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DC-DC converters form a class of highly nonlinear systems and are widely used in most practical applications. Positive Output Elementary Luo Converter (POELC) is a fourth-order converter used to regulate dc voltages in low power applications with varying input voltage and load conditions. POELC is employed to regulate dc voltages for sensitive load applications like SMPS, powering hard disks etc. The control of higher-order converters is always a challenging task due to the highly nonlinear nature of these converters. Hence the development of an optimal controller for POELC is proposed in this paper. The proposed control methods are investigated for transient and steady-state performances considering practical operating conditions. The controllers are designed, simulated and the performance of POELC with various controllers is evaluated in the MATLAB/Simulink environment. The PI controller exhibits better performance in the linear region whereas, in the nonlinear region, due to time variance and switching nature. To minimize the sensitivity to external disturbances and to improve the stability margins, an LQR is designed to regulate the output of POELC. The result shows that a well-designed LQR feedback can stabilize the system and enhances its performance in terms of Integral Absolute Error (IAE), Integral Square Error (ISE). Certain case studies are discussed concerning practical applications.

In this paper an offset-free model predictive control scheme is presented for fractional-order systems using the Grunwald–Letnikov derivative. The infinite-history fractional-order system is approximated by a finite-dimensional state-space system and the modeling error is cast as a bounded disturbance term. Using a state observer, it is shown that the unknown disturbance at steady state can be reconstructed and modeling errors and other persistent disturbances can be attenuated. The effectiveness of the proposed controller–observer ensemble is demonstrated in the optimal administration of an anti-arrhythmic medicine with fractional-order pharmacokinetics.

Since radiator takes an important role in controlling indoor air temperature and heat output of district heating system, efficient control of radiator is essential for thermal comfort and energy conservation. The governing equation of radiator heat transfer is a partial differential equation (PDE), which is not suitable for controller design. In this paper, an accurate model reduction method was established to reduce the radiator model. Comparison of the reduced and PDE models via Bode diagrams shows good approximation of the reduced model. The integrated model of room heating system was developed based on the reduced radiator model. In order to enhance the dynamic performance of room heating system, a new control algorithm, the two-degrees-of-freedom H ∞ control was proposed. The reference tracking and disturbance rejection performances of room heating system with H ∞ and PI controllers were compared. Dynamic performances of closed-loop system controlled by the two control algorithms under capacity parameter uncertainties were analyzed to verify the robustness of the proposed control algorithm. Results show that the proposed two-degrees-of-freedom H ∞ controller can ensure better reference tracking and disturbance rejection performances even when system uncertainty exists.

Orbital stabilization is one of the available alternatives to the classical asymptotic stabilization, known as the reference tracking control, which is typically considered and implemented for controlling motions of industrial robot manipulators. Since asymptotic orbital stability means convergence of solutions of a closed-loop system to an orbit of a reference trajectory, instead of tracking it as a function of time, new feedback designs can potentially improve performance with respect to several key criteria for industrial manipulators such as absolute path accuracy for tool’s motions and robustness to uncertainties in the model. The main outcomes of this paper are a new class of controllers that achieve asymptotic orbital stabilization of motions and a novel analytical method for analysis and redesign of system’s dynamics using an excessive set of easy-to-compute transverse coordinates. The contributions have been validated in a series of experimental studies performed on a standard industrial robot ABB IRB 140 with the IRC5-system extended with an open control interface. The outcomes of the tests show that the proposed redesign allows achieving significantly reduced deviations of the actual trajectories from the desired ones at different ranges of speeds and for several different paths, often outperforming the state-of-the-art commercial implementations. A comprehensive discussion of one of such experiments is given.

Distributed Model Predictive Control refers to a class of predictive control architectures in which a number of local controllers manipulate a subset of inputs to regulate a subset of outputs composing the overall system. These controllers may cooperate to find an optimal control sequence that minimizes a global cost function, as in the case of Cooperative Distributed Model Predictive Control (CD-MPC). In this paper two linear CD-MPC algorithms for tracking are proposed. The aim of these controllers is to drive the outputs of the overall system to any admissible piece-wise constant set-point, satisfying input and state constraints. However, in the available literature this result is achieved by using a set of centralized variables that keep track of the global state of the system. In contrast, we develop novel CD-MPC approaches for tracking that rely on “as local as possible” information instead of the plant-wide information flow. These new control strategies reduce the required communication overhead, local computational demands, and are more scalable than CD-MPC algorithms available in the literature. We illustrate the main characteristics and benefits of the proposed approaches by means of a multiple evaporator process example.

Multivariable controller design for grinding circuit is the subject of this work. Model of grinding circuit in Majdanpek Copper Mine is subjected to the newly proposed sequential design method, based on the Gauss-Jordan factorization and Nyquist-like techniques. Due to the nature of the applied design method, generalization to any other grinding circuit is straightforward. An extensive simulation analysis proved the effectiveness of proposed design in reference tracking, even in the case of some loop failures.

This paper aims to present a methodology to control the position of the clutch actuator. The objective is to improve the position reference tracking in order to get better performances and accuracy on the clutch slip control. The originality of this work is to use a model that takes into account the nonlinear characteristic of the stiffness of the clutch diaphragm. Instead of robustness approach, the nonlinearity is managed using the quasi-LPV Takagi-Sugeno representation and, additionally, because the nonlinearity is switching, the developed control law is, consequently, a nonlinear switching one. Moreover, in order to use unmeasured values in the controller, such as the current of the electric motor, a Takagi-Sugeno switching observer is designed. Some simulation results highlight the efficiency of the proposed approach.

In this paper, a non-cooperative distributed model predictive control (DMPC) algorithm for tracking constant references is developed and evaluated. As such, an augmented model is employed (i.e. the control loop is embedded with integrators) and the augmented state contains the state increments and the error between the reference and the predicted output. The algorithm is tested in real life experiments on the quadruple tank process with non-minimum phase behaviour. The experimental results show acceptable performance index for the DMPC method when compared with the centralized approach.

In this paper, an innovative sensorless two-degree-of-freedom current control scheme for the whole speed range is proposed. It consists of a model-based dynamic feedforward control to set the reference response and model reference tracking controllers providing disturbance rejection and the position error signals needed for sensorless control. For low- and zero-speed operation, alternating test current injection is used to gain a position error signal. A flatness-based test signal precontrol provides compensation for secondary saliencies like cross-saturation and higher harmonics. For mid- and high-speed operation, it is shown how the model-based dynamic feedforward control can be modified to obtain a high-quality position error signal from the tracking controller. No additional model-based estimator evaluating back-EMF information is needed. The effectiveness of the proposed method is proven by experimental results.

Several complex processes that are employed in industries, such as shipping, power plants, and the petrochemical industry, involve time-varying behavior as well as strong nonlinear behavior during operation. The fixed-parameter proportional-integral-derivative (PID) controllers have difficulty in dealing with control problems that occur in such processes. In this paper, we propose a method of designing a nonlinear PID controller for industrial processes that exhibit a large number of nonlinearities and time-varying behavior. The gains of the nonlinear PID controller are characterized by a simple nonlinear function of the error and/or error rate depending on the process set-point and output. We tune the user-defined parameters using a genetic algorithm by minimizing the integral of time absolute error (ITAE) index. We verify the effectiveness of the proposed method by performing a comparison of the proposed method and two other nonlinear and adaptive methods that are employed for reference tracking, disturbance-rejection performances, and robustness to parameter changes on a continuously stirred tank reactor.

This paper presents a new methodology to design multivariable Smith predictor for n×n processes with multiple time delays based on the centralised inverted decoupling structure. The controller elements are calculated in order to achieve good reference tracking and decoupling response. Independent of the system size, very simple general expressions for the controller elements are obtained. The realisability conditions are provided and the particular case of processes with all of its elements as first-order plus time delay systems is discussed in more detail. A diagonal filter is added to the proposed control structure in order to improve the disturbance rejection without modifying the nominal set-point response and to obtain a stable output prediction in unstable plants. The effectiveness of the method is illustrated through different simulation examples in comparison with other works.

An LED driver consisting of dimmable current regulators and a boost converter with adaptive reference tracking control (ARTC) is proposed. The ARTC is realized with only one integrator and one subtractor to detect the voltage variation among the current regulators and then to generate an adaptive reference tracking voltage. Based on the reference tracking voltage, the driving voltage of the boost converter is dynamically adjusted, so as to not only maintain a minimum voltage on the current regulator but also keep the required LED-string current. A prototype control circuit including ARTC and PWM control fabricated with TSMC 0.35-µm 2P4M CMOS process validates the proposed technique. The measurement results show that the driving voltage of the boost converter is automatically regulated to compensate for the voltage alteration on the current regulators. Furthermore, the overall efficiency of the LED driver with ARTC is 6.1% better than that of the LED driver without ARTC.

Safety is a fundamental issue in robotics, especially in the growing application of human-robot interaction (HRI), where collision avoidance is an important consideration. In this paper, a novel real-time velocity based collision avoidance planner is presented to address this problem. The proposed algorithm provides a solution to deal with both collision avoidance and reference tracking simultaneously. An invariant safe set is introduced to exclude the dangerous states that may lead to collision, and a smoothing function is introduced to adapt different reference commands and to preserve the invariant property of the safe set. A real-time experiment with a moving obstacle is conducted on FANUC LR Mate 200iD/7L.

In this paper we study a security problem for resource-constrained autonomous systems. We consider a UAV tasked with tracking a reference trajectory, and an attacker capable of compromising the measurements taken at certain sensors. We consider a probabilistic attack model, where the attacker executes denial of service attacks against a subset of sensors based on a Bernoulli process. We assume that sensors have different accuracy, reliability, and require different computational times to be activated. Our approach is based on the formalism of Markov Jump Linear Systems. We develop and numerically validate an optimal security countermeasure that probabilistically selects which sensor to use at different time instants, so as to balance performance and security, and ultimately minimize the UAV's expected tracking error.

The paper presents a design of the robust model predictive control (RMPC) for a laboratory continuous stirred-tank reactor (CSTR). A neutralization reaction ran in the CSTR, and the reactants were acetic acid and sodium hydroxide. The controlled variable was pH of the reaction mixture. The control input was the volumetric flow-rate of the base. The system was modeled using experimental data of several step-responses. Measurement noise was reduced using the Hebky filter. The robust model-based control strategy was implemented to assure good control performance. The offset-free reference tracking was ensured by the implementation of RMPC with integral action.

This paper extends a recently developed interpolation-based approach to design gain-scheduled controllers for linear parameter-varying systems with a thorough evaluation, comprising both simulations and experiments, on an overhead crane system. In the first step of the approach, linear time-invariant controllers are designed for local working conditions of the system using a multiobjective H∞ method. With the help of this method, the fundamental tradeoff between reference tracking and disturbance rejection in the overhead crane control problem is analyzed. In the second step, a state-space interpolation method is used to calculate a gain-scheduled controller. Although this approach does not guarantee stability and performance under parameter variations, experiments on the crane setup show that these variations do not compromise the performance of the obtained controller.

A patient with hypoxia requires immediate oxygen therapy to enhance oxygenation. Individual model including disease and parameter variation is needed, which limits all model-based approaches for the task of reference tracking control. In this article, a non-identifier based control algorithm, called funnel control, is proposed to solve this clinical problem in real practice. With this control technique, it requires less a priori knowledge of the complicated nonlinear and time-delay plant. The design of a funnel controller relies only upon an output feedback and the difficult control problem of such system is simplified by the design of a funnel boundary, which is a time-varying gain to force error dynamics inside this boundary. Funnel controllers with relative degree one and two are presented and simulated with the proposed cardiopulmonary system for low tidal volume, simulating the existing and abrupt change of atelectasis.

There have been several design methodologies of impedance control without using force sensors, most of which use an observer to estimate external forces and conduct impedance control based on the observed external force. Since the external forces are estimated in a feedback way in this type of force observer-based impedance control, it has been impossible to achieve reference tracking performance when the impedance is designed low for compliant interaction. This paper proposes a novel frequency-shaped impedance control which can perform compliant motions and reference tracking simultaneously. The proposed algorithm is based on the disturbance observer design which allows a straightforward design of compliant interactive force and employs feedforward controller to compensate for the frequency bandwidth that can be sacrificed due to low impedance design. Experiments with an industrial robot verify the effectiveness of the proposed controller.

This paper provides a novel solution to the problem of tuning linear output feedback model predictive control (MPC). A systematic tuning method that allows to obtain all the parameters of an unconstrained output feedback MPC based on disturbance model and observer is presented. It is shown that such tuning can be translated to a frequency domain control design problem, which can be solved using existing techniques. Experimental results on a quadrotor reference tracking problem show the effectiveness of the proposed MPC tuning method.

This paper describes the problem of load disturbance rejection using feedforward for the case when perfect compensation is not realizable due to processes delays inversion. First, a new generalized open-loop design tuning rule for feedforward compensators is proposed. Simple and intuitive guidelines are given for aggressive, moderate, and conservative performance results. Moreover, a switching feedforward compensator is proposed to be used when oscillations are not allowed in the process output. Simulation results show important improvements in disturbance rejection, reference tracking error and control effort.

In this paper, an approach for high dynamic torque control of an industrial engine test bed is proposed. The main goal is to develop a control concept that is capable of periodic reference tracking at high control bandwidth while at the same time sufficiently rejecting disturbances coming from external excitations. For that reason, model predictive control (MPC) is utilized which offers two major benefits as compared to classical controllers. On the one hand, its capability to explicitly consider constraints can be applied to limitations of the actuating variable on the test bed. On the other hand, it can also be used to increase control bandwidth by anticipating future reference trajectories. For MPC, an accurate test bed model is of vital importance. Therefore, a system model is developed and validated using measurements obtained from the engine test bed. Moreover, a robustifying approach is proposed based on an extended system model to overcome hardly observable, weakly damped engine block suspension dynamics which are difficult to model. The proposed control concept is discussed and validated through simulations as well as through experimental results.

This paper analyzes for the first time the influence of the master roller placement of roll-to-roll systems and the effects of velocity and tension bandwidths. In such systems, each motor driven roller is controlled separately (decentralized control). The influence of the master roller position, which is only controlled in velocity and therefore gives the web speed, is studied. The other motor driven rollers are also controlled using optimized PI web tension controllers, automatically synthesized in the fixed-order and structure H∞ framework. The web speed and tension control bandwidths play a major role on the system performances and therefore have to be chosen carefully. The impact of the master roller placement, considering several setting values of speed and control bandwidths, is analyzed with respect to reference tracking, disturbance rejection and robustness to web elasticity variations. Several configurations and settings are compared in time domain simulations and frequency system/signal analysis.

This study addresses two major single-input single-output control problems involving both feedback and feedforward actions: (i) the model matching in reference tracking and (ii) the rejection of measurable disturbances. Its aim is to overcome the limitations of inversion-based feedforward design methods when system uncertainty is considered, and to find a control engineering solution based on the quantitative feedback theory (QFT). The proposed methodology leads to minimum cost of feedback by limiting the feedback action to the strictly necessary amount that enables the use of a feedforward controller. Although the model matching problem had drawn some attention of the QFT community in the last few years, the measurable disturbance rejection problem remained unaddressed. This study provides a novel solution for both of them in which the need for feedback is linked to the existence of a common feedforward solution for all plants within the model uncertainty. This work also deals with the generation of the corresponding quadratic inequalities and new QFT bounds for the mentioned feedback demand. A practical and well-known benchmark example illustrates the main details and advantages of the new methodology.

This paper proposes an H ∞ robust static output fuzzy controller for dc–dc converters using Takagi–Sugeno fuzzy models. In the proposed approach, the controller is designed using the output voltage which is the measured signal. Therefore, the number of sensors does not increase in comparison with traditional approaches. In addition, the proposed controller is designed to not only ensure a good reference tracking with disturbance rejection, but also provide the robustness with respect to the input voltage and load variations. The asymptotic tracking of signal is guaranteed, in the Lyapunov sense, by satisfying some sufficient conditions given in Linear Matrix Inequality form. Numerical examples show the good steady-state and dynamic behaviors.

This paper provides the design of an MPC controller applied to grid-connected inverters with LCL filters. The approach here uses an MPC controller to control the current injected to the grid. The control design leads to a controller with fixed gains implemented with a classical state-feedback control law, ensuring the reference tracking capacity and the rejection of harmonic disturbances in the grid voltage. The closed-loop system is validated by means simulations and frequency response analysis.

This paper proposes a single on/off reference tracking buck converter for DVFS application with a novel turning point prediction based on the turning point of the output voltage. The equation to determine the turning point of the output voltage for optimal reference tracking is analyzed and implemented by a current multiplier and divider circuit. In addition, a new reference tracking scheme is introduced to avoid undershoot of output voltage caused by load change. This work is simulated in a 0.13-μm CMOS process and simulation results show fast reference tracking capability with 1.48 μs/V for up reference tracking, 1.91 μs/V for down reference tracking, and effective reduction of the undershoot and overshoot problem.

International audience; Reference tracking is a challenging problem in the presence of saturation. This paper proposes a hybrid controller that ensures global convergence to zero of the error dynamics of a saturated multidimensional double integrator in the presence of a time-varying reference. Such a controller combines a local linear feedback, which ensures the tracking in the presence of small errors (local mode), and a global stabilizing quasi time-optimal controller, which handles large errors and the saturation (global mode). The proposed switching hybrid logic is applied also to the reference. In global mode, the reference trajectory is slowed down to promote the stabilization task. Once in local mode, the controller speeds up the reference to restore the nominal behavior. The proposed strategy has been extensively tested via simulations. The proposed solution has shown a graceful performance degradation in the presence of disturbances that do not allow the controller to remain in the local mode.

The purpose of this paper is first to review the standard Generalized Predictive Controller (GPC) design, second, to establish a comparative study between the GPC with a prefilter T f (q −1 ), the GPC with a parameter of the future reference trajectory and the GPC that includes a positional model but with a integral polynomial weighing factor for the error. Simulation results are shown and discussed.

A super twisting repetitive control (STRC) system is proposed, to improve periodic reference tracking performance, as well as compensate periodic and aperiodic disturbances. The design algorithm is based on the concept of super twisting control (STC), and repetitive control (RC). With five tuning parameters, the STRC provides a convenient method to solve the complex engineering problems. The comparison studies were conducted to demonstrate the effectiveness of STRC over conventional RC and STC.

This paper presents a model based switching control strategy to drive the neuromuscular blockade (NMB) level of patients undergoing general anesthesia to a predefined reference. A single-input single-output Wiener system with only two parameters is used to model the effect of two different muscle relaxants, atracurium and rocuronium , and a switching controller is designed based on a bank of total system mass control laws. Each of such laws is tuned for an individual model from a bank chosen to represent the behavior of the whole population. The control law to be applied at each instant corresponds to the model whose NMB response is closer to the patient's response. Moreover a scheme to improve the reference tracking quality based on the analysis of the patient's response is presented. The results are illustrated by means of several simulations.

This paper presents a nonlinear control strategy using robust nonlinear dynamic inversion (RNDI) for an electric throttle which is a dc-motor driven valve for automotive engines. Controlling of the electric throttle is a great challenge due to strong nonlinearities, such as “limp-home” nonlinearity, friction and backlash. In this paper, a novel robust nonlinear dynamic inversion technique is proposed in order to achieve a fast and accurate reference tracking performance even in the presence of highly nonlinear characteristics. The effectiveness of the proposed method is analyzed through computer simulations.

The standard way to achieve offset-free tracking in MPC is to add the disturbance dynamics to the prediction model and then use an observer to estimate the real disturbance. Existing algorithms only consider piecewise constant signals, while in practice it is often desirable to have a wider choice of reference and disturbance dynamics, such as sinusoids and ramps. This work provides a generalization of the disturbance estimation approach to arbitrary unstable dynamics. Zero offset is achieved under the assumption that the disturbance and reference dynamics are appropriately included in the prediction model and feasibility of the commanded reference is given.

A switching control strategy for drug infusion in patients undergoing surgery is presented in this article. This strategy is based on a bank of stabilising controllers, aiming to improve the reference tracking performance of the patient response. Theoretical results which ensure overall stability and reference tracking under switching are obtained. These results are illustrated by simulations for the case of neuromuscular blockade control which show that, in this biomedical application, this switching controller yields better performance than a fixed one. The proposed control scheme also presents a good performance in clinical environment.

This research deals with a new modelling of a three-phase network in association with a parallel active filter with the help of linear state representation in closed loop. Using this approach the harmonics compensation of current networks is treated like a matter of disturbances rejection with the tools of linear control theory. This reasoning is different from common methods which are usually based on reference tracking control. The proposed strategy is validated firstly using simulation then using a test bench fitted with a three-phase shunt active filter whose control law is implemented in real time.

[EN] In this paper, we propose a control method to achieve three objectives simultaneously: velocity regulation during free motion, impact damping and finally force reference tracking. During impact, the parameters are switched in order to dissipate the energy of the system as fast as possible and the optimal switching criteria are deduced. The possibility of sliding regimes is analysed and the theoretical results are verified in simulations., We would like to thank the R&D&I Linguistic Assistance Office, Universidad Politecnica de Valencia (Spain), for Granting financial support for the linguistic revision of this paper. This work has been partially funded by the European project MASMICRO (Project number 500095-2), by the projects FEDER-CICYT with reference, DPI2005-08732C02-02 and DP12006-15320-C03-01, of the Ministry of Education and Science as well as by the research Project of the Generalitat Valenciana, GVPRE/2008 20080916.

The most dangerous part of a force control task is the impact. This article proposes a regulator that achieves both impact control and force reference tracking. The former is obtained switching of the mass of the system in order to dissipate the energy of the system as fast as possible. It is demonstrated how the virtual mass may be switched. Also, the optimal switching criteria are deduced in order to dissipate the energy as fast as possible. It is demonstrated that the system does not enter the sliding regimes when the mass is switched. The theoretical conclusions are verified in simulations.

This article describes an improvement to integral resonance damping control (IRC) for reference tracking applications such as Scanning Probe Microscopy and nanofabrication. It is demonstrated that IRC control introduces a low-frequency pole into the tracking loop which is detrimental for performance. In this work, the location of this pole is found analytically using Cardano's method then compensated by parameterizing the tracking controller accordingly. This approach maximizes the closed-loop bandwidth whilst being robust to changes in the resonance frequencies. The refined IRC controller is comprehensively compared to other low-order methods in a practical environment.

International audience; (Quasi) LPV control and more generally L2 gain control methods, referred to as nonlinear H ∞ control ones, are usually applied in order to ensure reference tracking and disturbance rejection. In this paper, we exhibit a counterexample that reveals that these specifications can not be ensured by these methods. We then propose a new LPV based approach in order to a priori ensure these specifications by combining the LPV method with the incremental L 2 gain analysis of nonlinear performance. Its benefit is illustrated on the counterexample.

This paper describes the application of an offset free nonlinear model predictive controller (NMPC) to regulate the self-optimizing variables and active constraints in a wastewater treatment plant, particularly the activated sludge process using the benchmark simulation model No. 1 (BSM1). A set of terminal constraints have been added to the NMPC formulation in order to ensure stability. The procedure to find the self-optimizing variables as the best controlled variables in an economic sense, has also been described briefly, considering the most important measurements of the process. This methodology provides the optimum combination of measurements to keep constant with minimum economic loss. The simulation results show good reference tracking for typical average load disturbances.

Steady-state control error occurs in case of unmeasured disturbances or disagreement between the model and the actual behaviour of the system because, state-space controllers do not have integral character. This problem (offset-free reference tracking) of state-space controllers has been observed in both theoretical and application areas (industrial MPC Implementation IDCOM, DMC, and QDMC IDCOM-M) for long time. The common solution is based on the model of the controlled system which is extended with the disturbance model. The article describes a simple approach to implement a system based on standard state-space controller with state vector estimation with additional parallel I-controller. Approach involving the I-controller in the process model of the controlled system is considered as another variant of predictive controller. The proposed solution with four variants of state-space controllers are demonstrated by simulation of MIMO system with three inputs and two.

International audience; This paper focuses on the lateral control of intelligent vehicles; the aim is to minimize the lateral displacement of the autonomous vehicle withrespect to a given reference path. The control input is the steering angle and the output is the lateral error displacement. We present the designand validation of a robust lateral controller based on the Immersion and Invariance (I&I) principle in order to ensure robust stability and goodperformances with respect to parametric variations and uncertainties that are encountered in driving applications. To validate our control law, testswere performed on SCANeR Studio, a driving simulation engine, according to several real driving scenarios. Simulations were also performedusing experimental data acquired by the DYNA vehicle (a Peugeot 308) belonging to the Heudiasyc laboratory. The validation demonstrates therobustness and good performances of the proposed control approach and clearly shows the improvement due to the I&I controller.

This paper presents an approach for a coordinated voltage - reactive power control using VSC HVDC lines embedded in large AC networks. The proposed control algorithm incorporates the HVDC into the overall Var dispatch strategy of the network. Additionally, it is able to fulfil the dynamic voltage support requirements following grid short circuits. The models of these hierarchical two-stage controllers have been described in detail and approaches for coordination of their operation explained. Simulation examples demonstrate the disturbance as well as the reference tracking behavior of the controller.

A sliding mode based repetitive control system is proposed, to improve reference tracking performance, as well as compensate output disturbances. The design algorithm is based on the concept of sliding mode controller (SMC), feedback controller, and modified repetitive controller (MRC). With two tuning parameters, the sliding mode based RC provides a simple and convenient method to solve the complex engineering problems. The comparison study was conducted to demonstrate the effectiveness of sliding mode based RC over state feedback based RC.

The conventional output regulation problem aims to achieve reference tracking and disturbance rejection while references and disturbances are generated by an autonomous exosystem. When the exosystem is perturbed by an external event, a novel robust perturbed output regulation problem is formulated and solved in this paper. The formulation arises from a kind of synchronization problem of multiple agents. Hence, the proposed solution leads to a decentralized control algorithm for synchronization of multiple agents with nonlinear heterogeneous dynamics.

This note presents a method for analysis of random reference tracking in feedback systems with saturating actuators. The development is motivated by the frequency domain approach to linear systems, where the bandwidth and resonance peak of the sensitivity function are used to predict the quality of step reference tracking. Similarly, based on the so-called saturating random sensitivity function, we introduce tracking quality indicators and show that they can be used to determine both the quality of random reference tracking and the nature of track loss under actuator saturation. The shortcomings of the method are also discussed.

This work presents a predictive-control approach to active mechanical filtering of complex, periodic motions of organs induced by respiration or heart beating in robotized surgery. Two different predictive-control schemes are proposed for the compensation of respiratory motions or cardiac motions. For respiratory motions, the periodic property of the disturbance has been included into the input-output model of the controlled system so as to have the robotic system learn and anticipate perturbation motions. A new cost function is proposed for the unconstrained generalized predictive controller (GPC), where reference tracking is decoupled from the rejection of predictable periodic motions. Cardiac motions are more complex, since they are the combination of two periodic nonharmonic components. An adaptive disturbance predictor is proposed which outputs future predicted disturbance values. These predicted values are used to anticipate the disturbance by using the predictive feature of a regular GPC. Experimental results are presented on a laboratory testbed and in vivo on pigs. They demonstrate the effectiveness of the two proposed methods to compensate complex physiological motion.

This paper concerns a design method for an H, compensator which achieve robust stability as well as adequate disturbance rejection and reference tracking properties. A practical and systematic design method for the H, compensator is proposed. The practical applicability of the H, compensator for a typical plant in process industries comparing with the control performance obtained by the robust PID controller is highlighted.

In this Technical Note, the problem of random reference tracking by linear feedback systems is addressed. The approach is based on the so-called random sensitivity function, which plays the same role as the usual sensitivity function in step reference tracking. Using the random sensitivity function, quality indicators for random reference tracking are introduced, and their utilization for analysis and design of servomechanisms is illustrated.

A disturbance observer-based vehicle stability controller is proposed in this paper. The lumped disturbance to the vehicle yaw rate dynamics caused by the uncertain factors such as uncertain tire forces and parameters is estimated by the disturbance observer, which is utilized by the robust controller to stabilize the lateral dynamics of the vehicle. The dynamics of the hydraulic actuator is incorporated in the vehicle stability controller design using the model reduction technique. Modular control design methodology is adopted to effectively deal with the mismatched uncertainty. Simulation results indicate that the proposed disturbance observer-based vehicle stability controller can achieve the desired reference tracking performance as well as sufficient level of robustness.