Search

This paper presents a new approach to bounded-error state estimation involving time uncertainties. For a given bounded observation of a continuous-time non-linear system, it is assumed that neither the values of the observed data nor their acquisition instants are known exactly. For systems described by state-space equations, we prove theoretically and demonstrate by simulations that the proposed constraint propagation approach enables the computation of bounding sets for the systems’ state vectors that are consistent with the uncertain measurements. The bounding property of the method is guaranteed even if the system is strongly non-linear. Compared with other existing constraint propagation approaches, the originality of the method stems from our definition and use of bounding tubes which enable to enclose the set of all feasible trajectories inside sets. This method makes it possible to build specific operators for the propagation of time uncertainties through the whole trajectory. The efficiency of the approach is illustrated on two examples: the dynamic localization of a mobile robot and the correction of a drifting clock. [ABSTRACT FROM AUTHOR]

In this paper, the stability of parallel-operated inverters in the sense of boundedness is investigated. At first, the non-linear model of parallelled inverters with a generic linear or non-linear load is obtained by using the generalised dissipative Hamiltonian structure and then the robust droop controller, recently proposed in the literature for parallel operation of inverters, is implemented in a way to produce a bounded control output. The proposed controller is called the bounded droop controller (BDC). It introduces a zero-gain property and can guarantee the boundedness of the closed-loop system solution. Therefore, for the first time, the closed-loop stability in the sense of boundedness is guaranteed for parallelled inverters feeding generic non-linear/linear loads. The controller structure is further improved to increase its robustness with respect to initial conditions, numerical errors or external disturbances while maintaining the stability property. Moreover, the controller is tuned to avoid any possible limit cycles in the voltage dynamics. Real-time simulation results for two single-phase inverters operated in parallel loaded with a non-linear load are presented to verify the effectiveness of the proposed BDC. [ABSTRACT FROM AUTHOR]

This work deals with the problem of designing observers for the estimation of a single function of the states for discrete-time nonlinear systems. Necessary and sufficient conditions for the existence of lower order functional observers with linear dynamics and linear output map are derived. The results provide a direct generalization to Luenberger's linear theory of functional observers. [ABSTRACT FROM AUTHOR]

Abstract: The paper presents a methodology for an optimal input design for model discrimination. To allow analytical solutions, the method, using Pontryagin’s maximum principle, is developed for non-linear single-state systems that are affine in their joint input. The method is demonstrated on a fed-batch reactor case study with first-order and Monod kinetics. [Copyright &y& Elsevier]

Abstract: We study a predictive control formulation for uncertain discrete-time non-linear uniformly continuous plant models where controller output data is transmitted over an unreliable communication channel. The channel introduces Markovian data-loss and does not provide acknowledgments of receipt. To achieve robustness with respect to dropouts, at every sampling instant the controller transmits packets of data. These contain possible control inputs for a finite number of future time instants, and minimize a finite horizon cost function. At the actuator side, received packets are buffered, providing the plant inputs. Within this context, we adopt a stochastic Lyapunov function approach to establish stability results of the networked control system. A distinguishing aspect of this work is that it considers situations where the maximum number of consecutive packet dropouts has unbounded support. [Copyright &y& Elsevier]

Abstract: Small gain theorems are used to verify the stability of a feedback interconnection of causal stable systems. In this work, we extend the small gain condition to test the stability of a feedback interconnection of two stable systems at least one of which is non-causal. This result may find application in the robust controller design for time-delay systems. [Copyright &y& Elsevier]

Abstract: This work tackles the problem of expanding Volterra models using Laguerre functions. A strict global optimal solution is derived when each multidimensional kernel of the model is decomposed into a set of independent orthonormal bases, each of which parameterized by an individual Laguerre pole intended for representing the dominant dynamic of the kernel along a particular dimension. It is proved that the solution derived minimizes the upper bound of the squared norm of the error resulting from the practical truncation of the Laguerre series expansion into a finite number of functions. This is an extension of the results in Campello, Favier and Amaral [(2004). Optimal expansions of discrete-time Volterra models using Laguerre functions. Automatica, 40, 815–822.], where an optimal solution was obtained for the usual yet particular case in which a single Laguerre pole is used for expanding a given kernel along all its dimensions. It is also proved that the particular and extended solutions are equivalent to each other when the Volterra kernels are symmetric. [Copyright &y& Elsevier]

Abstract: A recursive prediction error algorithm for identification of systems described by non-linear ordinary differential equation (ODE) models is presented. The model is an ODE model, parameterized with coefficients of a multi-variable polynomial that describes one component of the right-hand side function of the ODE. This avoids over-parameterization problems. The selected model can also handle systems with more complicated right-hand side structure, by identification of a local input–output equivalent system in the coordinate system of the selected state variables. A novel technique based on scaling of the sampling period is proposed. The technique can improve the conditioning of the identification problem, thereby enhancing the chances of convergence to the correct minimum of the criterion. The algorithm is applied to live data from a system consisting of two cascaded tanks, with promising results. A MATLAB software package, which implements the proposed algorithm and a set of support scripts, can be freely downloaded from http://www.it.uu.se/research/reports/. [Copyright &y& Elsevier]

Abstract: Consistency relations are often used to design residual generators based on non-linear process models. A main difficulty is that they generally include time differentiated versions of known signals which are difficult to estimate in a noisy environment. The main results of this paper show how to lower the need to estimate derivatives of known signals in order to compute a residual. Necessary and sufficient conditions for lowering the order of the derivatives in one step are presented and a main step in the approach is to obtain a state-space realization of the residual generator. An attractive feature of the approach is that general differential algebraic system descriptions can be handled in the same way as for example ordinary differential equations and also that stability of the residual generator is always guaranteed. [Copyright &y& Elsevier]

Abstract: The topic of this paper is the identification of an accurate model for magneto-rheological (MR) dampers. A semi-active MR-damper is a dynamic system, where the inputs are the elongation velocity and the command current; the current is the control input which modulates at high-bandwidth the damping characteristic through the variation of a magnetic field. The output is the force delivered by the damper. Among the broad set of applications where MR-dampers can be used, the results proposed in this work refer to MR-dampers for the control of vehicle dynamics. MR-damper are highly non-linear systems, and their accurate modeling is a non-trivial task. MR-dampers can be modeled using two different model classes: semi-physical models and black-box models. Both approaches are considered in this work. The purpose of this brief paper is to make a concise but complete presentation and discussion of a non-trivial system identification problem. The problem considered herein is particularly interesting from the system identification point of view: from one side, the MR-damper is a very attractive actuator, which is likely to become the key device for many dynamics and vibration control systems in the near future; on the other side, it is an example of an application problem where the accurate modeling of the actuation device is one of the most crucial part of the whole control design problem. [Copyright &y& Elsevier]

The paper presents an optimal parametric sensitivity controller for estimation of a set of parameters in an experiment. The method is demonstrated for a fed-batch bioreactor case study for optimal estimation of the half-saturation constant KS and the parameter combination μmaxX/Y in which μmax is the maximum specific growth rate, X is the biomass concentration, and Y the yield coefficient. The resulting parametric sensitivity controller for the parameter KS is utilized in two sequential experiments using a ‘bang–bang-singular’ control strategy. Comparison with an optimal solution for the weighted sum of squared sensitivities for both parameters are compared with the individual cases where only one specific parametric output sensitivity is controlled. The parametric uncertainty is handled in a completely deterministic way as to arrive at a control law that maximizes the parametric output sensitivity. [Copyright &y& Elsevier]

This paper shows how well-established control system techniques can be introduced to formulate guidelines for clinical testing and monitoring of HIV/AIDS disease and the estimation of HIV/AIDS parameters. It is assumed that the viral load and healthy CD4+T cell in plasma are measured. The objective is to estimate all parameters in the basic three-dimensional HIV/AIDS model. For this purpose, through an analysis of basic system properties, the minimal number of measurement samples for the CD4+T cell and the viral load counts is first obtained. The paper determines then the HIV progression stages when an estimation of all parameters is impossible. Outside these stages, the paper proposes two on-line estimation algorithms for all HIV parameters based on the well-known techniques of adaptive identifiers and adaptive observers. Conditions for parameter convergence are discussed. Simulation results are demonstrated for the parameter estimation using adaptive observers. [Copyright &y& Elsevier]

This paper investigates the accuracy of the linear component that forms part of an overall Hammerstein model-structure estimate, and a key finding is that the process of estimating the non-linear element can have a strong effect on the associated estimate of the linear dynamics. Furthermore, this effect is not explained simply by way of considering how the input spectrum is changed by the non-linearity. Instead, it arises that the linear model-estimate variability may be dominated by a term that depends on the frequency response of the linear system itself. Amongst other things, the main results derived here have experiment design implications for Hammerstein system estimation. [Copyright &y& Elsevier]

This paper provides results on input–output L p stability of networked control systems (NCSs) implemented over WirelessHART (WH). WH is a communication protocol widely used in process instrumentation. It is mainly characterised by its multi-hop structure, slotted communication cycles, and the possibility to simultaneously transmit over different frequencies. We propose a non-linear hybrid model of WH–NCSs that is able to capture these network functionalities, and that it is more general than existing models in the literature. Particularly, the multi-hop nature of the network is translated into an interesting mathematical structure in our model. We then follow the emulation approach to stabilise the NCS. We first assume that we know a stabilising controller for the plant without the network. We subsequently show that, under reasonable assumptions on the scheduling protocol, stability is preserved when the controller is implemented over the network with sufficiently frequent data transmission. Specifically, we provide bounds on the maximum allowable transmission interval (MATI) under which all protocols that satisfy the property of being persistently exciting (PE) lead to L p stable WH–NCSs. These bounds exploit the mathematical structure of our WH–NCS model, improving the existing bounds in the literature. Additionally, we explain how to schedule transmissions over the hops to satisfy the PE property. In particular, we show how simultaneous transmissions over different frequency channels can be exploited to further enlarge the MATI bound. [ABSTRACT FROM AUTHOR]