Recent advances in multi-axis control systems highly rely on new control algorithms and system architectures. The system-on-chip technology is able to realize the novel multi-axis control systems efficiently. But the system-on-chip design and implementation are still challenging and time-consuming for most control system practitioners. This article presents a system-on-chip-based solution for multi-axis control systems. With the high-level synthesis technology, the proposed system can be used as a rapid prototyping for multi-axis control or a test platform for modern control algorithms. A study case of the proposed solution is given to prove its feasibility. The advantage of this implementation is efficient system integration with rich functionality due to the high flexibility of system-on-chip. In order to verify the proposed solution of using system-on-chip to implement modern control algorithms, a mixed H2/H∞ state-feedback robust controller via linear matrix inequalities is designed for multi-axis synchronization. Experimental results are shown to prove the efficiency of the proposed system-on-chip-based solution.
MonmassonEIdkhajineLCirsteaMN. FPGAs in industrial control applications. IEEE T Ind Inform2011; 7(2): 224–243.
2.
FongKILinCPHuangJS. Linear matrix inequality stability conditions from a parameter-dependent Lyapunov functional for linear systems with a time-varying delay. Proc IMechE, Part I: J Systems and Control Engineering2010; 224(6): 701–712.
3.
LuYSLeeYC. Generalized Clegg integrator for integral feedback control systems. Proc IMechE, Part I: J Systems and Control Engineering2013; 227(6): 556–560.
4.
MekidS. Spatial thermal mapping using thermal infrared camera and wireless sensors for error compensation via open architecture controllers. Proc IMechE, Part I: J Systems and Control Engineering2010; 224(7): 789–798.
5.
ChangYHLinWHLeeJH. Fuzzy-scheduling control of a linear permanent magnet synchronous motor with payload variations. Proc IMechE, Part I: J Systems and Control Engineering2008; 222(6): 465–479.
6.
LuYS. Integral variable-structure control with variable-structure sliding dynamics for antireset windup. Proc IMechE, Part I: J Systems and Control Engineering2008; 222(3): 209–216.
7.
Jaen-CuellarAYDe Santiago-PerezJJRomero-TroncosoRJ. A hardware–software system for coordinated multi-axis control based on a non uniform rational B-splines interpolator applied to industrial computer numerically controlled machines. Proc IMechE, Part I: J Systems and Control Engineering2012; 226(6): 831–840.
MonmassonEIdkhajineLNaouarMW. FPGA-based controllers. IEEE Ind Electron Mag2011; 5(1): 14–26.
11.
MonmassonECirsteaMN. FPGA design methodology for industrial control systems—a review. IEEE T Ind Electron2007; 54(4): 1824–1842.
12.
BahriBIdkhajineLMonmassonE. Hardware/software co-design guidelines for system on chip FPGA-based sensorless AC drive applications. IEEE T Ind Inform2013; 9(4): 2165–2176.
13.
CongJLiuBNeuendorfferS. High-level synthesis for FPGAs: from prototyping to deployment. IEEE T Comput Aid D2011; 30(4): 473–491.
14.
GrantMGaryS. High-level synthesis: past, present, and future. IEEE Des Test Comput2009; 26(4): 18–25.
15.
DenisNOscarLLuisAB. High-level synthesis for accelerating the FPGA implementation of computationally-demanding control algorithms for power converters. IEEE T Ind Inform2013; 9(3): 1371–1379.
16.
LinFJChouPHChenCS. Three-degree-of-freedom dynamic model-based intelligent nonsingular terminal sliding mode control for a gantry position stage. IEEE T Fuzzy Syst2012; 20(5): 971–985.
17.
TeoCSTanKKLimSY. Dynamic modeling and adaptive control of a H-type gantry stage. Mechatronics2007; 17(7): 361–367.
18.
ZhaoDLiCZhuQ. Low-pass-filter-based position synchronization sliding mode control for multiple robotic manipulator systems. Proc IMechE, Part I: J Systems and Control Engineering2011; 225(8): 1136–1148.
19.
ShaoXSunD. Development of a new robot controller architecture with FPGA-based IC design for improved high-speed performance. IEEE T Ind Inform2007; 3(4): 312–321.
20.
ElBeheiryEM. Contouring error control of machine tool drives with backlash compensation. Proc IMechE, Part I: J Systems and Control Engineering2006; 220(5): 395–410.
21.
SunDTongMC. A synchronization approach for the minimization of contouring errors of CNC machine tools. IEEE T Autom Sci Eng2009; 6(4): 720–729.
YehSSHsuPL. Analysis and design of the integrated controller for precise motion systems. IEEE T Contr Syst T1999; 7(6): 706–717.
24.
MoorePRChenCM. Fuzzy logic coupling and synchronised control of multiple independent servo-drives. Control Eng Pract1995; 3(12): 1697–1708.
25.
SunD. Position synchronization of multiple motion axes with adaptive coupling control. Automatica2003; 39(6): 997–1005.
26.
AzimiVNekouiMAFakharianA. Robust multi-objective H2/H∞ tracking control based on the Takagi-Sugeno fuzzy model for a class of nonlinear uncertain drive systems. Proc IMechE, Part I: J Systems and Control Engineering2012; 226(8): 1107–1118.
27.
YangCDSunYP. Mixed H2/H∞ cruise controller design for high speed train. Int J Control2001; 74(9): 905–920.
28.
BahriIIdkhajineLGahinet MonmassonE. Optimal hardware/software partitioning of a system on chip FPGA-based sensorless AC drive current controller. Math Comput Simulat2013; 90: 145–161.
29.
YouSSChaiYH. Multi-objective control synthesis: an application to 4WS passenger vehicles. Mechatronics1999; 9(4): 363–390.
30.
YangCDSunYP. Mixed H2/H∞ state-feedback design for microsatellite attitude control. Control Eng Pract2002; 10(9): 951–970.
31.
GahinetPNemirovskiiALaubAJ. The LMI control toolbox. In: Proceedings of the 33rd IEEE conference on decision and control, Lake Buena Vista, FL, 14–16 December 1994, pp.2038–2041. New York: IEEE.
32.
ChilaliMGahinetP. H∞ design with pole placement constraints: an LMI approach. IEEE T Autom Contr1996; 41(3): 358–367.
ChoiJWLeeSC. Antiwindup strategy for PI-type speed controller. IEEE T Ind Electron2009; 56(6): 2039–2046.
35.
SencerBMoriTShamotoE. Design and application of a sliding mode controller for accurate motion synchronization of dual servo systems. Control Eng Pract2013; 21(11): 1519–1530.
