Abstract-The purpose of this paper is to review the literature on modeling and previous control strategies of the hydraulic actuator system proposed by most of the researchers around the world.Before comes to the main discussion, some background information related to hydraulic actuator will be presented. This review includes a short summary and conclusion for hydraulic actuator system. The repercussion of this review is for future inventions of a better and robust hydraulic actuator system.

<p>This paper presents the design of the modified sliding mode controller (MSMC) for the purpose of tracking the nonlinear system with mismatched disturbance. Provided that the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA), and particle swarm optimization (PSO) techniques are used to optimize these parameters in order to achieve a predefined system’s performance. In respect of system’s performance, it is evaluated based on the tracking error present between reference inputs transferred to the system and the system output. This is followed by verification of the efficiency of the designed controller in simulation environment under various values, with and without the inclusion of external disturbance. It can be seen from the simulation results that the MSMC with PSO exhibits a better performance in comparison to the performance of the similar controller with GSA in terms of output response and tracking error.</p>

Electro-Hydraulic Actuator (EHA) system is a third order non-linear system which is highly suffer from system uncertainties such as Coulomb friction, viscous friction and pump leakage coefficient which makes this system more complicated for the designing of the controller. The Proportional-Integral-Derivative (PID) controller has proposed in this paper to control EHA system and main problem in its application is to tune the parameter to its optimum value. Two different methods are used to tune the PID controller which are trial and error and Ziegler-Nichols method. MATLAB Simulink is used to simulate the system. In order to determine the performance of EHA system for the position tracking. 3 different of external disturbance such as 0N, 5000N and 10000N has been injected into the system. Simulation results show that the Ziegler-Nichols fine tuning method provides the better tracking performance when compared to the trial and error method for every specific disturbance setting. The Ziegler Nichols method provides better disturbance rejection as the performances indexes such as percentage overshoot, settling time and steady state error are not affected by the varying of disturbance.

The Electro-hydraulic actuator (EHA) systems known to be extremely nonlinear due to its dynamic characteristics and these existing nonlinearities and uncertainties yield to the constraint in the control of EHA system, which influences the position tracking accuracy and affect the occurrences of leakage and friction in the system. The purpose of this work is to develop the mathematical model for the industrial electrohydraulic actuator, then to design a controller by proportional-integral-derivative (PID) and optimize the parameters using Particle Swarm Optimization-Gravitational Search Algorithm (PSOGSA). A few controllers such as conventional PID (CPID) and model reference adaptive control (MRAC) designed for comparison. The performance of PID, PID-PSOGSA and modern controller MRAC will be compared in order to determine the most efficient controller. Despite all controllers are capable to provide good performance, PID-PSOGSA control methods generate good response compared to PID and MRAC in term of positioning.

Electro-hydraulic actuator (EHA) system inherently suffers from uncertainties, nonlinearities and time- varying in its model parameters which cause the modeling and controller designs are more complicated. Proportional Integral Derivative (PID) control scheme has been proposed and the main problem with its application is to tune the parameters to its optimum values. This study will look into an optimization of PID parameters using particle swarm optimization (PSO). Simulation study has been done in Matlab and Simulink.