DIGITAL PID CONTROLLER DESIGN FOR DELAYED MULTIVARIABLE SYSTEMS

A new methodology is proposed to design digital PID controllers for multivariable systems with time delays. Except for a few parameters that are preliminarily selected, most of the PID parameters are systematically tuned using the developed plant state‐feedback and controller state‐feedforward LQR approach, such that satisfactory performance with guaranteed closed‐loop stability is achieved. In order to deal with the modeling error owing to the delay time rational approximation, an IMC structure is utilized, such that robust stability is achieved, without need for an observer, and with improved online tuning convenience. Using the prediction‐based digital redesign method, the digital implementation is obtained based on the above‐proposed analog controller, such that the resulting mixed‐signal system performance will closely match that of the analog controlled system. An illustrative example is given for comparison with alternative techniques.     

Restricted Structure Control Loop Performance Assessment For Pid Controllers And State‐Space Systems

A novel H₂ optimal control performance assessment and benchmarking problem is considered for discrete‐time state‐space multivariable systems, where the structure of the controller is assumed to be fixed apriori. The controller structure may be specified to be of PID, reduced order, or lead/lag forms. The theoretical problem considered is to represent the state‐space model in discrete polynomial matrix form and to then obtain the causal, stabilising, controller, of a prespecified form, that minimises an H₂ criterion. This then provides the performance measure against which other controllers can be judged. The underlying practical problem of importance is to obtain a simple method of performance assessment and benchmarking low order controllers. The main theoretical step is to derive a simpler cost‐minimization problem whose solution can provide both the full order and restricted structure (PID) optimal benchmark cost values. This problem involves the introduction of spectral factor and diophantine equations and is solved via a Wiener type of cost‐function expansion and simplification. The numerical solution of this problem is straightforward and involves approximating the simplified integral criterion by a fixed number of frequency points. The main benchmarking theorem applies to multivariable systems that may be unstable, non‐minimum phase and non‐square.     

PID数字控制器多指标优化模拟设计方法研究

建立PID数字控制器多指标统一优化模拟设计方法;用SIMULINK仿真研究数字PID控制对模拟PID控制的复现能力和PID计算机控制系统的阶跃响应,用MATLAB仿真筛选PID参数的优化组合值;提出并建立了一种新的PID数字控制器多指标优化模拟设计方法,包括:PID初值确定方法、模拟PID优化参数MATLAB筛选方案和软件流程图、模拟PID参数转换数字PID参数的方法、SIMULINK仿真验证设计结果的有效性的方法等;研究表明,该方法可用于1～5ms采样周期的PID数字控制器多指标优化模拟设计,且能独立使用、无需PID经验数据和其它设计/整定方法;提供了4个代表性的实例设计,验证了该方法的有效性。     

State controllability and optimal regulator control of time-delayed systems

An important recent advance in the solution of the optimal regulator control problem for time-delayed systems is extended here to multivariable systems and to systems which exhibit multiple time delays. The state equations are partitioned into discrete and continuous portions through a state transformation such that the solution of the optimal regulator problem reduces to finding a steady-state controller gain based on both a discrete and continuous Riccati matrix. The discrete Ricatti matrix is found independently of the continuous solution due to the partitioning of the state equations, and it is not necessary to solve the system of partial differential Riccati equations which arise in the traditional solution of the linear quadratic regulator (LQR) problem for time-delayed systems. In addition, through this state transformation it becomes possible to extend the standard state controllability tests to time-delayed systems. It is shown that the controllability of the transformed state space is necessary for a feasible solution to the optimal regulator problem for time-delayed systems. This is an important test to determine the practicality of various time-delayed system realizations. Numerical examples illustrate the application of the technique to systems exhibiting multiple time delays, multivariable systems and time-series models. It is shown that the classic Wood-Berry distillation model realization does not possess state controllability properties which explains why this system has been historically difficult to control using feedback techniques.     

Robust Controller Design And Pid Tuning For Multivariable Processes

In this paper, a robust controller design method is first formulated to deal with both performance and robust stability specifications for multivariable processes. The optimum problem is then dealt with using a loop‐shaping H_∞ approach, which gives a sub‐optimal solution. Then a PID approximation method is proposed to reduce a high‐order controller. The whole procedure involves selecting several parameters and the computation is simple, so it serves as a PID tuning method for multivariable processes. Examples show that the method is easy to use and the resulting PID settings have good time‐domain performance and robustness.     

A unified method for the design of nonovershooting linear multivariable state-feedback tracking controllers

We consider the use of linear multivariable feedback control to achieve a nonovershooting step response. A method is given for designing a linear time invariant state feedback controller to asymptotically track a constant step reference with zero overshoot and arbitrarily small rise time, under some mild assumptions. We present a unified design method that can be applied to continuous and discrete time systems, square and non-square systems, minimum and nonminimum phase systems, and also strictly proper and nonstrictly proper systems.     

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.     

Partially‐observable stochastic hybrid systems (poshss) state estimation and optimal control

This paper discusses the state estimation and optimal control problem of a class of partially‐observable stochastic hybrid systems (POSHS). The POSHS has interacting continuous and discrete dynamics with uncertainties. The continuous dynamics are given by a Markov‐jump linear system and the discrete dynamics are defined by a Markov chain whose transition probabilities are dependent on the continuous state via guard conditions. The only information available to the controller are noisy measurements of the continuous state. To solve the optimal control problem, a separable control scheme is applied: the controller estimates the continuous and discrete states of the POSHS using noisy measurements and computes the optimal control input from the state estimates. Since computing both optimal state estimates and optimal control inputs are intractable, this paper proposes computationally efficient algorithms to solve this problem numerically. The proposed hybrid estimation algorithm is able to handle state‐dependent Markov transitions and compute Gaussian‐ mixture distributions as the state estimates. With the computed state estimates, a reinforcement learning algorithm defined on a function space is proposed. This approach is based on Monte Carlo sampling and integration on a function space containing all the probability distributions of the hybrid state estimates. Finally, the proposed algorithm is tested via numerical simulations.     

Receding Horizon Optimization Approach to PID Controller Parameters Auto-tuning

A novel supervised receding horizon optimal scheme is presented for discrete time systems in the process control.In the employing level,PID controller is used,while the receding horizon approach is applied to the optimized level.The considered problem is to optimize the employing level PID controller parameters through minimizing a generalized predictive control criterion.Compared with a fixed parameters PID controller,the proposed algorithm provides well performance over a range of operating condition.     

PID控制器参数调整的滚动优化算法

A novel supervised receding horizon optimal scheme is presented for discrete time systems in the process control. In the employing level, PID controller is used, while the receding horizon approach is applied to the optimized level. The considered problem is to optimize the employing level PID controller parameters through minimizing a generalized predictive control criterion. Compared with a fixed parameters PID controller, the proposed algorithm provides well performance over a range of operating condition.     

Optimal digital controller and observer design for multiple time-delay transfer function matrices with multiple input–output time delays

In this article, we address the optimal digital design methodology for multiple time-delay transfer function matrices with multiple input–output time delays. In our approach, the multiple time-delay analogue transfer function matrix with multiple input–output time delays is minimally realised using a continuous-time state-space model. For deriving an explicit form of the optimal digital controller, the realised continuous-time multiple input–output time-delay system is discretised, and an extended high-order discrete-time state-space model is constructed for discrete-time LQR design. To derive a low-order optimal digital observer for the multiple input–output time-delay system, the multiple time-delay state obtained from the multiple time-delay outputs is discretised. Then, the well-known duality concept is employed to design an optimal digital observer using the low-order discretised multiple input time-delay system together with the newly discretised multiple time-delay state. The proposed approach is restricted to multiple time-delay systems where multiple time delays arise only in the input and output, and not in the state.     

A new anti‐windup strategy for PID controllers with derivative filters

This paper presents a new strategy for suppressing the windup effect caused by actuator saturation in proportional–integral–derivative (PID) controlled systems. In the proposed approach, the windup effect is modeled as an external disturbance imported to the PID controller and an observer‐based auxiliary controller is designed to minimize the difference between the controller output signal and the system input signal in accordance with an H‐infinite optimization criterion. It is shown that the proposed anti‐windup (AW) scheme renders the performance of the controlled system more robust toward the effects of windup than conventional PID AW schemes and provides a better noise rejection capability. In addition, the proposed PID AW scheme is system independent and is an explicit function of the parameters of the original PID controller. As a result, the controller is easily implemented using either digital or analog circuits and facilitates a rapid, on‐line tuning of the controller parameters as required in order to prevent the windup effect. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

PID控制器的状态空间描述和二次型优化设计

提出了一种双输入双输出的状态空间描述,用于表达PID控制系统.这种描述方法,忠实地反映了PID控制的结构、信号关系,避免了现有PID控制系统状态空间描述过程中的近似或冗余.可以在此描述的基础上,用状态空间的方法,讨论跟踪控制、优化控制等各种PID的控制问题.在PID控制系统的状态空间描述的基础上,讨论了满足二次型性能的PID控制器优化设计,并给出例子说明本文提出方法的有效性.这些例子说明,与现有的二次型优化PID控制器设计方法比较,本文方法更加灵活、控制器更加实用,且适用于各种阶次的被控对象.     

Stabilization for a class of nonlinear systems: A fuzzy logic approach

In this paper, the problem of stabilization for the class of continuous time nonlinear systems which are discretized in closed form is addressed. By using the Takagi–Sugeno model approach, a discrete controller capable of stabilizing the discrete Takagi–Sugeno model and the continuous model as well, is obtained. This scheme allows using a digital controller for stabilizing an analog plant.     

基于模糊神经网络PID控制器的EEC数字化设计

为实现航空发动机模拟式电子控制器(EEC)的数字化设计,以其低压压气机导流叶片调节通道为主要研究对象,提出一种模糊神经网络PID控制器,将模糊控制、神经网络、PID控制相结合,利用模糊控制专家经验优势和神经网络的自学习、自适应能力,优化PID控制参数,实现控制性能提升。仿真结果显示,基于模糊神经网络的PID控制器控制性能有较大提高,具有比常规神经网络PID控制器更小的超调量和更好的抗干扰性;适用于定常系统和非定常系统,具有更好的自适应性与鲁棒性;可应用于航空发动机模拟式电子控制器(EEC)的数字化设计。     

Fundamental limitation on achievable decentralized performance

A commonly accepted fact is that the diagonal structure of the decentralized controller poses fundamental limitations on the achievable performance, but few quantitative results are available for measuring these limitations. This paper provides a lower bound on the achievable quality of disturbance rejection using a decentralized controller for stable discrete time linear systems with time delays, which do not contain any finite zeros on or outside the unit circle. The proposed result is useful for assessing when full multivariable controllers can provide significantly improved performance, as compared to decentralized controllers. The results are also extended to the case, where the individual subcontrollers are restricted to be PID controllers.     

Pid And Pid‐Like Controller Design By Pole Assignment Within D‐Stable Regions

This paper presents a new PID and PID‐like controller design method that permits the designer to control the desired dynamic performance of a closed‐loop system by first specifying a set of desired D‐stable regions in the complex plane and then running a numerical optimisation algorithm to find the controller parameters such that all the roots of the closed‐loop system are within the specified regions. This method can be used for stable and unstable plants with high order degree, for plants with time delay, for controller with more than three design parameters, and for various controller configurations. It also allows a unified treatment of the controller design for both continuous and discrete systems. Examples and comparative simulation results are provided to illustrate its merit.     

Guaranteed cost PID control for uncertain discrete‐time stochastic systems with additive gain perturbations

This paper investigates a novel design method for robust nonfragile proportional‐integral‐derivative (PID) control that is based on the guaranteed cost control (GCC) problem for a class of uncertain discrete‐time stochastic systems with additive gain perturbations. On the basis of linear matrix inequality (LMI), a class of fixed PID controller parameters is obtained, and some sufficient conditions for the existence of the GCC are derived. Although the additive gain perturbations are included in the feedback systems, both the stability of closed‐loop systems and adequate cost bound are attained. As a sequel, decentralized GCC PID for a class of discrete‐time uncertain large‐scale stochastic systems is also considered. Finally, the numerical results demonstrate the efficiency of the proposed controller synthesis. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Robust H2 guaranteed cost fuzzy control for uncertain discrete‐time fuzzy systems via poly‐quadratic Lyapunov functions

In this paper, new approaches regarding H₂ guaranteed cost stability analysis and controller synthesis problems for a class of discrete‐time fuzzy systems with uncertainties are investigated. The state‐space Takagi‐Sugeno fuzzy model with norm‐bounded parameter uncertainties is adopted. Based on poly‐quadratic Lyapunov functions, sufficient conditions for the existence of the robust H₂ fuzzy controller can be obtained in terms of linear matrix inequalities (LMIs). Furthermore, a convex optimization problem with LMI constraints is formulated to design a suboptimal fuzzy controller which minimizes the upper bound on the quadratic cost function. The effectiveness of the proposed design approach is illustrated by two examples. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Design of digital PID controllers using the parameter space approach

In this paper, a parameter space approach is taken for designing digital PID controllers. The stability domains of the coefficients of the controllers are computed. The existing continuous-time results are extended to the case of discrete-time systems. In this approach, the stability region is obtained in the plane of two auxiliary controller coefficients by assuming a fixed value for a third auxiliary controller coefficient. The stability region is defined by several line segments or equivalently by several linear equalities and inequalities. Then, through mapping from the auxiliary coefficient space to the original controller coefficient space, exact stability domain in the (K_P ???K_I ???K_D ) space is obtained. The method is also extended for locating the closed-loop poles of PID control systems inside the circles with arbitrary radii, centred at the origin of the z-plane. The results can be used in the design of dead-beat control systems.