A hybrid PC/PLC architecture for manufacturing-system control—theory and implementation

This paper presents a novel and generic PC/PLC-based software/hardware architecture for the control of flexible manufacturing workcells. The proposed implementation methodology is based on the utilization of any one of the available formal discrete-event-system control theories in conjunction with state-of-the-art industrial programmable-logic controllers (PLCs). The methodology has been illustrated to be a viable technique through its actual implementation in our laboratory using a robotic-workcell testbed. The specific control theory used is a combination of Extended Moore Automata and Ramadge-Wonham Automata that has been developed by our research group. The modular control software architecture has been developed for MS-Windows environments (running on one PC interfaced to the PLCs) and allows the use of different formal control theories as well as different commercial PLC hardware. The effective graphical user interface provides a transparent programming environment, where users are not expected to have a full knowledge of the formal control theory used.     

Robots positioning control revisited

Positioning control systems for robot arms are presented within a general framework in view of unification and classification. Treating coupling torques from other links as an external disturbance reduces the design of the control system to that of SISO servomechanisms driving each of the robot axes individually. A short survey of many control strategies proposed in the literature presents them as different methods aiming at attenuation of this disturbance. The use of disturbance observers is shown to provide a nice and simple way for that purpose. This could be applied to the improvement of actual industrial robots at the cost of slight software modifications.     

Robust ℋ︁∞ PID control for multivariable networked control systems with disturbance/noise attenuation

In this paper, we study the design problem of PID controllers for networked control systems (NCSs) with polyhedral uncertainties. The load disturbance and measurement noise are both taken into account in the modeling to better reflect the practical scenario. By using a novel technique, the design problem of PID controllers is converted into a design problem of output feedback controllers. Our goal of this paper is two‐fold: (1) To design the robust PID tracking controllers for practical models; (2) To develop the robust ??_∞ PID control such that load and reference disturbances can be attenuated with a prescribed level. Sufficient conditions are derived by employing advanced techniques for achieving delay dependence. The proposed controller can be readily designed based on iterative suboptimal algorithms. Finally, four examples are presented to show the effectiveness of the proposed methods. Copyright © 2011 John Wiley & Sons, Ltd.     

On the robust control of stable minimum phase plants with large uncertainty in a time constant. A fractional-order control approach

This paper addresses the problem of designing controllers that are robust to a great uncertainty in a time constant of the plant. Plants must be represented by minimum phase rational transfer functions of an arbitrary order. The design specifications are: (1) a phase margin for the nominal plant, (2) a gain crossover frequency for the nominal plant, (3) zero steady state error to step commands, and (4) a constant phase margin for all the possible values of the time constant (T$T$): 0<T<∞$0<T<\infty$. We propose a theorem that defines the structure of the set of controllers that fulfil these specifications and show that it is necessary for these robust controllers to include a fractional-order PI$PI$ term. Examples are developed for both stable and unstable plants, and the results are compared with a standard PI$PI$ controller and a robust controller designed using the QFT$QFT$ methodology.     

Genetic based sensorless hybrid intelligent controller for strip loop formation control between inter-stands in hot steel rolling mills

Safe operating environment is essential for all complex industrial processes. The safety issues in steel rolling mill when the hot strip passes through consecutive mill stands have been considered in this paper. Formation of sag in strip is a common problem in the rolling process. The excessive sag can lead to scrap runs and damage to machinery. Conventional controllers for mill actuation system are based on a rolling model. The factors like rise in temperature, aging, wear and tear are not taken into account while designing a conventional controller. Therefore, the conventional controller cannot yield a requisite controlled output. In this paper, a new Genetic-neuro-fuzzy hybrid controller without tension sensor has been proposed to optimize the quantum of excessive sag and reduce it. The performance of the proposed controller has been compared with the performance of fuzzy logic controller, Neuro-fuzzy controller and conventional controller with the help of data collected from the plant. The simulation results depict that the proposed controller has superior performance than the other controllers.     

A closed-loop cross-correlation method for detecting model mismatch in MIMO model-based controllers

Correlation between a dithering signal and the prediction error has been used for detecting model mismatch in univariate model based control systems. This paper extends that approach to MIMO control systems. A closed-loop cross-correlation method is presented to detect which specific input-output pairings of a model-based controller are mismatched. This method may be used in screening the complete set of models and in selecting candidate models for re-identification. The method first finds the rows and columns of the transfer function matrix that contain mismatch, and then the candidates are found by the intersection of the said rows and columns. Placing the system under partial control, whereby one or more of the manipulated variables are held constant, can be used to further reduce the set of candidate models.     

光伏快速充电站配电变压器端电能质量综合控制研究

针对光伏快速充电站将光伏发电与电动汽车快速充电站有机结合,在充分发挥清洁能源优势和大量提升充电效率的同时所带来的电能质量扰动类型复杂、变化快速等问题,提出了一种基于串并联组合配电网柔性交流输电(distribution flexible AC transmission system, DFACTS)的新型电能质量补偿器的电能质量综合控制方法。深入研究了新型电能质量补偿器主电路拓扑,建立起了动态工作模型。详细分析了新型电能质量补偿器线性自抗扰控制方法的工作原理,设计出线性自抗扰控制器。并针对各DFACTS控制器间的交互影响,提出多DFACTS控制器的协调控制策略。最后搭建仿真模型,进行仿真验证。仿真结果表明,所提出的新型电能质量补偿器采用线性自抗扰控制方法相比传统PI控制方法,提高了电能质量扰动快速变化时的综合补偿能力和动态响应能力。并且验证了该协调控制能有效提高系统电压稳定能力,具有良好的可行性和有效性。     

Feedback stabilization for high order feedforward nonlinear time-delay systems

This paper investigates the problem of global strong stabilization by state feedback, for a family of high order feedforward nonlinear time-delay systems. The uncertain nonlinearities are assumed to satisfy a polynomial growth assumption with an input or delayed input dependent rate. With the help of the appropriate Lyapunov–Krasovskii functionals, and a rescaling transformation with a gain to be tuned online by a dynamic equation, we propose a dynamic low gain state feedback control scheme. A simulation example is given to demonstrate the effectiveness of the proposed design procedure.     

A survey on industrial applications of fuzzy control

Fuzzy control has long been applied to industry with several important theoretical results and successful results. Originally introduced as model-free control design approach, model-based fuzzy control has gained widespread significance in the past decade. This paper presents a survey on recent developments of analysis and design of fuzzy control systems focused on industrial applications reported after 2000.