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International audience; A decentralized adaptive fuzzy sampled-data control problem for switched large-scale nonlinear systems with time-varying delays is considered in this paper. Fuzzy logic systems are applied to handle unknown nonlinear terms. A novel fuzzy adaptive law is proposed utilizing only the information of the system states at sampling instants. Moreover, a proper common Lyapunov function and a new decentralized adaptive sampled-data control law are constructed to ensure that all states of the closed-loop system are bounded. The developed strategy's effectiveness is verified with two examples.

An overview is given of the locally positive stabilization problem for positive infinite-dimensional linear systems with a bounded control operator. The impossibility of solving this problem by using a nonnegative input is established. Two methods for solving the problem by means of state feedback, namely spectral decomposition and control invariance, are described. The results are illustrated by means of a perturbed diffusion equation with Dirichlet boundary conditions and a diffusion equation with Neumann boundary conditions and pointwise control.

The problem of making the output of a linear system with polytopic uncertainties and discontinuities in the state evolution totally insensitive to an unknown disturbance input by state feedback is investigated. Suitable geometric notions are introduced and used to provide a structural, constructive solvability condition. The requirement of achieving global robust asymptotic stability of the compensated dynamics is then added and further solvability conditions are provided by requiring that the time instants at which discontinuities in the state evolution, or jumps, occur are sufficiently far from each other.

International audience; A model predictive control algorithm based on offline optimization of prediction dynamics enables an efficient online computation. However, the price for this efficiency is a reduction in the degree of optimality. This paper presents a new method for overcoming this weakness, yielding a significant improvement in the degree of optimality, and achieving this with no increase in online computational load. Two numerical examples with comparison to earlier solutions from the literature illustrate the effectiveness of the proposed algorithm.

International audience; This paper presents a robust hybrid fault-tolerant optimal predictive control (HFTPC), for an industrial robot arm under hybrid (electric and pneumatic) actuator faults and/or varying time-delays. Based on the error dynamics, estimated states, and a predictive controller, a new state feedback control law is proposed and implemented for the reformulation of the optimal control problem of a nonlinear faulty hybrid actuator system based on predictive control via linear matrix inequalities (LMIs). First, a robust MPC scheme is performed in which the future control sequence is used to compensate the varying time-delays. Then, a robust stable hybrid fault tolerant predivtive control is implemented to handle actuators faults to effect robust trajectory tracking. In fact, the stability of hybrid systems based on the proposed control scheme is a very sensitive criterion. Therefore, stability conditions are required for controlling the industrial arm under faulty hybrid (electric and pneumatic) actuator, based on the Lyapunov-Krasovskii (L-K) theory, less conservative stable conditions in terms of LMIs are given and used to ensure the asymptotically robust stability of closed-loop constrained system that dependent delay-range. To highlight the robustness and effectiveness of the proposed approach, a simulation study of an industrial robot arm example is proved, where the results showed the prompt and the accuracy of the proposed scheme.

International audience; In this paper, a large class of time-varying Riccati equations arising in stochastic dynamic games is considered. The problem of the existence and uniqueness of some globally defined solution, namely the bounded and stabilizing solution, is investigated. As an application of the obtained existence results, we address in a second step the problem of infinite-horizon zero-sum two players linear quadratic (LQ) dynamic game for a stochastic discrete-time dynamical system subject to both random switching of its coefficients and multiplicative noise. We show that in the solution of such an optimal control problem, a crucial role is played by the unique bounded and stabilizing solution of the considered class of generalized Riccati equations.

espanolUna plataforma bola-placa es un ejemplo comun de sistema dinamico utilizado para aplicar los conceptos de modelado y control estudiados en algunos cursos de ingenieria. En este tipo de sistemas, un cuerpo esferico se coloca sobre una placa movil con dos grados de libertad. El sistema es accionado por dos servomotores que provocan el desplazamiento de la esfera en los ejes x e y en el plano de la plataforma. Se sabe que dicho sistema es altamente inestable y no lineal. Inicialmente, a partir de un analisis fenomenologico se obtuvo una representacion del sistema en el espacio de estado. A continuacion, un controlador de realimentacion de estado basado en el metodo de asignacion de polos fue disenado para mantener una posicion deseada de la esfera sobre el plano. Una tecnica de vision por computador fue usada para medir la posicion bidimensional de la esfera sobre el plano en tiempo real. El modelado de la planta en estudio y el diseno del controlador para el posicionamiento de la esfera se validaron experimentalmente considerando diferentes puntos de ajuste. Los resultados obtenidos mostraron que el controlador disenado es estable y responde satisfactoriamente a las perturbaciones de posicion de la esfera alrededor del punto de referencia. EnglishA ball-and-plate platform is a common example of the dynamical system used to apply modeling and control concepts studied in some engineering courses. In this kind of systems, a spherical body is positioned on a mobile plate with two degrees of freedom. The system is operated by two servo motors that cause displacement of the sphere in the x and y axis in the plane of the platform. It is known that such a system is highly unstable and non-linear. Initially, from a phenomenological analysis we obtained a state-space representation of the system. Then, a state feedback controller using the pole assignment method was designed to maintain a desired position of the sphere over the plane. A computer vision technique allowed us measuring the two-dimensional position of the sphere over the plane in real time. Model of the plant under study and controller design for sphere positioning were experimentally validated considering different set-points. Obtained results let us know that our plant-controller is stable and responds satisfactorily to position disturbances around a reference point.

This paper examines the problem of planning and stabilizing the trajectory of one smooth body rolling on the surface of another. The two control inputs are the angular velocity of the moving body about two orthogonal axes in the contact tangent plane; spinning about the contact normal is not allowed. To achieve robustness and computational efficiency, our approach to trajectory planning is based on solving a series of optimization problems of increasing complexity. To stabilize the trajectory in the face of perturbations, we use a linear quadratic regulator. We apply the approach to examples of a sphere rolling on a sphere and an ellipsoid rolling on an ellipsoid. Finally, we explore the robustness and performance of the motion planner. Although the planner is based on non-convex optimization, in practice the planner finds solutions to nearly all randomly-generated tasks, and the solution trajectories are smoother and shorter than those found in previous work in the literature.

The aim of this paper is to report analytical and individual-based methods forantibiotic dose selection, that are based on tools from system and control theory. A brief system analysis of standard population pharmacokinetic models proves that such models are nonnegative and stable. Then, an input-output analysis leads to an open-loop control law which yields a dosing for the "average" patient, based on the equilibrium trajectory of the system. This approach is then incorporated into a "worst-case" analysis based on the monotony of the statetrajectories with respect to the clearance (model parameter). Finally, an heuristic method of an estimated state feedback is presented. Thanks to numerical simulations, these methods were successively illustrated on a model describing the pharmacokinetic of meropenem, an intravenous antibiotic for treatment of severe sepsis., The aim of this paper is to report analytical and individual-based methods for antibiotic dose selection, that are based on tools from system and control theory. A brief system analysis of standard population pharmacokinetic models proves that such models are nonnegative and stable. Then, an input-output analysis leads to an open-loop control law which yields a dosing for the "average" patient, based on the equilibrium trajectory of the system. This approach is then incorporated into a "worst-case" analysis based on the monotony of the state trajectories with respect to the clearance (model parameter). Finally, an heuristic method of an estimated state feedback is presented. Thanks to numerical simulations, these methods were successively illustrated on a model describing the pharmacokinetic of meropenem, an intravenous antibiotic for treatment of severe sepsis.

This paper considers the synthesis of stabilizing controllers for nonlinear control-affine systems under multiple state constraints. A new control Lyapunov-barrier function approach is introduced for solving the considered problem. Assuming a classical control Lyapunov function, two possible methods for constructing new control Lyapunov-barrier functions are discussed. Sufficient conditions for the existence of new control Lyapunov-barrier functions are derived. With modifying the Sontag's formula, an explicit state-constrained stabilizing feedback law is presented. Finally, two numerical examples are provided to illustrate the obtained theoretical results.

Magnetic Levitation System or Maglev system is a modern and future technology that has many advantages and applications. Its characteristic is highly nonlinear, fast dynamics, and unstable, so it is challenging to make a suitable controller. The model of the Maglev system is in nonlinear state-space representation, and then feedback linearization is implemented to obtain the linear model system. Then, the integral state feedback control that tuned by the coefficient diagram method is implemented. The robustness of the controller is determined using the coefficient diagram method. The result of the standard coefficient diagram parameter will be compared with the robustness parameter. The open-loop test simulation showed that the maglev system has a nonlinear characteristic. Among all of the uncertainties, the uncertainty of resistance provides the highest nonlinearity, even by the small value of uncertainty. The examination of the mass, inductance, and resistance uncertainties showed that the robustness parameter is able to handle them and to provide a robust controller.

In this study, an extreme learning-based non-linear model predictive controller (NMPC) is proposed for path following planning of an autonomous underwater vehicle (AUV) using horizontal way-points. The proposed controller comprises a kinematic controller and a dynamic controller. The kinematic controller is designed by using back-stepping approach whilst the dynamic controller is designed by employing the NMPC approach. The dynamics of the AUV is identified in real-time by employing an extreme learning machine (ELM) structure. In view of achieving improved performance of the ELM structure, its hidden layer parameters are optimally determined by applying Jaya optimisation algorithm. The resulting ELM model is then used to design a NMPC considering the constraint on rudder planes. The tracking performance of the proposed controller is compared with that of two recently reported control algorithms namely, $H_\infty $ H ∞ state feedback controller and inverse optimal self-tuning proportional–integral–derivative (PID) controller. The proposed controller is implemented using MATLAB and then in real-time on a prototype AUV developed in the authors’ laboratory. From both the simulation and experimental results obtained, it is observed that the proposed controller exhibits superior tracking performance compared to both $H_\infty $ H ∞ state feedback controller and inverse optimal self-tuning PID controller.

In this paper, we are concerned with drive-response synchronization for a class of fuzzy cellular neural networks with time varying delays. Based on the exponential dichotomy of linear differential equations, the Banach fixed point theorem and the differential inequality technique, we obtain the existence of almost periodic solutions of this class of networks. Then, we design a state feedback and an impulsive controller, and construct a suitable Lyapunov function to study the problem of global exponential almost periodic synchronization for the drive-response systems considered. At the end of the paper, we provide an example to verify the effectiveness of the theoretical results.

The paper deals with development of active anti-sway feedback control method for gantry cranes. Inertial measurement unit is chosen as a load motion sensing device allowing to close a feedback loop. The paper provides guidelines for the successive steps of mathematical modelling, data-driven identification and model-based controller design. The proposed method is experimentally validated on an industrial overhead crane system.

This letter covers the model predictive control of linear discrete-time systems subject to stochastic additive disturbances and chance constraints on their state and control input. We propose a simplified control parameterization under the framework of affine disturbance feedback, and we show that our method is equivalent to parameterization over the family of state feedback policies. Using our method, associated finite-horizon optimization can be computed efficiently, with a slight increase in conservativeness compared with conventional affine disturbance feedback parameterization.

The problem explored in this article concerns the stability of the state feedback control of the upper-triangular stochastic nonlinear systems whose control coefficients are time-varying. First, the state feedback control of the corresponding nominal system is carried out by utilizing the backstepping technique combined with the appropriate Lyapunov function. Then, low-gain homogeneous domination technology and the efficient coordinate transformation method are adopted to realize the state feedback control of the original system and ensure the global asymptotic stability (GAS) in probability of the system. Finally, an example is given to illustrate the feasibility and correctness of the method.

A velocity-free state feedback fault-tolerant control approach is proposed for the rigid satellite attitude stabilization problem subject to velocity-free measurements and actuator and sensor faults. First, multiplicative faults and additive faults are considered in the actuator and the sensor. The faults and system states are extended into a new augmented vector. Then, an improved sliding mode observer based on the augmented vector is presented to estimate unknown system states and actuator and sensor faults simultaneously. Next, a velocity-free state feedback attitude controller is designed based on the information from the observer. The controller compensates for the effects of actuator and sensor faults and asymptotically stabilizes the attitude. Finally, simulation results demonstrate the effectiveness of the proposed scheme.

This paper proposes a robust control strategy for the uncertainties of permanent magnet synchronous generator-based wind energy conversion system, based on state feedback. Meanwhile, the detailed design and analysis process of this robust controller also have been presented. Compared with the conventional control, the new method with a better robustness can not only make the whole closed-loop system stable but also reduce the major harmonics and total harmonic distortion of currents and ripples of torque. And then, we set up a detailed 2 MW simulation test platform based on MATLAB/SIMULINK/SimPowerSysterms. The simulation results verify the effectiveness and correctness of the algorithm.

In this paper, we consider the problem of marking estimation in labeled Petri nets whose initial marking is known to belong to a given convex set, in the presence of silent transitions (i.e., transitions labeled with the empty word) and indistinguishable transitions (i.e., transitions sharing the same label with other transitions). First, we demonstrate that all sets of markings consistent with a given sequence of observations can be described in linear algebraic terms (as a union of convex sets); subsequently, this observation is used to construct (offline) a marking observer under appropriate boundedness assumptions. Using the marking observer we show how to derive, at design time, a state feedback control law under the assumption that all transitions sharing a label can be enabled or disabled simultaneously as a group; this way, the most burdensome part of the computations is performed offline. © 1963-2012 IEEE. 62 4 1813 1824

In networked control systems (NCSs), extensive data exchange between plants and controllers leads to an unnecessary usage of communication and computational resources. Aperiodic sample-and-hold methods such as event-triggered control (ETC) can reduce the number of transmissions, allowing more applications to operate within the same network. However, most existing event-triggering mechanisms enforce a Lyapunov function of the continuous-time closed-loop system to be (almost) always decreasing. We propose a relaxed triggering condition for periodic event-triggered control (PETC) based on bounding the Lyapunov function with an exponentially decaying reference function, which reduces the communications while guaranteeing the same decay rate as competing strategies. We provide sufficient global exponential and input-to-state stability conditions for linear time-invariant (LTI) systems under our event-based state feedback, giving explicit performance guarantees in the presence of additive disturbances. Finally, some simulation results illustrate the performance of the proposed control strategy.

The paper presents a method for designing a state feedback controller of an active suspension system of a quarter car model. This is a survey based on a specific example. The designed controller of the active suspension system improves the driving control, safety and stability, because during the ride, the periodic swinging motion generated by the road irregularities on wheels can be decreased. This periodic motion damages the driving comfort, and may cause traffic accidents. The state feedback controller is designed to stand road induced displacements. Computer simulations of the designed controller have been performed in the frame of Scilab and XCos.

During petroleum drilling, the drill-string electrical drive is prone to significant torsional vibrations caused by tool vs. rock stick-slip friction and drill-string torsional compliance, which may cause mechanical failure and excessive wear of critical parts of the drilling system. Hence, the drill-string electrical drive needs to be equipped with active vibration damping functionality. This paper presents the development of a full-order state controller based on straightforward estimation of un-measurable state variables by means of state variable filtering approach, which may be well-suited for torsional vibrations active damping purposes. The effectiveness of the proposed control system design is verified by means of simulations for different drill-string configurations.

[EN] This work focuses on the design and construction of an experimental test bench of three degrees of freedom with application in educational environments. It is constituted by a gyroscopic structure that allows the movements of a quadcopter to analyze the control systems. In this context, the main features of the mechanical and electronic design of this prototype are described. At the same time, the main characteristics with respect to existing platforms are highlighted in aspects such as: system autonomy, cost, safety level, operation ranges, experimental flexibility, among others. The possible controller design approaches for quadcopter stabilization can extend to many basic and advanced techniques. In this work, to show the operation and didactic use of the platform, the development of the controller for tilt angle stabilization under two different approaches are presented. The first approach is through PID control, oriented for undergraduate students with basic level in control theory. The second approach is by means of State Feedback, oriented to students with more advanced level in this field. The result of this work is an open test bench, enabled for the experimentation of control algorithms using Matlab-Simulink., This work was supported partially by the Ministerio de Ciencia, Innovacion y Universidades, Spain, under Grant RTI2018-096904-B-I00.

For linear, time-invariant, stabilizable multivariable systems, we examine the problem of the existence and computation of proper denominator assigning and internally stabilizing feedback compensators, which give rise to a closed-loop system, whose transfer function matrix is equal to one that can be obtained by the action of state variable feedback. We establish a sufficient condition for the solution of this problem for the class of systems with the same number of inputs and outputs and non-singular transfer function matrix with all its zeros located in the open left half of the complex plane.

A novel partitioning approach for linear switching large-scale systems is presented. We assume that the modes of the switching system are unknown a priori but can be detected. We propose an online partitioning scheme that can partition the system when the mode switches, thus adapting the partition to the mode. Moreover, after the system has been partitioned, we apply a decentralized state-feedback control scheme to stabilize the system. We also apply a dwell time stability scheme to prove that the closed-loop system remains stable even after both the mode and partition changes. The proposed approach is illustrated by means of an automatic generation control problem related to frequency deviation regulation in a large-scale power network., This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 675318 (INCITE). (Wicak Ananduta and Tomás Pippia are co-first authors.)

We consider the problem of stabilizing a class of systems formed by a set of decoupled subsystems (nodes) interconnected through a set of controllers (arcs). Controllers are network-decentralized, i.e., they use information exclusively from the nodes they interconnect. This condition requires a block-structured feedback matrix, having the same structure as the transpose of the overall input matrix of the system. If the subsystems do not have common unstable eigenvalues, we demonstrate that the problem is solvable. In the general case, we provide sufficient conditions for solvability. When subsystems are identical and each input agent controls a pair of subsystems with input matrices having opposite sign (flow networks), we prove that stabilization is possible if and only if the system is connected with the external environment. Our proofs are constructive and lead to structured linear matrix inequalities (LMIs).

Coupled inductors can be used to connect cells in parallel in a voltage source inverter to increase both rated power and bandwidth. To successfully implement this strategy it is critical to achieve a balanced contribution to the output current by all paralleled cells. Circulating currents should also be controlled and minimized to prevent additional losses in the switching devices. This paper presents an effective method to achieve current sharing between inverter cells paralleled via magnetically coupled inductors, using a state feedback controller. Experimental results are presented validating the performance of the proposed balancing method.

This work deals with the novel application of the sliding mode (discontinuous) output regulation theory to a nonlinear electrical circuit, the so-called boost power converter. This theory has excelled due to the fact that trajectory tracking plays a central role. The control of a boost power converter for the output tracking of a DC biased sinusoidal signal is a challenging problem for control engineers. The main difficulties are the computation of a proper reference signal for the inductor current, and the stabilization of the inductor current dynamics or to guarantee the correct output tracking of the capacitor voltage. With the application of the discontinuous output regulation these problems are solved in this work. Simulations and real time experiments were carried out with an unknown variation of the DC input voltage, where the good output tracking of the capacitor voltage was verified along with the stabilization of the inductor current. The discontinuous output regulation theory has proven to be a suitable tool in the output tracking for the boost power converter.

This paper presents the modelling and the control strategies based on the states feedback control of an Electrical Vehicle (EV). The Electromechanical behaviour of studied system is modelled by using the states representation deduced from the electrical and dynamical laws. Two kinds of methods are used to determine the values of control's parameters, first one is the states feedback regulator using pole placement, and the second one is the Linear Quadratic Regulator (LQR). The Pole-placement design allows determining the values of the controller's parameters by the displacement of the poles to specified locations according to the zeros of a desired polynomial, whereas the values of feedback vector gains are obtained by resolving the Ricatti equation in LQR method. Finally, the simulation of the proposed controller was carried out for the European, the American and the stander driving cycles as the EV speed references in order to validate its robustness and its dynamical performances.

In this paper, the control of the stationary response of a quarter car model to random road excitation with a Magnetorheological (MR) damper as a semi-active suspension device is considered. The MR damper is a hypothetical analytical damper whose parameters are determined optimally using a multi-objective optimization technique Non-dominated Sorting Genetic Algorithm II (NSGA II). The hysteretic behaviour of the MR damper is characterized using Bingham and modified Bouc-Wen models. The multi-objective optimization problem is solved by minimizing the difference between the root mean square (rms) sprung mass acceleration, suspension stroke and the road holding responses of the quarter car model with the MR damper and those of the active suspension system based on linear quadratic regulator (LQR) control with the constraint that the MR damper control force lies between �5 percent of the LQR control force. It is observed that the MR damper suspension systems with optimal parameters perform an order of magnitude better than the passive suspension and perform as well as active suspensions with limited state feedback and closer to the performance of fully active suspensions. � 2012 Elsevier Ltd. All rights reserved.

For a class of positive unstable infinite-dimensional linear systems, a method is described for computing a positively stabilizing state feedback, such that the resulting input trajectory remains in an affine cone. This design results in a possibly negative lower bound on the input, which makes the resulting closed-loop system stable and which maintains the nonnegativity of the state trajectory for specific initial states.

This paper presents an algorithm to solve the infinite horizon constrained linear quadratic regulator (CLQR) problem using operator splitting methods. First, the CLQR problem is reformulated as a (finite-time) model predictive control (MPC) problem without terminal constraints. Second, the MPC problem is decomposed into smaller subproblems of fixed dimension independent of the horizon length. Third, using the fast alternating minimization algorithm to solve the subproblems, the horizon length is estimated online, by adding or removing subproblems based on a periodic check on the state of the last subproblem to determine whether it belongs to a given control invariant set. We show that the estimated horizon length is bounded and that the control sequence computed using the proposed algorithm is an optimal solution of the CLQR problem. Compared to state-of-the-art algorithms proposed to solve the CLQR problem, our design solves at each iteration only unconstrained least-squares problems and simple gradient calculations. Furthermore, our technique allows the horizon length to decrease online (a useful feature if the initial guess on the horizon is too conservative). Numerical results on a planar system show the potential of our algorithm., Comment: This technical report is an extended version of the paper titled "Constrained LQR Using Online Decomposition Techniques" submitted to the 2016 Conference on Decision and Control

It is well known that the straight forward application of controller design methods to two-time-scale systems is susceptible to numerical ill-conditioning and stiffness problems. However, it has been demonstrated in this paper that the presence of time-scales can be exploited for achieving better computational efficiency in case of the design of controllers based on periodic output feedback and fast output sampling principles. In particular, an approach for design of periodic output feedback and fast output sampling controllers for a two-time-scale system by decomposition into a slow and a fast subsystem problems, has been presented. These smaller order problems are then separately solved and the results thus obtained for the slow and fast subsystems are combined to obtain the solution of the original design problems. The procedure has been illustrated with the help of a very simplified nuclear reactor model. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

The unified power-quality conditioner (UPQC) is used to provide balanced and sinusoidal source currents and load voltages under unbalanced and distorted three-phase supply voltages and load currents in a power distribution network. In this paper, a particle swarm optimization-based feedback controller is designed for UPQC. This feedback controller has optimal performance in various operating conditions and is robust to parametric uncertainties when compared to the conventional feedback controllers, such as the linear quadratic regulator. The proposed method is implemented on a distribution system and detailed simulation and experimental results are presented. � 2010 IEEE.

Energy Management Strategies for hybrid powertrains control the power split, between the engine and electric motor, of a hybrid vehicle, with fuel consumption or emission minimization as objective. Optimal control theory can be applied to rewrite the optimization problem to an optimization independent of time. Estimation of the Lagrange parameter, e.g., by feedback on the battery State-Of-Charge (SOC), can be used to arrive at a real-time implementable strategy. Nevertheless, it is still required to solve a nonconvex optimization problem with limited onboard computational power. This paper suggests to solve this optimization problem, offline, for different values of the Lagrange parameter, crankshaft rotational speed, and torque request. The resulting strategy is evaluated with simulations of a hybrid distribution truck on two different velocity trajectories. The influence of several control parameters is investigated also. © 2010 IFAC.

A simple and robust procedure with good transient response is proposed for d-q voltage control in conjunction with harmonics reduction in the output of stand-alone single-phase inverters. The distortion in the load voltage waveform is mainly due to the voltage drop in the filter-inductor caused by the harmonic components of the current. For extracting the in-phase and quadrature signals from harmonic-rich periodic waveforms, a composite observer has been developed, which is faster and more accurate than a simple observer. Separate observers have been provided for the voltage and current signals. Feed forward compensation has been obtained by using the quadrature components derived from the composite current observer. Further, an Inverter could be modeled as a feed back control system with the fundamental component as the desired output and the harmonics as the noise creeping into the output. The well-known control strategy of using a large feed back around the noise signal can be employed to reduce its effect at the output, exhibiting low total harmonic distortion under non-linear loads. The controllers can be easily modeled in the discrete-time domain and the ideas can be directly implemented digitally for single-phase inverters controlled by FPGA or DSP chips. � 2010 IEEE.

Published version of an article from the journal: Modeling Identification and Control. Also available from publisher: http://dx.doi.org/10.4173/mic.2010.1.3 The main contribution of the paper is the development of an adaptive backstepping controller for a nonlinear hydraulic-mechanical system considering valve dynamics. The paper also compares the performance of two variants of an adaptive backstepping tracking controller with a simple PI controller. The results show that the backstepping controller considering valve dynamics achieves significantly better tracking performance than the PI controller, while handling uncertain parameters related to internal leakage, friction, the orifice equation and oil characteristics.

International audience; In this article, a method for computing an optimal state feedback control law for continuous-time switched affine systems exhibiting cyclic behaviour in steady state is presented. The hybrid solutions are deduced from the Fillipov solutions. It is shown that the optimal trajectory synthesis implies to determine singular arcs. Algebraic conditions are given to obtain these particular arcs of the trajectory. A numerical procedure is then proposed to generate optimal trajectories on a given state space area avoiding the classical two-point boundary value problem occurring in optimal control synthesis. The interpolation of the solutions set, through a neural network, yields a state feedback control law. Several examples in the power converters field show the feasibility and the efficiency of the method.

If a Kalman Filter (KF) is applied to Global Positioning System (GPS) baseband signal preprocessing, the estimates of signal phase and frequency can have low variance, even in highly dynamic situations. This paper presents a novel preprocessing scheme based on a dual-filter structure. Compared with the traditional model utilizing a single KF, this structure avoids carrier tracking being subjected to code tracking errors. Meanwhile, as the loop filters are completely removed, state feedback values are adopted to generate local carrier and code. Although local carrier frequency has a wide fluctuation, the accuracy of Doppler shift estimation is improved. In the ultra-tight GPS/Inertial Navigation System (INS) integration, the carrier frequency derived from the external navigation information is not viewed as the local carrier frequency directly. That facilitates retaining the design principle of state feedback. However, under harsh conditions, the GPS outputs may still bear large errors which can destroy the estimation of INS errors. Thus, an innovative integrated navigation filter is constructed by modeling the non-negligible errors in the estimated Doppler shifts, to ensure INS is properly calibrated. Finally, field test and semi-physical simulation based on telemetered missile trajectory validate the effectiveness of methods proposed in this paper.

Due to the fast development of wind energy and exponential growing of installed wind turbines, the number of places with optimal wind conditions is limited and wind turbines are installed in the sea. For deep sea levels a concept known as floating offshore wind turbine has been developed. There are diverse types of turbines documented with different structures and ways of reaching stability. In this thesis the wind turbine spar buoy concept is analyzed, modeled and validated against FAST, an already developed and non linear complex model of a floating offshore wind turbine. In order to design a controller which guarantees the stable operation of the turbine and will achieve to obtain the maximum energy of it, different controllers are developed and used for this task. Finally the performance of the system with all the controllers is tested and compared. Máster Universitario en Ingeniería Industrial por la Universidad Pública de Navarra Nafarroako Unibertsitate Publikoko Unibertsitate Masterra Industria Ingeniaritzan

54th IEEE Conference on Decision and Control, CDC 2015; Osaka International Convention Center (Grand Cube)5-3-51 Nakanoshima, Kita-KuOsaka; Japan; 15 December 2015 through 18 December 2015, In this study, a partial state feedback controller is proposed for the link position tracking control problem of flexible tendon driven robotic systems. Specifically; a nonlinear model based controller is formulated for tendon driven robot manipulators under the constraint that only the link position and tendon expansion force measurements are available. Despite the lack of link and actuator side velocity and actuator position measurements, the proposed controller ensures exponential link position tracking. To eliminate the need of actuator position and velocity measurements, a model based velocity observer has been utilized. Stability of the closed loop system and boundedness of system states are proven via Lyapunov based arguments. The performance of the purposed observer-controller couple is then verified by a set of numerical simulations.

Synchronization with the power system is an essential part of control of grid-connected converters. This paper proposes a grid-voltage sensorless synchronization and control scheme for a grid-connected converter equipped with an LCL filter, measuring only the converter currents and the DC voltage. A discrete-time pole-placement design method is used to formulate an adaptive full-order observer for estimation of the angle and magnitude of the grid voltage. The analytically derived design is experimentally validated, and the results demonstrate rapid convergence of the estimated angle and magnitude.

In this note, we consider the finite-time stabilization of discrete-time linear systems subject to disturbances generated by an exosystem. Finite-time stability can be used in all those applications where large values of the state should not be attained, for instance in the presence of saturations. The main result provided in the note is a sufficient condition for finite-time stabilization via state feedback. This result is then used to find some sufficient conditions for the existence of an output feedback controller guaranteeing finite-time stability. All the conditions are then reduced to feasibility problems involving linear matrix inequalities (LMIs). Some numerical examples are presented to illustrate the proposed methodology.

The characterization of the similarity classes of matrices A + BF + KC + KWF obtained by State Feedback and Output Injection on a system (A, B, C, W) are revisited. New, more straighforward proofs are obtained. The results hold working on arbitrary fields.

This paper discusses the forbidden state problem, as specified by generalized mutual exclusion constraints, in the context of supervisory control of discrete event systems modelled by Petri nets. The case of backward-conflict-free and free-choice uncontrollable subnets is considered and it is shown how to transform such subnets in well-formed free-choice nets. Then, the well-formed free-choice nets are decomposed in marked graph components by recurring to minimal T-invariants. The forbidden state problem is so reformulated for the obtained marked graph components into an equivalent one which is shown to be a linear programming problem. Thus, improving existing results in literature, a polynomial complexity solution, suitable for on-line control, is achieved. Free-choice relationship and cycle modelling, that frequently occur in real-life situations, are so allowed in the uncontrollable subnet

Dimirovski, Georgi M. (Dogus Author) -- 16th Triennial World Congress of International Federation of Automatic Control, IFAC 2005; Prague; Czech Republic; 3 July 2005 through 8 July 2005; Code 85501 This paper deals with the robust H∞ control problem for a class of multi-input non-minimum-phase nonlinear systems with parameter uncertainty. A system of this class is assumed to be in a special interlaced form, which includes a strict triangular form as a special case. By using an extension of backstepping, nonlinear static-state feedback controllers are designed such that the closed-loop system is input-to-state stable with respect to the disturbance input and has the prescribed L2-gain from the disturbance input to the controlled output for all admissible parameter uncertainties. This work was supported by the NSF of China under Grant 60274009, by SRFDP under Grant 20020145007 and by NSF of Liaoning Province under Grant 20032020.

A general framework is constructed upon which an explicit parametric formula can be derived for state feedback controllers containing all the possible combination of parameters. The relation between the parameters is nonlinear in general, and therefore, many different constraint may be imposed by the designer to obtain desired performance criteria. A couple of illustrative examples are presented.

In this paper we consider the problem of designing a state feedback controller for a labeled Petri net whose initial marking is known to belong to a given convex set. We allow for silent transitions (i.e., transitions labeled with the empty word) and indistinguishable transitions (i.e., transitions sharing the same label with other transitions). Transitions that are neither silent nor indistinguishable, are said to be observable since the observation of their label univocally identifies them. Moreover, we divide the set of observable transitions into controllable and uncontrollable (all unobservable transitions are obviously uncontrollable). Based on our previous results on marking observation in the above setting, we show how to derive, at design time, a state feedback control law; this way, the most burdensome part of the computations, is performed off-line. © 2014 IEEE.

The present study concerns the feedback stabilisation of the unstable equilibria of a two-dimensional nonlinear pool-boiling system with essentially heterogeneous temperature distributions in the fluid–heater interface. Regulation of such equilibria has great potential for application in, for instance, micro-electronics cooling. Here, as a first step, stabilisation of these equilibria is considered. To this end, a control law is designed that regulates the heat supply to the heater as a function of the Fourier–Chebyshev modes of its internal temperature distribution. These modes are intimately related to the physical eigenmodes of the system and thus admit robust and efficient regulation on the basis of the natural composition of the temperature field. Key to this modal-control strategy and its application for controller design are an interchangeable PDE form and state-space form of the linearised model. Derivation of these forms is a central theme of this study. Performance of modal controllers thus designed is demonstrated and analysed by simulations of the nonlinear closed-loop system.