Keywords: Linear and nonlinear systems
Abstract: We discuss stabilisability issues for discrete-time linear switched systems, assuming that one can use the switching law as a control function either in feedback form or as an open loop control. Stabilisability properties may be characterised through suitable indices such as the joint spectral subradius and the stabilisability radius. The paper focuses on the numerical computation of these quantities, especially for what concerns lower bounds, and investigates conditions under which they are different. Our analysis shed light on some counterintuitive phenomena related to stabilisation of discrete-time linear switched systems. In particular, one can construct examples of systems which are (exponentially) stabilisable for every initial condition, yet no periodic stabilising switching law exists, except for a set of initial conditions of measure zero.

Keywords: Mathematical systems theory, Linear and nonlinear systems
Abstract: We present some results on the uniform exponential stability of singularly perturbed linear systems undergoing switching. In absence of dwell-time constraints, the switching parameter can evolve on the same time scale as the fast variables, or even faster. We investigate the effect of switching laws evolving at a time scale comparable with the fast variables, describing the corresponding asymptotic effect on the slow variable. Based on this analysis, we propose stability criteria for the overall system, uniform for small values of the parameter of singular perturbation.

Keywords: Mathematical systems theory, Modeling of complex systems, Linear and nonlinear systems
Abstract: In this paper, in the framework of stability analysis of switched systems, we review and analyze multiple Lyapunov functions structures. We formalize and study a class of Lyapunov functions that do not only depend on the state, but also on the past switching sequence, the ``memory'', in a general language-theory setting. We recall and extend an equivalence result between these stability criteria and a class of combinatorial Lyapunov techniques, also known as path-complete Lyapunov functions. We provide the dual results based on the knowledge/prediction of the future values of the switching signals and we illustrate our techniques via numerical examples.

Keywords: Time-delay systems, Mathematical systems theory
Abstract: In this paper we deal with a class of time-varying delay systems. We show that the existence of a non-coercive Lyapunov–Krasovskii functional is necessary and sufficient for local exponential stability. This result extends what is recently given in [3] for globally Lipschitz systems to a class of locally Lipschitz systems. A switched system approach is used to elaborate this result.

Keywords: Linear and nonlinear systems, Mathematical systems theory
Abstract: The work is concerned with dead-beat stability of autonomous discrete-time switched linear systems, having in mind a potential application to cryptography. As far as control theory is concerned, we propose an algorithm to construct a switched system whose shorter dead-beat stabilizing sequence has a prescribed length. We discuss the pecularities when the dynamical systems under consideration are defined over finite fields. Then, it is shown how the algorithm can be used to addressed the design of self-synchronizing stream ciphers involving switched automata.

Keywords: Estimations and identification, Mathematical systems theory
Abstract: WImplicit discretization has many advantages over explicit discretization, especially for differential inclusion. Concerning sliding modes, the implicit discretization allows to reduce high frequency oscillations and ensures a larger stability domain. Nevertheless, it is not directly applicable to homogeneous differential equations and more particularly to homogeneous differentiators. This is why semi-implicit discretization methods have been developed in the literature. In this paper, we propose a semi-implicit discretization method with corrective terms for a homogeneous differentiator of order 4.

Keywords: Fractional order systems, Estimations and identification, Power systems
Abstract: Identification in time domain represents an accurate alternative technique for the Electrochemical Impedance Spectroscopy (EIS) measurements that requires long measurement time to characterize low frequency behavior. This paper focuses on the parameter identification of a Li-ion cell fractional model using measurements in time domain. The fractional model is based on an Equivalent Circuit Model (ECM) and is derived from the simplified Randles model. The parameters of the impedance fractional model are identified using Levenberg-Marquardt optimization algorithm. Results are validated in time domain using simulation data and experimental data obtained from chronopotentiometry experiments performed on a 3.4 Ah Li-ion cell. Experiments are carried out at different States Of Charge (SOC) and show the interest and the relevance of the employed methodology.

Keywords: Fractional order systems, Linear and nonlinear systems, Modeling and simulation
Abstract: In this paper, we generalize the infinite state representation to the modeling of fractional order nonlinear differential systems. This technique is based on the infinite dimension modal model of the fractional integrator whose internal frequency distributed state defines the nonlinear fractional differential systems (FDS) state. Thanks to numerical simulations, we demonstrate that system dynamical behaviors are dependant on infinite dimension distributed initial conditions. Moreover, we show that these initial conditions have a direct consequence on system stability.

Keywords: Estimations and identification, Fractional order systems, Time-delay systems
Abstract: This paper studies the non-asymptotic and robust pseudo-state estimation problem for a linear fractional-order time-delay system with multiple proportional delays. To handle the multiple proportional delays, the delay operator is introduced. The considered system is transformed into the fractional-order observer normal form via a bicausal generalized change of coordinates. On this basis, the modulating functions method is applied to derive exact algebraic integral formulas, where novel fractional-order modulating functions are utilized. Then, the original issue can be tackled by the inverse change of coordinates. Finally, a numerical simulation is provided to demonstrate the efficiency and the robustness against noises of the proposed estimator.

Keywords: Fractional order systems, Control applications
Abstract: Within this work we apply the concept of partial fractional-order pole-zero cancelation to the experimental setup of an inverted pendulum on a cart. We design a state feedback and extend it with a fractional-order compensator. The introduced algebraic convergence of the fractional-order terms is reduced by increased controller gains. Finally the adopted controller shows an improved input disturbance sensitivity and reduces the peaks in the control signal maintaining the designed closed-loop bandwidth. The controller is evaluated in simulation and experiment, showing its effectiveness compared to the simple state-feedback.

Keywords: Fractional order systems, Estimations and identification
Abstract: This paper investigates a new way of estimating the state of a class of fractional-order linear systems. Based on the generalized modulating functions method, the proposed estimator is non-asymptotic and robust against noises. First, the system is transformed into the observable normal form before being converted into the input-output differential equation, on which the generalized modulating functions method is applied. Then, the state variables are obtained by calculating a group of initial values and output integrals, which are all provided by algebraic integral formulas. Finally, to illustrate the performance of the proposed method, a numerical simulation example is provided.

Keywords: Fractional order systems, Estimations and identification, Linear and nonlinear systems
Abstract: In this paper, novel output-based algebraic integral formulas are provided to estimate disturbances for a class of fractional order linear systems. First, the disturbed fractional order linear systems are formulated into a pseudo-state space representation with exogenous disturbances. Second, in order to estimate the disturbances with fast convergence and good robustness to noises, the output-based algebraic integral formulas of the exogenous system's initial value are derived by using the modulating functions. Finally, numerical simulation results are presented to illustrate the efficiency and robustness of the proposed algebraic disturbance estimation method.

Keywords: Time-delay systems
Abstract: We present a method for estimating the transport speed of a class of systems modeled by a 1-D hyperbolic Partial Differential Equation (PDE) where the quantity governed by the PDE is a speed deficit and the measurement fed to the estimator is the transport speed minus this deficit at a given location. Such problem arises when estimating the free flow wind speed using measurements taken inside the wake zone of a wind turbine. We present a simple and easy to implement method and provide sufficient conditions for its convergence.

Keywords: Estimations and identification, Modeling of complex systems, Renewable Energy
Abstract: The modeling of the dynamic behavior of Proton Exchange Membrane (PEM) electrolyzers is a crucial issue to consider when connecting them with renewable energy sources. Indeed, this behavior is strongly dependent on the operating conditions provided by these sources. For this reason, it is important to determine a lot of dynamic models associated with different operating conditions. After a discussion on the modeling issue of the dynamic behavior, an experimental test bench is presented. The methodology is based on polynomial models by using pseudorandom binary sequences as inputs of the PEM electrolyzer in the test bench. A discussion on the obtained models is done to bring out control and aging of PEM electrolyzer perspectives.

Keywords: Modeling and simulation, Modeling of complex systems, Mathematical systems theory

Keywords: Renewable Energy, Modeling and simulation, Control applications
Abstract: The need for predictive maintenance of wind turbines has increased. Prognostics and Health Management research is working on estimating the Remaining Useful Life with greater accuracy and to determine future operating conditions, taking into account system constraints on safety and reliability when power generation capacity is also an issue. Torsional phenomena contribute to wind turbine life degradation, and the rate of degradation depends on wind profiles. To meet health management requirements, deterioration-aware control plays a role in adjusting control responses to mitigate the resulting stress depending on known wind parameters that characterize different wind speed conditions. Therefore, a degradation analysis is proposed to analyze the degradation results for different Ornstein-Uhlenbeck parameters that express the wind speed and can be estimated with a standard Kalman Filter.

Keywords: Optimization, Fault detection and Diagnostics, Manufacturing systems
Abstract: Constant-stress Accelerated Degradation Testing (ADT) has become a common method to get degradation data of components/systems. The ADT design aims to build an optimal ADT plan under specific constraints, e.g., limited test resources. Bayesian optimal design is a method of decision theory under uncertainty, which uses historical data and expert information to find the optimal test plan. In this paper, we develop a Bayesian-based approach for optimizing ADT plan of a LED component considering the self-heating phenomenon. In that way, D-optimal is used as a main criterion to find the optimal ADT plan under limited resources. Experimental data from LED components demonstrate the proposed method. The obtained results highlight the robustness and performance of the proposed approach.

Keywords: Modeling and simulation, Renewable Energy
Abstract: Anion exchange membrane (AEM) electrolysis is the process for hydrogen generation using electricity. In this article, a 1D steady state model was introduced and elaborated to determine the performance of the AEM Electrolyser. In particular, the role of addition of Potassium Hydroxide (KOH) and its overall impact on the Multiphysics phenomenon inside the membrane electrode assembly was investigated. The simulation and experiments showed a significant reduction of the ion exchange / transport, ionic resistance as well as an improvement of the reaction kinetics at the electrodes upon addition of KOH to the pure water feedstock. The modelling efforts also resulted in a better understanding of the several Multiphysics phenomena that account for the kinetics and mass-transfer losses in the electrolyser. In particular, we also assess the fluid, geometric and flow parameters for the AEM electrolyser and the extent of their impact on the device performance.

Keywords: Optimization, Power systems, Modeling and simulation
Abstract: The problem of determination the maximum rotational speed of a gas turbine after a load rejection event (Gas Turbine Overspeed Analysis) using a complex simulation model is a major task in the engineering of gas turbines for power plants. In this paper two algorithms for optimization of expensive black-box functions are applied to the problem instead of the time-consuming commonly used simulation approach.

Conventional optimization methods that are using the functions gradients are not applicable to this simulation study as they use information about the gradients of the objective function that are not available for this model. Both algorithm use radial basis functions to approximate the objective function for optimization. The algorithms are compared and it is shown that both are able to provide sufficient solutions for the problem mentioned using a little number of simulations or, in other words, in shorter time.

Keywords: Power systems, Renewable Energy, Modeling and simulation
Abstract: The integration of wind source in the electrical network is very important for these technical and economic advantages and to protect the environment. In this work, a study is applied for the integration of a wind farm which contains an asynchronous machine of the squirrel cage induction generator (SCIG) type in an electrical network and seeks the best location. This study is made on the standard electrical network IEEE-14 bus under MATLAB environment.

Keywords: Power systems, Robust control and Hinfty control, Process control and instrumentation
Abstract: An effective Maximum Power Point Tracking (MPPT) technique, that can be used in a variety of environmental conditions, is tackled with in this note. To this aim, an MPPT control based on a T–S fuzzy model is applied improving thus the performance and the efficiency of a solar photovoltaic (PV) generator. The nonlinear system’s dynamics are embedded in a T–S fuzzy model. Sufficient criteria for designing such fuzzy control policy are presented in terms of linear matrix inequalities based on a quadratic Lyapunov function combined with some helpful slack variables (i.e. dilated quadratic LMI conditions). The proposed method reduces tracking time while overcoming the oscillation that usually appear near the maximum powerpoint. Besides, the simulation of a photovoltaic system using the proposed control policy demonstrates the efficiency of the approach even in the case of climate changes.

Keywords: Power systems
Abstract: The amount of data to be treated in data centers is increasing more and more, which makes an obligation to optimize the use of servers in a way that reduces energy consumption and then minimizes the cost. The study of correlation between server resources and energy consumption is a crucial step and involves well-founded strategies to optimize both the use of resources servers and their energy consumption. There are various tools to measure energy consumption of servers. In our work we apply different workloads on servers and then we measure energy consumption using two methods. Internal sensors (performance counters) which allow extracting resources usage information by using listeners on the sensors or external tools, and energy meters and software to acquire data. Error rate of both methods varies according to the integrated sensors in the machine and the type and accuracy of the power meter used. We study the correlation between the power of CPU server and its utilization as well as the correlation between energy consumption of server and its utilization in term of CPU, Memory, and hard drive.

Keywords: Power systems
Abstract: The power quality indicators play a significant role in the characterization of the technical-economic performances of the electric distribution networks (EDNs), influencing the energy efficiency of the activities carried out at the end-user level. From the point of view of a decision-making process, it is difficult for the Distribution Network Operators (DNOs) to identify a global indicator that allows the evaluation of the power quality due to the various factors that should be considered. In this context, a two-stage methodology based on the K-means clustering algorithm has been proposed in the paper to identify and characterize the power quality based on slow voltage variations and unplanned interruptions. The advantages related to the quick processing of large data amounts uploaded from databases with records of the current and voltage measurements (CVMs) and the extraction of the main features allowed the identification of the various patterns of the power quality in the case of a rural distribution area with 232 electric distribution substations (EDSs) belonging to a Romanian DNO.

Keywords: Modeling of complex systems, Renewable Energy, Estimations and identification
Abstract: Water quality and availability worldwide are greatly affected by climate changes due to global warming. For instance, recently, the water levels in numerous European rivers decreased compared to their levels in centuries. Treated and desalinated water represents a promising strategic option to mitigate water scarcity. The global cost of wastewater treatment plants (WWTPs) depends significantly on their energy consumption. A precise prediction of energy consumption of WWTPs can comprehend and predict the plant behavior to support process design and monitoring and enhance optimization of overall performances. This paper presents a practical machine-learning approach to predict WWTP energy consumption through Light Gradient Boosting Machine (LightGBM) approach. Data from a full-scale WWTP at Melbourne eastern over five years is employed in this study. Results indicate that the LightGBM is more accurate than the other fourteen machine commonly used machine-learning models. In addition, results revealed that including lagged measurements in constructing the investigated models improves the prediction accuracy. This study shows that the dynamic, optimized LightGBM model outperformed all models with reasonable root-mean-square error and mean absolute error of 37.38 and 28.63, respectively.

Keywords: Fractional order systems, Estimations and identification, Robust control and Hinfty control
Abstract: The main idea of this work is to design a robust observer for disturbed Fractional-Order Systems with Time-Varying-Delay (D-FOSTVD). Firstly, existence conditions of such observer are given. Then, a new sufficient condition is obtained based on the indirect Lyapunov approach. These conditions are presented as a set of Linear Matrix Inequalities (LMIs) constraint, which guarantees the rejection of the disturbances effect on the estimation error, and its stability. By solving the given LMIs, the gains matrices of the observer can be deduced. To illustrate the effectiveness of the proposed approach, a numerical example is given.

Keywords: Fractional order systems, Control applications, Robust control and Hinfty control
Abstract: In this paper, switched 2D fractional order positive systems described by the Roesser model are introduced. The state space representation of each subsystem is given using the fractional difference definition. Necessary and sufficient conditions for the asymptotic stability are established via the methods of common Lyapunov function for any switching. Finally, numerical examples are employed to validate the proposed theoretical results.

Keywords: Estimations and identification, Power systems
Abstract: Owing to the inconsistent decay among cells during their applications, the battery uniformity is low, which seriously restricts the economy and efficiency of the cascade utilization of large-scale retired lithium batteries.Moreover, due to the complex chemical reaction inside the battery, the degradation process cannot be accurately described. It is particularly critical to select appropriate health indicators (HI) for screening and evaluating the value of the battery for echelon utilization. Given the above problems, this paper uses the measurement of a battery tester to extract suitable HI subsets from the charging curve, IC curve, and other curves, and uses the Pearson correlation coefficient to analyze the correlations for subsets of HI. The effective HIs for screening the secondary use of the battery are suggested. Experimental results prove the good correlation characteristics of the recommended HI with battery capacity, which can be further used to improve the accuracy and efficiency of battery screening.

Keywords: Renewable Energy, Optimal control, Fuzzy and neural systems
Abstract: Modeling difficulty, time-varying model, and uncertain external inputs are the main challenges for energy management of fuel cell hybrid electric vehicles. In the paper, a fuzzy reinforcement learning-based energy management strategy for fuel cell hybrid electric vehicles is proposed to reduce fuel consumption, maintain the batteries' long-term operation, and extend the lifetime of the fuel cells system. Fuzzy Q-learning is a model-free reinforcement learning that can learn itself by interacting with the environment, so there is no need for modeling the fuel cells system. In addition, frequent startup of the fuel cells will reduce the remaining useful life of the fuel cells system. The proposed method suppresses frequent fuel cells startup by considering the penalty for the times of fuel cell startups in the reward of reinforcement learning. Moreover, applying fuzzy logic to approximate the value function in Q-Learning can solve continuous state and action space problems. Finally, a python-based training and testing platform verify the effectiveness and self-learning improvement of the proposed method under conditions of initial state change, model change and driving condition change.

Keywords: Modeling and simulation, Modeling of complex systems, Renewable Energy
Abstract: State of health (SOH) estimation is one of the essential functions of an electric vehicle battery management system. An accurate estimation result is conducive to extending the life of lithium-ion batteries and ensuring vehicles’ safe and reliable operation. Based on data-driven SOH estimation of the lithium-ion battery, a cross-entropy feature selection method is proposed in this work. Firstly, 51 features are extracted based on the partial charging voltage and incremental capacity curves, and each feature is evaluated by the Pearson correlation coefficient, the Kendall correlation coefficient, and cross-entropy, respectively. Then, features with an absolute value greater than 0.9 are picked out. Finally, selected feature sets are compared via the back propagation neural network, Gaussian process regression, and random forest. Experimental results show that the feature selection method based on cross-entropy achieves better SOH estimation accuracy.

Keywords: Fault detection and Diagnostics
Abstract: Cost and durability are crucial factors limiting the widespread commercialization of proton exchange membrane fuel cells (PEMFC). Prognostics, aiming at health indicator extraction and remaining useful life prediction, is a key issue for PEMFC durability enhancement. However, deploying prognostics for PEMFC under dynamic load still faces challenges in extracting health indicators reliably and predicting the degradation evolution efficiently. This work proposes a data-driven PEMFC prognostics approach, in which Hilbert-Huang transform is used to extract health indicator in dynamic operating conditions and symbolic-based gated recurrent unit model is used to predict the remaining useful life. The proposed method is tested using long-term dynamic load ageing experiments. The results show that the method can provide reliable prognostics horizons and improve real-time performance.

Keywords: Fault detection and Diagnostics, Control applications, Signal processing
Abstract: This paper deals with the design of an active fault-tolerant control for a twin wind turbine consisting of two wind turbines mounted on the same tower. When one turbine is influenced by electrical faults, precisely a stator inter-turn short circuits fault or a demagnetization fault, the sparse recovery diagnosis method is used for the detection, isolation and estimation of the active fault. An active fault-tolerant control law is designed for the supervision of the faulty machine. Both methods, concerning diagnosis and control, are based on homogeneous theory and consequently converge in finite time. Simulation results highlighting the relevance of the proposed approach are also presented.

Keywords: Estimations and identification, Control applications, Motion control
Abstract: Peaking phenomenon (pp) which usually takes place at transient regime, presents a serious hindrance that should be handled when output feedback controller is designed. To cope with the pp issue for uniformly observable class of multi-output nonlinear systems, we propose in this paper a slight modification on the correction term of the standard high gain observer (SHGO) by the incorporation of nested saturation functions. The design of peaking free observer is thus carried out in the case of sampled multi-outputs leading to a "continuous-discrete non-peaking HGO" (CD-NPHGO). Of fundamental interest, it is shown that the proposed scheme ensures a cancelation of large peaking at starting operation while preserving SHGO benefits in terms of arbitrarily fast convergence at the steady state. An application to the speed-sensorless control of induction motors (IM) highlight the features of the proposed approach in the ability to handle large ripples at transient as well as achieving accurate state estimation in very short time.

Keywords: Estimations and identification, Linear and nonlinear systems, Time-delay systems
Abstract: This note is devoted to the redesign of a high-gain observer that has been conceived for a class uniformly observable nonlinear systems where the output measurements are assumed to be available continuously in time. The ultimate motivation of this redesign consists in providing an observer structure to properly tackle the problem of sampled output measurements while accounting for an eventual output measurement time delay in the case of continuous-time output measurements as well as in in the case of sampled output measurements. This leads to a unified high-gain observer with a versatile structure that accounts for the different scenarios related to the output measurements availability. A particular emphasis is put on the observer structure bearing in mind the main motivation of the involved observer redesign. Of a primary importance, it is shown that the proposed observer inherits the same properties as its underlying observer using an adequate technical lemma.

Keywords: Estimations and identification, Modeling of complex systems, Control algorithms implementation
Abstract: In this paper, we have proposed a practical condition for constructing a high gain observer using higher dimensional immersion. The state estimation of the initial system does not require the knowledge of the nonlinearity of the normal form, nor the expression of the inverse of the immersion. We have also given some examples to illustrate our theoretical approach.

Keywords: Robotics, Signal processing, Modeling and simulation
Abstract: Bin picking is one of the core tasks in robotics. In terms of automating industrial processes, bin-picking shows to be a fundamental step. Although highly researched, it is still a challenging task as it combines 3D object recognition and pose estimation, handling and path planning. This paper focuses on recognition and pose estimation. Here a concept for picking Lego blocks laying randomly in a bin using CAD models of objects to be handles and 3D point cloud is presented. The approach relies on aligning the point cloud captured by a Cognex camera with the CAD models, then uses a best-fit method to determine the gripping position and orientation of the object. The concept has been validated in an experimental setup and compared to a state-of-the-art tool. Results demonstrate the efficiency and robustness of the proposed approach.

Keywords: Mathematical systems theory, Linear and nonlinear systems, Control applications
Abstract: In this paper, by employing the time scales theory, we establish the necessary and sufficient conditions for the controllability and observability of piecewise impulsive dynamic systems on arbitrary time domains. We constructed a piecewise control function which controls the system not only at the final time of the intervals but also at every impulse point, i.e., we investigate the so-called total controllability results. In this study, we mainly use the Gramian type matrices, variation of parameter formula, and time scales theory. We give some simulated results for different time domains to validate the theoretical results. Furthermore, we provide an application of these results to the population dynamics. The obtained results are non-trivial and new, extending and generalising the existing ones.

Keywords: Estimations and identification, Modeling and simulation
Abstract: Time-scale theory, due to its ability to unify the continuous and discrete cases, allows handling intractable nonuniform measurements, such as intermittent received signals. In this work, we address the state estimation problem of a vibration-induced intermittent optical wireless communication (OWC) system by designing a Kalman filter on time scales. First, the algorithm of the time-scale Kalman filter is introduced and a numerical example is given for illustration. Then the studied intermittent OWC system is presented, and experimental data are collected to determine the time scale’s form, which has bounded graininess (a.k.a, bounded time jumps). Finally, we design a Kalman filter on the previously defined time scale for the intermittent OWC system and critically analyzed its estimation performance. Moreover, the obtained conclusions are further validated on a reference system. The simulation results corroborate that the time-scale Kalman filtering technique is considerably promising to solve the state estimation problem with non-uniform measurements. This study reveals for the first time the feasibility of applying the time-scale Kalman filter theory to practical applications.

Keywords: Robust control and Hinfty control, Control applications, Modeling and simulation
Abstract: A two-axis gimbaled seeker in missile identifies targets and commands the gimbal to maintain the selected target in the field-of-view. It has to stabilize the gimbal axis in the inertial plane against external disturbances induced by maneuvering and aerodynamic force of the missile using the stabilization control loop of the track control loop. It has been widely known that the precise target tracking is highly affected by missile motion decoupling capability of the stabilization control loop. This paper presents the two robust control design methods including parameter uncertainties on the stability and performance of the closed-loop system with application to the stabilization control loop of the two-axis gimbaled seeker. The performance analysis shows that the proposed control design methods are very effective for achieving superior stabilization control performances for the two-axis gimbaled seeker.

Keywords: Robust control and Hinfty control, Control applications, Robotics
Abstract: This manuscript proposes a first-order sliding mode controller for tracking tasks applied to second-order nonlinear systems subjected to asymmetric state restrictions. The stability proof employs an asymmetric Barrier Lyapunov function to ensure the fulfillment of the state restrictions and the finite-time convergence of the trajectories towards the siding surface despite the presence of matched uncertainties and unmodeled dynamics. Consequently, the tracking error has an asymptotically stable equilibrium point. Numerical simulations compare this proposal against classical control techniques.

Keywords: Robust control and Hinfty control, Estimations and identification, Linear and nonlinear systems
Abstract: The observer-controller design study for linear continuous-time systems with norm-bounded uncertainties is tackled using a finite frequency method. More precisely, the study uses the Generalized Lemma of Kalman Yakobovich Popov (GKYP) to develop conditions over finite frequency ranges, formulated into Linear Matrix Inequalities (LMIs), to design a controller in one step method. The provided conditions reduce the conservatism factor by optimizing the uncertainties performance. At the end of the paper, a comparative study is given through an example of illustration to highlight the effectiveness of the suggested approach.