An electromagnetic linear actuator (EMLA) has a promising application in direct motion control. However, ELMA will inevitably inherit uncertainties in the face of load changes, system parameter perturbation, and inherent system nonlinearities, all of which constitute disturbances adversely affecting the precision and adaptability of the control system. A model-free adaptive control (MFAC) strategy based on full form dynamic linearization (FFDL) was proposed to reduce the sensitivity of the control system to the disturbances. An adaptive control of direct drive servo valve was achieved based on the online interaction of characteristic parameters and control algorithms. The feasibility and precision of the proposed algorithm were verified through simulation and experimental results. The results show that the proposed algorithm could achieve adaptive adjustment of the servo valve response at different openings of 0-3 mm without changing control parameters, with the response time controlled within 10ms and steady state error less than 0.04mm. Furthermore, the proposed algorithm had better robustness and capacity of resisting disturbance.

For the direct drive electro-hydraulic servo system is difficult to build an accurate model, the modeling method based on the Simscape under Matlab/Simulink multi domain integrated modeling was proposed, studied application of electromagnetic linear actuator (ELA) direct drive electro-hydraulic servo system, the mathematical model and simulation analyze and the physical model are built up under Simscape, The results show that the physical modeling in use of multi field is closer to real system, verify the feasibility of the electromagnetic linear actuator used in direct drive electro-hydraulic servo valve at the same time.The system is stable and reliable, has good dynamic response and the displacement signal tracking ability.

Against EMLA (Electromagnetic Linear Actuator) in the long-running, the changed parameters of actuator coil resistance and inductance caused by temperature rise resulted in degradation of control performance, and parameters recondition in the inverse system control program. By using parameter identification method based on recursive least squares method (RLSM), the adaptive inverse system control is implemented in electromagnetic linear actuator. Under Matlab/Simulink it establishes the simulation model to simulate online identification process and the adaptive inverse control system strategy which achieve the control effect when the parameters change, and the test data are identified off-line verification. The results show that it is able to accurately identify the actuator coil resistance and inductance parameters, and at the same time, it can identify system's dynamic mass, viscous friction coefficient and disturbance force of load. Finally, the test platform was built to verify, the identification results was used to control parameters online real-time. And the parameters identification was used in the practical application of inverse system control, implemented system's adaptive control, improved system's robustness in long run.

The iron loss of inner yoke accounts for the majority of iron loss of an electromagnetic linear actuator (ELA). Therefore, the reduction of iron loss of inner yoke is of great importance to the reduction of iron loss of the whole ELA. This study investigates the formation mechanism and distribution law of ELA iron loss and proposes a reduction scheme by arranging groove structures in the inner yoke. The direction of groove arranged in inner yoke was determined based on the formation mechanism of inner yoke iron loss. Through simulation and calculation based on finite-element model of electromagnetic field, the authors investigated the effects of the number of grooves as well as groove width on the iron loss and performance of ELA. The optimal grooving scheme of ELA was determined by comprehensive analysis and analytic hierarchy process. Finally, block and static force tests were carried out based on ELA prototype. It was found that the simulation results were consistent with test results, indicating the accuracy of the simulation model.

Due to the motion control system of electromagnetic linear actuator (EMLA) is a nonlinear system with poor controllability; single control strategy has been difficult to meet the requirements of its control. A compound control strategy based on inverse system control (ISC) and proportional-integral (PI) is Keywords: electromagnetic linear actuator, fuzzy switching, inverse system, PICopyright © 2017 Universitas Ahmad Dahlan. All rights reserved. IntroductionWith linear position servo's characteristics of high performance, high response and high precision, EMLA has been widely used in many fields, such as direct drive type servo valve [1], electromagnetic gas distribution mechanism [2], and automatic transmission (AMT) etc. While get applied at the same time, it has also put forward higher requirement to its control strategy. On the one hand, it can meet the performance index of control accuracy as far as possible in the steady state response; On the other hand, response should be fast enough to shorten the adjust time of reaching the target position as far as possible in the transient response.Regarding motion control requirement of high performance, In literature [3], Liu and Chang uses inverse system control algorithm, and also applies to electromagnetic valve actuator. It obtains a high response but also has a good seating control at the same time. In order to improve its anti-interference ability and system robustness, An auto disturbance rejection control algorithm is used which based on extended state observer in [4]. In addition, the fuzzy control of direct torque control of induction motor studied in depth [5]. It has outstanding contribution to the improvement and progress of system performance. Using a single control strategy has a good control performance on the one hand, but there is still room for improvement in adaptability [6]. But the compound control strategy is adopted, when switching the algorithm, due to the selection of switching position, it will cause system jitter, also easily causes instability. But if using fuzzy rule to switch of compound algorithm, it can achieve a smooth transition between different algorithms. So multi model control has attracted much attention. Issam Salhi [7] and M.Kalyan Chakravarthi [8] etc. conduct deep research on multi model PI controller. Baozhu Jia has come up with a fuzzy switched PID (FS-PID), which combines the advantages of fuzzy control and PID control [9]. Fuzzy PID is used to increase the transient response speed, while traditional PID to improve the tracking error of steady state. Ahmed Rubaai applies the fuzzy switch position controller to the traditional bang-bang control [10] which improves the control precision of system, especially in the case of interference, which can still be able to ensure superior control performance.In this paper, the advantages of two control strategies are combined, and a compound control strategy based on inverse system control and PI control is proposed. Based on the fuzzy switching rules, it achieves the smo...