Dissipative Stabilization of Linear Systems with Time-Varying General Distributed Delays (Complete Version)

New methods are developed for the stabilization of a linear system with general time-varying distributed delays existing at the system's states, inputs and outputs. In contrast to most existing literature where the function of time-varying delay is continuous and bounded, we assume it to be bounded and measurable. Furthermore, the distributed delay kernels can be any square-integrable function over a bounded interval, where the kernels are handled directly by using a decomposition scenario without using approximations. By constructing a Krasovski\u{i} functional via the application of a novel integral inequality, sufficient conditions for the existence of a dissipative state feedback controller are derived in terms of matrix inequalities without utilizing the existing reciprocally convex combination lemmas. The proposed synthesis (stability) conditions, which take dissipativity into account, can be either solved directly by a standard numerical solver of semidefinite programming if they are convex, or reshaped into linear matrix inequalities, or solved via a proposed iterative algorithm. To the best of our knowledge, no existing methods can handle the synthesis problem investigated in this paper. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed methodologies.Comment: Accepted by Automatic

Robust Stability and Design of State Feedback Controller for Straightforward Active Queue Management

The straightforward active queue management ($AQM$), which is based on the prediction of arrival rate is investigated by means of state-space approach. We formulate the feedback control design problem for linearized system of additive increase multiplicative decrease ($AIMD$) dynamic models as state-space model. Then the Lyapunov-Krasovskii method is provided to achieve the robust stability and sufficient stabilization condition and afterwards the term of linear inequality matrix ($LMI$) is used to show the results. We present the simulation results and show the superiority of our proposed method to other control mechanisms

Procedimiento de diseño para minimizar el consumo de potencia y los retrasos en WSAN

ResumenActualmente existe un gran interés por el desarrollo de aplicaciones industriales utilizando redes inalámbricas, principalmente por el aumento de la flexibilidad del sistema y la disminución de los costos de implementación. Sin embargo, los retrasos y el jitter que introduce la red de comunicaciones en las aplicaciones de control, han dado lugar a que en algunos casos no se obtenga una buena correspondencia entre los resultados experimentales y los objetivos de control propuestos, esto como consecuencia del uso de modelos imprecisos para analizar y diseñar estos sistemas, métodos de validación poco elaborados y plataformas que no soportan los modelos empleados. En este trabajo se presenta un procedimiento de diseño que permite encontrar un modo de funcionamiento óptimo del sistema, que garantiza el cumplimiento de los plazos de tiempo de las aplicaciones, y minimiza el consumo de potencia y los retrasos

LQ-optimal Sample-data Control under Stochastic Delays: Gridding Approach for Stabilizability and Detectability

We solve a linear quadratic optimal control problem for sampled-data systems with stochastic delays. The delays are stochastically determined by the last few delays. The proposed optimal controller can be efficiently computed by iteratively solving a Riccati difference equation, provided that a discrete-time Markov jump system equivalent to the sampled-data system is stochastic stabilizable and detectable. Sufficient conditions for these notions are provided in the form of linear matrix inequalities, from which stabilizing controllers and state observers can be constructed.Comment: 28 pages, 3 figure

Networked Control System Design and Parameter Estimation

Networked control systems (NCSs) are a kind of distributed control systems in which the data between control components are exchanged via communication networks. Because of the attractive advantages of NCSs such as reduced system wiring, low weight, and ease of system diagnosis and maintenance, the research on NCSs has received much attention in recent years. The first part (Chapter 2 - Chapter 4) of the thesis is devoted to designing new controllers for NCSs by incorporating the network-induced delays. The thesis also conducts research on filtering of multirate systems and identification of Hammerstein systems in the second part (Chapter 5 - Chapter 6). Network-induced delays exist in both sensor-to-controller (S-C) and controller-to-actuator (C-A) links. A novel two-mode-dependent control scheme is proposed, in which the to-be-designed controller depends on both S-C and C-A delays. The resulting closed-loop system is a special jump linear system. Then, the conditions for stochastic stability are obtained in terms of a set of linear matrix inequalities (LMIs) with nonconvex constraints, which can be efficiently solved by a sequential LMI optimization algorithm. Further, the control synthesis problem for the NCSs is considered. The definitions of H₂ and H∞ norms for the special system are first proposed. Also, the plant uncertainties are considered in the design. Finally, the robust mixed H₂/H∞ control problem is solved under the framework of LMIs. To compensate for both S-C and C-A delays modeled by Markov chains, the generalized predictive control method is modified to choose certain predicted future control signal as the current control effort on the actuator node, whenever the control signal is delayed. Further, stability criteria in terms of LMIs are provided to check the system stability. The proposed method is also tested on an experimental hydraulic position control system. Multirate systems exist in many practical applications where different sampling rates co-exist in the same system. The l₂-l∞ filtering problem for multirate systems is considered in the thesis. By using the lifting technique, the system is first transformed to a linear time-invariant one, and then the filter design is formulated as an optimization problem which can be solved by using LMI techniques. Hammerstein model consists of a static nonlinear block followed in series by a linear dynamic system, which can find many applications in different areas. New switching sequences to handle the two-segment nonlinearities are proposed in this thesis. This leads to less parameters to be estimated and thus reduces the computational cost. Further, a stochastic gradient algorithm based on the idea of replacing the unmeasurable terms with their estimates is developed to identify the Hammerstein model with two-segment nonlinearities. Finally, several open problems are listed as the future research directions

A Novel Predictor Based Framework to Improve Mobility of High Speed Teleoperated Unmanned Ground Vehicles

Teleoperated Unmanned Ground Vehicles (UGVs) have been widely used in applications when driver safety, mission eciency or mission cost is a major concern. One major challenge with teleoperating a UGV is that communication delays can significantly affect the mobility performance of the vehicle and make teleoperated driving tasks very challenging especially at high speeds. In this dissertation, a predictor based framework with predictors in a new form and a blended architecture are developed to compensate effects of delays through signal prediction, thereby improving vehicle mobility performance. The novelty of the framework is that minimal information about the governing equations of the system is required to compensate delays and, thus, the prediction is robust to modeling errors. This dissertation first investigates a model-free solution and develops a predictor that does not require information about the vehicle dynamics or human operators' motion for prediction. Compared to the existing model-free methods, neither assumptions about the particular way the vehicle moves, nor knowledge about the noise characteristics that drive the existing predictive filters are needed. Its stability and performance are studied and a predictor design procedure is presented. Secondly, a blended architecture is developed to blend the outputs of the model-free predictor with those of a steering feedforward loop that relies on minimal information about vehicle lateral response. Better prediction accuracy is observed based on open-loop virtual testing with the blended architecture compared to using either the model-free predictors or the model-based feedforward loop alone. The mobility performance of teleoperated vehicles with delays and the predictor based framework are evaluated in this dissertation with human-in-the-loop experiments using both simulated and physical vehicles in teleoperation mode. Predictor based framework is shown to provide a statistically significant improvement in vehicle mobility and drivability in the experiments performed.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146026/1/zhengys_1.pd

Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts

The climate changes that are visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this book presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications such as hybrid and microgrid power systems based on energy internet, blockchain technology, and smart contracts, we hope that they are of interest to readers working in the related fields mentioned above

Design procedure to minimize power consumption and latency in WSAN

[EN] Currently there is great interest in the development of industrial applications using wireless networks, principally to increase flexibility and reliability of these applications and to reduce the implementation cost. However, in control applications, as a consequence of latency and jitter generated by the network, not always a similarity between experimental results and desired performance can be obtained. This is because imprecise models for analyzing and designing these systems have been used, and to use inadequate validation methods and platforms that do not support the models utilized. This paper presents a design method to get a system optimal configuration in order to fulfill with desired performance in control applications and a significant energy saving.[ES] Actualmente existe un gran interés por el desarrollo de aplicaciones industriales utilizando redes inalámbricas, principalmente por el aumento de la flexibilidad del sistema y la disminución de los costos de implementación. Sin embargo, los retrasos y el jitter que introduce la red de comunicaciones en las aplicaciones de control, han dado lugar a que en algunos casos no se obtenga una buena correspondencia entre los resultados experimentales y los objetivos de control propuestos, esto como consecuencia del uso de modelos imprecisos para analizar y diseñar estos sistemas, métodos de validación poco elaborados y plataformas que no soportan los modelos empleados. En este trabajo se presenta un procedimiento de diseño que permite encontrar un modo de funcionamiento óptimo del sistema, que garantiza el cumplimiento de los plazos de tiempo de las aplicaciones, y minimiza el consumo de potencia y los retrasos.Este trabajo fue financiado parcialmente por el proyecto D2ARS de CYTED, código UNESCO: 120325; 330417; 120314; 120305, y por el proyecto SIDIRELI DPI2008-06737-C02-01/02 financiado por el Ministerio de Ciencia e Innovación español y fondos europeos FEDER.Martínez, D.; Balbastre, P.; Blanes, F.; Simó, J.; Crespo, A. (2010). Procedimiento de Diseño para Minimizar el Consumo de Potencia y los retrasos en WSAN. Revista Iberoamericana de Automática e Informática industrial. 7(3):95-110. https://doi.org/10.1016/S1697-7912(10)70046-7OJS9511073Audsley, N., Burns, A., Richardson, M., Tindell, K., & Wellings, A. J. (1993). Applying new scheduling theory to static priority pre-emptive scheduling. Software Engineering Journal, 8(5), 284. doi:10.1049/sej.1993.0034Balbastre, P., Ripoll, I., & Crespo, A. (2008). Minimum Deadline Calculation for Periodic Real-Time Tasks in Dynamic Priority Systems. IEEE Transactions on Computers, 57(1), 96-109. doi:10.1109/tc.2007.70787Bonivento A., Sangiovanni-Vincentelli A., Graziosi F., Santucci F.: “SERAN: A Semi Random Protocol Solution for Clustered Wireless Sensor Networks”, Proc. of MASS 2005. 2005.Bonivento, A., Carloni, L. P., & Sangiovanni-Vincentelli, A. (2006). Platform based design for wireless sensor networks. Mobile Networks and Applications, 11(4), 469-485. doi:10.1007/s11036-006-7194-1How does control timing affect performance? Analysis and simulation of timing using Jitterbug and TrueTime. (2003). IEEE Control Systems, 23(3), 16-30. doi:10.1109/mcs.2003.1200240Dormido, S., Sánchez, J., & Kofman, E. (2008). Muestreo, Control y Comunicación Basados en Eventos. Revista Iberoamericana de Automática e Informática Industrial RIAI, 5(1), 5-26. doi:10.1016/s1697-7912(08)70120-1Hespanha, J. P., Naghshtabrizi, P., & Xu, Y. (2007). A Survey of Recent Results in Networked Control Systems. Proceedings of the IEEE, 95(1), 138-162. doi:10.1109/jproc.2006.887288Hristu-Varsakelis D., Levine W. S. (Eds.): “Handbook of Networked and Embedded Control Systems”. Páginas: 677–720. Birkhäuser 2005.Hu, S., & Yan, W.-Y. (2008). Stability of Networked Control Systems Under a Multiple-Packet Transmission Policy. IEEE Transactions on Automatic Control, 53(7), 1706-1711. doi:10.1109/tac.2008.929379Huang, D., & Nguang, S. K. (2008). State Feedback Control of Uncertain Networked Control Systems With Random Time Delays. IEEE Transactions on Automatic Control, 53(3), 829-834. doi:10.1109/tac.2008.919571Lester H. J.: “System architecture for wireless sensor networks”. PhD thesis. University of California, Berkeley. 2003.Marinoni, M., & Buttazzo, G. (2007). Elastic DVS Management in Processors With Discrete Voltage/Frequency Modes. IEEE Transactions on Industrial Informatics, 3(1), 51-62. doi:10.1109/tii.2006.890494Martínez D., Blanes F., Simo J., Crespo A.: “Evaluación del Comportamiento Temporal de Sistemas Distribuidos de Control Sobre IEEE 802.15.4 y CAN”. 21st Symposium on Integrated Circuits and Systems Design – Workshop on Sensor Networks and Applications. Gramado, Brasil. Septiembre de 2008.Pantazis, N.A.; Vergados, D.D.: “A survey on power control issues in wireless sensor networks”. IEEE Communications Surveys & Tutorials, 4th Quarter 2007. vol 9, No. 4.Pillai, P., & Shin, K. G. (2001). Real-time dynamic voltage scaling for low-power embedded operating systems. ACM SIGOPS Operating Systems Review, 35(5), 89-102. doi:10.1145/502059.502044Ripoll, I., Crespo, A., & Mok, A. K. (1996). Improvement in feasibility testing for real-time tasks. Real-Time Systems, 11(1), 19-39. doi:10.1007/bf00365519Saewong S. and Rajkumar R.: “Practical Voltage-Scaling for Fixed-Priority RT-Systems”. Proceedings of the 9th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS’03) 2003 IEEE.Salt, J., Casanova, V., Cuenca, A., & Pizá, R. (2008). Sistemas de Control Basados en Red Modelado y Diseño de Estructuras de Control. Revista Iberoamericana de Automática e Informática Industrial RIAI, 5(3), 5-20. doi:10.1016/s1697-7912(08)70157-2Spuri M.: “Holistic Analysis for Deadline Scheduled Real-Time Distributed Systems”. Tech. Rep. RR-2873, INRIA, France, April 1996.Tabbara, M., Nesic, D., & Teel, A. R. (2007). Stability of Wireless and Wireline Networked Control Systems. IEEE Transactions on Automatic Control, 52(9), 1615-1630. doi:10.1109/tac.2007.904473Tindell, K., Burns, A., & Wellings, A. J. (1995). Analysis of hard real-time communications. Real-Time Systems, 9(2), 147-171. doi:10.1007/bf01088855TinyOS: http://www.tinyos.net/Walsh, G. C., Hong Ye, & Bushnell, L. G. (2002). Stability analysis of networked control systems. IEEE Transactions on Control Systems Technology, 10(3), 438-446. doi:10.1109/87.998034WirelessHART: http://www.hartcomm2.org/hart_protocol/wireless_hart/wirelesshart_datasheet.pdf.Xiong, J., & Lam, J. (2009). Stabilization of Networked Control Systems With a Logic ZOH. IEEE Transactions on Automatic Control, 54(2), 358-363. doi:10.1109/tac.2008.2008319Yang, T. C. (2006). Networked control system: a brief survey. IEE Proceedings - Control Theory and Applications, 153(4), 403-412. doi:10.1049/ip-cta:20050178Stability of networked control systems. (2001). IEEE Control Systems, 21(1), 84-99. doi:10.1109/37.898794Zigbee Specification. http://www.Zigbee.or