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This paper presents an enhanced internal model control (EIMC) scheme for a time-delayed second order unstable process, which is subjected to exogenous disturbance and model variations. Even though the conventional internal model control (IMC) can provide an asymptotic tracking response with desired stability margins, the major limitation of conventional IMC is that it cannot be applied for an unstable system because a small exogenous disturbance can trigger the control signal to grow unbounded. Hence, modifying the conventional IMC structure to guarantee the internal stability, we present an EIMC scheme which can offer better trade-off between setpoint tracking and disturbance rejection characteristics. To improve the load disturbance rejection characteristics and attenuate the effect of sensor noise, we solve the selection of controller gains as an H∞ optimization problem. One of the key aspects of the EIMC scheme is that the robustness of the closed loop system can be tuned via a single tuning parameter. The performance of the EIMC scheme is experimentally assessed on a magnetic levitation plant for reference tracking application. Experimental results substantiate that the EIMC scheme can effectively counteract the inherent time delay in the model and offer precise tracking, even in the presence of exogenous disturbance. Moreover, by comparing the trajectory tracking performance of EIMC with that of the proportional integral velocity (PIV) controller through cumulative power spectral density (CPSD) of the tracking error, we show that the EIMC can offer better low frequency servo response with minimal vibrations.
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Rocznik
Tom
Strony
293–--306
Opis fizyczny
Bibliogr. 15 poz., rys., tab., wz.
Twórcy
autor
- VIT University, Vellore, India-632102
autor
- Eindhoven University of Technology, Eindhoven 5600 MB, The Netherlands
autor
- VIT University, Vellore, India-632102
autor
- VIT University, Vellore, India-632102
autor
- VIT University, Vellore, India-632102
Bibliografia
- [1] Yadav A.K., Gaur P., Intelligent modified internal model control for speed control of nonlinear uncertain heavy duty vehicles, ISA Transactions, vol. 56, pp. 288–298 (2015).
- [2] Zhu H.A, Hong G.S., Teo C.L., Poo A.N., Internal model control with enhanced robustness, International Journal of Systems Science, vol. 26, no. 2, pp. 277–293 (1995).
- [3] Jin Q.B., Liu Q., Analytical IMC-PID design in terms of performance/robustness trade-off for integrating processes: From 2-Dof to 1-Dof, Journal of Process Control, vol. 24, no. 3, pp. 22–32 (2014).
- [4] Wang Q., Lu C., PanW., IMC PID controller tuning for stable and unstable processes with time delay, Chemical Engineering Research and Design, vol. 105, pp. 120–129 (2016).
- [5] Qiu Z., Santillo M., Jankovic M., Sun J., Composite Adaptive Internal Model Control and Its Application to Boost Pressure Control of a Turbocharged Gasoline Engine, IEEE Transactions on Control Systems Technology, vol. 23, no. 6, pp. 2306–2315 (2015).
- [6] Li D., Zeng F., Jin Q., Pan L., Applications of an IMC based PID Controller tuning strategy in atmospheric and vacuum distillation units, Nonlinear Analysis: Real World Applications, vol. 10, pp. 2729–2739 (2009).
- [7] Rivals I., Personnaz L., Nonlinear Internal Model Control Using Neural Networks: Application to Processes with Delay and Design Issues, IEEE Transactions on Neural Networks, vol. 11, no. 1, pp. 80–90 (2000).
- [8] Rupp D., Guzzella L., Adaptive internal model control with application to fueling control, Control Engineering Practice, vol. 18, no. 8, pp. 873–881 (2010).
- [9] Clergeta C.H., Grimaldia J.P., Chebre M., Petit N., An example of robust internal model control under variable and uncertain delay, Journal of Process Control, vol. 60, pp. 4–23 (2017).
- [10] Bouzid Y., Siguerdidjane H., Bestaoui H., Nonlinear internal model control applied to VTOL multirotors UAV, Mechatronics, vol. 47, pp. 49–66 (2017).
- [11] Morari M., Zarifiriou E., Robust process control, Prentice hall, New Jersey (1989).
- [12] TanW., Marquez H.J., Chen T., IMC design for unstable processes with time delays, Journal of Process Control, vol. 13, no. 3, pp. 203–213 (2003).
- [13] Elumalai V.K., Jerome J., Algebraic Riccati equation based Q and R matrices selection algorithm for optimal LQR applied to tracking control of 3rd order magnetic levitation system, Archives of Electrical Engineering, vol. 65, no. 1, pp. 151–168 (2016).
- [14] Butler H., Position control in lithographic equipment: an enabler for current-day chip manufacturing, IEEE Transactions on Control Systems, vol. 31, no. 5, pp. 28–47 (2011).
- [15] Elumalai V.K., Jerome J., LQR based Optimal Tuning of PID Controller for Trajectory Tracking of Magnetic Levitation System, Procedia Engineering, vol. 64, pp. 654–664, 2013.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
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Bibliografia
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