A scheduling method based on fuzzy feedback priority and variable sampling period for a networked control system with resource constraints is proposed in this paper. Firstly, each control loop weight is adjusted dynamically according to a control loop data transmission error through a quadratic square root mapping function. A different weight is given for each loop. A fuzzy feedback priority scheduling strategy is designed combined with dynamic weight, system output and system output error rate. The priority of each control loop is adjusted dynamically. Then, considering the current network status, the new network utilization is predicted through proportional control. A least-squares support vector machine (LSSVM) algorithm is used for controlled loop packet transmission time prediction. A variable sampling period for each control loop is determined by using a controlled loop dynamic weight, network utilization and data transmission time. Finally, a fuzzy feedback priority scheduler and variable sampling period scheduler are combined. The merits of the two schedulers are utilized to achieve the optimization goal. A simulation experiment is carried out using the True Time toolbox. Simulation results show that the scheduling method can make the network utilization rate converge to the desired value under resource constraints, improve the output response performance of the control loop, reduce the integral absolute error value of the control loop and decrease the data transmission time of the control loop. The networked control system performance is improved and the scheduling method of this paper is effective.