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Fuzzy Environmental Control

For those looking for practical applications of fuzzy logic in a real-world product, please read on. This isn’t a sexy application with millions of dollars thrown at it – it’s just a company trying to build a better product using fuzzy logic. They did just that …

     Number 31                                            October 92
                      The Huntington Technical Brief  
                          By David Brubaker Ph.D.
                       FUZZY ENVIRONMENTAL CONTROL


In January 1992, Liebert Corporation of Columbus, Ohio, specialists in environment control units for computer installations, introduced the LogiCool, a precision temperature and humidity controller with a fuzzy control unit at its heart. This Technical Brief briefly discusses both the design of LogiCool’s fuzzy controller, and the process through which Liebert elected to use a fuzzy approach.


Control of the environment for large computing systems is often a far greater challenge than for rooms inhabited by people. Not only do the systems themselves generate heat, but they are often specified by their manufacturers to be maintained in as little as a plus-or-minus 1 degree (Fahrenheit) range. Humidity is also a challenge, causing, for example, corrosion and jamming of associated mechanical systems at high humidity levels and the enhanced possibility of static discharge with low levels. Humidity control is often specified to be 50% relative humidity, with a maximum swing of plus-or-minus 3% per hour.

In addition, the design of a precision environmental control system also faces nonlinearities, caused by such system behavior as air flow delay and dead times, uneven airflow distribution patterns, and duct work layouts. Uncertainties in system parameters are often present, for example, room size and shape, location of heat-producing equipment, thermal mass of equipment and walls, and amount and timing of external air introduction.

Recognizing these challenges, Liebert undertook the design of a control system requiring (in general terms):

In short, Liebert wanted to precisely control with simple hardware a nonlinear system with significant uncertainties. Several traditional linear approaches were considered but proved inadequate. A fuzzy logic approach was investigated and ultimately implemented. Design specifics – The LogiCool control system has six fuzzy inputs, three fuzzy outputs, and 144 principles (rules). It runs on a Motorola 6803 microprocessor, and is programmed in C.

LogiCool’s fuzzy input variables are: e_temperature, the temperature relative to a setpoint; delta_T/delta_t, the rate of temperature change; e_humidity, the humidity relative to a setpoint; delta_H/delta_t, the rate of humidity change; and two proprietary variables associated with the action of the controllers.

Fuzzy outputs control: 1) amount of cooling, 2) amount of dehumidification, and 3) heat. Outputs can also be treated as fedback input variables, and time delays are treated as fuzzy outputs as well. Each fuzzy variable is assigned seven membership functions as values, with the traditional Large_Negative, Medium_Negative, Small_Negative, Near_Zero, Small_ Positive, Medium_Positive, and Large_Positive as labels. Ranges for the values of each variable are proprietary.

An example of a temperature control principle, using the as …then … (rather than the if … then …) syntax, is:

as temperature relative to set point is small_positive and temperature rate of change is medium_positive then amount of cooling is small_positive;

The Liebert design also incorporates time delays into their principles. The following demonstrates both this as well as the use of a fuzzy output as a feedback variable.

as temperature relative to setpoint is small_negative and amount of cooling is small_positive then wait delay to cooling change is medium_positive;

A fuzzy OR operator (maximizer) is used as the defuzzification technique, avoiding the complicated calculations associated with a centroid approach. Liebert has found that with the large number of principles, a more elaborate approach is unnecessary. Inputs are sampled, the principle-base accessed, and outputs are updated once a second. The “long” inter-sample delay allows the 6803, a simple eight-bit microprocessor, to implement this rather large fuzzy system.


A key feature of the system is LogiCool’s Economizer, which also runs under fuzzy control. When appropriate (for example in the cool of the morning), the outdoor ambient temperature is used to assist in internal temperature control. While on/off control of the Economizer could have been used, fuzzy logic greatly reduced the number of system cycles, thereby significantly reducing wear on the damper.


The sequence that resulted in the decision to use fuzzy logic started roughly eighteen months ago. From the engineering side, the decision was driven by being able to meet difficult requirements. Two Liebert engineers, Terry Bush and Dennis Weber, had already read, become interested in, and familiarized themselves with fuzzy technology, and were therefore able to recognize that a fuzzy approach could satisfy the stringent requirements. Simultaneously, Liebert marketing was both aware of fuzzy logic controlled air conditioning systems available outside the United States, and was also getting feedback from customers indicating that an improved method of handling complex internal environmental control was needed. Putting the two together, engineering was asked to investigate a fuzzy controller.

Liebert engineers designed and implemented the system in-house, with the entire fuzzy logic controller portion completed in two to three months. A commercially available fuzzy development tool was not used, primarily because in the beginning there was insufficient confidence in the approach to justify the expense of such a tool. Liebert is still satisfied with the decision to “roll its own” system, as it resulted in a design that incorporates a number of features not easily provided in the tools available at the time, for example the delaying of output actions by fuzzily defined wait delays.

Liebert engineers did ultimately write a PC-based simulator to test the fuzzy design under simulation prior to committing it to hardware. Conclusion – Although quantitative metrics are not available, Liebert reports that LogiCool has fully met its design goals. Damper and compressor cycling times have been greatly reduced, especially during Economizer operation. This reduction in cycling times results in increased reliability and increased expected component life. LogiCool also meets Liebert’s operational requirements associated with precisely controlling temperature and humidity in rooms with uncertain and nonlinear characteristics. Moreover, installation includes no tuning procedure – the same set of principles satisfies all installations.

Liebert is completely satisfied with the response to LogiCool. Sales since its introduction last January are better than expected, and production run sizes are being increased to respond to the demand. In addition, in recognition of the innovation in overall design, the LogiCool has been recognized by HVAC News as a 1992 Design Winner. For more information on the LogiCool, call Liebert Corporation, at 1-800-877-9222.

The Huntington Technical Brief is published, monthly and free of charge, as part of the marketing effort of Dr. David Brubaker of The Huntington Group. A full collection of past issues (starting with number 5 — issues 1 through 4 are unrelated to fuzzy logic and are unavailable) may be obtained directly from Dr. Brubaker by calling 415-325-7554. There is minimal charge for getting back issues.

Copyright 1992 by The Huntington Group
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