In this paper, a dynamic model of an industrial rotary dryer was formulated, and the model of the system was linearized using the Jacobian method. Adaptive particle swarm and gray wolf optimization-based tuning of parameters of fractional order proportional, integral, and derivative (FOPID) and conventional Ziegler-Nichols proportional, integral, and derivative (ZN-PID) was assessed with simulation for a solid moisture control rotary dryer system. The main feature of fractional order PID is that it may have a greater degree of freedom compared to conventional PID. Here, particle swarm and gray wolf optimization algorithms will be used for tuning the parameters of the FOPID controller against the kinds of disturbances that exist in this plant. The performance of the controller is compared to that of typical PID and gray wolf optimizer (GWO) tuning of fractional order PID controllers (FOPID). The performance of the developed controller is evaluated by assessing various time domain metrics. Using the application of the PSO-FOPID control, a satisfactory result was obtained with an integral time square error (ITSE) of 0.0032 compared to 0.0039 and 0.0366 in the cases of GWO-FOPID and ZN-FOPID, returning the expected and desired output moisture. In order to determine the robustness of the proposed control system, random linear density of solids and drying air, inlet temperature of solids, inlet moisture of solids, and linear velocity of solids are subjected to the controller. Therefore, from the simulation result, the performance of the PSO-FOPID controller will show good time domain specifications, such as an overshoot of 16.14%, a rise time of 0.1378 s and a settling time of 5.39 s.