Terrence L. Blevins

PID Advances in Industrial Control

Abstract Major advances that improve control in the process industry have been made over the last ten years in the basic PID technology of modern distributed control systems. This paper addresses the impact that international standards have on control implementation and the tools utilized in industry for monitoring and commissioning PID control. Examples are used to illustrate how new technologies, such as model switching for process identification, have allowed manufacturers to introduce a new level of ease-of-use in tools developed for on-demand and adaptive tuning. This paper discusses PID modifications that improve the speed of recovery from process saturation conditions that are common in industrial applications. Also, details are provided on PID modifications that enable effective control with non-periodic measurement updates by wireless transmitters. Finally, prospective future directions for industrial PID controllers are sketched.

Evaluating PID adaptive techniques for industrial implementation

This paper outlines several adaptive techniques considered for implementation in the PID controller. It presents frequency domain interpolators for tracking ultimate gain and ultimate period, model-free tuning based on balancing P and I terms, and the adaptation of controller switching and model switching with the interpolation of parameters. From the perspective of the authors, a model switching technique using the interpolation of parameters offers a clear advantage, particularly for feedforward/feedback loops and multivariable control.

Data cleaning in the process industries

Abstract In the past decades, process engineers are facing increasingly more data analytics challenges and having difficulties obtaining valuable information from a wealth of process variable data trends. The raw data of different formats stored in databases are not useful until they are cleaned and transformed. Generally, data cleaning consists of four steps: missing data imputation, outlier detection, noise removal, and time alignment and delay estimation. This paper discusses available data cleaning methods that can be used in data pre-processing and help overcome challenges of “Big Data”.

Bridging the gap between universities and industry

The distributed control system (DCS) is the most prevalent means of implementing batch and continuous control in the process industry. The DCS platform may also be effectively used for the evaluation and demonstration of innovative algorithms developed at a university. The integrated online advanced controls, diagnostics, data analytics, and process modeling capability of a DCS facilitate university research. This working environment also prepares students for careers in industry. The paper discusses the industrial standards adopted by the DCS that allow students and researchers to concentrate on the application of new control capabilities. External applications such as Matlab can be used with the DCS to explore control and process modeling. In this environment, the student and researchers may take advantage of preconfigured and automated features of the DCS. Process simulations may be integrated into the DCS to create a virtual plant capability that is capable of running faster than real-time. The DCS supports wireless and internet access to the virtual plant which increases ease of use in a lab or pilot plant. The DCS system enables rapid exploration, discovery, and prototyping of process modeling and control technologies in a university environment and deployment in industry.

Intelligent PID Product Design

Abstract This paper outlines intelligent PID design for DCS. The design includes a PID algorithm with diverse standard options and algorithm extensions for wireless/event-driven control and for surge control. The core of the PID intelligence is adaptive process modeling based on model switching and parameter interpolation. The developed process model is applied to loop tuning, adaptive control, loop performance evaluation and valve diagnostics. A user-friendly interface provides insight into a loops current state and history events. The interface also provides advice about how to improve loop performance.

Improving PID Recovery from Limit Conditions

Abstract This paper addresses the performance of the PID under startup or during normal operation when the PID output becomes limited. Common techniques that have been utilized to reduce the time required to get to setpoint during process startup are reviewed. The response of the PID to conditions that limit PID operation during normal operating conditions is discussed for different implementation approaches. In particular under limiting conditions, anti-reset windup is automatically activated when a positive feedback network is used to create the reset contribution. For such implementations, the recovery from a process saturation condition may be improved by modifying the PID operation. An application example is used to show the impact of this modification on response speed and overshoot.