In this paper, we present a new model reference adaptive control (MRAC) for flight control system of unmanned aerial vehicle (UAV) with uncertainties. The beginning of new algorithm design is combining direct MRAC wit...
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ISBN:
(纸本)9781509017386
In this paper, we present a new model reference adaptive control (MRAC) for flight control system of unmanned aerial vehicle (UAV) with uncertainties. The beginning of new algorithm design is combining direct MRAC with indirect adaptivecontrol, which is called composite model reference adaptive control (CMRAC). hi the indirect part, we use a reverse filter to filter the system input. Then, we employ sigma-modification to improve robustness of the flight control system. CMRAC with this kind of modification results in better tracking performance in the presence of parameter uncertainties and rapidly changing command input. Stability of the closed-loop system is formally proven by using Lyapunov theory. The effectiveness of the proposed algorithm is also illustrated through some simulations about the longitudinal dynamics of UAV.
In this paper a novel stability proof for direct model reference adaptive control is presented. Especially the case of redundant inputs is taken into account in order to consider actuator failures and even change in t...
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ISBN:
(纸本)9781467383455
In this paper a novel stability proof for direct model reference adaptive control is presented. Especially the case of redundant inputs is taken into account in order to consider actuator failures and even change in the control direction. To this end, a weaker assumption than positive definiteness of the control effectiveness matrix is formulated. Furthermore, it is shown that with a special choice of parameter initial values, the parameter set can be reduced avoiding overparameterization. The control law is applied to a hexarotor example and simulation results show the performance.
Based on the property of Nussbaum function and the approximation capability of neural networks, model reference adaptive control (MRAC) is presented for a class of nonlinear systems with unknown gain signs and unmodel...
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ISBN:
(纸本)9781467397148
Based on the property of Nussbaum function and the approximation capability of neural networks, model reference adaptive control (MRAC) is presented for a class of nonlinear systems with unknown gain signs and unmodeled dynamics. The approach eliminates the requirement for a priori knowledge of the control gain sign to be known by using the property of Nussbaum function. A dynamic signal is introduced to deal with the dynamic uncertainty problem. It is proved that all the signals in the closed-loop control system are semi-globally uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the proposed approach.
Abrupt structural damage poses significant challenges to the flight safety and flight quality of aircraft. In this paper,a direct model reference adaptive control(MRAC) method based on a linear parameter-varying(LPV) ...
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ISBN:
(纸本)9781509009107
Abrupt structural damage poses significant challenges to the flight safety and flight quality of aircraft. In this paper,a direct model reference adaptive control(MRAC) method based on a linear parameter-varying(LPV) model is proposed to recover the control performance and flight quality of damaged aircraft. The design of the controller is based on a polytopic LPV model and the higher order singular value decomposition(HOSVD) model reduction method to reduce the computational cost of identifying the damaged aircraft model. The proposed controller also extends a previous MRAC method which assumes the input matrix is unchanged for different damage cases by identifying an uncertain input parameter online. The developed LPV-MRAC method is validated by simulation on NASA's generic transport model(GTM) with left wing tip loss damage and shown to be capable of compensating the damage effects and restoring the aircraft's control performance shortly after the damage. The flight quality of the closed-loop damaged aircraft is also evaluated by the C-star criterion and shown to be within Class I under the proposed controller.
Multirotor unmanned aerial vehicles (MAVs) with the capability of interaction with their surroundings have recently received increasing attention. However, the rapid change parameters during flight present a challenge...
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ISBN:
(纸本)9781509020652
Multirotor unmanned aerial vehicles (MAVs) with the capability of interaction with their surroundings have recently received increasing attention. However, the rapid change parameters during flight present a challenge for the stable control of MAVs. In this paper, the baseline controller of a quadrotor is developed based on classical model reference adaptive control (MRAC) and an identifier is introduced to cope with the uncertainty in parameters. Specifically, the recursive least squares method with forgetting factor (FFRLS) is used to design the identifier. Both the baseline MRAC controller and augmented-MRAC controller are simulated to verify their effectiveness. The results show the improvements on stability in the presence of parameter change.
In order to maintain stability and satisfy operating constraints, the control system on the following vehicle needs information about the motion of preceding vehicle. A one-vehicle look-ahead control strategy is propo...
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In order to maintain stability and satisfy operating constraints, the control system on the following vehicle needs information about the motion of preceding vehicle. A one-vehicle look-ahead control strategy is proposed and will be investigated for this operation. A mathematical model for this control strategy is obtained and simulated. This paper describes the process of designing an adaptivecontroller gain for a road vehicle following system. This is done through simulations and is further discussed to find the effectiveness of the method.
In this paper, a novel Linear Matrix Inequality (LMI) condition for Uniform Ultimate Boundedness (UUB) of model reference adaptive control with sigma-Modification in the presence of unmatched parametric uncertainties ...
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ISBN:
(纸本)9781479964666
In this paper, a novel Linear Matrix Inequality (LMI) condition for Uniform Ultimate Boundedness (UUB) of model reference adaptive control with sigma-Modification in the presence of unmatched parametric uncertainties is presented. Due to the presence of unmatched uncertainties and due to the usage of the sigma-Modification, the control objective of tracking a referencemodel may only be achieved approximately. A formulation of the UUB condition within the LMI framework provides less conservative bounds on the tracking error. This feature also enables the extension of the UUB condition towards a gain synthesis procedure, which allows the explicit specification of tracking error requirements. For a low-order system, it is demonstrated that the theoretically guaranteed bound on the tracking error of the synthesized adaptivecontroller is not overly conservative.
In this paper, novel control and update laws for predictor-based model reference adaptive control for the case of overactuated systems are presented. A weaker assumption than positive definiteness of the control effec...
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ISBN:
(纸本)9781509035496
In this paper, novel control and update laws for predictor-based model reference adaptive control for the case of overactuated systems are presented. A weaker assumption than positive definiteness of the control effectiveness matrix is formulated. This allows to take actuator failures and even changes in the control direction into account. Furthermore, it is shown that the number of adaptive parameters can be reduced avoiding overparameterization. The control law is applied to a hexarotor example and simulation results demonstrate the control law's capabilities.
In this paper, the sensorless field-oriented control of asynchronous machine with squirrel-cage rotor (AMS) at the low-speed operation will be observed. The identification of rotor speed from adaptive flux error as we...
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ISBN:
(纸本)9781509061280
In this paper, the sensorless field-oriented control of asynchronous machine with squirrel-cage rotor (AMS) at the low-speed operation will be observed. The identification of rotor speed from adaptive flux error as well as the adaptation mechanism will be investigated. At first, the background of modelreferenceadaptive system (MRAS) will be revised. Later, the mathematical model of AMS in the stationary reference frame will be presented for decoupling of flux term. After that, the adaptive scheme based on relevant flux terms will be presented. One as a referencemodel and one another as an adaptivemodel. Finally, the simulation result based on defined parameters will be discussed.
This paper attempts to revisit primary control for an isolated microgrid system by using a model reference adaptive control technique for voltage reference tracking. The advantages of this technique lies in its simple...
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ISBN:
(纸本)9781509001286
This paper attempts to revisit primary control for an isolated microgrid system by using a model reference adaptive control technique for voltage reference tracking. The advantages of this technique lies in its simple gain feedback structure. The controller relies on relaxed model matching conditions between the referencemodel obtained from the concept of 'high-frequency-gain-matrix' and mathematical model of the system. The controller is derived in dq reference frame and prior knowledge of microgrid parameters becomes redundant. The simulation results demonstrate the improved performance of the proposed technique with respect to the existing techniques. model of induction motor is integrated with the state space model of the system to demonstrate the robustness of derived controller to unmodeled dynamics.
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