Intelligent Integrated Optimization Control Design of Comprehensive Production Indices for Sintering Process

The sintering process is a strong nonlinear system with complexity and multi-parameters. An intelligent integrated optimization algorithm based on comprehensive production Indices is presented to solve the optimization control problem of comprehensive production Indices. First, the neural network prediction model for the comprehensive production indices is proposed, which is synthesizing a lot of techniques, including correlation analysis, principal components analysis, and neural network and so on. And the target function was deduced using the multi-objective satisfactory optimization technology. At last, this paper incorporates chaos algorithm into the particle swarm optimization algorithm, and proposes a multi-objective particle swarm optimization algorithm based on chaos searching to calculate the optimization parameters, and the optimization guidance is introduced. The results of actual runs show that the proposed intelligent integrated algorithm provides a efficient and applied way to resolve the problem of optimization control for the complex strong correlation coupling, time-varying delay industrial process, and provides an effective and new idea to implement the global optimization control for process industry.