Topic: Advanced Control

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Surprise! Field-Based Control Beats DCS
It Is Evident That Device-Based Control Exceeds DCS-Based Control in Reliability and Performance

Control Software
The Latest in Functionality and Features for Control Software

Adaptive Level Control
Exploring the Complexities of Tuning Level Controllers and How an Adaptive Controller Can Be Used in Level Applications

Is Field-Based Control Really All That?
Recent Studies Shown That the Fieldbus-for-I/O-Only Approach Is Likely a Source of Compromised Performance and Unknown Latencies

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White Papers: In Depth Research

Plant Modeling: A First Step to Early Verification of Control Systems
Author: Arkadiy Turevskiy, Technical Marketing Manager, The MathWorks
Posted: 03/02/2010
Today's control system engineers face competing design demands: increase embedded system performance and functionality, without sacrificing quality or breaking the budget. It is difficult to meet these challenges using traditional design and verification approaches.

Without simulation it is impossible to verify a control design until late in the development process when hardware prototypes become available. This is not an insurmountable problem for simpler designs with predictable system behavior, because there are fewer sources of error in simpler control algorithms--and those errors can often be resolved by tuning the controller on the hardware prototype.

Today's multidomain designs combine mechanical, electrical, hydraulic, control, and embedded software components. For these systems, it is no longer practical to delay verification until late in the development process. As system complexity grows, the potential for errors and suboptimal designs increase. These problems are easiest to address when they are identified early in the development process. When design problems are discovered late, they are often expensive to correct and require time-consuming hardware fixes. In some cases the hardware simply cannot be changed late in the development process, resulting in a product that fails to meet its original specifications.

Traditional verification methods are also inadequate for testing all corner cases in a design. For some control applications, it is impractical or unsafe to test the full operating envelope of the system on hardware.

Reducing Energy Cost through Improved Disturbance Rejection
Author: Robert C. Rice, PhD, & Douglas J. Cooper, PhD, Control Station, Inc.
Posted: 02/23/2010
Two of the most popular architectures for improving regulatory performance and increasing profitability are 1) cascade control and 2) feed forward with feedback trim. Both architectures trade off additional complexity in the form of instrumentation and engineering time for a controller better able to reject the impact of disturbances on the measured process variable. These architectures neither benefit nor detract from set point tracking performance. This paper compares and contrasts the two architectures and links the benefits of improved disturbance rejection with reducing energy costs in addition to improved product quality and reduced equipment wear. A comparative example is presented using data from a jacketed reactor process.

The cost per barrel of crude oil has risen dramatically, increasing the burden on process facilities for both quality and profitable production. Adjusted for inflation, the cost of oil averaged $19.61 from 1945 thru 2003. October 2004 saw the per barrel cost of oil rise to $55.67, rising 70% over a 10-month timeframe and negatively impacting the profitability of companies across the process industries. According to the U.S. Department of Energy, 43% of all energy consumed by the average pulp and paper mill is production related. This percentage is small when compared to other industry segments such as chemicals (74%), glass (89%), and aluminum (93%). In all cases, the higher cost of energy suggests that all process companies need to examine ways of curbing energy consumption and unnecessary increases to their cost of goods sold. Improving disturbance rejection through cascade control or feed forward with feedback trim provides one way of achieving those objectives.

Improved disturbance rejection is linked to increased product quality and decreased equipment wear. These are important benefits, indeed. Consider the market value of high quality white paper produced by an average mill. On-spec production is sold at a premium of approximately $2,000 per ton whereas "seconds" are sold on the aftermarket at a discounted rate. Of the 6%-8% that fails to meet spec, only 2% is classified as "broke" and able to be re-pulped Next consider the investment in production facilities. With initial costs of $400-$500 million and annual maintenance budgets approaching 10%, mills must operate 24 x 7 in order to recoup the investment. Effective disturbance rejection provides a valuable means of achieving a return on those investments through increased quality and decreased equipment wear. Additionally, it offers significant value in terms of reduced energy consumption and lower cost of goods sold.

A Simple Single Setting Controller Yields PI Performance
Author: Robert L Heider, PE, & Zachary Wegmann
Posted: 02/23/2010
This paper presents a simple velocity control algorithm with output modification that has equivalent PI controller dynamic performance. The controller features a single control setting. The controller can be easily configured in most distributed control systems, DCS and programmable logic controllers, PLC. This paper describes the controller structure and behavior as well as a control discussion on how to calculate the gain setting to determine the control period. To test the controller on real processes, the algorithm was applied to a level and temperature control loops in a laboratory, pilot plant setting.

A control algorithm presented by W. Steven Woodward describes a velocity temperature controller [1] that modifies the output based on the pervious output value when the process variable, PV, crosses the set point, SP. This modification is the algebraic mean of the current calculated output and the output value at the previous zero error crossing. The term coined for this algorithm is "Take-Back-Half", TBH. This algorithm has some acceptance as an embedded application controller. In this paper we will demonstrate how this controller has applicability to the process control community. In section 2, we will describe how this simple controller functions and how to program the algorithm. Section 3 discusses the controller system design and how to determine the gain setting and closed loop period. In section 4 we will present the results of the pilot scale controller’s performance. In section 5 we will set forth the conclusions.

Model-Based Tuning Methods for PID Controllers
Author: Jeffrey Arbogast, Department of Chemical Engineering University of Connecticut; Douglas J. Cooper, PhD, Control Station, Inc.; & Robert C. Rice, PhD, Control Station, Inc.
Posted: 02/23/2010
The manner in which a measured process variable responds over time to changes in the controller output signal is fundamental to the design and tuning of a PID controller. The best way to learn about the dynamic behavior of a process is to perform experiments, commonly referred to as "bump tests." Critical to success is that the process data generated by the bump test be descriptive of actual process behavior. Discussed are the qualities required for "good" dynamic data and methods for modeling the dynamic data for controller design. Parameters from the dynamic model are not only used in correlations to compute tuning values, but also provide insight into controller design parameters such as loop sample time and whether dead time presents a performance challenge. It is becoming increasingly common for dynamic studies to be performed with the controller in automatic (closed loop). For closed loop studies, the dynamic data is generated by bumping the set point. The method for using closed loop data is illustrated. Concepts in this work are illustrated using a level control simulation.

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