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Journal articles on the topic 'Robust passivity'

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Author: Grafiati

Published: 14 March 2023

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1

Lin, Zhongwei, Jizhen Liu, and Yuguang Niu. "Robust Passivity and Feedback Design for Nonlinear Stochastic Systems with Structural Uncertainty." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/460348.

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This paper discusses the robust passivity and global stabilization problems for a class of uncertain nonlinear stochastic systems with structural uncertainties. A robust version of stochastic Kalman-Yakubovitch-Popov (KYP) lemma is established, which sustains the robust passivity of the system. Moreover, a robust strongly minimum phase system is defined, based on which the uncertain nonlinear stochastic system can be feedback equivalent to a robust passive system. Following with the robust passivity theory, a global stabilizing control is designed, which guarantees that the closed-loop system is globally asymptotically stable in probability (GASP). A numerical example is presented to illustrate the effectiveness of our results.

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2

Bu, Ni, and Mingcong Deng. "Passivity-Based Tracking Control for Uncertain Nonlinear Feedback Systems." Journal of Robotics and Mechatronics 28, no. 6 (December 20, 2016): 837–41. http://dx.doi.org/10.20965/jrm.2016.p0837.

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[abstFig src='/00280006/07.jpg' width='300' text='The asymptotic tracking performance and the passivity property' ] The tracking control problem for the uncertain nonlinear feedback systems is considered in this paper by using passivity-based robust right coprime factorization method. Concerned with the passivity for the nonlinear feedback system, two stable controllers are designed such that the nonlinear feedback system is robust stable and the plant output asymptotically tracks to the reference output. A numerical example is given to show the validity of the control scheme as well as the tracking performance.

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3

Lin, Shanrong, Yanli Huang, and Erfu Yang. "Passivity and Synchronization of Coupled Different Dimensional Delayed Reaction-Diffusion Neural Networks with Dirichlet Boundary Conditions." Complexity 2020 (January 8, 2020): 1–21. http://dx.doi.org/10.1155/2020/4987962.

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Two types of coupled different dimensional delayed reaction-diffusion neural network (CDDDRDNN) models without and with parametric uncertainties are analyzed in this paper. On the one hand, passivity and synchronization of the raised network model with certain parameters are studied through exploiting some inequality techniques and Lyapunov stability theory, and some adequate conditions are established. On the other hand, the problems of robust passivity and robust synchronization of CDDDRDNNs with parameter uncertainties are solved. Finally, two numerical examples are given to testify the effectiveness of the derived passivity and synchronization conditions.

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4

Samorn, Nayika, Narongsak Yotha, Pantiwa Srisilp, and Kanit Mukdasai. "LMI-Based Results on Robust Exponential Passivity of Uncertain Neutral-Type Neural Networks with Mixed Interval Time-Varying Delays via the Reciprocally Convex Combination Technique." Computation 9, no. 6 (June 10, 2021): 70. http://dx.doi.org/10.3390/computation9060070.

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The issue of the robust exponential passivity analysis for uncertain neutral-type neural networks with mixed interval time-varying delays is discussed in this work. For our purpose, the lower bounds of the delays are allowed to be either positive or zero adopting the combination of the model transformation, various inequalities, the reciprocally convex combination, and suitable Lyapunov–Krasovskii functional. A new robust exponential passivity criterion is received and formulated in the form of linear matrix inequalities (LMIs). Moreover, a new exponential passivity criterion is also examined for systems without uncertainty. Four numerical examples indicate our potential results exceed the previous results.

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5

Sheng, Yin, and Zhigang Zeng. "Passivity and robust passivity of stochastic reaction–diffusion neural networks with time-varying delays." Journal of the Franklin Institute 354, no. 10 (July 2017): 3995–4012. http://dx.doi.org/10.1016/j.jfranklin.2017.03.014.

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6

Li, Gui Fang, Yong Cheng Sun, and Sheng Guo Huang. "Robust Passivity Control for Uncertain Time-Delayed Systems." Applied Mechanics and Materials 29-32 (August 2010): 2025–30. http://dx.doi.org/10.4028/www.scientific.net/amm.29-32.2025.

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This paper focuses on the robust passivity synthesis problem for a class of linear time-delayed systems subject to parameter uncertainties. The time delay is assumed to be unknown, and the parameter uncertainties are allowed to appear in all matrices of the model. The aim lies in designing observer-based dynamic controller that render the closed-loop system be strongly robustly stable and strict passive for all admissible uncertainties, independently of time delay. Using a scaling parameterization approach, the problem being considered is transformed into a class of strongly stable and strictly passive control problem for a parameterized system without uncertainties. And then, the controller gain and the observer gain are obtained in terms of a linear matrix inequality. Finally, a numerical example is provided to demonstrate the validity of the proposed approach.

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7

Gallegos, Javier A., Norelys Aguila‐Camacho, and Manuel A. Duarte‐Mermoud. "Robust adaptive passivity‐based PI λ D control." International Journal of Adaptive Control and Signal Processing 34, no. 11 (October 12, 2020): 1572–89. http://dx.doi.org/10.1002/acs.3167.

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8

Loría, Antonio, Gerardo Espinosa-Pérez, and Erik Chumacero. "Robust passivity-based control of switched-reluctance motors." International Journal of Robust and Nonlinear Control 25, no. 17 (November 11, 2014): 3384–403. http://dx.doi.org/10.1002/rnc.3270.

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9

Bao, J., P. L. Lee, F. Wang, and W. Zhou. "Robust Process Control Based on the Passivity Theorem." Developments in Chemical Engineering and Mineral Processing 11, no. 3-4 (May 15, 2008): 287–308. http://dx.doi.org/10.1002/apj.5500110407.

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10

Deng, Mingcong, and Ni Bu. "Robust Control for Nonlinear Systems Using Passivity-Based Robust Right Coprime Factorization." IEEE Transactions on Automatic Control 57, no. 10 (October 2012): 2599–604. http://dx.doi.org/10.1109/tac.2012.2188426.

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11

Du, Haohao, Chenghu Jing, Bingsheng Yan, and Chunbo Liu. "Passivity-based adaptive robust super-twisting nonlinear control for electro-hydraulic system with uncertainties and disturbances." Mechanics 29, no. 1 (February 6, 2023): 51–58. http://dx.doi.org/10.5755/j02.mech.32405.

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In this paper, a passive-based adaptive robust super-twisting nonlinear controller (PBARSNC) is proposed for high accuracy torque tracking control of the novel electro-hydraulic loading system with disturbances and uncertainties. The construction of the stability of this electro-hydraulic control system is given using passivity theory that results in a passivity-based controller (PBC). Considering parameter uncertainties and constant or slowly varying disturbances, adaptive law is adopted in the passivity-based controller. Furthermore, super-twisting second-order sliding mode control is used to reject modeling uncertainties and matched disturbances. Passivity theory, adaptive method and super-twisting algorithm are synthesized via the recursive design method. The proposed passive-based adaptive robust super-twisting nonlinear control can guarantee the torque tracking performance in the presence of various uncertainties, which is very important for high-accuracy tracking control of hydraulic servo systems. Extensive simulations are carried out to verify the high-accuracy tracking performance of the proposed control strategy.

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12

Mehrmann, V., and P. Van Dooren. "Optimal robustness of passive discrete-time systems." IMA Journal of Mathematical Control and Information 37, no. 4 (July 14, 2020): 1248–69. http://dx.doi.org/10.1093/imamci/dnaa013.

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Abstract We study different representations of a given rational transfer function that represents a passive (or positive real) discrete-time system. When the system is subject to perturbations, passivity or stability may be lost. To make the system robust, we use the freedom in the representation to characterize and construct optimally robust representations in the sense that the distance to non-passivity is maximized with respect to an appropriate matrix norm. We link this construction to the solution set of certain linear matrix inequalities defining passivity of the transfer function. We present an algorithm to compute a nearly optimal representation using an eigenvalue optimization technique. We also briefly consider the problem of finding the nearest passive system to a given non-passive one.

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13

Chen, Weizhong, Yanli Huang, and Shunyan Ren. "Passivity and Robust Passivity of Delayed Cohen–Grossberg Neural Networks With and Without Reaction–Diffusion Terms." Circuits, Systems, and Signal Processing 37, no. 7 (October 22, 2017): 2772–804. http://dx.doi.org/10.1007/s00034-017-0693-4.

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14

Ahmadian, M. T., G. Vossoughi, and F. Tajaddodianfar. "Robust stable control of haptic devices based on transparency maximization." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 225, no. 7 (November 2011): 954–67. http://dx.doi.org/10.1243/09596518jsce1015.

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The performance of haptic devices is evaluated based on the concept of transparency, while their stability has prevalently been evaluated based on the passivity criterion. Due to the conservativeness of passivity, it appears as an obstacle to improving transparency. In the present paper, passivity is suggested to be replaced by the complementary stability criterion which accounts for the robust stability of the interaction in the presence of uncertain user hand dynamics. In this respect, an algorithm is proposed which guarantees transparency of the haptic device in a stable manner. Assuming that the dynamics of the device is known, a certain compensatory structure is assigned. This special structure guarantees transparency of the device by compensating for the dynamics of the device and its control loop. The design objective is to obtain a stabilizing controller which achieves robust interaction stability in the presence of parametric uncertainties of user hand dynamics and other sources of uncertainties. An iterative method is implemented, in conjunction with the D-K iteration algorithm, to derive controller dynamics. The algorithm is applied to a series elastic actuator-based haptic device. This results in a widened frequency range of transparent impedance emulation. Simulation results confirm enhanced transparency and robust stability.

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15

Volery, Maxime, Xinxin Guo, and Hervé Lissek. "Robust direct acoustic impedance control using two microphones for mixed feedforward-feedback controller." Acta Acustica 7 (2023): 2. http://dx.doi.org/10.1051/aacus/2022058.

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This paper presents an acoustic impedance control architecture for an electroacoustic absorber combining both feedforward and feedback microphone-based strategies on a current-driven loudspeaker. Feedforward systems enable good performance for direct impedance control. However, inaccuracies in the required actuator model can lead to a loss of passivity, which can cause unstable behaviour. The feedback contribution allows the absorber to better handle model errors and still achieve an accurate impedance, preserving passivity. Numerical and experimental studies were conducted to compare this new architecture against a state-of-the-art feedforward control method.

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16

Jung and Bang. "Posture Stabilization of Wheeled Mobile Robot Based on Passivity-Based Robust Switching Control with Model Uncertainty Compensation." Applied Sciences 9, no. 23 (December 1, 2019): 5233. http://dx.doi.org/10.3390/app9235233.

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Thisstudy presents apassivity-based robust switching control for the posture stabilization of wheeled mobile robots (WMRs) with model uncertainty. Essentially, this proposed strategy is switching between (1) passivity-based robust control to lead the robot to the neighborhood of local minima with a finite time and (2) another robust control to perturb the w-rotational motion of the WMR before the v-kinetic energy of the WMR become meaningless, thereby, eventually converging to the desired posture. Thus, combining two switching control laws ensures the global convergence of (x,y)-navigation of WMRs from any initial position to desired set. Especially, the inter-switching time is intentionallyselected before the WMR completely loses its mobility, which ensures a strict decrease in (x,y)-navigation potential energy and a better global convergence rate. In addition, this control architecture also includes model uncertainty compensation, often neglected in practice, and analytical study of rotational perturbation was also conducted. The Lyapunov technique and energetic passivity wereutilized to derive this control law. Simulation results are presented to illustrate the effectiveness of the proposed technique. It wasfound from the results that the WMR wasquickly converged to the desired posture even under the presence of model uncertainty.

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17

Haninger, Kevin, and Masayoshi Tomizuka. "Robust Passivity and Passivity Relaxation for Impedance Control of Flexible-Joint Robots with Inner-Loop Torque Control." IEEE/ASME Transactions on Mechatronics 23, no. 6 (December 2018): 2671–80. http://dx.doi.org/10.1109/tmech.2018.2870846.

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18

Tagne, Gilles, Reine Talj, and Ali Charara. "Passivity Analysis and Design of a Robust Nested Passivity-Based Controller for Trajectory Tracking of Autonomous Vehicles." IFAC Proceedings Volumes 47, no. 3 (2014): 9840–46. http://dx.doi.org/10.3182/20140824-6-za-1003.01685.

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19

Li, Jiahui, Hongli Dong, Zidong Wang, Nan Hou, and Fuad E. Alsaadi. "On passivity and robust passivity for discrete-time stochastic neural networks with randomly occurring mixed time delays." Neural Computing and Applications 31, no. 1 (May 13, 2017): 65–78. http://dx.doi.org/10.1007/s00521-017-2980-1.

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20

Ayubirad, Mostafa Ali, Simin Amiri Siavoshani, and Mohammad Javad Yazdanpanah. "A robust passivity based control strategy for quasi‐resonant converters." IET Power Electronics 14, no. 7 (May 2021): 1360–70. http://dx.doi.org/10.1049/pel2.12133.

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21

Hao, Sheng, Yuh Yamashita, and Koichi Kobayashi. "Robust passivity‐based control design for active nonlinear suspension system." International Journal of Robust and Nonlinear Control 32, no. 1 (October 9, 2021): 373–92. http://dx.doi.org/10.1002/rnc.5827.

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22

Loukianov, A. G., Hector Huerta, V. A. Utkin, and J. M. Cañedo. "Nonlinear Passivity Robust Decentralized Controller for Large Scale Power System." IFAC Proceedings Volumes 42, no. 4 (2009): 474–79. http://dx.doi.org/10.3182/20090603-3-ru-2001.0559.

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23

Chen, Guoliang, Jian Sun, and Jie Chen. "Passivity-Based Robust Sampled-Data Control for Markovian Jump Systems." IEEE Transactions on Systems, Man, and Cybernetics: Systems 50, no. 7 (July 2020): 2671–84. http://dx.doi.org/10.1109/tsmc.2018.2825474.

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24

Liang, Jinling, Zidong Wang, and Xiaohui Liu. "Robust passivity and passification of stochastic fuzzy time-delay systems." Information Sciences 180, no. 9 (May 2010): 1725–37. http://dx.doi.org/10.1016/j.ins.2010.01.003.

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25

Samuel, Elizabeth Rita, Francesco Ferranti, Luc Knockaert, and Tom Dhaene. "Robust Passivity Preserving Parametric Model Order Reduction using Matrix Interpolation." IFAC Proceedings Volumes 45, no. 13 (2012): 717–22. http://dx.doi.org/10.3182/20120620-3-dk-2025.00119.

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26

Cai, X. S., and Z. Z. Han. "Robust stabilisation and passivity of nonlinear systems with structural uncertainty." IEE Proceedings - Control Theory and Applications 153, no. 6 (November 1, 2006): 641–46. http://dx.doi.org/10.1049/ip-cta:20045225.

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27

Lechevin, N., C. A. Rabbath, and P. Sicard. "A passivity perspective for the synthesis of robust terminal guidance." IEEE Transactions on Control Systems Technology 13, no. 5 (September 2005): 760–65. http://dx.doi.org/10.1109/tcst.2005.847341.

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28

Li, Chensong, and Jun Zhao. "Robust passivity-based H ∞ control for uncertain switched nonlinear systems." International Journal of Robust and Nonlinear Control 26, no. 14 (January 6, 2016): 3186–206. http://dx.doi.org/10.1002/rnc.3499.

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29

Guifang, Li, Li Huiying, and Yang Chengwu. "Delay-dependent robust passivity control for uncertain time-delay systems." Journal of Systems Engineering and Electronics 18, no. 4 (December 2007): 879–84. http://dx.doi.org/10.1016/s1004-4132(08)60035-3.

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30

Gupta, Sandeep. "Robust stability analysis using LMIs: Beyond small gain and passivity." International Journal of Robust and Nonlinear Control 6, no. 9-10 (November 1996): 953–68. http://dx.doi.org/10.1002/(sici)1099-1239(199611)6:9/10<953::aid-rnc261>3.0.co;2-l.

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31

Rahmani, Reza, Saleh Mobayen, Afef Fekih, and Jong-Suk Ro. "Robust Passivity Cascade Technique-Based Control Using RBFN Approximators for the Stabilization of a Cart Inverted Pendulum." Mathematics 9, no. 11 (May 27, 2021): 1229. http://dx.doi.org/10.3390/math9111229.

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This paper proposes a novel passivity cascade technique (PCT)-based control for nonlinear inverted pendulum systems. Its main objective is to stabilize the pendulum’s upward states despite uncertainties and exogenous disturbances. The proposed framework combines the estimation properties of radial basis function neural networks (RBFNs) with the passivity attributes of the cascade control framework. The unknown terms of the nonlinear system are estimated using an RBFN approximator. The performance of the closed-loop system is further enhanced by using the integral of angular position as a virtual state variable. The lumped uncertainties (NN—Neural Network approximation, external disturbances and parametric uncertainty) are compensated for by adding a robustifying adaptive rule-based signal to the PCT-based control. The boundedness of the states is confirmed using the passivity theorem. The performance of the proposed approach was assessed using a nonlinear inverted pendulum system under both nominal and disturbed conditions.

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32

Chang, Jeang-Lin, and Tsui-Chou Wu. "Robust Output Feedback Passivity-Based Variable Structure Controller Design for Nonlinear Systems." Journal of Control Science and Engineering 2019 (May 19, 2019): 1–10. http://dx.doi.org/10.1155/2019/9156261.

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This paper examines the use of an output feedback variable structure controller with a nonlinear sliding surface for a class of SISO nonlinear systems in the presence of matched disturbances. With only the measurable system output, the discontinuous observer reconstructs the system states and ensures that the estimation errors exponentially approach zero. Using the estimation states, the proposed nonlinear sliding surface with variable damping ratio can simultaneously achieve low overshoot and short settling time. Then the passivity-based controller including a discontinuous term can guarantee that the closed-loop system asymptotically converges to the sliding surface. Compared with other sliding mode controllers, the proposed passivity-based control scheme has better transient performance and effectively reduces the control gain. Finally, simulation results demonstrate the validity of the proposed method.

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33

Lu, Chien-Yu, Chin-Wen Liao, and Hsun-Heng Tsai. "Delay-Range-Dependent Global Robust Passivity Analysis of Discrete-Time Uncertain Recurrent Neural Networks with Interval Time-Varying Delay." Discrete Dynamics in Nature and Society 2009 (2009): 1–14. http://dx.doi.org/10.1155/2009/430158.

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This paper examines a passivity analysis for a class of discrete-time recurrent neural networks (DRNNs) with norm-bounded time-varying parameter uncertainties and interval time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. Based on an appropriate type of Lyapunov functional, sufficient passivity conditions for the DRNNs are derived in terms of a family of linear matrix inequalities (LMIs). Two numerical examples are given to illustrate the effectiveness and applicability.

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34

Pang, Hongbo, and Shuo Liu. "Robust Finite Time Passivity and Stabilization of Uncertain Switched Nonlinear System." IEEE Access 9 (2021): 36173–80. http://dx.doi.org/10.1109/access.2021.3062661.

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35

Jothiappan, Palraj, and Mathiyalagan Kalidass. "Robust Passivity Analysis of Stochastic Genetic Regulatory Networks with Levy Noise." International Journal of Control, Automation and Systems 20, no. 10 (September 30, 2022): 3241–51. http://dx.doi.org/10.1007/s12555-021-0552-8.

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36

Liu, Kang-Zhi. "Neo Robust Control Theory–Beyond The Small-Gain and Passivity Paradigms–." IFAC Proceedings Volumes 41, no. 2 (2008): 5962–68. http://dx.doi.org/10.3182/20080706-5-kr-1001.01006.

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37

Peiris, Lokukankanamge Dushyantha Hashan, Andrew R. Plummer, and Jonathan L. Bois. "Normalized passivity control for robust tuning in real‐time hybrid tests." International Journal of Robust and Nonlinear Control 32, no. 7 (January 27, 2022): 4355–75. http://dx.doi.org/10.1002/rnc.6029.

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38

Joshi, S. M., and A. G. Kelkar. "Passivity-based robust control of systems with redundant sensors and actuators." International Journal of Control 74, no. 5 (January 2001): 474–81. http://dx.doi.org/10.1080/00207170010010588.

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39

Zeng, Hong-Bing, Ju H. Park, and Hao Shen. "Robust passivity analysis of neural networks with discrete and distributed delays." Neurocomputing 149 (February 2015): 1092–97. http://dx.doi.org/10.1016/j.neucom.2014.07.024.

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40

Mocanu, Razvan, and Alexandru Onea. "Robust Control of Permanent Magnet Synchronous Machine Based on Passivity Theory." Asian Journal of Control 20, no. 5 (November 29, 2017): 2034–41. http://dx.doi.org/10.1002/asjc.1699.

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41

Pang, Hongbo, and Jun Zhao. "Robust passivity, feedback passification and global robust stabilisation for switched non-linear systems with structural uncertainty." IET Control Theory & Applications 9, no. 11 (July 16, 2015): 1723–30. http://dx.doi.org/10.1049/iet-cta.2014.1273.

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42

Wang, Jin-Liang, and Huai-Ning Wu. "Robust stability and robust passivity of parabolic complex networks with parametric uncertainties and time-varying delays." Neurocomputing 87 (June 2012): 26–32. http://dx.doi.org/10.1016/j.neucom.2012.02.004.

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43

Zhu, Huawei, and Xiaorong Hou. "Exponential Feedback Passivity of Switched Polynomial Nonlinear Systems." Mathematical Problems in Engineering 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/6283875.

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The exponential feedback passivity problem of switched polynomial nonlinear systems is studied. To obtain this aim, a method of parameterization of controller is presented and parameter solution algorithm is described. Then, the addressed method is utilized to solve the robust stabilization for a class of switched polynomial nonlinear systems with parameter uncertainties and external disturbance. This result extends the previous results on exponential feedback passivity from the case of nonlinear systems to switched nonlinear systems. A numerical example is given to demonstrate the effectiveness of the proposed result.

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44

Anbalagan, Pratap, Raja Ramachandran, Jehad Alzabut, Evren Hincal, and Michal Niezabitowski. "Improved Results on Finite-Time Passivity and Synchronization Problem for Fractional-Order Memristor-Based Competitive Neural Networks: Interval Matrix Approach." Fractal and Fractional 6, no. 1 (January 11, 2022): 36. http://dx.doi.org/10.3390/fractalfract6010036.

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This research paper deals with the passivity and synchronization problem of fractional-order memristor-based competitive neural networks (FOMBCNNs) for the first time. Since the FOMBCNNs’ parameters are state-dependent, FOMBCNNs may exhibit unexpected parameter mismatch when different initial conditions are chosen. Therefore, the conventional robust control scheme cannot guarantee the synchronization of FOMBCNNs. Under the framework of the Filippov solution, the drive and response FOMBCNNs are first transformed into systems with interval parameters. Then, the new sufficient criteria are obtained by linear matrix inequalities (LMIs) to ensure the passivity in finite-time criteria for FOMBCNNs with mismatched switching jumps. Further, a feedback control law is designed to ensure the finite-time synchronization of FOMBCNNs. Finally, three numerical cases are given to illustrate the usefulness of our passivity and synchronization results.

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45

Xu, Ruiping, Zhen Liu, Cunchen Gao, and Huimin Xiao. "Observer-Based Robust Passive Control for a Class of Uncertain Neutral Systems: An Integral Sliding Mode Approach." Journal of Control Science and Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/308681.

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The problem of integral sliding mode control (ISMC) with passivity is investigated for a class of uncertain neutral systems with time-varying delay (NTSTD) and external disturbance. The system states are unavailable. An ISMC strategy is proposed based on the state estimate. By employing a novel sliding functional, a new sufficient criterion of robust asymptotic stability and passivity for both the error system and the sliding mode (SM) dynamic system is derived via linear matrix inequality (LMI) technique. Then, a SM controller is synthesized to guarantee the reachability of the sliding surface predefined in the state estimate space. Finally, a numerical example shows the feasibility and superiority of the obtained result.

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46

Sakthivel, R., M. Sathishkumar, B. Kaviarasan, and S. Marshal Anthoni. "Robust Finite-Time Passivity for Discrete-Time Genetic Regulatory Networks with Markovian Jumping Parameters." Zeitschrift für Naturforschung A 71, no. 4 (April 1, 2016): 289–304. http://dx.doi.org/10.1515/zna-2015-0405.

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AbstractThis article addresses the issue of robust finite-time passivity for a class of uncertain discrete-time genetic regulatory networks (GRNs) with time-varying delays and Markovian jumping parameters. By constructing a proper Lyapunov–Krasovskii functional involving the lower and upper bounds of time delays, a new set of sufficient conditions is obtained in terms of linear matrix inequalities (LMIs), which guarantees the finite-time boundedness and finite-time passivity of the addressed GRNs for all admissible uncertainties and satisfies the given passive performance index. More precisely, the conditions are obtained with respect to the finite-time interval, while the exogenous disturbances are unknown but energy bounded. Furthermore, the Schur complement together with reciprocally convex optimisation approach is used to simplify the derivation in the main results. Finally, three numerical examples are provided to illustrate the validity of the obtained results.

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47

Gosavi, S. V., and A. G. Kelkar. "Modelling, Identification, and Passivity-Based Robust Control of Piezo-actuated Flexible Beam." Journal of Vibration and Acoustics 126, no. 2 (April 1, 2004): 260–71. http://dx.doi.org/10.1115/1.1687392.

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This paper presents modelling, system identification, simulation, and experimental results for passivity-based robust control of piezo-actuated flexible beam. The flexible beam configuration considered is a cantilever aluminum beam with a piezoelectric transducer used as the actuator and tip-accelerometer as the sensor. The actuator and sensor are non-collocated. The Lagrangian formulation is used to obtain mathematical model of the flexible link dynamics with piezo actuator. For control design purposes, a finite dimensional approximate model is derived using assumed modes approach. It is shown that the approximate model compares very well with the experimentally identified model. Since the system is inherently not passive, passification techniques are used to render the system robustly passive which enables the use of passivity-based feedback control design. The controller design is validated both in simulation as well as in experiments. The simulation and experimental results demonstrate the effectiveness of controller in suppressing the tip vibrations of the link. The controller design is shown to be robust to both parametric uncertainties and unmodeled dynamics.

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48

Li, Qiang, Weiqiang Gong, Linzhong Zhang, and Kai Wang. "Robust dissipativity and passivity of stochastic Markovian switching CVNNs with partly unknown transition rates and probabilistic time-varying delay." AIMS Mathematics 7, no. 10 (2022): 19458–80. http://dx.doi.org/10.3934/math.20221068.

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<abstract><p>This article addresses the robust dissipativity and passivity problems for a class of Markovian switching complex-valued neural networks with probabilistic time-varying delay and parameter uncertainties. The main objective of this article is to study the proposed problem from a new perspective, in which the relevant transition rate information is partially unknown and the considered delay is characterized by a series of random variables obeying bernoulli distribution. Moreover, the involved parameter uncertainties are considered to be mode-dependent and norm-bounded. Utilizing the generalized It$ \hat{o} $'s formula under the complex version, the stochastic analysis techniques and the robust analysis approach, the $ (M, N, W) $-dissipativity and passivity are ensured by means of complex matrix inequalities, which are mode-delay-dependent. Finally, two simulation examples are provided to verify the effectiveness of the proposed results.</p></abstract>

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Kelkar, A. G., and S. M. Joshi. "Control of Elastic Systems via Passivity-Based Methods." Journal of Vibration and Control 10, no. 11 (November 2004): 1699–735. http://dx.doi.org/10.1177/1077546304042066.

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In this paper we present a controller synthesis approach for elastic systems based on the mathematical concept of passivity. For nonlinear and linear elastic systems that are inherently passive, robust control laws are presented that guarantee stability. Examples of such systems include flexible structures with col-located and compatible actuators and sensors, and multibody space-based robotic manipulators. For linear elastic systems that are not inherently passive, methods are presented for rendering them passive by compensation. The “passified” systems can then be robustly controlled by a class of passive linear controllers that guarantee stability despite uncertainties and inaccuracies in the mathematical models. The controller synthesis approach is demonstrated by application to five different types of elastic systems.

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Serrano-Delgado, Javier, Santiago Cobreces, Mario Rizo, and Emilio Bueno. "Low-Order Passivity-Based Robust Current Control Design for Grid-Tied VSCs." IEEE Transactions on Power Electronics 36, no. 10 (October 2021): 11886–99. http://dx.doi.org/10.1109/tpel.2021.3068057.

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