Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 5136407, 2 pages
http://dx.doi.org/10.1155/2016/5136407

Editorial

New Developments on Robust Nonlinear Control and Its Applications 2016

Ming-Cong Deng,¹ Hong-Nian Yu,² Shu-Hui Bi,³ and Sheng-Jun Wen⁴

¹Department of Electrical and Electronic Engineering, Tokyo University of Agriculture and Technology, 2-24-16 Nakacho, Koganei, Tokyo 184-8588, Japan
²School of Design, Engineering and Computing, Bournemouth University, Poole House P316, Talbot Campus, Poole BH12 5BB, UK
³Jinan University, Jinan, Shandong, China
⁴Department of Electronic and Information Engineering, Zhongyuan University of Technology, Zhongyuan Road No. 41, Zhengzhou 450007, China

Received 6 November 2016; Accepted 7 November 2016

Copyright © 2016 Ming-Cong Deng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The aim of this special issue is to encourage the development of analysis and design techniques for uncertain or disturbed nonlinear systems. Although the problems of achieving robustness with respect to disturbances and model uncertainties are as old as feedback control itself, effective systematic methods for the robust design of nonlinear systems are still a challenging topic, especially for the potential of robust nonlinear controllers in engineering applications. In the last two decades, many interesting control design techniques including nonlinear control schemes have been proposed, such as feedback linearization control method [1], sliding mode control method [2], adaptive control approach [3], neural network approach [4], and operator based right coprime factorization method [5] (see the references in [5]). Robustness of nonlinear systems can be guaranteed by sliding mode control for parameter uncertainties and internal and external disturbances. Also, neural network is applied to deal with robust nonlinear control by using the ability of its adaptive learning.

Particularly, operator based robust right coprime factorization method has been proved to be a new and effective method to solve the robust control design problem of the nonlinear systems [6–8]. The main focus of the issue is on interdisciplinary theoretical studies, computational algorithm development, and applications of uncertain or disturbed nonlinear systems, but also related areas such as nonlinear modeling, simulation, and estimation are included.

Seven papers on the new developments have been discussed for uncertain or disturbed nonlinear systems in this special issue. Some of the works provide specific solutions for challenging robust nonlinear control problems, and some interdisciplinary theoretical studies of the robust nonlinear control combining with other approaches are shown. Optimal control of holding motion by nonprehensile two-cooperative-arm robot is considered. Multiobjective trajectory optimization for hypersonic glide vehicle is given based on normal boundary intersection method. Denoising and trend terms elimination algorithm of accelerometer signals is included. Adaptive robust backstepping control of permanent magnet synchronous motor chaotic system with fully unknown parameters and external disturbances is discussed. Further, speed control based on ESO is reported for pitching axis of satellite cameras. Robust stability, stabilization, and infinity control of a class of nonlinear discrete time stochastic systems are also studied. Moreover, dynamic output feedback robust MPC with input saturation based on zonotopic set-membership estimation is reported.

However, fault often occurs in modern industrial control systems. In the future special issue, topics will also contain robust nonlinear safety control algorithm developments related to the above fault. Meanwhile, fault-tolerant control is also an interesting topic.

Acknowledgments

Finally, as guest editors of this special issue, we would like to thank all the authors for their contributions. We wish that the readers can benefit from the above seven papers. We would also like to thank the reviewers for their excellent job on evaluating these papers.

Ming-Cong Deng
Hong-Nian Yu
Shu-Hui Bi
Sheng-Jun Wen

References

A. Isidori, Nonlinear Control Systems, Springer, London, UK, 3rd edition, 1995.

V. I. Utkin, “Sliding mode control design principles and applications to electric drives,” IEEE Transactions on Industrial Electronics, vol. 40, no. 1, pp. 23–36, 1993.

H. Yu and S. Lloyd, “Variable structure adaptive control of robot manipulators,” IEE Proceeding-Control Theory and Applications, vol. 144, no. 2, pp. 167–176, 1997.

D. Wang and J. Huang, “Neural network-based adaptive dynamic surface control for a class of uncertain nonlinear systems in strict-feedback form,” IEEE Transactions on Neural Networks, vol. 16, no. 1, pp. 195–202, 2005.

M. Deng, Operator-Based Nonlinear Control Systems Design and Applications, Wiley-IEEE Press, 2014.

S. Wen and M. Deng, “Operator-based robust nonlinear control and fault detection for a Peltier actuated thermal process,” Mathematical and Computer Modelling, vol. 57, no. 1-2, pp. 16–29, 2013.

A. Wang and M. Deng, “Operator-based robust nonlinear tracking control for a human multi-joint arm-like manipulator with unknown time-varying delays,” Applied Mathematics and Information Sciences, vol. 6, no. 3, pp. 459–468, 2012.

S. Bi, M. Deng, and S. Wen, “Operator-based output tracking control for non-linear uncertain systems with unknown time-varying delays,” IET Control Theory and Applications, vol. 5, no. 5, pp. 693–699, 2011.