Improved Third Order PID Sliding Mode Controller for Electrohydraulic Actuator Tracking Control

An electrohydraulic actuator (EHA) system is a combination of hydraulic systems and electrical systems which can produce a rapid response, high power-to-weight ratio, and large stiffness. Nevertheless, the EHA system has nonlinear behaviors and modeling uncertainties such as frictions, internal and external leakages, and parametric uncertainties, which lead to significant challenges in controller design for trajectory tracking. Therefore, this paper presents the design of an intelligent adaptive sliding mode proportional integral and derivative (SMCPID) controller, which is the main contribution toward the development of effective control on a third-order model of a double-acting EHA system for trajectory tracking, which significantly reduces chattering under noise disturbance. The sliding mode controller (SMC) is created by utilizing the exponential rule and the Lyapunov theorem to ensure closed-loop stability. The chattering in the SMC controller has been significantly decreased by substituting the modified sigmoid function for the signum function. Particle swarm optimization (PSO) was used to lower the total of absolute errors to adjust the controller. In order to demonstrate the efficacy of the SMCPID controller, the results for trajectory tracking and noise disturbance rejection were compared to those obtained using the proportional integral and derivative (PID), the proportional and derivative (PD), and the sliding mode proportional and derivative (SMCPD) controllers, respectively. In conclusion, the results of the extensive research given have indicated that the SMCPID controller outperforms the PD, PID, and SMCPD controllers in terms of overall performance.

Third-order robust fuzzy sliding mode tracking control of a double-acting electrohydraulic actuator

In the industrial sector, an electrohydraulic actuator (EHA) system is a common technology. This system is often used in applications that demand high force, such as the steel, automotive, and aerospace industries. Furthermore, since most mechanical actuators' performance changes with time, it is considerably more difficult to assure its robustness over time. Therefore, this paper proposed a robust fuzzy sliding mode proportional derivative (FSMCPD) controller. The sliding mode controller (SMC) is accomplished by utilizing the exponential law and the Lyapunov theorem to ensure closed loop stability. By replacing the fuzzy logic control (FLC) function over the signum function, the chattering in the SMC controller has been considerably reduced. By using the sum of absolute errors as the objective function, particle swarm optimization (PSO) was used to optimize the controller parameter gain. The experiment results for trajectory tracking and the robustness test were compared with the sliding mode proportional derivative (SMCPD) controller to demonstrate the performance of the FSMCPD controller. According to the findings of the thorough study, the FSMCPD controller outperforms the SMCPD controller in terms of mean square error (MSE) and robustness index (RI)