Optimization of PID Parameters of Hydraulic System of Elevating Wheelchair Based on AMESim Hui Cao a*, Hui Guo b

Transcription

1 Available online at Procedia Engineering 15 (2011) Advanced in Control Engineering and Information Science Optimization of PID Parameters of Hydraulic System of Elevating Wheelchair Based on AMESim Hui Cao a*, Hui Guo b a School of Mechanical Engineering, Shenyang University of Technology, Shenyang , China b School of Mechanical Engineering, Shenyang University of Technology, Shenyang , China Abstract Elevating wheelchair use hydraulic lifting system with PID control to drive seat rise and fall. In order to ensure the hydraulic lift system of wheelchair runs fast and smooth, PID Parameters of Hydraulic System of elevating wheelchair was optimized with AMESim and NLPQL algorithm. The global optimal solution was obtained effectively Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011] Open access under CC BY-NC-ND license. Keywords: AMESim; PID; NLPQL algorithm; Optimization 1. Preface AMESim offers a complete platform of systems engineering design, users are able to establish the complex multi-discipline domain system's model in a platform, and on this basis simulation calculation and in-depth analysis are carried. For a hydraulic system, regardless of the designer or the user hopes that it is most superior and pursues the best stable state and the dynamic property. In order to ensure the hydraulic lift system of wheelchair runs fast and smooth, PID Parameters of Hydraulic system of elevating wheelchair was optimized with AMESim and NLPQL algorithm. 2. System composition In order to facilitate the demands of different height of wheelchair users as well as in the course of using needs, seat is designed to be lifting hydraulic system structure. The diagram shown in Figure 1. Simulation schematic diagram of hydraulic lifting system of wheelchair as shown in Figure 2. The system consisted of hydraulic cylinders, displacement sensors, servo valve, PID controller and other components. * Corresponding author: address: jonywxl@163.com Published by Elsevier Ltd. doi: /j.proeng Open access under CC BY-NC-ND license.

2 Hui Cao and Hui Guo / Procedia Engineering 15 (2011) Four-way slide valve as a switching Amplifier element converted and enlarged input displacement signals into a hydraulic signal output to hydraulic cylinder, hydraulic cylinder as implementation component drive the load moves. Meanwhile, the output signal of cylinder feedback to valve body by displacement sensor. The slide-valve controls its widths through the PID controller, thus control hydraulic cylinder piston rod movement. In this case inputting a step signal to observe the step response of system after PID control [1]. Fig.1. Diagram of the elevating wheelchair Fig.2. AMESim simulation schematic diagram of hydraulic lifting system of wheelchair 3. Setting system parameters Three position four-way servo-valve flow of the circuits current is 1L/min,the pressure drop is 0.1MPa,rated current is 40mA,natural frequency is 80 Hz,damping ratio is 0.8.PID controler,k p =25,k i =0.03,k d =0.25.Setting the simulation time is 10s,the sampling period is 0.1s,in the run mode simulation results obtained is shown in Fig 3,4. Fig 3, 4 shows that the stable system has no overshoot but the longer rising time. The rising time reflects the rapidity of the system, therefore three parameters of PID controller was optimized. Searching in the global scope, optimal solutions that meet the system stability, rapid, accurate were found. First determine the range of parameters, the range of the final parameters decided by batch simulation were k P (0 ~300), k i (0~1), k d (0~10).

3 3712 Hui Cao and Hui Guo / Procedia Engineering 15 (2011) Fig.3. System speed curve Fig.4. System displacement curve Fig.5. Running process of DOE experiment

4 Hui Cao and Hui Guo / Procedia Engineering 15 (2011) Optimization design 4.1. Do the export setup Inputs: k p,k i,k d. Outputs: Piston displacement (dis), Piston speed (v). Compound Outputs: Piston maximum speed: globmax (v), Constraints and control conditions: Maintaining stability in the hydraulic cylinder in 2~10s: globmax (abs (restrict (dis, 2, 10) -0.2)) Design of Experiments Use the AMESim design exploration module. The first step toward define DOE consists in analyzing parameters and drawing relationships between input and response by experiments. With this technique, if there are N controls each with a high and low value, every combination of parameters is run. This gives N 2 runs. Here N=3 giving eight runs. As shown in Fig Run pid_doe and display the effect table The tables of Fig 6 show linear regression coefficients. The positive value indicates that the piston maximum speed increases as PID increases whereas the negative value indicates the piston maximum speed reduces as PID increases [2]. Fig.6. Effect table 4.4. Optimization The optimization design was carried on using the NLPQL algorithm. Inputs: k p,k i,k d. Outputs: Piston displacement (dis), Piston speed (v). Constraints and control conditions: globmax(abs (restrict (dis, 2, 10) -0.2)) Upper bound 0. As shown in Fig 7, optimized PID parameters: k p =0.69,k i =0.99,k d =0.

5 3714 Hui Cao and Hui Guo / Procedia Engineering 15 (2011) Fig.7. Optimization results 5. Conclusion Optimization design of using AMESim is a fast, easy, and effective ways. Using optimization results make further Simulation to achieve combination of simulation and optimization. Acknowledgements Many thanks to my colleagues: Xue yan Sun, Professor, for reading my essays and offering valuable advice. Thanks must go to my colleagues: He ying Wang, who subjected my text to rigorous scrutiny and much improved its quality. References [1] Junjun Zang, Lingling Jiang. Optimal Design of Hydraulic Position Servo-system Based on AMESim and Genetic Algrhythm. Machine Tool and Hydraulic,2008, p [2] Yongling Fu, Xiaoye Qi. AMESim System Modeling and Simulation,Bei Jing:Bei Jing University of Aeronautics Press,2005. Appendix A. Basic circuit of hydraulic A.1. Flow control circuit A.2. Pressure control circuit Appendix B. Getting started with AMESim design exploration features B.1. Design of experiments B.2. Optimization