Search

This paper addresses a problem of optimal error quantification in the framework of robust control theory in the 1 setup. The upper bounds of biased external disturbance and the gains of coprime factor perturbations in a discrete-time linear time invariant SISO plant are assumed to be unknown. The computation of optimal data-consistent upper bounds under a known bias of external disturbance has been simplified to linear programming. This allows for the computation of optimal estimates in real-time and their application to achieve optimal robust steady-state tracking even when facing an unknown bias in the external disturbance. The presented results have been illustrated through computer simulations. [ABSTRACT FROM AUTHOR]

Petrochemical and dairy industries, waste management, and paper manufacturing fall under the category of process industries where flow and liquid control are essential. Even when liquids are mixed or chemically treated in interconnected tanks, the fluid and flow should constantly be observed and controlled, especially when dealing with nonlinearity and imperfect plant models. In this study, we propose a nonlinear dynamic multiple-input multiple-output (MIMO) plant model. This model is then transformed through linearization, a technique frequently utilized in the analysis and modeling of fractional processes, and decoupling for decentralized fixed-structure H-infinity robust control design. Simulation tests based on MATLAB and SIMULINK are subsequently executed. Numerous assessments are conducted to evaluate tracking performance, external disturbance rejection, and plant parameter fluctuations to gauge the effectiveness of the proposed model. The objective of this work is to provide a framework that anticipates potential outcomes, paving the way for implementing a reliable controller synthesis for MIMO-connected tanks in real-world scenarios. [ABSTRACT FROM AUTHOR]

A direct data-driven iterative algorithm is developed to accurately estimate the H ∞ norm of a linear time-invariant system from continuous operation, i.e., without resetting the system. The main technical step involves a reversed-circulant matrix that can be evaluated in a model-free setting by performing experiments on the real system. [ABSTRACT FROM AUTHOR]

• A new approach for Explicit Model Predictive Control is presented. • Adjustable Robust Optimization is employed to account for plant-model mismatch. • Performance of the explicit model predictive controller is compared to online MPC. • Results show the proposed explicit controller is promising for real-life systems. Conventional model predictive control (MPC) involves solving an optimization problem online to determine the control actions that minimize a performance criterion function. The high computational expense associated with conventional MPC may make its application challenging for large-scale systems. Explicit MPC has been developed to solve the optimization problem offline. In this work, adjustable robust optimization is used to obtain the explicit solution to the MPC optimization problem offline for discrete-time linear time invariant systems with constraints on inputs and states. In the robust model formulation, an uncertain additive time-varying error is introduced to account for model uncertainty resulting from plant-model mismatch caused by un-measurable disturbances or process nonlinearities. The explicit solution is an optimal time-varying sequence of feedback control laws for the control inputs parameterized by the system's states. The control laws are evaluated in a time-varying manner when the process is online using state measurements. This study shows that the resulting control laws ensure the implemented control actions maintain the system states within their feasible region for any realizations of the uncertain parameters that are within the user-defined uncertainty set. Three case studies are presented to demonstrate the proposed approach and to highlight the benefits and limitations of this method. The proposed framework advances the development of Explicit MPC by further expanding its application to large as well as nonlinear systems. [ABSTRACT FROM AUTHOR]

This paper presents a frequency domain analysis toward the robustness, convergence speed, and steady-state error for general linear time invariant (LTI) iterative learning control (ILC) for single-input-single-output (SISO) LTI systems and demonstrates the optimality of norm-optimal iterative learning control (NO-ILC) in terms of balancing the tradeoff between robustness, convergence speed, and steady-state error. The key part of designing LTI ILC updating laws is to choose the Q-filter and learning gain to achieve the desired robustness and performance, i.e., convergence speed and steady-state error. An analytical equation that characterizes these three terms for NO-ILC has been previously presented in the literature. For general LTI ILC updating laws, however, this relationship is still unknown. Adopting a frequency domain analysis approach, this paper characterizes this relationship for LTI ILC updating laws and, subsequently, demonstrates the optimality of NO-ILC in terms of balancing the tradeoff between robustness, convergence speed, and steady-state error. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a novel data‐driven approach is proposed to obtain output regulation for linear systems in finite time, requiring only limited information about the plant and the exosystem. The resulting regulator is robust because it does not rely on the knowledge of perturbed or even nominal plant parameters. Finite‐time regulation is achieved, combining the use of the external‐model technique with the deadbeat controller design. The core of the method lies in an error‐feedback reset logic for the state of the external model to compensate for the contribution of the exosystem on the plant output response, then an ancillary control law is introduced to steer the error to zero in a preassigned time interval, trading‐off between convergence rate, and control effort. [ABSTRACT FROM AUTHOR]

Summary: A new robust controller design method that satisfies the H∞ criterion is developed for linear time‐invariant single‐input single‐output (SISO) systems. A data‐driven approach is implemented in order to avoid the unmodeled dynamics associated with parametric models. This data‐driven method uses fixed‐order controllers to satisfy the H∞ criterion in the frequency domain. The necessary and sufficient conditions for the existence of such controllers are presented by a set of convex constraints. These conditions are also extended to systems with frequency‐domain uncertainties in polytopic form. It is shown that the upper bound on the weighted infinity norm of the sensitivity function converges monotonically to the optimal value, when the controller order increases. Additionally, the practical issues involved in computing fixed‐order rational H∞ controllers in discrete‐time or continuous‐time by convex optimization techniques are addressed. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Fractional calculus increases their applications in system design and analysis problems because of providing more realistic modeling of real systems. Owing to computational complexity of fractional calculus, the computer-aided design and analysis methods are required for engineering applications of fractional order systems. This study presents a numerical method for parametric robust stabilization of fractional order systems by employing single-parameter perturbation. This method implements a fractional order perturbation strategy on the basis of brute-force search technique for system stabilization problems. In order to meet a predefined minimum argument root design specification, the proposed algorithm searches for a desired placement of the minimum argument characteristic root within the first Riemann sheet by performing iterative perturbations of the fractional order. This approach can provide a straightforward numerical solution for robust stabilization problems of fractional order systems by employing an order perturbation scheme. Moreover, a possible utilization of a fractional order derivative operator as a system stabilizer is theoretically discussed. Illustrative examples show the utilization of the proposed stabilization algorithms for computer-aided fractional order system design applications. [ABSTRACT FROM AUTHOR]

The Simple Adaptive Control (SAC) controls an augmented plant that comprises the true plant with Parallel Feedforward . The Almost Strictly Positive Real (ASPR) property of the augmented plant guarantees the stability of the tracking loop and leads to asymptotic following. Prior publications have shown that, based only on the prior knowledge on stabilizability properties of systems (usually available), the Parallel Feedforward Configuration (PFC) allows adaptive control of realistic systems, even if they are both unstable and non-minimum phase. However, it was commonly thought that the addition of the PFC requires a price when compared with good linear time invariant (LTI) designs that do not use any addition to the plant. The paper shows that the use of a properly designed SAC with PFC, as Add-On to LTI system design, improves the performance. Although SAC doesn't directly control the true plant tracking error, it always gives smaller tracking error and reduced sensitivity to plant disturbance and output measurement noise with respect to the best LTI controller. [ABSTRACT FROM AUTHOR]

The need to guarantee robustness of adaptive control systems in the presence of disturbances seems to affect the quality of tracking even in ideal environments. A recent paper revisited and modified the use of various components of the simple adaptive control (SAC) approach of linear time-invariant (LTI) systems and showed how one can use passivity concepts such that, while it maintains robustness with disturbances, it also allows asymptotically perfect tracking in ideal conditions. Using the extension of passivity conditions to nonstationary systems, this paper extends the analysis of robustness with disturbances and asymptotically perfect tracking in ideal conditions to nonstationary and nonlinear systems. (Presented in shorter form at 20th IFAC World Congress, Toulouse, France, July 9-14, 2017). [ABSTRACT FROM AUTHOR]

In this paper, solvability, stability, and robust stability of linear time-varying singular systems of second order difference equations are studied. The leading coefficient is allowed to be singular, i.e., the system does not generate an explicit recursion. By transforming the system into an appropriate form, the existence and uniqueness of solutions are established under the so-called strangeness-free assumption. Consistent initial conditions are also explicitly constructed. Then, some criteria for exponential stability and a Bohl–Perron-type theorem are presented. Finally, we investigate the robust stability when the system coefficients are subject to structured perturbations. Examples are also given for illustration. The approach presented here can be extended to the analysis of singular systems of high order and delay difference equations. [ABSTRACT FROM AUTHOR]

This work deals with computing the worst-case stability and the worst-case H ∞ performance of linear time-invariant systems subject to mixed real-parametric and complex-dynamic uncertainties in a compact parameter set. Our novel algorithmic approach is tailored to the properties of the nonsmooth worst-case functions associated with stability and performance, and this leads to a fast and reliable optimization method, which finds good lower bounds of μ. We justify our approach theoretically by proving a local convergence certificate. Because computing μ is known to be NP-hard, our technique should be used in tandem with a classical μ upper bound to assess global optimality. Extensive testing indicates that the technique is practically attractive. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper proposes a control architecture that employs event-triggered control techniques to achieve output synchronization of a group of heterogeneous linear time-invariant agents. We associate with each agent an event-triggered output regulation controller and an event-triggered reference generator. The event-triggered output regulation controller is designed such that the regulated output of the agent approximately tracks a reference signal provided by the reference generator in the presence of unknown disturbances. The event-triggered reference generator is responsible for synchronizing its internal state across all agents by exchanging information through a communication network linking the agents. We first address the output regulation problem for a single agent where we analyze two event-triggered scenarios. In the first one, the output and input event detectors operate synchronously, meaning that resets are made at the same time instants, while in the second one, they operate asynchronously and independently of each other. It is shown that the tracking error is globally bounded for all bounded reference trajectories and all bounded disturbances. We then merge the results on event-triggered output regulation with previous results on event-triggered communication protocols for synchronization of the reference generators to demonstrate that the regulated output of each agent converges to and remains in a neighborhood of the desired reference trajectory and that the closed-loop system does not exhibit Zeno solutions. Several examples are provided to illustrate the advantages and issues of every component of the proposed control architecture. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a new technique for order reduction of linear time-invariant systems is presented. This technique is intended for both single-input single-output (SISO) and multi-input multi-output (MIMO) systems. Motivated by other reduction techniques, the new proposed reduction technique is based on modified pole clustering and factor division algorithm with the objective of obtaining a stable reduced-order system preserving all essential properties of the original system. The new technique is illustrated by three numerical examples which are considered from the literature. To evaluate the superiority and robustness of the new technique, the results of the proposed technique are compared with other well-known and recently developed order-reduction techniques like Routh approximation and Big Bang-Big Crunch algorithm. The comparison of performance indices shows the efficiency and powerfulness of the new technique. [ABSTRACT FROM AUTHOR]

We study 2D systems with a continuous and discrete time axis. We embed known results about the stability and H ∞ -performance properties of such systems into multiplier theory from robust control. It is shown that this opens the way for applying recently developed gain-scheduled controller synthesis techniques in order to solve the H ∞ -design problem for 2D systems without any conservatism. This is presented if the discrete-time axis is either one- or two-sided, the latter leading to non-conservative H ∞ -synthesis result for infinite string interconnections of identical linear time-invariant systems. [ABSTRACT FROM AUTHOR]

This paper presents a data-driven receding horizon fault estimation method for additive actuator and sensor faults in unknown linear time-invariant systems, with enhanced robustness to stochastic identification errors. State-of-the-art methods construct fault estimators with identified state-space models or Markov parameters, without compensating for identification errors. Motivated by this limitation, we first propose a receding horizon fault estimator parameterized by predictor Markov parameters. This estimator provides (asymptotically) unbiased fault estimates as long as the subsystem from faults to outputs has no unstable transmission zeros. When the identified Markov parameters are used to construct the above fault estimator, stochastic identification errors appear as model uncertainty multiplied with unknown fault signals and online system inputs/outputs (I/O). Based on this fault estimation error analysis, we formulate a mixed-norm problem for the offline robust design that regards online I/O data as unknown. An alternative online mixed-norm problem is also proposed that can further reduce estimation errors at the cost of increased computational burden. Based on a geometrical interpretation of the two proposed mixed-norm problems, systematic methods to tune the user-defined parameters therein are given to achieve desired performance trade-offs. Simulation examples illustrate the benefits of our proposed methods compared to recent literature. [ABSTRACT FROM AUTHOR]

The negative imaginary property is a property that many practical systems exhibit. This paper is concerned with the negative imaginary synthesis problem for linear time-invariant systems by output feedback control. Sufficient conditions are developed for the design of static output feedback controllers, dynamic output feedback controllers and observer-based feedback controllers. Based on the design conditions, a numerical algorithm is suggested to find the desired controllers. Structural constraints can be imposed on the controllers to reflect the practical system constraints. Also, the separation principle is shown to be valid for the observer-based design. Finally, three numerical examples are presented to illustrate the efficiency of the developed theory. [ABSTRACT FROM AUTHOR]

Coefficient diagram method is a controller design technique for linear time-invariant systems. This design procedure occurs into two different domains: an algebraic and a graphical. The former is closely paired to a conventional pole placement method and the latter consists on a diagram whose reading from the plotted curves leads to insights regarding closed-loop control system time response, stability and robustness. The controller structure has two degrees of freedom and the design process leads to both low overshoot closed-loop time response and good robustness performance regarding mismatches between the real system and the design model. This article presents an overview on this design method. In order to make more transparent the presented theoretical concepts, examples in M atlabcode are provided. The included code illustrates both the algebraic and the graphical nature of the coefficient diagram design method. [ABSTRACT FROM AUTHOR]

In this paper, a robust decentralized and linear time-invariant controller is proposed for quadrotors to achieve trajectory tracking. The designed closed-loop control system includes three loops: 1) an attitude loop that controls the attitude angles; 2) a position loop that controls the translational trajectory of the quadrotor; and 3) a robust compensating loop that restrains the influence of uncertainties including parameter uncertainties, nonlinear and coupling dynamics, and external disturbances in the rotational and translational dynamics. It is proven that the tracking errors can converge into a priori set neighborhood of the origin ultimately. Experimental results are given to confirm the advantages of the proposed control method, compared with the linear time-invariant H_\infty control method. [ABSTRACT FROM AUTHOR]

This paper extends the results of a new model-free approach which has been applied to guarantee nominal stability and performance. In this paper, using a particular controller structure, the robust stability (RS) and robust performance (RP) criteria for single input single output linear time invariant (SISO-LTI) plants with multiplicative uncertainty are transformed to affine functions in terms of controller parameters. It is shown that solving the feasibility problem of these new criteria will lead to controllers that guarantee the RS and performance. There is no need for a plant mathematical model. The required data for controller synthesis are just the frequency responses corresponding to limited samples of the uncertain plant. Also, there is no need for exact data at each frequency for the whole set of frequency responses. The approach is also applicable for designing both low- and high-order controllers. The effectiveness of the proposed technique is illustrated by simulation results. [ABSTRACT FROM AUTHOR]

In this paper, the problem of robust discretisation of linear time-invariant (LTI) systems with polytopic uncertainties is introduced. More specifically, the main objective is to provide a systematic way to find an approximate discrete-time (DT) model of a continuous-time (CT) plant with uncertainties in polytopic domain. The system matrices of polytopic DT model to be found are expressed as parameter-dependent matrices which are homogeneous polynomials of arbitrary degree with respect to the uncertain variables in the simplex, and is obtained in such a way that the norm between the system matrices and the truncated power series of the exact DT model is minimised while preserving the polytopic structure of the original CT plant. The solution procedures proposed are presented in terms of single-parameter minimisation problems subject to linear matrix inequality (LMI) constraints which are numerically tractable via LMI solvers. Finally, examples are given to show the validity and effectiveness of the proposed techniques. [ABSTRACT FROM PUBLISHER]

A square membrane structure with clamped edges and four lead zirconate titanate bimorph actuators is modeled using Kirchhoff's plate theory. Two systems are considered, defined by the relative location of the actuators on the membrane. The finite element method is used to generate linear time-invariant models in the second-order form. The number of elements used in the finite element method is determined via a systematic analysis based on the convergence of fundamental natural frequencies and mode shapes. Characteristics that are essential for system analysis and control design such as stability, controllability, and observability are investigated using methods based on the linear time-invariant first-order form of the linear equations of motion and methods based on the linear time-invariant second-order form directly generated via the finite element method. Comparisons between the accuracy and reliability of these methods are performed. Next, modern control problems aimed at minimizing vibrations and the control energy are formulated using the linearized equations of motion. The feasibility of using the linear time-invariant second-order form in solving these problems is illustrated. Comparisons of responses to initial conditions perturbations for systems that rely only on material damping and systems that rely on a control system to damp out membrane vibrations are performed, indicating the effectiveness of modern feedback control in damping out vibrations. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of robust stabilization for discrete linear time-varying (LTV) systems subject to time-varying normalized coprime factor uncertainty. Operator theoretic results which generalize similar results known to hold for linear time-invariant (infinite-dimensional) systems are developed. In particular, we compute an upper bound for the maximal achievable stability margin under TV normalized coprime factor uncertainty in terms of the norm of an operator with a time-varying Hankel structure. We point to a necessary and sufficient condition which guarantees compactness of the TV Hankel operator, and in which case singular values and vectors can be used to compute the time-varying stability margin and TV controller. [ABSTRACT FROM AUTHOR]

This paper proposes a fault-tolerant control (FTC) scheme for linear parameter-varying (LPV) systems based on integral sliding modes (ISMs) and control allocation (CA) and describes the implementation and evaluation of the controllers on a 6-degree-of-freedom research flight simulator called SIMONA. The FTC scheme is developed using an LPV approach to extend ideas previously developed for linear time-invariant systems, in order to cover a wide range of operating conditions. The scheme benefits from the combination of the inherent robustness properties of ISMs (to ensure sliding occurs throughout the simulation) and CA, which has the ability to redistribute control signals to all available actuators in the event of faults/failures. [ABSTRACT FROM PUBLISHER]

While time delays typically lead to poor control performance, and even instability, previous research shows that time delays can, in some cases, be beneficial. This paper presents a new benefit of time-delayed control (TDC) for single-input single-output (SISO) linear time invariant (LTl) systems: it can be used to improve robustness. Time delays can be used to approximate state derivative feedback (SSD), which together with state feedback (SF) can reduce sensitivity and improve stability margins. Additional sensors are not required since the state derivatives are approximated using available measurements and time delays. A systematic design approach, based on solution of delay differential equations (DDEs) using the Lambert W method, is presented using a scalar example. The method is then applied to both single- and two-degree of freedom (DOF) mechanical systems. The simulation results demonstrate excellent performance with improved stability margins. [ABSTRACT FROM AUTHOR]

This study focuses on the design of the robust fault-tolerant control (FTC) system based on adaptive observer for uncertain linear time invariant (LTI) systems. In order to improve robustness, rapidity, and accuracy of traditional fault estimation algorithm, an adaptive fault estimation algorithm (AFEA) using an augmented observer is presented. By utilizing a new fault estimator model, an improved AFEA based on linear matrix inequality (LMI) technique is proposed to increase the performance. Furthermore, an observer-based state feedback fault-tolerant control strategy is designed, which guarantees the stability and performance of the faulty system. Moreover, the adaptive observer and the fault-tolerant controller are designed separately, whose performance can be considered, respectively. Finally, simulation results of an aircraft application are presented to illustrate the effectiveness of the proposed design methods. [ABSTRACT FROM AUTHOR]

This paper investigates the possible adoption of a fractional order sliding surface for the robust control of perturbed integer-order LTI systems. It is proved that the standard approach used in Sliding Model Control (SMC) cannot be used and a substantial redesign of the control policy is needed. A novel control strategy is discussed, ensuring that the sliding manifold is hit at an infinite sequence of time instants becoming denser as time grows. Interesting asymptotic properties are derived relatively to the closed loop response in the presence of a wide class of disturbances. It is also proved that the chattering phenomenon may be remarkably alleviated. A careful simulation study is reported using an electromechanical system taken from the literature, which includes also a comparative analysis of performances with respect to standard SMC and second-order SMC. [ABSTRACT FROM AUTHOR]

A fractional order PID controller is designed to stabilize fractional delay systems with commensurate orders and multiple commensurate delays, where the time delays in the system may belong to several distinct intervals. Moreover, the controller parameters should belong to given intervals. In order to stabilize the system, the D-subdivision method is employed to choose the stabilizing set of the controller parameters from their available values. Furthermore, the nearest values of the obtained stabilizing set to their mean values are selected as the controller parameters so that a non-fragile controller is concluded. Two numerical examples evaluate the proposed control design method. [ABSTRACT FROM AUTHOR]

This article provides a framework for robust performance analysis of linear time-invariant uncertain multivariable systems obtained by classical system identification methods. The performance measures are in terms ofH2orH∞norm of a closed-loop transfer matrix. An upper bound for the performance analysis criterion is computed via an LMI-based optimisation problem. The LFT description is used as a tool for uncertainty modelling. The proposed performance conditions are derived based on using the parameter-dependent Lyapunov functions and are deduced via a parametrisation for the set of multipliers corresponding to the ellipsoidal uncertainty set delivered by system identification procedure. The effectiveness of the proposed analysis approach is demonstrated by a numerical example. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper deals with the problem of the stabilization and control of linear time invariant high order systems with two unstable real poles plus time delay. A simple observer-based controller is designed in order to achieve a stable behavior of the closed-loop system. Necessary and sufficient conditions for the existence of the proposed control structure are stated. Hence, only four proportional gains and the model of the plant are enough to obtain a stable response of the delayed system. Moreover, a robustness analysis is presented in order to compute the maximal uncertainty bound accepted for the delay term. In addition, a two degree of freedom proportional-integral control action is implemented in order to track step references and to reject step disturbances. The achieved performance of the proposed control strategy is illustrated by mean of numerical simulations. © 2013 Curtin University of Technology and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this article, by using the fractional order PIλcontroller, we propose a simple and effective method to compute the robust stability region for the fractional order linear time-invariant plant with interval type uncertainties in both fractional orders and relevant coefficients. The presented method is based on decomposing the fractional order interval plant into several vertex plants using the lower and upper bounds of the fractional orders and relevant coefficients and then constructing the characteristic quasi-polynomial of each vertex plant, in which the value set of vertex characteristic quasi-polynomial in the complex plane is a polygon. The D-decomposition method is used to characterise the stability boundaries of each vertex characteristic quasi-polynomial in the space of controller parameters, which can obtain the stability region by varying λ orders in the range (0, 2). These regions of each vertex plant are computed by using three stability boundaries: real root boundary (RRB), complex root boundary (CRB) and infinite root boundary (IRB). The method gives the explicit formulae corresponding to these boundaries in terms of fractional order PIλcontroller parameters. Thus, the robust stability region for fractional order interval plant can be obtained by intersecting stability region of each vertex plant. The robustness of stability region is tested by the value set approach and zero exclusion principle. Our presented technique does not require sweeping over the parameters and also does not need linear programming to solve a set of inequalities. It also offers several advantages over existing results obtained in this direction. The method in this article is useful for analysing and designing the fractional order PIλcontroller for the fractional order interval plant. An example is given to illustrate this method. [ABSTRACT FROM PUBLISHER]

Abstract: This paper studies the problem of robust stabilization by a stable controller for a linear time-invariant single-input single-output infinite dimensional system. We consider a class of plants having finitely many simple unstable zeros but possibly infinitely many unstable poles. First we show that the problem can be reduced to an interpolation–minimization by a unit element. Next, by the modified Nevanlinna–Pick interpolation, we obtain both lower and upper bounds on the multiplicative perturbation under which the plant can be stabilized by a stable controller. In addition, we find stable controllers to provide robust stability. We also present a numerical example to illustrate the results and apply the proposed method to a repetitive control system. [Copyright &y& Elsevier]

Balanced truncation is a standard and very natural approach to approximate dynamical systems. We present a version of balanced truncation for model order reduction of linear time-delay systems. The procedure is based on a coordinate transformation of the position and preserves the delay structure of the system. We therefore call it (structure-preserving) position balancing. To every position, we associate quantities representing energies for the controllability and observability of the position. We show that these energies can be expressed explicitly in terms of the solutions to corresponding delay Lyapunov equations. Apart from characterizing the energies, we show that one block of the (operator) controllability and observability Gramians in the operator formulation of the time-delay system can also be characterized with the delay Lyapunov equation. The delay Lyapunov equation undergoes a contragredient transformation when we apply the position coordinate transformation and we propose to truncate it in a classical fashion, such that positions which are only weakly connected to the input and the output in the sense of the energy concepts are removed. [ABSTRACT FROM AUTHOR]

SUMMARY In this paper, we develop a new approach to computing the entire set of stabilizing controllers for a given continuous-time linear time-invariant system by using recent results from interval positivity. The discrete counterpart is also presented. The approaches are based on the sign-definite decomposition that enables us to deal with functions that are polynomially dependent on the parameters of interests. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: This paper analyzes the robustness of global exponential stability of stochastic recurrent neural networks (SRNNs) subject to parameter uncertainty in connection weight matrices. Given a globally exponentially stable stochastic recurrent neural network, the problem to be addressed here is how much parameter uncertainty in the connection weight matrices that the neural network can remain to be globally exponentially stable. We characterize the upper bounds of the parameter uncertainty for the recurrent neural network to sustain global exponential stability. A numerical example is provided to illustrate the theoretical result. [Copyright &y& Elsevier]

In this study, the problem of cooperative fault accommodation in formation flight of unmanned vehicles represented by linear time-invariant models that are subject to loss-of-effectiveness actuator faults is investigated through a hierarchical framework. Three hierarchical levels are envisaged, namely a low-level fault recovery (LLFR), a formation-level fault recovery and a high-level supervisor. In the LLFR module, a recovery controller is designed by using an estimate of the actuator fault. A performance monitoring module is then introduced at the high-level to identify a 'partially low-level recovered' vehicle because of inaccuracy in the fault severity estimate that results in violating the 'error specification' of the formation mission. The high-level supervisor then activates the formation-level fault recovery module to compensate for the resulting performance degradations of the partially low-level (LL) recovered vehicle at the expense of other healthy vehicles. The fault is accommodated by reconfiguring the formation structure through the novel notion of the weighted absolute measurement formation digraph, activating a robust controller for the partially LL recovered vehicle, and imposing a constraint on the desired input signals. Numerical simulations for a formation flight of five satellites in the planetary orbital environment are presented to confirm the validity and effectiveness of the proposed analytical work. [ABSTRACT FROM AUTHOR]

An approach allowing the creation of parameter uncertainties and external disturbances without any hardware parts supplementary to the nominal system is proposed in this manuscript. The emulating signal, reflecting the plant variations, essential for testing of controllers, is created in software and added to the plant input, forcing the nominal system output to resemble the output of a system with actual uncertainties and disturbances, thus allowing us to test the controller’s robustness prior to an actual field test. In addition, the full state vector of the emulated system may be reconstructed and fed back to the controller, if necessary. The proposed methods allow simultaneous emulation of any combination of time-varying parameter variations and external disturbances. The method can be related to a class of enhanced hardware-in-the-loop simulations, since the nominal hardware is present in the setup in addition to the controller under test. The proposed techniques can be used to test the performance of advanced control algorithms before their mass production. Extended simulation results are reported to confirm the feasibility of the proposed approaches. [ABSTRACT FROM PUBLISHER]

This paper presents a new passivity enforcement technique for linear time-invariant multiport systems generated from tabulated measured or simulated data. Traditional methods based on iterative eigenvalue/singular value perturbation do not guarantee convergence, and the error introduced is sometimes large due to the lack of explicit error control. The key to the new algorithm is to correct passivity violations locally with moderate increase of system size. Since all violations are fixed locally, the impact on system transfer function outside the passivity violating frequency range is minimized. Thus, the convergence issue is avoided and the accuracy degradation due to passivity enforcement can also be minimized. The proposed method is very efficient, as optimization procedures are not required. Experimental results demonstrate its performance. [ABSTRACT FROM AUTHOR]

Abstract: A passive system with positive definite storage function is not only stable but is intrinsically robustly stable with respect to a wide class of feedback disturbances. For linear time invariant systems, passivity can be characterized either in time domain or in frequency domain from positive realness. This paper aims to generalize this concept to continuous-time switched linear systems. Analysis is performed by taking into account state dependent and arbitrary time dependent switching functions with a prescribed dwell time. A control design problem related to the determination of a switching strategy, based upon output measurements, that renders a switched linear system passive is also considered. The methods introduced in the paper can be effectively applied to the control of the duty cycle and passivation of switched circuits. [Copyright &y& Elsevier]

This paper presents a high-performance and simple guidance method for a short-range missile. Missile control systems are designed along the estimated flight envelope of the missile based on coefficient diagram method. The linear time invariant (LTI) models are obtained by linearizing missile nonlinear model at specific operating points. The governing equations of motion are accurately modeled by taking into account the effect of the mass rate and the center of gravity shift. A novel algebraic approach called coefficient diagram method (CDM) is used to design normal acceleration and roll angle control systems. The proportional navigation law is considered as the guidance law. One case of engagement scenarios is studied and the missile performance is evaluated. The robustness of the proposed controller is tested against parameter uncertainties and wind disturbance. [ABSTRACT FROM AUTHOR]

Analyses of range and precision are important for high-level synthesis and verification of fixed-point circuits. Conventional range and precision analysis methods mostly focus on combinational arithmetic circuits and suffer from major inefficiencies when dealing with sequential linear-time-invariant circuits. Such problems mainly include inability to analyze precision when quantization of constant coefficients is taken into account, and lacking efficient word-length optimization algorithms to handle both variables and constants, while satisfying the error metrics. The algorithms presented in this paper solve these problems. Experiments illustrate the efficiency and robustness of our algorithms. [ABSTRACT FROM AUTHOR]

Abstract: It has already been recognized that looking for a positive definite Lyapunov function such that a high-order linear differential inequality with respect to the Lyapunov function holds along the trajectories of a nonlinear system can be utilized to assess asymptotic stability when the standard Lyapunov approach examining only the first derivative fails. In this context, the main purpose of this paper is, on one hand, to theoretically unveil deeper connections among existing stability conditions especially for linear time-invariant (LTI) systems, and from the other hand to examine the effect of the higher-order time-derivatives approach on the stability results for uncertain polytopic LTI systems in terms of conservativeness. To this end, new linear matrix inequality (LMI) stability conditions are derived by generalizing the concept mentioned above, and through the development, relations among some existing stability conditions are revealed. Examples illustrate the improvement over the quadratic approach. [Copyright &y& Elsevier]

Abstract: In this paper, a robust water level control system for the horizontal steam generator (SG) using the quantitative feedback theory (QFT) method is presented. To design a robust QFT controller for the nonlinear uncertain SG, control oriented linear models are identified. Then, the nonlinear system is modeled as an uncertain linear time invariant (LTI) system. The robust designed controller is applied to the nonlinear plant model. This nonlinear model is based on a locally linear neuro-fuzzy (LLNF) model. This model is trained using the locally linear model tree (LOLIMOT) algorithm. Finally, simulation results are employed to show the effectiveness of the designed QFT level controller. It is shown that it will ensure the entire designer’s water level closed loop specifications. [Copyright &y& Elsevier]