Abstract:

Chemical processes are usually high-dimensional multivariable systems. When designing the bottom regulatory PID control system, the traditional subjective analysis methods relying on control engineers are difficult to be applied and fail to the optimal control configuration, so a simple and fast computer optimization algorithm is urgently needed. So, an optimization algorithm for decentralized control loop configuration is proposed based on genetic algorithm. In this algorithm, the structure matrix is encoded in string form and the variable pairings are transformed into an integer array, then through choosing the right genetic operator the operations involving crossover, mutation and selection are applied on the integer array. The optimal variable pairing scheme under unconstrained condition is obtained. Moreover, the genetic operator is improved and adjusted according to the constraint conditions. Based on the optimal pairing scheme under unconstrained conditions, the optimal variable pairing scheme with constraints can be obtained by only using mutation and selection operators with a faster calculation speed. Finally, the validity and correctness of the algorithm are tested by case studies involving TE process.

摘要：

化工过程通常为高维大系统，在进行底层常规PID控制系统设计时，难以得到最佳配对方案，迫切需要一种简便且快速的计算机优化算法解决该问题。对此提出了一种基于遗传算法的分散常规控制系统结构设计的优化求解算法。该算法基于遗传算法的思想，对结构矩阵进行字符串形式的编码，将变量配对转换成数组形式，选择合适的遗传算子，通过交叉、变异、选择等遗传操作，解得无约束条件下的最优变量配对方案。其次，结合约束条件对遗传算子适当改进和调整，以无约束条件下的最优配对方案为基础，仅需通过变异和选择算子，就可解得存在约束条件的最优变量配对方案，并且具有较快的计算速度。最后通过包括TE过程在内的实例分析证明了该算法的有效性与准确性。