**DESIGN AND EVALUATION OF AN AUTO-TUNING CONTROL SYSTEM**

FOR AN ALTITUDE TEST FACILITY

Abstract

FOR AN ALTITUDE TEST FACILITY

Abstract

Simulated altitude testing of large aircraft engines is a

very expensive, but essential step in the development and

certification of gas turbines used by commercial airlines. A

significant contributor to the cost of this process is the

time-intensive task of manually tuning the facility control

system that regulates the simulated flight condition. Moreover,

control system tuning must be performed each time

the test conductor changes the flight condition. An adaptive

control system that automatically performs this task can

significantly reduce the costs associated with this type of

engine testing.

This paper examines the features of an auto-tuning

controller architecture that contains both disturbance feedforward

and PID feedback components in a two-input, twooutput

multivariable configuration. The paper reviews the

underlying concepts of an auto-tuning system and contrasts

its advantages/disadvantages with respect to other adaptive

control techniques. The algorithm used to automatically

tune the controller does not require a facility model. However,

a nonlinear facility model was developed and used to

substantiate a decoupled-loop design approach, to validate

the controller design concept, and to evaluate the resulting

adaptive control system design performance. This analysis

and other practical design issues that impact the auto-tuning

control system performance are addressed in the paper. The

paper also presents results that illustrate the automatic tuning

sequence and the disturbance rejection performance

exhibited by this system during large engine transients at

several key points in the flight envelope. The auto-tuning

controller described in the paper was implemented at a

Pratt & Whitney flight test facility used in the development

of large, high bypass ratio gas turbines.

Rationale for the Auto Tune Control Concept

Unlike the MRAC and STR concepts, the Auto-Tune adjustment

(adaptation) mechanism does not require any a

priori information about system dynamics to compute the

PID controller parameters. Moreover, an Auto-Tune system

only updates the controller on an operator-demand basis.

The MRAC and STR methods do not explicitly interact

with the system operator. These two characteristics of the

auto-tuning concept were the primary factors in selecting

this adaptive concept for the altitude test facility application.

This section examines the underlying features of the

Auto-Tune concept and motivates the rationale for selecting

a PID controller for this application.

The automatic tuning performed with this scheme can be

characterized as a crude, but robust method that identifies

two key parameters characterizing process dynamics. The

Auto-Tune adaptation algorithm approaches the control

design in a manner quite familiar to first-generation single

input/single output control system designers. The fundamental

idea centers on determining the gain and frequency

at which the system dynamics become conditionally stable

under pure proportional feedback control. These frequencydomain

characteristics of the system are designated as the

ultimate gain and ultimate frequency, respectively. Using

Ziegler-Nichols relationships, the PID controller parameters

can be determined from the ultimate gain and frequency

information. It is well known that PID control systems

designed with the Ziegler-Nichols method exhibit

very good disturbance rejection performance, but tend to

have significant overshoot when responding to set-point

changes (Astrom & Hagglund - 1995). Degraded set point

responses do not present a problem in the altitude test facility

application since the control problem focuses completely

on disturbance rejection performance. The chamber

pressure and plenum pressure set points remain at fixed

values throughout an engine transient test scenario.

As in most control system synthesis problems, both time

and frequency based methods exist for formulating an experiment

that produces the information required to compute

the Ziegler-Nichols gains. In most practical control applications,

a frequency-based experiment produces superior results

and was the method chosen in this application. The

central idea in the frequency-based approach relies on the

fact that most real systems produce stable limit-cycles under

relay feedback. The theoretical basis for this statement

was developed in Astrom - 1991. The method of harmonic

balance or describing function method (Gelb and VanderVelde

– 1968) provides the mathematical framework for

analyzing relay-induced limit-cycles and extracting the

ultimate gain and ultimate frequency from the experimental

data.

http://web.iac-online.com/images/Publications/35.pdf

**On-line PID Controller Design via a Single Auto-tuning Neuron**

**Abstract:**

A simple tuning strategy for PID controller design will be proposed in this paper. With the

use of single neural estimator (SNE), three control gains of PID controller are not fixed during the

control procedure, but will be adjusted on-line such that better output response can be achieved. In

this control strategy the exact model of plant will not need to be known and identified. Lastly, two

simulation results are provided to show the control performance by using the proposed adaptive PID controller.

1. Introduction

2. Preliminaries

2.1 Auto-tuning neuron

2.2 PID controller

3. Self-tuning Adaptive PID

Controller

3.1 MIT rule

3.2 Control structure and algorithm

3.2.1 A tuning algorithm for PID control gains

3.2.2 A tuning algorithm for the SNE

4. Illustrative Examples

5. Conclusions

http://www.kyu.edu.tw/93/95paper/v8/95-061.pdf

**Auto-Tuning of PID Controllers via Extremum Seeking**

**Abstract**—The proportional-integral-derivative (PID) controller

is widely used in the process industry, but to various

degrees of effectiveness because it is sometimes poorly tuned.

The goal of this work is to present a method using extremum

seeking (ES) to tune the PID parameters such that optimal

performance is achieved. ES is a non-model based method

which searches on-line for the parameters which minimize a

cost function; in this case the cost function is representative

of the controllers performance. Furthermore, this method has

the advantage that it can be applied to plants in which

there is no knowledge of the model. We demonstrate the

ES tuning method on a cross section of plants typical of

those found in industrial applications. The PID parameters

are tuned based on the results of step response simulations to

produce a response with minimal settling time and overshoot.

Additionally, we have compared these results to those found

using other tuning methods widely used in industry.

Overall ES PID tuning scheme.

http://www.nt.ntnu.no/users/skoge/prost/proceedings/acc05/PDFs/Papers/0401_ThA17_2.pdf