New model reference adaptive control with input constraints

A new scheme of adaptive control is proposed for a class of linear time-invariant( LTI) dynamical systems,especially in aerospace,with matched parametric uncertainties and input constraints. Based on a typical and conventional direct model reference adaptive control scheme,various modifications have been employed to achieve the goal. "C omposite model reference adaptive control"of higher performance is seam-lessly combined with "positive μ-mod",which consequently results in a smooth tracking trajectory despite of the input constraints. In addition,bounded-gain forgetting is utilized to facilitate faster convergence of parameter estimates. The stability of the closed-loop systemcan be guaranteed by using Lyapunov theory.The merits and effectiveness of the proposed method are illustrated by a numerical example of the longitudinal dynamical systems of a fixed-wing airplane.

Robust adaptive control of hypersonic vehicle considering inlet unstart

In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight technology,hypersonic vehicles have been gradually moving to the stage of weaponization.During the maneuvers,changes of attitude,Mach number and the back pressure can cause the inlet unstart phenomenon of scramjet.Inlet unstart causes significant changes in the aerodynamics of AHV,which may lead to deterioration of the tracking performance or instability of the control system.Therefore,we firstly establish the model of hypersonic vehicle considering inlet unstart,in which the changes of aerodynamics caused by inlet unstart is described as nonlinear uncertainty.Then,an MRAC augmentation method of a linear controller is proposed and the radial basis function(RBF)neural network is used to schedule the adaptive parameters of MRAC.Furthermore,the Lyapunov function is constructed to prove the stability of the proposed method.Finally,numerical simulations show that compared with the linear control method,the proposed method can stabilize the attitude of the hypersonic vehicle more quickly after the inlet unstart,which provides favorable conditions for inlet restart,thus verifying the effectiveness of the augmentation method proposed in the paper.

A Sliding Mode Controller Based on Robust Model Reference Adaptive Proportional-integral Control for Stand-alone Three-phase Inverter

This paper proposes a sliding mode controller based on robust model reference adaptive proportional-integral(RMRA-PI)control for a stand-alone voltage source inverter(SA-VSI).The proposed controller has two control loops where the coefficients of PI controller are regulated by the adaptive sliding law.This method is used to regulate the output voltage of the inverter under different load conditions and uncertainty,and adapts the output to the reference model to reduce the total harmonic distortion(THD).In this paper,the stability of the proposed controller is proven by using Lyapunov's theory and Barbalet’s lemma.The proposed controller performs well in voltage regulation such as low THD under sudden load change and uncertainty.Also,the results of the proposed controller are compared with PI controller to show the effectiveness of the presented control system.

Inter-relationship between approximate dynamic inversion and MRAC augmented with proportional-integral controller

Approximate Dynamic Inversion (ADI) is basically an approximation of exact dynamic inversionor feedback linearisation, which converts a nonlinear system to an equivalent linear structure.This method can be widely applied for controlling minimum phase, nonaffine-in-control systems.For applying the ADI method, a fast dynamic subsystem for deriving explicit inversion of thenonaffine equation is required. With full state feedback, ADI may be expressed in the same way asa Proportional Integral (PI) controller with only knowledge of the sign of control effectiveness andalso without any approximation. The Model Reference Adaptive Controller (MRAC) augmentedwith the PI method is an adaptive control technique where the PI parameters are updated/tunedas per the control methodology based on the MRAC-Massachusetts Institute of Technology (MIT)rule so that the plant is capable to follow the reference model. The main objective of this paperis to find the relationship between ADI and MRAC augmented with a PI controller.

Novel Lyapunov-based rapid and ripple-free MPPT using a robust model reference adaptive controller for solar PV system

The technological,economic,and environmental benefits of photovoltaic(PV)systems have led to their wide-spread adoption in recent years as a source of electricity generation.However,precisely identifying a PV system’s maximum power point(MPP)under normal and shaded weather conditions is crucial to conserving the maximum generated power.One of the biggest concerns with a PV system is the existence of partial shading,which produces multiple peaks in the P–V characteristic curve.In these circumstances,classical maximum power point tracking(MPPT)approaches are prone to getting stuck on local peaks and failing to follow the global maximum power point(GMPP).To overcome such obstacles,a new Lyapunov-based Robust Model Reference Adaptive Controller(LRMRAC)is designed and implemented to reach GMPP rapidly and ripple-free.The proposed controller also achieves MPP accurately under slow,abrupt and rapid changes in radiation,temperature and load profile.Simulation and OPAL-RT real-time simulators in various scenarios are performed to verify the superiority of the proposed approach over the other state-of-the-art methods,i.e.,ANFIS,INC,VSPO,and P&O.MPP and GMPP are accomplished in less than 3.8 ms and 10 ms,respectively.Based on the results presented,the LRMRAC controller appears to be a promising technique for MPPT in a PV system.

Modified robust optimal adaptive control for flight environment simulation system with heat transfer uncertainty

To solve the rapid transient control problem of Flight Environment Simulation System(FESS) of Altitude Ground Test Facilities(AGTF) with large heat transfer uncertainty and disturbance, a new adaptive control structure of modified robust optimal adaptive control is presented.The mathematic modeling of FESS is given and the influence of heat transfer is analyzed through energy view. To consider the influence of heat transfer in controller design, we introduce a matched uncertainty that represents heat transfer influence in the linearized system of FESS. Based on this linear system, we deduce the design of modified robust optimal adaptive control law in a general way. Meanwhile, the robust stability of the modified robust optimal adaptive control law is proved through using Lyapunov stability theory. Then, a typical aero-engine test condition with Mach Dash and Zoom-Climb is used to verify the effectiveness of the devised adaptive controller. The simulation results show that the designed controller has servo tracking and disturbance rejection performance under heat transfer uncertainty and disturbance;the relative steady-state and dynamic errors of pressure and temperature are both smaller than 1% and 0.2% respectively. Furthermore,the influence of the modification parameter c is analyzed through simulation. Finally, comparing with the standard ideal model reference adaptive controller, the modified robust optimal adaptive controller obviously provides better control performance than the ideal model reference adaptive controller does.

Direct fractional order MRAC adaptive control design for a class of fractional order commensurate linear systems

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.