研究了服务率不确定情况下的单站点传送带给料加工站(CSPS)系统的鲁棒优化控制问题。在仅知服务率区间的条件下,以CSPS系统的前视距离作为控制变量,将鲁棒优化控制问题建模成不确定参数的半马尔可夫决策过程(SMDP)的极大极小优化问题,在状态相关的情况下,给出全局优化算法进行鲁棒控制策略求解。首先,运用遗传算法求解固定策略下的最差性能值;其次,根据求解得到的最差性能值,运用模拟退火算法求解最优鲁棒控制策略。仿真结果表明,服务率不确定的CSPS系统的最优鲁棒性能代价与服务率固定为区间中值系统的最优性能代价相差不大,并且随着不确定区间的缩小,两者的差值越小,说明了全局优化算法的有效性。
The robust optimal control of single Conveyor-Serviced Production Station (CSPS) with uncertain service rate was researched. Under the cases where only the interval of service rate was given and the look-ahead range was controllable, the optimal robust control problem could be described as a mini-max problem by using Semi-Markov Decision Process (SMDP) with uncertain parameters. Global optimization method was adopted to derive the optimal robust control policy when states were dependent. Firstly, the worst performance value was obtained under fixed policy by genetic algorithm. Secondly, according to the obtained worst performance value, the optimal robust control policy was achieved with simulated annealing algorithm. The simulation results show that there is little difference between optimal performance cost of the system whose service rate is fixed as the mean of interval and optimal robust performance cost of the CSPS system with uncertain service rate. Moreover, the difference is getting smaller when the uncertain interval narrows and it means that the global optimization algorithm works effectively.