Soft Computing and Fuzzy Logic
IEEE Software
Expert Systems with Applications: An International Journal
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
An architecture for adaptive fuzzy control in industrial environments
Computers in Industry
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The objective of process control in a reduction furnace is to optimise nickel recovery, while minimising fuel consumption and environmental contamination. This entails the exact control of temperature and gas composition in the furnace. Controlling the temperature of a multiple hearth furnace is a difficult task. Fast and extensive changes in operating conditions occur, complicated by non-linear and time-varying behaviour of the process and interaction between the different variables. Failing to solve the control problem with a normal PID controller led to development of a knowledge-based fuzzy controller, which keeps the temperature as close to the set profile as possible. Such controller is endowed with a set of 60 rule bases, which are dynamically switched depending on technological constraints and/or operating regions. The algorithm used for the resulting MIMO controller has a Mamdani-type inference system. This paper describes the implementation and the first field tests of a control algorithm, the results of which are very positive and encouraging.