统的正向模型和设计逆模控制器.首先简要介绍了SVMR的原理,然后将其应用于内模控制问题,并建立了SVMR模型.其次,在控制过程可逆的条件下设计了SVMR控制器.最后将该控制方法应用于一可逆非线性系统和具未知干扰的温室环境控制问题,仿真结果表明该方法与神经网络IMC相比,具有较简单的模型和较好的控制性能.     

基于小波网络的非线性内模控制

针对非线性内模控制结构,给出了小波网络逼近系统正、逆模型的充分条件的实现方法。在内模控制结构中引入PID补偿控制,改进了内模控制器的性质。仿真结果表明,小波网络用于非线性内模控制是有效的,内模＋PID控制较单一内模控制具有更快速和平稳的跟踪性能。     

Optimized Model Based Controller with Model Plant Mismatch for NMP Mitigation in Boost Converter

In this paper, an optimized Genetic Algorithm (GA) based internal model controller-proportional integral derivative (IMC-PID) controller has been designed for the control variable to output variable transfer function of dc-dc boost converter to mitigate the effect of non-minimum phase (NMP) behavior due to the presence of a right-half plane zero (RHPZ). This RHPZ limits the dynamic performance of the converter and leads to internal instability. The IMC PID is a streamlined counterpart of the standard feedback controller and easily achieves optimal set point and load change performance with a single filter tuning parameter λ. Also, this paper addresses the influences of the model-based controller with model plant mismatch on the closed-loop control. The conventional IMC PID design is realized as an optimization problem with a resilient controller being determined through a genetic algorithm. Computed results suggested that GA–IMC PID coheres to the optimum designs with a fast convergence rate and outperforms conventional IMC PID controllers.     

典型时滞时变过程的鲁棒数字双PI 控制

针对具有时滞时变以及负载干扰等复杂特性的时滞系统，在强时滞鲁棒数字PID控制方法的基础上，结合二自由度的IMC结构，给出一种数字双PI调节器的设计，在已知闭环系统时滞时变范围内，对确定性定值负载干扰的影响实现了无静差鲁棒调节控制。     

基于改进Smith预估控制结构的二自由度PID控制

针对工业过程中的二阶不稳定时滞过程, 基于改进史密斯预估控制结构提出了一种简单的两自由度控制方案.设定值跟踪控制器和扰动抑制控制器采用同一设计程序, 并基于内模控制原理提出了控制器解析设计方案.设定值跟踪控制器和抗扰动控制器可分别通过单性能参数独立调节和优化, 每个控制器都具有PID形式, 给出了控制器调整参数的选择范围和扰动抑制闭环保证鲁棒稳定性的条件.仿真实例验证了提出方法对于近期其他方法的优越性.     

Tuning algorithms for fractional order internal model controllers for time delay processes

This paper presents two tuning algorithms for fractional-order internal model control (IMC) controllers for time delay processes. The two tuning algorithms are based on two specific closed-loop control configurations: the IMC control structure and the Smith predictor structure. In the latter, the equivalency between IMC and Smith predictor control structures is used to tune a fractional-order IMC controller as the primary controller of the Smith predictor structure. Fractional-order IMC controllers are designed in both cases in order to enhance the closed-loop performance and robustness of classical integer order IMC controllers. The tuning procedures are exemplified for both single-input-single-output as well as multivariable processes, described by first-order and second-order transfer functions with time delays. Different numerical examples are provided, including a general multivariable time delay process. Integer order IMC controllers are designed in each case, as well as fractional-order IMC controllers. The simulation results show that the proposed fractional-order IMC controller ensures an increased robustness to modelling uncertainties. Experimental results are also provided, for the design of a multivariable fractional-order IMC controller in a Smith predictor structure for a quadruple-tank system.     

Data driven nonparametric identification and model based control of glucose-insulin process in type 1 diabetics

Closed loop control of glucose homeostasis via subcutaneous insulin infusion and continuous glucose monitoring system can give better living to a type 1 diabetic patient. This paper deals with the real time implementation of internal model control (IMC) of subcutaneous insulin infusion. The model based control is applied on the nonparametric model of the patient identified in real time from input–output data. Meal simulation model of the glucose-insulin system of type 1 diabetic patient based on the work of Dalla Man et. al. is considered. This model is constructed in hardware platform that acts as the virtual patient. The data-driven nonparametric model of the virtual patient is identified in real time by computing Volterra kernels. The kernels are solved up to second order using recursive least squares (RLS) algorithm with short memory length of M = 2. The validation results of the identified model output and the actual output have shown good fit in both simulation and real time environments. The frequency domain kernels are used in internal model control to generate insulin dosage. The control algorithm is developed in simulation and implemented in real time with hardware in loop on dSPACE platform. The closed loop system yields good meal disturbance rejection, less undershoots, settling time and more profoundly smaller requirement of insulin infusion as compared to the earlier reported data.     

Guidance and nonlinear control system for autonomous flight of minirotorcraft unmanned aerial vehicles

Small unmanned aerial vehicles (UAVs) are becoming popular among researchers and vital platforms for several autonomous mission systems. In this paper, we present the design and development of a miniature autonomous rotorcraft weighing less than 700 g and capable of waypoint navigation, trajectory tracking, visual navigation, precise hovering, and automatic takeoff and landing. In an effort to make advanced autonomous behaviors available to mini‐ and microrotorcraft, an embedded and inexpensive autopilot was developed. To compensate for the weaknesses of the low‐cost equipment, we put our efforts into designing a reliable model‐based nonlinear controller that uses an inner‐loop outer‐loop control scheme. The developed flight controller considers the system's nonlinearities, guarantees the stability of the closed‐loop system, and results in a practical controller that is easy to implement and to tune. In addition to controller design and stability analysis, the paper provides information about the overall control architecture and the UAV system integration, including guidance laws, navigation algorithms, control system implementation, and autopilot hardware. The guidance, navigation, and control (GN&C) algorithms were implemented on a miniature quadrotor UAV that has undergone an extensive program of flight tests, resulting in various flight behaviors under autonomous control from takeoff to landing. Experimental results that demonstrate the operation of the GN&C algorithms and the capabilities of our autonomous micro air vehicle are presented. © 2009 Wiley Periodicals, Inc.     

预测函数控制的内模控制理论

内模控制是一种基于过程数学模型进行控制器设计的新型控制策略,是研究预测控制重要的理论基础。预测函数控制是一种控制量计算方程简单,实时控制效果好的新型预测控制算法。本文用内模控制理论研究预测函数控制,分析了系统的鲁棒性和稳定性,最后进行了参数设计和仿真研究。     

Single-loop controller design via IMC principles

In this paper, a new internal model control (IMC)-based single-loop controller design is proposed. The model reduction technique is employed to find the best single-loop controller approximation to the IMC controller. Compared with the existing IMC-based methods, the proposed design is applicable to a wider range of processes, and yields a control system closer to the IMC counterpart. It can be made automatic for on-line tuning. The users have the option to choose between PID and high-order controllers to suit the applications better. It turns out that high-order controllers may be necessary to achieve high performance for essentially high-order processes.