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This article addresses the reference tracking issue of multi-degree-of-freedom robotic exoskeletons under exogenous perturbations. First, by considering the concept of iteration-dependent full-format dynamic linearization, the exoskeleton robot’s dynamics is reformulated as a linear data model in an iterative manner. Then, based upon an iterative sliding variable, a novel data-based model-free adaptive iterative learning integral terminal sliding mode control is designed. The superiority of the proposed study is that the reference tracking problem is just solved by using the measured input/output information of exoskeletons. In addition, its finite-iteration convergence is also affirmed by mathematical analysis. The simulation investigation together with the compared results also clarifies the efficiency of the developed learning-based control algorithm.

This paper proposes an unified procedure for time-varying dead-time compensation. The method is an adapted version of the Filtered Smith Predictor (FSP), which is coupled to a delay estimation scheme and two adaptive Linear Parameter Varying (LPV) blocks. These LPV blocks allow the DTC to autonomously regulate the amount of closed-loop robustness, with respect to the (estimated) amount of delay. The method is easily adjustable and can be tuned to provide a balance between robustness and performance objectives, while being able to deal with unstable and integrative processes. A series of numerical simulations are included to illustrate the advantages of the proposed method towards reference tracking, noise attenuation, disturbance rejection and uncertainty handling. This novel DTC enables enhanced performances with respect other methods from the literature.

This paper presents a new technique for the state estimation and reference tracking of nonlinear dynamic systems over the packet erasure channel, which is an abstract model for transmission via the Internet, WiFi wireless network and ZigBee modules. A new encoder and decoder for real time state estimation of nonlinear dynamic systems at the end of communication link when the measurements are sent through the limited capacity erasure channel, are presented. Then, using the available results from control theory, a controller for reference tracking and hence the stability of the system is also designed. That is, for nonlinear systems, almost sure asymptotic state estimation and reference tracking techniques including an encoder, decoder and a controller are presented. The satisfactory performances of the proposed state estimation and control techniques are illustrated via computer simulations by applying the proposed techniques on the unicycle model, which represents the dynamics of autonomous vehicles.

This paper is concerned with the model reference tracking control (MRTC) problem of discrete-time Markovian jump systems under external disturbance and input constraints. A state feedback controlle...

International audience; This paper presents a robust controller design method for reference tracking in multi-input multi-output preview systems. In the context of preview systems, it is supposed that future values of the reference signal are available a number of time steps ahead. The objective of the controller being to minimize a quadratic error between the reference and the system's output, the optimal solution needs to take into account the known future values of the reference. Furthermore, it is desired to maintain the control signal at an acceptable level. The feedforward preview is obtained by solving a mixed L 2 /L ∞ optimisation, where the L ∞ constraint is used to reduce the level of the control. The proposed solution combines a robust feedback controller with a feedforward preview filter. The feedback controller's purpose is to assure robustness of the closed-loop system to model uncertainties and is not detailed here. The focus of this paper is on the design of the feedforward preview filter taking into account that a feedback controller is present. The proposed solution is validated in simulation on a high dynamic engine testbed.

Iterative Learning Control (ILC) is a control strategy that improves the performance of repetitive systems by enabling near-perfect reference tracking. Iteration-invariant reference signals have been a fundamental assumption for most existing ILC developments. This assumption poses limitations on many applications of ILC where the iteration-varying reference is known to the controller a priori. This work presents a switch-based ILC scheme that combines the performance of standard ILC with guarantees on the error for switched reference signals. The proposed controller is formulated and its performance is analyzed. A simulation case study is provided at the end to illustrate the performance.

This work examines stabilisation and reference tracking problems for uncertain deterministic as well as switched stochastic nonlinear systems. The concept of input state stability is employed here ...

This article focuses on linear matrix inequality-based controller designs that can achieve stabilization and reference tracking for a small unmanned helicopter at various flight conditions. A nonlinear mathematical model of a small-scale helicopter is constructed. Then trim conditions are found and linearized around different equilibrium points. Local [Formula: see text] controllers are designed at trim conditions based on the local linear models. The pointwise controllers achieve local stability and performance, but fail at stabilization and tracking over the full envelope. A scheduling controller is built by blending the local controller outputs. In addition, grid-based [Formula: see text] controllers are designed at each operating point with common Lyapunov function. This allows controller scheduling between the adjacent design points with guaranteed stability and performance across the design envelope. Based on the family of linear systems which are obtained from the nonlinear model, an affine parameter-dependent model is built to exploit the approximate linear parameter dependency. Then, a parameter-dependent linear parameter varying controller is synthesized for the affine parameter-dependent model. Although local performance is satisfactory for all given design methods, local [Formula: see text] controllers and affine parameter-dependent controller cannot yield satisfactory performance over the full flight envelope apart from the grid-based controller with common Lyapunov function approach.

This paper investigates stability analysis and robust model reference tracking control problem for a class of switched nonlinear systems with input delay and disturbance. Using a new Lyapunov–Kraso...

Because of the existence of communication networks and control applications, DC microgrids can be attacked by cyber-attackers. False data injection attack (FDIA) is one type of cyber-attacks where attackers try to inject false data to the target DC microgrid to destruct the control system. This brief discusses the effect of FDIAs in DC microgrids that are structured by parallel DC/DC converters and they are controlled by droop based control strategies to maintain the desired DC voltage level. Also, an effective and proper strategy based on an artificial neural network-based reference tracking application is introduced to remove the FDIAs in the DC microgrid.

With the purpose of highlighting the concept of orbital stabilization as an alternative to the reference tracking control methodology, this paper considers simple, informative examples in relation to motion control of an one-degree-of-freedom, double integrator system. In this regard, the notions of (excessive) transverse coordinates, projections operators and the transverse linearization are introduced, and it is illustrated how these can be used both for the design and analysis of orbitally stabilizing feedback controllers. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

This paper considers the periodic reference tracking problem for continuous-time semi-Markovian jump systems. An observer-based robust H∞ modified repetitive controller with logarithmically quantis...

Photovoltaic (PV) source simulators are widely used to evaluate the performance of solar inverters and study their grid integration issues in the laboratory settings. Most of the commercial PV simulators are designed based on the programmable dc power supply platform. Owing to bulky output capacitors, the dynamic response and the bandwidth of these PV simulators are significantly limited, which, therefore, cannot meet the requirements to test advanced features of the solar inverters. In this study, a cost-effective high bandwidth PV simulator is proposed. A three-phase interleaved buck converter is utilised as the power stage and a novel sliding mode duty-cycle controller with auto current balancing algorithm is proposed to ensure the accurate and fast reference tracking along with phase current balancing. Both simulation and experimental studies are carried out to validate the feasibility and effectiveness of the proposed PV source simulator.

This article presents a model predictive control for tracking piecewise constant references with a new steady-state parametrisation. The modified algorithm is based on the artificial reference idea...

This paper focuses on the H U+221E model reference tracking control for a switched linear parameter-varying U+0028 LPV U+0029 model representing an aero-engine. The switched LPV aero-engine model is built based on a family of linearized models. Multiple parameter-dependent Lyapunov functions technique is used to design a tracking control law for the desirable H U+221E tracking performance. A control synthesis condition is formulated in terms of the solvability of a matrix optimization problem. Simulation result on the aero-engine model shows the feasibility and validity of the switching tracking control scheme.

This work deals with the problem of a model reference tracking based on the design of an Active Fault Tolerant Control (AFTC) for linear parameter varying (LPV) systems affected by actuator faults and unknown inputs. LPV systems are described by a polytopic representation with measurable gain scheduling functions. The main contribution is to design an Active Fault Tolerant Controller whose control law is described by an adaptive Proportional Integral (PI) structure. This one requires three types of on-line informations which are: reference outputs, measured real outputs and the fault estimation provided respectively by a model reference, sensors and an Adaptive Polytopic Observer (APO). These informations are used to reconfigure the designed controller which is able to compensate the fault effects and to make the closed loop system able to track reference outputs in spite of the presence of actuator faults and disturbances. The controller and the observer gains are obtained by solving a set of linear matrices inequalities (LMIs). Performances of the proposed method are compared to an other previous method in order to underline the relevant results.

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.

Spanish Government, Grant/Award Number: BES-2010-038486; Generalitat Valenciana, Grant/Award Number: BEST/2017/029 and APOSTD/2016/044

Robust output regulation is a controller design theory for achieving reference tracking and disturbance rejection as well as system stability. The main feature of the theory is that the reference a...

We address the constrained output tracking of constant references for linear parameter-varying systems. In model predictive control based on linear parameter-varying state-space representations, offset-free output tracking is generally not possible due to the variations in the scheduling signal. Therefore, we aim instead to guarantee a pre-specified tracking error bound which is achievable for all admissible variations of the scheduling variable. The construction of an invariant set in which such a bound can be satisfied is described. Subsequently a tube-based model predictive controller is designed which brings the state of the system inside this set in finite time. The properties of the approach are demonstrated on numerical examples.

Operational data from Chinese railways indicate a number of challenges for traction four-quadrant converter (4QC) control including low-order voltage and current harmonics and reference tracking. A control strategy for a single-phase three-level neutral-point-clamped 4QC employed in the electric multiple unit traction system is proposed in this study. The strategy is based on a multiple frequency tuned quasi-proportional resonant controller in the ac-side current loop and a multiple frequency tuned notch filter in the dc-link voltage loop. Under the typical supply voltage distortion present in the network, the proposed control strategy improves the current tracking performance and reduces the line current harmonics, when compared with conventional control strategies. Experimental results, both under purely sinusoidal and distorted supply voltages, validate the effectiveness of the proposed control strategy.

Classical and advanced hybridization methods are employed in the control literature to calibrate the tuning parameters of internal model control (IMC) and proportional-integral-derivative (PID) controllers. This paper presents an alternative tuning design for the generalized predictive controller (GPC) that is based on both the positional process model and cost function. The proposed method involves the selection of an integral polynomial weighting filter for reference and output signals to deal with reference tracking, disturbance rejection, model-plant mismatch (MPM), minimum control energy and closed-loop robustness. The filter positional GPC (FP-GPC) obtained is transformed into a two-degree-of-freedom polynomial filtered RST structure and then into filtered internal model control (F-IMC) and PID controllers. Also, a multi-objective optimization based on genetic algorithm is applied to tune the filter parameters. Numerical and experimental essays show the effectiveness of the proposed control methodology.

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.

This paper is devoted to proposing a simple method to tune the parameters of a fractional order PI (FOPI) controller. The studied control scheme is a fractional filtered Smith predictor (FFSP) structure, which can compensate for the inherently long dead time of the industrial processes. The proposed frequency domain scheme would be a practical approach to compensate the stable processes, which can be modeled by a fractional order counterpart of First Order Plus Dead Time (FOPDT) transfer function. Two fractional order filters are also used to improve the reference tracking and to enhance the robustness of the compensated system. The obtained results of practical implementation on a pressure plant and the comparison results are given to demonstrate the effectiveness of the proposed technique.

In this paper a linear Model Predictive Control (MPC) based controller for the path tracking of a given trajectory is proposed, which generates suitable references for the dynamical vehicle states. The goal of the path tracking is to achieve good performance on slippery conditions. The equations describing the evolution of the path are linearized in order to obtain a suitable model, and linear constraints on the produced reference states are applied based on the prior knowledge of the reachable equilibrium states which characterize steady-state cornering. A previously proposed low-level LQR-ISM (Integral Sliding Mode) controller is exploited for reference tracking, where the ISM component is required in order to enhance the robustness with respect to the several approximations introduced by the linearized models. IPG-CarMaker, a high-fidelity vehicle dynamics simulation software, is used for the validation. The performance is verified on a wet asphalt track characterized by segments of different curvature, and compared against the CarMaker driver.

A two wheeled inverted pendulum (TWIP), is an unstable system with highly non-linear dynamics. Therefore, it is necessary to design controllers that can react properly to different kinds of external disturbances, keeping tracking accuracy and robustness. The aim of this paper is tuning a Linear Quadratic Regulator (LQR) discrete controller using genetic algorithms (GA) for improve the reference tracking performance. The GA consider the ISE index in the reference tracking for the fitness function in order to obtain the optimal LQR controller parameters Q and R and state-feedback gains. Finally, test simulations are performed to compare the behavior of traditional LQR and the extended LQR-GA controller.

In this paper, variable structure control (VSC) with quasi-sliding mode for reduced chattering is proposed for voltage controlled three phase-three wire nine switch converter (NSC) with LCL filter. The NSC is used in general to replace the two independent three phase power converters for the independent control of two sets of three phase voltages with different amplitude, frequency and phase shift. The modelling of the proposed system is done with the detailed explanation for the selection of an extra degree of freedom. The decoupling approach is used to structure the sliding surfaces from which the switching methodologies are developed to make system to track references. The effectiveness of the reference tracking is validated through simulation studies.

In this paper, a computationally low-demanding control framework is presented to deal with the reference tracking and collision avoidance problems for a system of heterogeneous Unmanned Vehicles (UVs). The proposed solution is capable of guaranteeing absence of collisions in scenarios where the UVs are subject to disturbances, state and input constraints, and where reference trajectories might intersect. The proposed methodology exploits set-theoretic predictive arguments to coordinately design local tracking controllers and a centralized collision avoidance module. A simulation example, involving two UVs is performed to better explain the main features of the proposed framework.

A new hybrid scheme is proposed for the blood glucose (BG) regulatory system in type-l diabetes mellitus (T1DM) patients. Some of hybrid glucose-insulin controllers have combined the artificial intelligence such as fuzzy logic and metaheuristic algorithm with well-known Palumbo model. However, most of those approaches have focused on the glucose reference tracking, and the glucose sensor errors as well as various unmeasurable disturbances have not been well studied. In this paper, a hybrid method based on higher order sliding mode (HoSM) and unscented Kalman filter (UKF) has been presented. The high performance of the proposed hybrid scheme for desired BG level tracking and chattering reduction in presence of daily glucose level disturbances has been verified.

this paper presents a comparison between Proportional Integral (PI) and Proportional Resonant (PR) current controllers used in Single-phase Grid Connected Photovoltaic (PV) Inverters.The reference tracking with steady-state errors is enhanced with the second solution.The simulation results of the system shows that the PR controller with modified compensator has a good transient response compared to the conventional PI controller

Summary The rejection of unknown periodic disturbances in the plant output through adaptive feedback has been an active area of research. In most successful efforts, it is assumed that the plant mo...

We propose a control design for a constrained linear system to track reference signals within a given bounded error. The admissible reference signals are generated as output trajectories of a reference generator, which is a constrained linear system driven by unknown bounded inputs. The controller has to track the reference signals and to never violate a given tracking error bound, while satisfying state and input constraints, for any admissible reference. The design is based on a model predictive controller (MPC) enforcing a polyhedral robust control invariant set defined by the system and reference generator models and constraints. We describe an algorithm to compute the robust control invariant set and how to design the tracking MPC law that guarantees satisfaction of the tracking error bound and of the system constraints, and achieves persistent feasibility. We demonstrate the proposed method in two case studies.

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.

International audience; This paper addresses the problem of tracking a constant BIS reference during anesthesia taking into account control input saturation, multiple time scale dynamics and inter-patient variability. LMIs conditions are proposed to compute a state feedback involving an integral action to ensure a perfect output tracking. These conditions guarantee that the trajectories of the closed-loop system remain in an invariant ellipsoidal set. The theoretical conditions are numerically illustrated on a set of adult patients as a proof of principle.

This paper presents a new Direct Instantaneous Torque Control (DITC) developed to minimize the inherent torque ripple of an aerospace switched reluctance motor (SRM). In addition to good performance, the reliability and robustness of the overall system are of great concern in aerospace and other safety-critical applications. By taking that into consideration, a DITC, that is less prone to the common erroneous operating conditions associated with SRM control such as measurement errors and noise, integration errors and parameter variation errors, is developed and compared with the traditional current chopping control (CCC). The proposed control scheme involves simple torque estimation, distribution, and regulation strategies. The results obtained show that both the proposed DITC and the traditional CCC methods ensure accurate reference tracking. However, the proposed control exhibits better torque ripple reduction capability without compromising the system’s reliability and robustness

In this paper, the reference tracking problem for a class of flexible hypersonic vehicles, whose dynamics vary significantly as flight states changes, is investigated via a novel switched linear parameter-varying (LPV) framework. Specifically, ranges of velocity and altitude are divided into several partitions, and the flexible hypersonic vehicle dynamics is modeled as a LPV system in each partition. Then the switched LPV model for the underlying system is obtained over a wide range of operating conditions. Switched LPV tracking controllers based on the developed model are established under mode independent/dependent persistent dwell time (PDT/MPDT) switching signals, respectively. Compared with the conventional mode independent/dependent average dwell time (ADT/MADT) switching signals, the proposed PDT/MPDT switching signals can address some more general flight variations, such as slow maneuvers and frequent rapid maneuvers coexist in the same flight mission. Furthermore, stringent transient and steady-state performance and a guaranteed non-weighted H ∞ performance are achieved with the aid of multiple Lyapunov-like functions. A simulation is used to illustrate the designed controller via two proposed switching signals.

This paper presents the study of linear Offset-Free Model Predictive Control (OF-MPC) for an Active Magnetic Bearing (AMB) application. The method exploits the advantages of classical MPC in terms of stability and control performance and, at the same time, overcomes the effects of the plant-model mismatch on reference tracking. The proposed approach is based on a disturbance observer with an augmented plant model including an input disturbance estimation. Besides the abovementioned advantages, this architecture allows a real-time estimation of low-frequency disturbance, such as slow load variations. This property can be of great interest for a variety of AMB systems, particularly where the knowledge of the external load is important to regulate the behavior of the controlled plant. To this end, the paper describes the modeling and design of the OF-MPC architecture and its experimental validation for a one degree of freedom AMB system. The effectiveness of the method is demonstrated in terms of the reference tracking performance, cancellation of plant-model mismatch effects, and low-frequency disturbance estimation.

This paper presents an algorithm and a prototype system for tracking the spatial orientation of rigid objects. The system is based on geometric and photometric data captured with a range-imaging camera and a color camera, integrated into a single mobile device. The accuracy of the system is evaluated in the experiments, by measuring the orientation of two physical objects, using a commercial optical localizer as a reference tracking system. The mean absolute differences of the measured orientation angles between the tested system and the reference are between 1.41 and 3.4 degrees.

This paper shows an online MTPA control which considers not only magnetic saturation but also cross-coupling effects. In automotive applications, torque accuracy and high efficiency operation are important issues. It can be dealt as a constrained optimization problem to satisfy both torque reference tracking and loss minimizing operation. Nonlinear simultaneous equations are derived from Lagrange multiplier method, which could be solved by numerical algorithms. Among them, Levenberg-Marquardt algorithm is employed to guarantee a robust calculation of optimal current references. It is optimized to alleviate calculation burden while maintaining the stability of the proposed algorithm. The feasibility of the proposed method is verified under various operating conditions by simulation and experimental results. Through the proposed algorithms, accurate MTPA control is achieved under not only unsaturated but also highly-saturated operating conditions.

This paper presents a robust state space sinusoidal reference tracking controller that is able to estimate the overall friction faced by the platform attached to a linear voice coil motor. The system proposed is able to estimate overall friction faced by the platform attached and is also able to compensate for it. This paper discusses the various simple model of friction found in literature and uses them as a basis for the importance of friction compensation. Further analysis is provided on the formation of the sinusoidal reference tracking controller which is followed by the overall augmented system. A practical implementation of the systems is also provided which is used to obtain the results for the friction estimation. The results found from the implementation of the system are compared to the free-fall method used to estimate the Coulomb and viscous friction parameters.

This paper addresses the problem of actuators saturation that occur when one applies a moving mass concept to control the attitude of a mul- tirotor UAV. In particular, we propose to combine the moving mass control (MMC) with rotors' variations in a paradigm known as a mid- ranging control. We show that this control structure ensures reference tracking and disturbance rejection with the moving masses operating in the middle of their range, which eventually reduces the possibility to violate their saturation limits. We also address the stability and design of the proposed controller by employing Routh-Hourwitz criterion and root- locus analysis. The controller is verified within a simulation environment, where we test its performance and compare it with a basic MMC concept under various disturbances. Finally, we present experimental results that we obtained with a modified ArduCopter vehicle, which serves as an experimental platform for the MMC verification.

The main goal of this paper is to design a state feedback control that makes a point mass track a non-Zeno reference trajectory in a planar billiard. This objective is achieved by first determining a continuous-time dynamical model, whose trajectories approximate the solutions of the hybrid system. Hence, a state feedback that makes the hybrid system track a reference trajectory of the continuous-time one is proposed. Finally, these two techniques are combined in order to find a state feedback that achieves tracking of the trajectories of the unforced system. Examples are reported all throughout the paper to illustrate the theoretical results.

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.

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 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.

In this paper we present two linear filtered positional GMV control designs using the indirect and repetitive control approaches to cope with setpoint changes and step or periodic disturbance rejection. Also, an optimization algorithm is applied to tune the filter parameters. Numerical and practical essays with nonlinear models are shown to verify the efficiency, stability and robustness when moving the operating condition of the processes.

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.