An adaptive control scheme - expert system - that optimizes the operation of a proposed underground coal mining system with applications to shortwall, longwall and room and pillar mining systems

A proposed underground coal mining system consisting of an automatic extraction system (AES) type continuous miner, a surge bin, a shuttle car, a belt feeder and a main haulage belt is postulated. The problem posed is to develop an adaptive control strategy, expert system, that minimizes equipment delays while simultaneously maximizing the production of the proposed system. This problem is formulated and solved as a nonlinear optimization problem. The optimization strategy is formulated by specifying a nonlinear objective function with inequality constraints on the ranges of the controlled variables and a nonlinear equality constraint. A method of search is developed utilizing knowledge of the system and the form of the nonlinear constraint equation. The results of several computer runs are presented and analyzed. In every instance, the developed expert system operated more efficiently than either nonoptimum or suboptimum controlled systems. In most of the cases tested, the adaptively controlled system transports as much if not more coal as a bang-bang controlled system.