The PAM-actuated manipulator is a widely used type of robotic arm in industrial automation. However, its performance can be limited by non-linear dynamics and uncertainties in the system. To overcome these limitations, this paper proposes a synergetic control strategy based on the social spider optimization algorithm. The synergetic control approach allows for the coordination of multiple actuators to achieve a desired trajectory, while the social spider optimization algorithm (SSO) optimizes the control parameters to improve the overall performance.
A computer simulation study was conducted using MATLAB software to compare the performance of optimal Synergetic Algorithm Control Theory (SACT) and optimal Sliding Mode Controller (SMC). Both controllers were applied to a non-linear system with uncertainties. The provided simulation results have shown that the SACT controller performs much better than the SMC controller regarding tracking accuracy and uncertainty robustness. The SACT controller exhibited quicker convergence towards the desired trajectory and maintained a lower steady-state error as compared to the SMC controller. Additionally, the SACT controller demonstrated more resilience to variations in parameters and possessed more robust characteristics.