Multivariable Model Reference Adaptive Control Research Articles

Robust Adaptive Control of the Offshore Produced Water Treatment Process: An Improved Multivariable MRAC-Based Approach

The application of deoiling hydrocyclone systems as the downstream of three-phase gravity separator (TPGS) systems is one of the most commonly deployed produced water treatment processes in offshore oil and gas production. Due to the compact system’s complexity and tailor-made features, it is always challenging to develop some optimally coordinated control solution for the coupled hydrocyclone and TPGS systems. It is obvious that coordinated control can better fulfill legislative discharge regulation by robustly maintaining high separation efficiencies. This paper presents a new control solution for a set of integrated hydrocyclone and TPGS systems by applying an improved multi-variable model reference adaptive control (MV-MRAC) approach with the aim of achieving both asymptotic output tracking and unknown disturbance rejection. A robust MV-MRAC controller design is proposed based on a control parameterization derived from a factorization of a high-frequency gain matrix Kp=LDS as a product of three matrices, where L represents unity lower triangular, D=sign(D) represents diagonal, and S represents positive definite, and a teaching–learning-based optimization (TLBO) algorithm for optimizing the adaption rates. The developed solution is analyzed and compared with a commonly deployed PI control solution on a model that is derived from a lab-scale produced water treatment process. This simulation study demonstrates the promising potential of the proposed control solution compared with the currently deployed PI control solution.

Event-triggered robust model reference adaptive control for drag-free satellite

Aiming at the requirement of bounded disturbance suppression for low-frequency space gravitational wave detection satellite, a robust model reference adaptive drag-free control scheme is proposed in this paper via linear matrix inequalities (LMIs) approach. The multivariable model reference adaptive control (MRAC) scheme is applied to the drag-free control system with parameter uncertainties, which realizes the adaptive tracking to the reference state. The LMI system is established as an adaptive compensation term, which provides robustness against nonlinear disturbances. To reduce the communication burden of the actuation information and further save the total energies, an event-triggered mechanism (ETM) is introduced, with both the actuation inputs and the adaptive laws of the feedback gains updated only at the triggering time instants. The ultimately uniformly boundedness of the closed-loop signals is proved by Lyapunov analysis, with each system state convergence. From the feasibility analysis, Zeno behavior can be further proved to be strictly excluded. The numerical simulation verifies that the proposed scheme has efficient robustness to nonlinear disturbances with low energy cost, and achieves good effect in response to the requirements of space gravitational wave detection mission.

Partial State Feedback MRAC Based Reconfigurable Fault-Tolerant Control of Drag-Free Satellite With Bounded Estimation Error

Aiming at the ultra-precision and ultra-stable requirements of drag-free control in space detection missions, a multivariable model reference adaptive control (MRAC) scheme is proposed in this paper based on partial observation state, to provide adaptive suppression of uncertain disturbances and improve detection accuracy. The MRAC scheme utilizes model output matching with partial state containing uniform and bounded observation error, and estimates the unknown state parameters through the adaptive law and high-frequency gain decomposition. In response to the actuator bias fault of the drag-free satellite, a set of state error iterative convergence sequence in the actuator loop is established based on the sequence Lyapunov analysis, which is further introduced into the reconfiguration control input to achieve the fault-tolerant target without changing the nominal controller. Through the Lyapunov stability analysis, the convergence of the closed-loop system states in the presence of actuator faults and observation errors is obtained. Numerical simulation results for a 6-DOF drag-free control system demonstrate the effectiveness of the proposed MRAC-based reconfigurable fault-tolerant control scheme.

Corrigendum to “Multivariable Model Reference Adaptive Control of an Industrial Power Boiler Using Recurrent RBFN”

Corrigendum to “Multivariable Model Reference Adaptive Control of an Industrial Power Boiler Using Recurrent RBFN”

Multivariable Model Reference Adaptive Control of an Industrial Power Boiler Using Recurrent RBFN

In industrial steam systems, the process requires a specific pressure, and the maximum permissible operating pressure is different. If the inlet steam pressure to the steam consuming equipment exceeds the operating pressure, it may cause hazards. Therefore, the more precise control of the boiler pressure is important. Since we are dealing with a nonlinear, time-varying, and multivariable system, the control method must be designed to handle this system well. Most of the methods proposed so far are either not physically feasible or the system has considered very simple. Therefore, in this paper, while modeling the boiler and its pressure relations more precisely, we will introduce a recurrent type-2 fuzzy RBFN-based model reference adaptive control system with various uncertainties so that the uncertainty and inaccuracy of the model can be compensated. The experimental results prove the efficiency of the proposed method in boiler control.

Partial-state feedback multivariable MRAC and reduced-order designs

This paper develops a new model reference adaptive control (MRAC) framework using partial-state feedback for solving a multivariable adaptive output tracking problem. The developed MRAC scheme has full capability to deal with plant uncertainties for output tracking and has desired flexibility to combine the advantages of full-state feedback MRAC and output feedback MRAC. With such a new control scheme, the plant-model matching condition is achievable as with an output or state feedback MRAC design. A stable adaptive control scheme is developed based on LDS decomposition of the plant high-frequency gain matrix, which guarantees closed-loop stability and asymptotic output tracking. The proposed partial-state feedback MRAC scheme not only expands the existing family of MRAC, but also provides new features to the adaptive control system, including additional design flexibility and feedback capacity. Based on its additional design flexibility, a minimal-order MRAC scheme is also presented, which reduces the control adaptation complexity and relaxes the feedback information requirement, compared to the existing MRAC schemes. New results are presented for plant-model matching, error model, adaptive law and stability analysis. A simulation study of a linearized aircraft model is conducted to demonstrate the effectiveness and new features of the proposed MRAC control scheme.

Seamless Dynamics for Wild-Frequency Active Rectifiers in More Electric Aircraft

In this article, a seamless dynamics controller for wild-frequency active rectifiers in more electric aircraft (MEA) is presented. The novelty of the proposed control scheme resides in its ability to seamlessly regulate the output dc-bus voltage and input reactive power in the presence of rapid frequency changes. These smooth dynamics are achieved through a multivariable direct model reference adaptive control (MRAC) formulation, which allows the gains of the controller to adjust themselves to the wild-frequency operation of the MEA power generation. The validity and performance effectiveness of the proposed seamless dynamics control scheme is verified experimentally through a laboratory-scaled three-phase 1.5-kW 270-V SiC two-level voltage-source-converter using a variable-frequency programmable grid emulator. Moreover, a traditional proportional-integral controller is implemented experimentally with the same converter as a benchmark to highlight the merits of the proposed MRAC.

Multivariable adaptive control based consensus flight control system for UAVs formation

Formation flight contributes to improving the attack, reconnaissance and survival ability of the multiple unmanned aerial vehicles (UAVs). This paper studies a multivariable adaptive control based consensus flight method for UAVs formation. A majority of existing research is focused on the leader-following consensus problem assuming that only the parameters of followers are uncertain. However, they do not consider the leader dynamic uncertainty and the unknown external disturbances. Therefore, this paper addresses the problem of the UAVs consensus flight control with parametric uncertainties and unknown external disturbances for both the leader and follower. A multivariable model reference adaptive control (MRAC) based consensus flight control scheme is designed for UAVs formation, which enables the follower UAV to track the leader UAV. The stability of the multivariable MRAC based consensus flight control system is analyzed. Simulation results show that the proposed adaptive consensus flight control scheme has stronger robustness and adaptivity than the fixed control scheme.

A multivariable adaptive control scheme for automatic carrier landing of UAV

This paper studies a multivariable model reference adaptive control (MRAC) scheme for the automatic carrier-landing control problem of unmanned aerial vehicles (UAVs) with system dynamics of nonlinearity, multivariable coupling and parametric uncertainty. A complete automatic carrier landing system (ACLS) for carrier-based UAVs is developed, which consists of a guidance subsystem and a flight control subsystem. The MRAC scheme is based on a state feedback for output tracking framework with relaxed design conditions, which guarantees the reference glide slope tracking. Simulation results of a nonlinear UAV model demonstrate that the multivariable MRAC based ACLS has a better carrier-landing performance than a fixed control based ACLS.

Improved Adaptive Fault-Tolerant Control for a Quadruple-Tank Process with Actuator Faults

In this paper, a modified output–feedback multivariable model reference adaptive control (MRAC) scheme is proposed for a valve-actuated quadruple-tank process with actuator faults. First, a controller parametric model with unknown plant parameters is established, and actuator parameters are determined using a unified actuator fault model. Second, some existing proper modifications that allow MRAC to gain the ability of actuator fault compensation are given. Then final adaptive fault compensation controller is constructed by utilizing existing results and a new adaptation law that is based on a method first used for optimization purposes. The resulting controller allows increasing the learning rate of the adaptation algorithm without causing high-frequency oscillation in control signal and eventually leads to a faster smooth postfault transient response and less reference model tracking error. The stability of the proposed controller is proved such that all closed-loop signals are bounded and tracking erro...

Automatic landing system design via multivariable model reference adaptive control

The landing of a civil transport aircraft is one of the most critical phases due to parametric uncertainties and strong crosswind conditions. In this paper, separate controllers are designed for longitudinal and lateral-directional channels for the landing phase, which is divided into the final approach, flare, and decrab. A multivariable model reference adaptive control scheme is implemented with state feedback for output tracking. The safety and flight performance of the autolanding control system are demonstrated through Monte Carlo simulations of a nonlinear civil transport aircraft model.

Multivariable adaptive distributed leader-follower flight control for multiple UAVs formation

ABSTRACTThe Unmanned Aerial Vehicles (UAVs) become more and more popular due to various potential application fields. This paper studies the distributed leader-follower formation flight control problem of multiple UAVs with uncertain parameters for both the leader and followers. This problem has not been addressed in the literature. Most of the existing literature considers the leader-follower formation control strategy with parametric uncertainty for the followers. However, they do not take the leader parametric uncertainty into account. Meanwhile, the distributed control strategy depends on less information interactions and is more likely to avoid information conflict. The dynamic model of the UAVs is established based on the aerodynamic parameters. The establishment of the topology structure between a collection of UAVs is based on the algebraic graph theory. To handle the parametric uncertainty of the UAVs dynamics, a multivariable model reference adaptive control (MRAC) method is addressed to design the control law, which enables follower UAVs to track the leader UAV. The stability of the formation flight control system is proved by the Lyapunov theory. Simulation results show that the proposed distributed adaptive leader-following formation flight control system has stronger robustness and adaptivity than the fixed control system, as well as the existing adaptive control system.

Fractional‐order multivariable composite model reference adaptive control

SummaryA novel multivariable composite model reference adaptive control scheme is developed for multivariable fractional‐order systems with arbitrary relative degree. Firstly, by introducing right gain matrix to substitute left gain matrix, the stringent symmetry assumption is no longer required. The design procedures of controller with certain and uncertain high‐frequency gain matrix are then provided, respectively. The (robust) stability of the resulting closed‐loop control system is investigated by indirect Lyapunov method. It is shown that the composite model reference adaptive control can achieve better performance on output tracking than that of model reference adaptive control. Finally, the effectiveness and applicability of the proposed control scheme are demonstrated in 3 numerical examples.

Combustion Control of Diesel Engine using Feedback Error Learning with Kernel Online Learning Approach

This paper shows how to design Multivariable Model Reference Adaptive Control System (MRACS) for “Tokyo University discrete-time engine model” proposed by Yasuda et al (2014). This controller configuration has the structure of “Feedback error learning (FEL)” and adaptive law is based on kernel method. Simulation results indicate that “kernelized” adaptive controllers can improve the tracking performance, the speed of convergence and the robustness to disturbances.

A discrete-time multivariable MRAC scheme applied to a nonlinear aircraft model with structural damage

In this paper, a new discrete-time multivariable model reference adaptive control (MRAC) scheme is developed and its application to continuous-time nonlinear systems with structural damage is studied, for which several key technical issues are addressed. The relation of the infinite zero structures of the continuous-time nonlinear system and the linearized discrete-time system is established. Invariance properties of the system infinite zero structure and control gain matrix of the linearized discrete-time system under damage are studied for an aircraft flight control application. Desired system stability and asymptotic output tracking are ensured for the linearized discrete-time system with dynamics and damage uncertainties. A discrete-time linearization-based control design is constructed for control of a high-fidelity continuous-time nonlinear aircraft model with uncertain dynamics and structural damage. Simulation results show the desired system performance and demonstrate the effectiveness of the developed discrete-time adaptive control method for the nonlinear aircraft system model. ∇

MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft.

This paper develops a novel state-tracking multivariable model reference adaptive control (MRAC) technique utilizing prior knowledge of plant models to recover control performance of an asymmetric structural damaged aircraft. A modification of linear model representation is given. With prior knowledge on structural damage, a polytope linear parameter varying (LPV) model is derived to cover all concerned damage conditions. An MRAC method is developed for the polytope model, of which the stability and asymptotic error convergence are theoretically proved. The proposed technique reduces the number of parameters to be adapted and thus decreases computational cost and requires less input information. The method is validated by simulations on NASA generic transport model (GTM) with damage.

Lyapunov Design of Multivariable MRAC via Generalized Passivation

AbstractA Lyapunov design of multiple input, multiple output (MIMO) model‐reference adaptive control (MRAC) systems is proposed using new generalized passivity concepts based on WSPR and WASPR properties. The new design avoids control overparameterization and leads to the simplest unnormalized gradient algorithm by means of a passivating multiplier. To this end, a necessary and sufficient condition on the high frequency gain matrix to achieve the WASPR property is established. This condition is referred to as Positive Diagonal Jordan (PDJ) form. Based on the robustness WSPR and WASPR properties, a systematic determination of a robust passivating matrix multiplier is then presented. The advantages of the new design are illustrated by numerical simulation including a robotics adaptive visual servoing problem and a 4‐input‐4‐output dynamic system. © 2014 Chinese Automatic Control Society and Wiley Publishing Asia Pty Ltd

Multivariable adaptive control: A survey

Adaptive control is a control methodology capable of dealing with uncertain systems to ensure desired control performance. This paper provides an overview of some fundamental theoretical aspects and technical issues of multivariable adaptive control, and a thorough presentation of various adaptive control schemes for multi-input–multi-output systems, literature reviews on adaptive control foundations and multivariable adaptive control methods, and related technical problems. It covers some basic concepts and issues such as certainty equivalence, stability, tracking, robustness, and parameter convergence. It discusses some of the most important topics of adaptive control: plant uncertainty parametrization, stable controller adaptation, and design conditions for different adaptive control schemes. The paper also presents a detailed study of well-developed multivariable model reference adaptive control theory and design techniques. It provides an introduction to multivariable adaptive pole placement and adaptive nonlinear control, and it concludes by identifying some open research problems.

Adaptive Actuator Failure and Structural Damage Compensation of NASA Generic Transport Model

This paper studies design and evaluation of a multivariable model reference adaptive control (MRAC) scheme for aircraft systems under simultaneous actuator failures and structural damage. A key design condition–system infinite zero structure is investigated for nominal and posthazard aircraft systems and the invariance of this essential condition is concluded under realistic failure and damage conditions. The multivariable model reference adaptive control scheme is developed to ensure stability and asymptotic output tracking for the aircraft in the presence of uncertain actuator failures and structural damage. The developed fault-tolerant control design is evaluated by a high-fidelity nonlinear aircraft model–the NASA generic transport model.

Discrete‐time multivariable robust model reference adaptive control based on Kp = LDS factorization: an input–output approach

SUMMARYA direct scheme of robust model reference adaptive control is reinvestigated, in an input–output approach, for a large class of discrete‐time multivariable systems with unmodeled dynamics and bounded disturbances. Compared with the existing results, in virtue of a high‐frequency gain matrix factorization, the assumptions required in the scheme are further relaxed without overmuch complicating the controller structure, and a permissible range of the gain parameter in a modified adaptive algorithm is clearly specified. Moreover, paralleling the continuous‐time theoretic framework, robust stability and robust tracking performance are analyzed by using the multivariable versions of some important technical lemmas, such as an exponentially weighted norm‐relation lemma and two swapping lemmas. Copyright © 2012 John Wiley & Sons, Ltd.