Extension of IMC tuning correlations for non-self regulating (integrating) processes

The filter term of a PID with Filter controller reduces the impact of measurement noise on the derivative action of the controller. This impact is quantified by the controller output travel defined as the total movement of the controller output per unit time. Decreasing controller output travel is important to reduce wear in the final control element. Internal Model Control (IMC) tuning correlations are widely published for PI, PID, and PID with Filter controllers for self regulating processes. For non-self regulating (or integrating) processes, IMC tuning correlations are published for PI and PID controllers but not for PID with Filter controllers. The important contribution of this work is that it completes the set of IMC tuning correlations with an extension to the PID with Filter controller for non-self regulating processes. Other published correlations (not based upon the IMC framework) for PID with Filter controllers fix the filter time constant at one-tenth the derivative time regardless of the model of the process. In contrast, the novel IMC correlations presented in this paper calculate a filter time constant based upon the model of the process and the user's choice for the closed-loop time constant. The set point tracking and disturbance rejection performance of the proposed IMC tunings is demonstrated using simulation studies and a bench-scale experimental system. The proposed IMC tunings are shown to perform as well as various PID correlations (with and without a filter term) while requiring considerably less controller action.     

Disturbance-rejection-based tuning of proportional–integral–derivative controllers by exploiting closed-loop plant data

A systematic data-based design method for tuning proportional–integral–derivative (PID) controllers for disturbance attenuation is proposed. In this method, a set of closed-loop plant data are directly exploited without using a process model. PID controller parameters for a control system that behaves as closely as possible to the reference model for disturbance rejection are derived. Two algorithms are developed to calculate the PID parameters. One algorithm determines the optimal time delay in the reference model by solving an optimization problem, whereas the other algorithm avoids the nonlinear optimization by using a simple approximation for the time delay term, enabling derivation of analytical PID tuning formulas. Because plant data integrals are used in the regression equations for calculating PID parameters, the two proposed algorithms are robust against measurement noises. Moreover, the controller tuning involves an adjustable design parameter that enables the user to achieve a trade-off between performance and robustness. Because of its closed-loop tuning capability, the proposed method can be applied online to improve (retune) existing underperforming controllers for stable, integrating, and unstable plants. Simulation examples covering a wide variety of process dynamics, including two examples related to reactor systems, are presented to demonstrate the effectiveness of the proposed tuning method.     

Improving disturbance rejection of PID controllers by means of the magnitude optimum method

The magnitude optimum (MO) method provides a relatively fast and non-oscillatory closed-loop tracking response for a large class of process models frequently encountered in the process and chemical industries. However, the deficiency of the method is poor disturbance rejection performance of some processes. In this paper, disturbance rejection performance of the PID controller is improved by applying the“disturbance rejection magnitude optimum” (DRMO) optimisation method, while the tracking performance has been improved by a set-point weighting and set-point filtering PID controller structure. The DRMO tuning method requires numerical optimisation for the calculation of PID controller parameters. The method was applied to two different 2-degrees-of-freedom PID controllers and has been tested on several different representatives of process models and one laboratory set-up. A comparison with some other tuning methods has shown that the proposed tuning method, with a set-point filtering PID controller, is quite efficient in improving disturbance rejection performance, while retaining tracking performance comparable with the original MO method.     

PID tuning rules for SOPDT systems: review and some new results

PID controllers are widely used in industries and so many tuning rules have been proposed over the past 50 years that users are often lost in the jungle of tuning formulas. Moreover, unlike PI control, different control laws and structures of implementation further complicate the use of the PID controller. In this work, five different tuning rules are taken for study to control second-order plus dead time systems with wide ranges of damping coefficients and dead time to time constant ratios (D/tau). Four of them are based on IMC design with different types of approximations on dead time and the other on desired closed-loop specifications (i.e., specified forward transfer function). The method of handling dead time in the IMC type of design is important especially for systems with large D/tau ratios. A systematic approach was followed to evaluate the performance of controllers. The regions of applicability of suitable tuning rules are highlighted and recommendations are also given. It turns out that IMC designed with the Maclaurin series expansion type PID is a better choice for both set point and load changes for systems with D/tau greater than 1. For systems with D/tau less than 1, the desired closed-loop specification approach is favored.     

Design of PID controllers in double feedback loops for SISO systems with set-point filters

A PID controller is widely used to control industrial processes that are mostly open loop stable or unstable. Selection of proper feedback structure and controller tuning helps to improve the performance of the loop. In this paper a double-feedback loop/method is used to achieve stability and better performance of the process. The internal feedback is used for stabilizing the process and the outer loop is used for good setpoint tracking. An internal model controller (IMC) based PID method is used for tuning the outer loop controller. Autotuning based on relay feedback or the Ziegler-Nichols method can be used for tuning an inner loop controller. A tuning parameter (λ) that is used to tune IMC-PID is used as a time constant of a setpoint filter that is used for reducing the peak overshoot. The method has been tested successfully on many low order processes.     

Enhanced disturbance rejection for open-loop unstable process with time delay

The present study suggests a disturbance estimator design method for application to a recently published, two-degree-of-freedom, control scheme for open-loop, unstable processes with time delay. A simple PID controller cascaded with a lead-lag filter replaces the high-order disturbance estimator for enhanced performance. A new analytical method on the basis of the IMC design principle, featuring only one user-defined tuning parameter, is developed for the design of the disturbance estimator. Several illustrative examples taken from previous works are included to demonstrate the superiority of the proposed disturbance estimator. The results confirm the superior performance of the proposed disturbance estimator in both nominal and robust cases. The proposed method also offers several important advantages for industrial process engineers: it covers several classes of unstable process with time delay in a unified manner, and is simple and easy to design and tune.     

IMC-PID design based on model matching approach and closed-loop shaping

Motivated by the limitations of the conventional internal model control (IMC), this communication addresses the design of IMC-based PID in terms of the robust performance of the control system. The IMC controller form is obtained by solving an H-infinity problem based on the model matching approach, and the parameters are determined by closed-loop shaping. The shaping of the closed-loop transfer function is considered both for the set-point tracking and for the load disturbance rejection. The design procedure is formulated as a multi-objective optimization problem which is solved by a specific optimization algorithm. A nice feature of this design method is that it permits a clear tradeoff between robustness and performance. Simulation examples show that the proposed method is effective and has a wide applicability.     

Coupled-disturbance-observer-based position tracking control for a cascade electro-hydraulic system

The disturbance suppression is one of the most common control problems in electro-hydraulic systems. especially largely an unknown disturbance often obviously degrades the dynamic performance by biasing the desired actuator outputs (e.g., load forces or torques). In order to reject the dynamic disturbances in some multi-degree-of-freedom manipulators driven by electro-hydraulic actuators, this paper proposes a state feedback control of the cascade electro-hydraulic system based on a coupled disturbance observer with backstepping. The coupled disturbance observer is designed to estimate both the independent element and the coupled element of the external loads on each electro-hydraulic actuator. The cascade controller has the ability to compensate for the disturbance estimating, as well as guarantees the system state error convergence to a prescribed steady state level. The effectiveness of the proposed controller for the suppression of largely unknown disturbances has been demonstrated by comparative study, which implies the proposed approach can achieve better dynamic performance on the motion control of Two-Degree-of-Freedom robotic arm.     

气动位置伺服系统的NN-IMC控制研究

提出了一种用于气动伺服系统的内模控制与神经网络相结合的智能控制方法，即NN—IMC控制法。该方法在提高控制性能方面有许多优点，能减少扰动的影响，鲁棒性较强，易于进行稳定性分析，只有一个调整参数，所以在工业应用中具有明显优势。当对象含有非线性环节的时候，可用神经网络来获得适当的控制参数。将所提出的NN—IMC智能控制法应用于含有强非线性气动伺服系统中，通过实验验证了它的效果。     

Internal model control for industrial wireless plant using WirelessHART hardware-in-the-loop simulator

The emergence of wireless technologies such as WirelessHART and ISA100 Wireless for deployment at industrial process plants has urged the need for research and development in wireless control. This is in view of the fact that the recent application is mainly in monitoring domain due to lack of confidence in control aspect. WirelessHART has an edge over its counterpart as it is based on the successful Wired HART protocol with over 30 million devices as of 2009. Recent works on control have primarily focused on maintaining the traditional PID control structure which is proven not adequate for the wireless environment. In contrast, Internal Model Control (IMC), a promising technique for delay compensation, disturbance rejection and setpoint tracking has not been investigated in the context of WirelessHART. Therefore, this paper discusses the control design using IMC approach with a focus on wireless processes. The simulation and experimental results using real-time WirelessHART hardware-in-the-loop simulator (WH-HILS) indicate that the proposed approach is more robust to delay variation of the network than the PID.     

Optimal controller synthesis for second order time delay systems with at least one RHP pole

An optimal H₂ minimization framework is proposed in this paper for devising a controller of PID in nature, based on a refined IMC filter configuration. The tuning strategy is for controlling time delay system with at least one pole which falls on the right half of the s-plane. An underdamped model based filter is used in place of the unity damping ratio (critically damped) filter available in the literature to improve the reset action. The method has a single adjustable closed loop tuning parameter. Guidelines have been provided for choosing the pertinent tuning parameter based on the sensitivity function. Simulation work has been executed on diverse unstable models to support the advantages of the proposed scheme. The proposed controller yields improved performances over other recently reported tuning techniques in the literature. Experimental implementation is carried out on an inverted pendulum for demonstrating the practical applicability of the present method. The efficacy of the intended controller design is quantitatively analyzed using the time integral performance index.     

An analytical method for PID controller tuning with specified gain and phase margins for integral plus time delay processes

In this paper, an analytical method is proposed for proportional-integral/proportional-derivative/proportional-integral-derivative (PI/PD/PID) controller tuning with specified gain and phase margins (GPMs) for integral plus time delay (IPTD) processes. Explicit formulas are also obtained for estimating the GPMs resulting from given PI/PD/PID controllers. The proposed method indicates a general form of the PID parameters and unifies a large number of existing rules as PI/PD/PID controller tuning with various GPM specifications. The GPMs realized by existing PID tuning rules are computed and documented as a reference for control engineers to tune the PID controllers.     

采用内模控制理论的双馈感应风机鲁棒控制器设计

针对工程中双馈感应电机转子电流控制器参数整定的问题,提出一种利用内模控制理论设计转子电流控制器的鲁棒控制方法。首先定义内模控制的灵敏度函数和互补灵敏度函数,并推导双馈感应电机转子电流控制系统传递函数,建立了转子电流内环的内模数学模型。IMC控制器的设计以平方积分误差值和鲁棒稳定M值为准则,并与传统比例积分控制器进行比较。通过对1.5 MW双馈感应电机的MATLAB/SIMULINK仿真表明,本文方法稳态跟踪精度高、动态响应快、对模型误差和外界干扰具有较好的鲁棒性。最后在11 k W的双馈风机实验平台上验证了所提方法的有效性。     

基于微分平坦的旋转倒立摆双闭环抗扰 PID 控制

针对一类不稳定、欠驱动二自由度旋转倒立摆系统, 提出一种基于微分平坦的双闭环抗扰 PID 控制方法。 首先, 建立倒 立摆的非线性动力学模型, 利用近似线性化分析系统的不稳定零动态与非最小相位特性; 然后, 结合微分平坦理论, 设计倒立摆 平坦输出,重构系统平坦状态, 并建立平坦状态与角度输出之间的转化关系,克服倒立摆的非最小相位影响; 进一步, 针对微分 平坦系统, 设计抗扰 PID 双闭环控制结构和带宽化调节方法, 在主动抗扰机制下实现对摆杆角度与悬臂角度的精准控制; 最后, 通过仿真与实验, 验证所提方法的有效性和实用性。 所提方法为欠驱动系统提供了一种结构简单、抗扰能力强的控制方案。     

Anti-sway position control of an automated transfer crane based on neural network predictive PID controller

In this paper, we develop an anti-sway control in proposed techniques for an ATC system The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2 DOF PID controller The simulation and experimental results show that the proposed control scheme guarantees performances, trolley position, sway angle and settling time in NNP PID controller than other controller As the results in this paper, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard. Accordingly, the proposed algorithm in this study can be readily used for industrial applications     

Improving performance using cascade control and a Smith predictor

Many investigations have been done on tuning proportional-integral-derivative (PID) controllers in single-input single-output (SISO) systems. However, only a few investigations have been carried out on tuning PID controllers in cascade control systems. In this paper, a new approach, namely the use of a Smith predictor in the outer loop of a cascade control system, is investigated. The method can be used in temperature control problems where the secondary part of the process (the inner loop) may have a negligible delay while the primary loop (the outer loop) has a time-delay. Two different approaches, including an autotuning method, to find the controller parameters are proposed. It is shown by some examples that the proposed structure as expected can provide better performance than conventional cascade control, a Smith predictor scheme or single feedback control system.     

Tuning of linear active disturbance rejection controller with robustness specification

Active disturbance rejection control (ADRC) treats all the model uncertainties and all the external disturbances as a generalized disturbance. It uses an extended state observer (ESO) to estimate the generalized disturbance in real time, and compensate it using a state-feedback control law, thus can achieve good disturbance rejection performance. For linear ADRC (LADRC), the parameters can be tuned via the bandwidths of the ESO and the feedback control, thus an LADRC can be regarded as a fixed-structured controller with several parameters to tune, just like a PID controller. To help tuning the parameters of LADRC, a tuning rule is proposed in this paper, with the aim to minimize the load disturbance attenuation performance in the integral of time square error sense, under the constraint of a specified robustness measure for the first-order processes with deadtime. The tuning rule is tested for a variety of benchmark systems and the gravity drained tanks case, and the performances are compared with the well-known PID tuning methods.     

A simple nonlinear PD controller for integrating processes

Many industrial processes are found to be integrating in nature, for which widely used Ziegler–Nichols tuned PID controllers usually fail to provide satisfactory performance due to excessive overshoot with large settling time. Although, IMC (Internal Model Control) based PID controllers are capable to reduce the overshoot, but little improvement is found in the load disturbance response. Here, we propose an auto-tuning proportional-derivative controller (APD) where a nonlinear gain updating factor α continuously adjusts the proportional and derivative gains to achieve an overall improved performance during set point change as well as load disturbance. The value of α is obtained by a simple relation based on the instantaneous values of normalized error (e_N) and change of error (Δe_N) of the controlled variable. Performance of the proposed nonlinear PD controller (APD) is tested and compared with other PD and PID tuning rules for pure integrating plus delay (IPD) and first-order integrating plus delay (FOIPD) processes. Effectiveness of the proposed scheme is verified on a laboratory scale servo position control system.     

Performance assessment of PID and IMC tuning methods for a mixing process with time delay

A flow process with time delay has been considered for modeling and control. A dilute solution of sodium chloride is used as tracer and an online conductivity measurement unit as sensor and recorder. The objective of the current study is to design control algorithms and present corresponding robust control analysis for the process. The control methodologies considered are (i) conventional PID control and (ii) internal model control (IMC). The control structures are comparatively analyzed using standard robustness measures for stability and performance. Of the two control algorithms, conventional PID and IMC, IMC exhibits faster settling time, no overshoot, better set-point tracking and disturbance rejection, and good robust performance than the PID control scheme.     

A novel auto-tuning PID control mechanism for nonlinear systems

In this paper, a novel Runge–Kutta (RK) discretization-based model-predictive auto-tuning proportional-integral-derivative controller (RK-PID) is introduced for the control of continuous-time nonlinear systems. The parameters of the PID controller are tuned using RK model of the system through prediction error-square minimization where the predicted information of tracking error provides an enhanced tuning of the parameters. Based on the model-predictive control (MPC) approach, the proposed mechanism provides necessary PID parameter adaptations while generating additive correction terms to assist the initially inadequate PID controller. Efficiency of the proposed mechanism has been tested on two experimental real-time systems: an unstable single-input single-output (SISO) nonlinear magnetic-levitation system and a nonlinear multi-input multi-output (MIMO) liquid-level system. RK-PID has been compared to standard PID, standard nonlinear MPC (NMPC), RK-MPC and conventional sliding-mode control (SMC) methods in terms of control performance, robustness, computational complexity and design issue. The proposed mechanism exhibits acceptable tuning and control performance with very small steady-state tracking errors, and provides very short settling time for parameter convergence.