Guoliang Fan

Robust adaptive neural network control for a class of uncertain nonlinear systems with actuator amplitude and rate saturations

An adaptive controller which is designed with a priori consideration of actuator saturation effects and guarantees H^~ tracking performance for a class of multiple-input-multiple-output (MIMO) uncertain nonlinear systems with extern disturbances and actuator saturations is presented in this paper. Adaptive radial basis function (RBF) neural networks are used in this controller to approximate the unknown nonlinearities. An auxiliary system is constructed to compensate the effects of actuator saturations. Furthermore, in order to deal with approximation errors for unknown nonlinearities and extern disturbances, a supervisory control is designed, which guarantees that the closed loop system achieves a prescribed disturbance attenuation level so that H^~ tracking performance is achieved. Steady and transient tracking performance are analyzed and the tracking error is adjustable by explicit choice of design parameters. Computer simulations are presented to illustrate the efficiency of the proposed controller.

Adaptive trajectory tracking control system design for hypersonic vehicles with parametric uncertainty

A new nonlinear adaptive control scheme based on the immersion and invariance theory is presented to achieve robust velocity and altitude tracking for hypersonic vehicles with parametric uncertainty. The longitudinal dynamics of the hypersonic vehicle are first decomposed into velocity, altitude/flight-path angle, and angle of attack/pitch rate subsystems. Then a non-certainty-equivalent controller based on immersion and invariance, consisting of a control module and a parameter estimator, is designed for each subsystem with all the aerodynamic parameters unknown. The main feature of this method lies in the construction of the estimator, which is a sum of a partial estimate generated from the update law and an additional nonlinear term. The new term is capable of assigning appointed stable dynamics to the parameter estimate error. Stability analysis is presented using Lyapunov theory and shows asymptotical convergence of the tracking error to zero. Representative simulations are performed. Rapid and accurate command tracking is demonstrated in these numerical simulations, which illustrate the effectiveness and robustness of the proposed approach.

Immersion and Invariance-Based Output Feedback Control of Air-Breathing Hypersonic Vehicles

A new output feedback control design for robust velocity and altitude tracking of an air-breathing hypersonic vehicle (AHSV) is presented in this paper. The control scheme is performed on the assumption that only partial states of AHSV are measurable. The key idea is to employ the immersion and invariance approach to design globally asymptotically stable observers for the unmeasurable states. For controller design, the whole control architecture is constructed using dynamic surface control, based on the decomposition of the longitudinal dynamics of AHSV into velocity and altitude subsystems. Stability analysis is presented using the Lyapunov theory. Representative simulations are carried out on the high-fidelity model, which illustrate the effectiveness and robustness of the proposed scheme.

Direct adaptive type-2 fuzzy neural network control for a generic hypersonic flight vehicle

A direct adaptive interval type-2 fuzzy neural network (IT2-FNN) controller is designed for the first time in hypersonic flight control. The generic hypersonic flight vehicle is a multi-input multi-output system whose longitudinal model is high-order, highly nonlinear, tight coupling and most of all includes big uncertainties. Interval type-2 fuzzy sets with Gaussian membership functions are used in antecedent and consequent parts of fuzzy rules. The IT2-FNN directly outputs elevator deflection and throttle setting which make the GHFV track the altitude command signal and meanwhile maintain its velocity. The parameter adaptive law of IT2-FNN is derived using backpropagation method. The deviation of the control signal from the nominal dynamic inversion control signal is used as the reference output signal of IT2-FNN. The tracking errors of velocity and altitude are used as inputs of IT2-FNN. Tracking differentiator is designed to form an arranged transition process (ATP) of the command signal as well as ATP’s high-order derivatives. Nonlinear state observer is designed to get the approximations of velocity, altitude as well as their high-order derivatives. Simulation results validate the effectiveness and robustness of the proposed controller especially under big uncertainties.

Adaptive controller design for uncertain nonlinear systems with input magnitude and rate limitations

An adaptive controller for a class of multiple input-multiple-output (MIMO) uncertain nonlinear systems with extern disturbance and control input limitations is presented in this paper. The controller is designed with a priori consideration of input limitation effects, hence it can generate control signals satisfying input limitations. This controller uses adaptive radial basis function (RBF) neural networks to approximate the unknown nonlinearities. To compensate the effects of input limitations, an auxiliary system is constructed and used in neural network parameter update laws. Furthermore, in order to deal with approximation errors for unknown nonlinearities and extern disturbances, a supervisory control is designed, which guarantees that the closed loop system achieves a desired level H∞ tracking performance. The closed loop system performance is analyzed by Lyapunov method. Steady state and transient tracking performance index are established and can be adjusted by design parameters. Computer simulations are presented to illustrate the efficiency and tracking performance of the proposed controller.

Modeling for flying boats in regular wave

Although flying boats have been studied for over one hundred yeas, simulation of flying boats in waves and controllers designing for flying boats are still new research fields. After analyzing the forces acting on a flying boat, the flying boat is modeled in this paper as a special airplane. The forces from water are discussed and calculated by the 2-dimensional (2D) strip theory which is widely used in the force approximation of planing crafts. And the model is validated by experiment data, which shows the mathematical model has an acceptable performance on the motion-prediction of the flying boat in water with regular waves.

Autonomous reconfigurable flight control system design using control allocation

A new autonomous reconfigurable control scheme using control allocation is proposed in this paper. The shortcomings of other adaptive reconfigurable control methods, such as neural networks and sliding modes, are analyzed. On the other hand, the merits of control allocation based reconfiguration methods are given out. The dynamic control allocation method and a weighting matrix autonomous adjustment strategy are designed for control reconfiguration in the face of actuator damage faults. The validity of the proposed scheme is illustrated by the F18 HARV aircraft model. Simulation results show that autonomous reconfigurable flight control via control allocation can be carried out in the presence of actuator faults and satisfactory system performance can be obtained. The sequential quadratic programming method is used simultaneously in simulation for the sake of comparisons with the dynamic control allocation approach. Simulation results demonstrate the advantages of the latter for reconfigurable flight control.

Design of robust backstepping controller for unmanned aerial vehicle using analytical redundancy and extended state observer

In current flight control system (FCS) practice for unmanned aerial vehicles(UAVs), flight safety becomes more and more important in extreme weather or in the face of sensor and control effector failures. Flight safety is guaranteed traditionally by specifying functionally redundant control hardware. Compared with extra burden increased by hardware redundancy on UAV, design of analytical redundancy becomes attractive in recent years. This paper proposes a new hybrid design scheme of analytical redundance FCS, which is composed of analytical redundance, core flight control algorithm and uncertainties compensator. Analytical redundancy for attitude angle rates adopts reduced order nonlinear state observer method. The core backstepping flight controller realizes linearization and decoupling of the highly nonlinear and tightly coupled UAV model. For cancelling out uncertainties such as unmodeled dynamics and external disturbances, an extended state observer(ESO) compensator is designed to enhance the robustness of FCS. Pseudoinverse method is applied to establish the mapping between moments and multiple control surfaces. Numerical simulation shows that UAV equipped with the hybrid control scheme has good maneuverability, strong self-learning ability of compensating the unmodeled dynamics and enough robust stability against constraints of actuators.

Anti-crosswind Autolanding of UAVs based on Active Disturbance Rejection Control

The safe landing of unmanned aerial vehicles (UAVs) under various wind conditions has been a challenging task for decades. As the first step of landing, the longitudinal landing control has been well researched. But the lateral landing control, which is the second step of landing, is still facing a lot of challenges especially in crosswind conditions. In this paper, a UAV with wide span is researched. Due to its wide span, its wing tips may possibly touch the ground if the wings are not level at touchdown. An autolanding control scheme which consists of a longitudinal autolanding control system and a lateral autolanding control system is designed based on the Active Disturbance Rejection Control (ADRC) to enable the UAV to land safely in crosswind. The longitudinal autolanding control system is composed of a throttle control subsystem and an altitude control subsystem. The lateral autolanding control system is composed of a crabbing control subsystem and a decrabbing control subsystem. In contrast to previous methods, our approach can directly and real-timely estimate the UAV’s internal and external disturbances (e.g., system’s longitudinal and lateral couplings, wind disturbances) and then compensate for them. Simulations are done from the glide phase to the parking at the end of taxiing under wide range wind disturbances (e.g., constant crosswind, changing crosswind). Results show that our autolanding control scheme can land the UAV safely under wide range crosswind with the help of ADRC.

Automatic takeoff of unmanned aerial vehicle based on Active Disturbance Rejection Control

The safe takeoff of unmanned aerial vehicles (UAVs) under various wind conditions has been a challenging research for decades. We design an automatic takeoff control system based on the Active Disturbance Rejection Control (ADRC). The automatic takeoff control system consists of a taxiing control subsystem, an attack angle control subsystem, a pitch angle control subsystem, and a smooth switch control subsystem whose function is to switch the forenamed three subsystems smoothly without the jumps of the elevator actuator. In contrast to previous methods, our approach can directly and real-timely estimate the UAVs internal and external disturbances and then compensate for them. Simulation results show that our automatic takeoff control system can lead the UAV to takeoff safely under wide range wind disturbances (e.g., downburst, wind turbulence) with the help of ADRC.