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Fuzzy logic offers a great deal to a wide range of closed and open-loop applications. It is of particular benefit for processes with non-linear characteristics and sequences with opposing control objectives, for example the control of temperature and humidity. This form of logic is also ideal when more than one control variable is involved.

But what is fuzzy logic? By definition it is a form of reasoning that uses approximation rather than complex mathematical models. With fuzzy logic, control algorithms can be given in everyday language using if/then rules. Fuzzy control systems operate in three stages: fuzzification, where physical values are converted into linguistics; fuzzy inference, involving if/then rules generating output values; and defuzzification, the conversion of linguistic values back to physical values.

The problem with conventional proportional integrated (pid) devices and bang-bang controllers is that they can only handle one type of variable. Problems must be solved using a number of independently operating control loops, which are unable to talk to one another. When interdependencies of physical variables have to be exploited, the engineer must set up a complete mathematical model of the process and derive from it the differential equations that are essential to the solution.

In reality this is rarely feasible. Creating a mathematical model for a real-world problem can involve years of work. Most models therefore use extensive simplifications that require fudging to optimise the resulting controller. Optimising the system at one operating point using global factors inevitably degrades performance at other points.

This is where the fuzzy plc provides an elegant and highly efficient solution. Fuzzy logic lets engineers design supervisory multi-variable controllers from experience and experimentation, rather than from mathematical models. This can help engineers to slash over 50% off design times. The fuzzy plc can be programmed using approximate if/then rules in iterative loops, eliminating the need for complex formulae.

Moeller Electric's version of the fuzzy plc is available through its Closed Loop Toolbox package, designed for its PS4-416 and PS4-341 plcs. This allows regulator modules using fuzzy logic to be created. These can then be linked to the applications program as function blocks.

Once written, the fuzzy logic function blocks can be reused, with any parameter changes implemented to suit new applications. This makes considerable savings on engineering costs. The status information of variables is written colloquially in a special editor, with rules generated using if/then commands. Thus, it is possible to control even complex, non-linear processes that would be very difficult or impossible to describe mathematically.

Applying logic
The best way to appreciate the capabilities of fuzzy logic and the fuzzy plc is by looking at some of the diverse applications that have already benefited from their adoption.

One successful use of the fuzzy plc is in automatic gantry crane operation. The pendulum motion of loads suspended from a gantry crane can endanger the operating personnel and the load being transported. The crane operator, by skillful manual operation of the controls, must ensure that this unavoidable motion subsides as quickly as possible, since extended loading and unloading is costly. Increasingly, operating conditions mean that such suppression of load swing by the operator is not possible, so alternative mechanical or control engineering solutions have been sought. Mechanical solutions, such as cable bracing or scissor-action systems, are extremely expensive to install and maintain. Active crane swing compensation is a relatively inexpensive way to achieve greater safety and the faster transfer of loads.

An active crane swing compensation system developed by Moeller consists of positioning logic, encapsulated with a fuzzy logic regulator, to effect swing damping. This intelligent regulator, built into a fuzzy plc, reproduces the skill of the crane driver. When this type of anti-sway control system was recently applied to a 64-ton gantry crane the productivity increased by 20%.

As mentioned, fuzzy logic is tailor-made for temperature control. One area where it could be of use is plastics injection moulding machines, where precise temperature control is crucial to achieve high and consistent product quality. This requires laborious fine-tuning of the algorithms concerned because of the relatively large dead times involved in an extrusion machine and the significant coupling between the different temperature zones.

To reduce machine commissioning time, Moeller has developed a self-tuning controller using the fuzzy plc. With the fuzzy logic-based controller, the machine does not need to be cooled to room temperature before self-tuning. Even very difficult temperature zones with big dead times can be handled by this algorithm, resulting in a very robust controller.

This is important as the temperature characteristics of an empty machine and one filled with plastics material are poles apart. The fuzzy logic controller in the moulding machine can reach the setpoint faster and with a significantly smaller overshoot than the conventional solution.

The fuzzy plc is expected to play an increasing role in the control of heating, lighting and air conditioning systems in buildings. Climate control systems in particular show a high potential for energy savings using the technology. Their use was borne out in a recently completed application at a major hospital in Europe. The integration of fuzzy logic into the hospital's climate control system yielded a 25% saving on electrical energy, around 拢35 000 annually.

The fuzzy logic controller outputs the set values for the hospital system's coolant, water heater and humidifier water valves. The control strategy involves using different temperature and humidity sensors to determine how to operate the air conditioning process to conserve energy.

The capability of processing interdependent variables results in significant advantages over conventional approaches. For example, we know that when temperature rises, relative humidity of air decreases. This fact can be exploited by implementing a fuzzy logic control strategy that allows the humidity controller to be told in advance that activation of the heater valve is about to be needed. The humidity controller can then respond to this action before it detects it by its sensor. The result is an increase in control quality.

The key to success lies in the combination of conventional automation techniques and fuzzy logic. Fuzzy logic was never intended to replace conventional control engineering, rather it complements conventional approaches with a highly efficient methodology to implement multi-variable control strategies. Thus, the major potential for fuzzy lies in the implementation of supervisory control loops. The advent of the fuzzy plc means that its benefits are at the disposal of everyone and at the right price.