Model reference adaptive controllers with improved performance for applications in LCL-filtered grid-connected converters

This paper presents a discrete-time adaptive current controller for grid-connected pulse width modulation voltage source converters with LCL filter. The main attribute of the proposed current controller is that, in steady state, the damping of the LCL resonance does not depend on the grid characteristic since the adaptive feedback gains ensure a predefined behavior for the closed-loop current control. An overview of model reference adaptive state feedback theory is presented aiming to give the reader the required background for the adaptive current control design. The digital implementation delay is included in the model, and the stability concerning the variation of the grid parameters is analyzed in detail. Furthermore, current distortions due to the grid background voltage are rejected without using the conventional stationary resonant controllers or the synchronous proportional-plus-integral controllers. Simulation and experimental results are presented to validate the analysis and to demonstrate the good performance of the proposed controller for grid-connected converters subjected to large grid impedance variation and grid voltage disturbances.

Distributed model reference adaptive containment control of heterogeneous multi-agent systems with unknown uncertainties and directed topologies

MODEL REFERENCE ADAPTIVE ESTIMATION AND CONTROL APPLIED TO A CONTINUOUS FLOW FERMENTATION PROCESS

In an effort to increase the efficiency and power density of electric vehicles and aircraft, the automobile and aerospace industries are adopting variable-speed generators as part of the powertrain. Herein, the engine directly drives a permanent magnet synchronous machine, which generates a variable-frequency/amplitude output ac-voltage. More specifically, this unique ac-voltage profile serves as the input for an ac-dc power converter that energizes the main dc-bus of the powertrain. In this paper, a smart active rectifier for hybrid/all-electric powertrains is presented. A direct model reference adaptive control (MRAC) scheme is utilized to address the rapid changes in amplitude and frequency while regulating the dc-bus voltage at unity power factor. Moreover, the MRAC requires minimal tuning due to its capability of adjusting its gains adaptively with the input voltage variations. As a result, the MRAC exhibits seamless dynamics. The performance of the MRAC is verified experimentally under accelerating and decelerating variable-frequency/amplitude input voltage ramps using a laboratory-scale 2-kW 270-V SiC-MOSFET-based power converter supplied by a programmable grid emulator. Lastly, a classic proportional-integral (PI) control scheme is implemented experimentally with the same converter as a benchmark to highlight the merits of the proposed converter.

The nonignorable grid impedance is one of the characteristics of a weak grid. Meanwhile, the filter inductance also fluctuates with temperature or aging factors. The resonant frequency offset of an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LCL</i> filter will be caused by the change in power grid impedance and filter inductance. To this end, a strong adaptability control based on dual-division-summation (D-D-Σ) control is proposed in this article, which considers both the accuracy of grid-connected current tracking and resonance suppression under the variation of grid impedance and filter inductance. A full inductance parameter identification method based on an extended Kalman filter for simultaneously estimating filter inductance and grid impedance is proposed without remote voltage sampling. An enumeration method of the Routh array with less calculation is proposed. The algebraic relationship between control parameters and total inductance parameters is obtained by the Routh criterion. A gain correction method to realize strong adaptive control is proposed to deal with the variation of grid impedance and filter inductance. The experimental results prove the feasibility of D-D-Σ control in a three-phase <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LCL</i> -type grid-connected inverter under the variation of grid impedance and filter inductance.

This paper proposes a nonlinear fighter aircraft pitch rate tracking control scheme based on a Multiple Fuzzy Reference Model Adaptive Controller. The scheme consists of a direct Model Reference Adaptive Control (MRAC) with the reference model generated online using a fuzzy logic algorithm. The proposed control provides a soft multiple reference model switching for the aircraft multiple modes of operation, without prohibitive computational complexities or explicit system identification. In case of aircraft mode swings or sudden jumps, the reference model will be changed or generated based on the fuzzy logic scheme looking at the plant output and auxiliary parameters. Further the MRAC adaptively controls the plant and tracks the input pitch rate command signal effectively. The main advantage of the proposed scheme is the use of fuzzy generator to change the reference model as opposed to changing the controllers. The effectiveness of the proposed technique is assessed by simulation studies based on a 6- DOF high performance fighter aircraft undergoing pitch rate control at a wide range of operating contingencies.

In this paper, we introduce a direct fractional order adaptive control design based on model reference adaptive control (MRAC) structure for a class of commensurate fractional order linear systems with an arbitrary relative degree, and whose parameters are unknown. By generalising the application of standard direct MRAC strategy to plants described by fractional order models, we develop a fractional adaptive control scheme (FOMRAC) based on the output feedback. We also define an adaptation control law ensuring the stability of the closed-loop system and the good tracking of the reference trajectory. The asymptotic stability of the fractional order control system is proven using an extension of the Lyapunov theorem. Simulation results show the effectiveness of the proposed control method even for plants with model parametric variations and additive noises.

Presents the design of a robust direct model reference adaptive control (DMRAC) algorithm with focus on the satisfaction of an almost strictly positive real (ASPR) condition in the presence of plant unmodeled dynamics. These unmodeled dynamics are represented as either additive or multiplicative norm bounded perturbations in the transfer function. Frequency domain design conditions for a feedforward compensator have been developed utilizing the so-called Q parameterization. Illustrative examples are presented to validate the algorithm's use and applicability to control systems with unmodeled dynamics.

Recently, a class of adaptive control schemes called L1 Adaptive Control (L1-AC) has been proposed and widely advertised in aerospace control for achieving fast and robust adaptation and better performance than the existing Model Reference Adaptive Control (MRAC) Schemes. The L1-AC scheme is designed mainly for plants with full state measurement even though the name L1-AC has been used as an umbrella name for more general classes of plants. In this paper, we show that the L1-AC for plants with measured states is simply a standard MRAC with a low pass filter inserted in front of the control input. The analysis of the scheme is almost identical to that of MRAC as the same Lyapunov function is used to establish stability. The motivation for using the filter is the fact that for this class of adaptive schemes i.e. MRAC for plants with full state measurement the tracking error can be made arbitrarily small during transient by increasing the adaptive gain. A high adaptive gain however makes the differential equation of the adaptive law or estimator very stiff and leads to numerical problems that cause high oscillations in the estimated parameters leading to loss of adaptivity and deviations from what the theoretical properties dictate. The L1-AC approach mistook these numerical oscillations as properties of the adaptive scheme and inserted an input low pass filter in order to filter them out. While the filter helps reduce the frequency of these oscillations in the control law the price paid is high. First the numerical instability does not go away and the estimated parameters continue to oscillate without converging to the true parameters even in the presence of sufficiently rich signals. Second, due to the filter the tracking error is no longer guaranteed to converge to zero and the transient bounds for the tracking error also depend on the filter. As a result, the tracking properties of the L1-AC scheme are worse than what a simple MRAC scheme can generate with adaptive gains that could be high but away from the region of numerical instability. In addition, the presence of the filter reduces the robust stability margins in the presence of unmodeled dynamics and provides literally no advantage as simple robust MRAC techniques can solve the same problem achieving much better properties. The authors of L1-AC often compare the properties of a numerically unstable MRAC due to extremely high adaptive gains something that is prohibited by robust adaptive control with those of the filtered MRAC aka L1-AC to show that L1-AC performs better. Such comparisons are not only misleading but do not reveal what causes what giving the reader a false impression of a new theory that results to new performance and robustness improvements. The use of filters in adaptive control is not new and they are used to improve the performance and robustness of certain adaptive control schemes without destroying their ideal tracking properties. In this paper we present such a scheme that guarantees good transient performance and robustness and reveals the trade off between transient performance and robust stability.

Grid impedance estimation based hybrid islanding detection method for AC microgrids

Robust controller for grid-connected quasi-admittance source inverter for photovoltaic system

SUMMARY We study the convergence properties of a direct model reference adaptive control system by applying techniques from numerical analysis. In particular, a first-order discrete system coupled to a minimal control synthesis algorithm discretized by the one-step one-stage zero-order-hold sampling is studied. This results in a strongly non-linear dynamic system owing to the adaptive mechanism where stability at steady state, i.e. at the operating point, equates to successful control. This paper focuses on the convergence analysis of the overall dynamical system for understanding accuracy, stability and performance at steadystate. The local stability of the steady state solution is considered by linearizing the system in the neighbourhood of an operating point when the input is a step function. This analysis allows us to specify two gain space domains which define the region of local stability. Moreover, both the accuracy and the frequency-domain analyses give insight into the range of adaptive control weightings that results in optimal performance of the minimal control synthesis algorithm and also highlights a possible approach to a priori selection of the time step and adaptive weighting values. The effectiveness of the proposed analysis is further demonstrated by simulations and experiments on a first-order plant. Copyright # 2006 John Wiley & Sons, Ltd.

Owing to the imposed but undesired accelerations such as quadrature error and cross-axis perturbation, the micro-machined gyroscope would not be unconditionally retained at resonant mode. Once the preset resonance is not sustained, the performance of the micro-gyroscope is accordingly degraded. In this article, a direct model reference adaptive control loop which is integrated with a modified disturbance estimating observer (MDEO) is proposed to guarantee the resonant oscillations at drive mode and counterbalance the undesired disturbance mainly caused by quadrature error and cross-axis perturbation. The parameters of controller are on-line innovated by the dynamic error between the MDEO output and expected response. In addition, Lyapunov stability theory is employed to examine the stability of the closed-loop control system. Finally, the efficacy of numerical evaluation on the exerted time-varying angular rate, which is to be detected and measured by the gyroscope, is verified by intensive simulations.

Bivalirudin is a direct thrombin inhibitor used in the cardiac intensive care unit when heparin is contraindicated due to heparin-induced thrombocytopenia. Since it is not a commonly used drug, clinical experience with its dosing is sparse. In earlier work [1], we developed a dynamic system model that accurately predicts the effect of bivalirudin given dosage over time and patient physiological characteristics. This paper develops adaptive dosage controllers that regulate its effect to desired levels. To that end, and in the case that bivalirudin model parameters are available, we develop a Model Reference Control law. In the case that model parameters are unknown, an indirect Model Reference Adaptive Control scheme is applied to estimate model parameters first and then adapt the controller. Alternatively, direct Model Reference Adaptive Control is applied to adapt the controller directly without estimating model parameters first. Our algorithms are validated using actual patient data from a large hospital in the Boston area.

This paper is the second part of a pair of papers, which together present a direct model reference adaptive controller for discrete-time (including sampled-data) systems that are possibly nonminimum phase. The present paper and its companion paper (Part 1) together analyze that stability of the retrospective cost model reference adaptive controller.