A delay-dependent dual-rate PID controller over an ethernet network

n this paper, a methodology to design controllers able to cope with different load conditions on an Ethernet network is introduced. Load conditions induce time-varying delays between measurements and control. To face these variations an interpolated, delay-dependent gain scheduling law is used. The lack of synchronization is solved by adopting an event-based control approach. The dual-rate control action computation is carried out at a remote controller, whereas control actions and measurements are taken out locally at the controlled process site. Stability is proved in terms of probabilistic linear matrix inequalities. TrueTime simulations in an Ethernet case show the benefit of the proposal, which is later validated on an experimental test-bed Ethernet environment.Manuscript received June 07, 2010; revised September 05, 2010; accepted September 15, 2010. Date of publication October 18, 2010; date of current version February 04, 2011. The authors A. Cuenca, J. Salt, and R. Piza are grateful to Grant PAID06-08 by the Universidad Politecnica de Valencia, Grant dpi2009-14744-c03-03 from the Spanish Ministry of Education, and Grant gv/2010/018 by Generalitat Valenciana. In addition, A. Cuenca is grateful to Grant dpi2008-06737-c02-01 by the Spanish Ministry of Education, and A. Sala is grateful to the financial support of the Spanish Ministry of Education Research Grant dpi2008-06731-c02-01, and Generalitat Valenciana Grant prometeo/2008/088. Paper no. TII-10-06-0127.Cuenca Lacruz, ÁM.; Salt Llobregat, JJ.; Sala Piqueras, A.; Pizá Fernández, R. (2011). A delay-dependent dual-rate PID controller over an ethernet network. IEEE Transactions on Industrial Informatics. 7(1):18-29. doi:10.1109/TII.2010.2085007S18297

Finite-horizon estimation of randomly occurring faults for a class of nonlinear time-varying systems

This paper is concerned with the finite-horizon estimation problem of randomly occurring faults for a class of nonlinear systems whose parameters are all time-varying. The faults are assumed to occur in a random way governed by two sets of Bernoulli distributed white sequences. The stochastic nonlinearities entering the system are described by statistical means that can cover several classes of well-studied nonlinearities. The aim of the problem is to estimate the random faults, over a finite horizon, such that the influence from the exogenous disturbances onto the estimation errors is attenuated at the given level quantified by an H∞-norm in the mean square sense. By using the completing squares method and stochastic analysis techniques, necessary and sufficient conditions are established for the existence of the desired finite-horizon H∞ fault estimator whose parameters are then obtained by solving coupled backward recursive Riccati difference equations (RDEs). A simulation example is utilized to illustrate the effectiveness of the proposed fault estimation method

Scalable Approach to Uncertainty Quantification and Robust Design of Interconnected Dynamical Systems

Development of robust dynamical systems and networks such as autonomous aircraft systems capable of accomplishing complex missions faces challenges due to the dynamically evolving uncertainties coming from model uncertainties, necessity to operate in a hostile cluttered urban environment, and the distributed and dynamic nature of the communication and computation resources. Model-based robust design is difficult because of the complexity of the hybrid dynamic models including continuous vehicle dynamics, the discrete models of computations and communications, and the size of the problem. We will overview recent advances in methodology and tools to model, analyze, and design robust autonomous aerospace systems operating in uncertain environment, with stress on efficient uncertainty quantification and robust design using the case studies of the mission including model-based target tracking and search, and trajectory planning in uncertain urban environment. To show that the methodology is generally applicable to uncertain dynamical systems, we will also show examples of application of the new methods to efficient uncertainty quantification of energy usage in buildings, and stability assessment of interconnected power networks

Control and filtering of time-varying linear systems via parameter dependent Lyapunov functions

The main contribution of this dissertation is to propose conditions for linear filter and controller design, considering both robust and parameter dependent structures, for discrete time-varying systems. The controllers, or filters, are obtained through the solution of optimization problems, formulated in terms of bilinear matrix inequalities, using a method that alternates convex optimization problems described in terms of linear matrix inequalities. Both affine and multi-affine in different instants of time (path dependent) Lyapunov functions were used to obtain the design conditions, as well as extra variables introduced by the Finsler\u27s lemma. Design problems that take into account an H-infinity guaranteed cost were investigated, providing robustness with respect to unstructured uncertainties. Numerical simulations show the efficiency of the proposed methods in terms of H-infinity performance when compared with other strategies from the literature

A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version

Stability of singular jump-linear systems with a large state space : a two-time-scale approach

This paper considers singular systems that involve both continuous dynamics and discrete events with the coefficients being modulated by a continuous-time Markov chain. The underlying systems have two distinct characteristics. First, the systems are singular, that is, characterized by a singular coefficient matrix. Second, the Markov chain of the modulating force has a large state space. We focus on stability of such hybrid singular systems. To carry out the analysis, we use a two-time-scale formulation, which is based on the rationale that, in a large-scale system, not all components or subsystems change at the same speed. To highlight the different rates of variation, we introduce a small parameter ε>0. Under suitable conditions, the system has a limit. We then use a perturbed Lyapunov function argument to show that if the limit system is stable then so is the original system in a suitable sense for ε small enough. This result presents a perspective on reduction of complexity from a stability point of view

Delay Estimation and Predictive Control of Uncertain Systems With Input Delay: Application to a DC Motor

International audienceIt is well-known that standard predictive techniques are not very robust to parameter uncertainties and to external disturbances. Furthermore, they require the exact knowledge of the delay. In practice, these constraints are rarely satisfied. In this paper, solutions are presented to allow the use of predictive control in presence of external disturbances, parameter uncertainties and an unknown input delay. First, a recent predictive control method developed to attenuate the effect of external disturbances is shown to be also robust to parameter uncertainties. In addition, a delay estimator is presented to estimate unknown time-varying delays. Theoretical results are widely illustrated through experimental tests on a DC motor

Cooperative control of autonomous connected vehicles from a Networked Control perspective: Theory and experimental validation

Formation control of autonomous connected vehicles is one of the typical problems addressed in the general context of networked control systems. By leveraging this paradigm, a platoon composed by multiple connected and automated vehicles is represented as one-dimensional network of dynamical agents, in which each agent only uses its neighboring information to locally control its motion, while it aims to achieve certain global coordination with all other agents. Within this theoretical framework, control algorithms are traditionally designed based on an implicit assumption of unlimited bandwidth and perfect communication environments. However, in practice, wireless communication networks, enabling the cooperative driving applications, introduce unavoidable communication impairments such as transmission delay and packet losses that strongly affect the performances of cooperative driving. Moreover, in addition to this problem, wireless communication networks can suffer different security threats. The challenge in the control field is hence to design cooperative control algorithms that are robust to communication impairments and resilient to cyber attacks. The work aim is to tackle and solve these challenges by proposing different properly designed control strategies. They are validated both in analytical, numerical and experimental ways. Obtained results confirm the effectiveness of the strategies in coping with communication impairments and security vulnerabilities