Fast Adaptive Robust Differentiator Based Robust-Adaptive Control of Grid-Tied Inverters with a New L Filter Design Method

In this research, a new nonlinear and adaptive state feedback controller with a fast-adaptive robust differentiator is presented for grid-tied inverters. All parameters and external disturbances are taken as uncertain in the design of the proposed controller without the disadvantages of singularity and over-parameterization. A robust differentiator based on the second order sliding mode is also developed with a fast-adaptive structure to be able to consider the time derivative of the virtual control input. Unlike the conventional backstepping, the proposed differentiator overcomes the problem of explosion of complexity. In the closed-loop control system, the three phase source currents and direct current (DC) bus voltage are assumed to be available for feedback. Using the Lyapunov stability theory, it is proven that the overall control system has the global asymptotic stability. In addition, a new simple L filter design method based on the total harmonic distortion approach is also proposed. Simulations and experimental results show that the proposed controller assurances drive the tracking errors to zero with better performance, and it is robust against all uncertainties. Moreover, the proposed L filter design method matches the total harmonic distortion (THD) aim in the design with the experimental result

Fault tolerant longitudinal aircraft control using non-linear integral sliding mode

Copyright © 2014 Institution of Engineering and Technology (IET)This study proposes a novel non-linear fault tolerant scheme for longitudinal control of an aircraft system, comprising an integral sliding mode control allocation scheme and a backstepping structure. In fault free conditions, the closed loop system is governed by the backstepping controller and the integral sliding mode control allocation scheme only influences the performance if faults/failures occur in the primary control surfaces. In this situation, the allocation scheme redistributes the control signals to the secondary control surfaces and the scheme is able to tolerate total failures in the primary actuator. A backstepping scheme taken from the existing literature is designed for flight path angle tracking (based on the non-linear equations of motion) and this is used as the underlying baseline controller in nominal conditions. The efficacy of the scheme is demonstrated using a high-fidelity aircraft benchmark model. Excellent results are obtained in the presence of plant/model uncertainty in both fault free and faulty conditions

An Adaptive Dynamic Surface Controller for Ultralow Altitude Airdrop Flight Path Angle with Actuator Input Nonlinearity

In the process of ultralow altitude airdrop, many factors such as actuator input dead-zone, backlash, uncertain external atmospheric disturbance, and model unknown nonlinearity affect the precision of trajectory tracking. In response, a robust adaptive neural network dynamic surface controller is developed. As a result, the aircraft longitudinal dynamics with actuator input nonlinearity is derived; the unknown nonlinear model functions are approximated by means of the RBF neural network. Also, an adaption strategy is used to achieve robustness against model uncertainties. Finally, it has been proved that all the signals in the closed-loop system are bounded and the tracking error converges to a small residual set asymptotically. Simulation results demonstrate the perfect tracking performance and strong robustness of the proposed method, which is not only applicable to the actuator with input dead-zone but also suitable for the backlash nonlinearity. At the same time, it can effectively overcome the effects of dead-zone and the atmospheric disturbance on the system and ensure the fast track of the desired flight path angle instruction, which overthrows the assumption that system functions must be known

Fractional Order Fault Tolerant Control - A Survey

In this paper, a comprehensive review of recent advances and trends regarding Fractional Order Fault Tolerant Control (FOFTC) design is presented. This novel robust control approach has been emerging in the last decade and is still gathering great research efforts mainly because of its promising results and outcomes. The purpose of this study is to provide a useful overview for researchers interested in developing this interesting solution for plants that are subject to faults and disturbances with an obligation for a maintained performance level. Throughout the paper, the various works related to FOFTC in literature are categorized first by considering their research objective between fault detection with diagnosis and fault tolerance with accommodation, and second by considering the nature of the studied plants depending on whether they are modelized by integer order or fractional order models. One of the main drawbacks of these approaches lies in the increase in complexity associated with introducing the fractional operators, their approximation and especially during the stability analysis. A discussion on the main disadvantages and challenges that face this novel fractional order robust control research field is given in conjunction with motivations for its future development. This study provides a simulation example for the application of a FOFTC against actuator faults in a Boeing 747 civil transport aircraft is provided to illustrate the efficiency of such robust control strategies

Backpropagating constraints-based trajectory tracking control of a quadrotor with constrained actuator dynamics and complex unknowns

In this paper, a backpropagating constraints-based trajectory tracking control (BCTTC) scheme is addressed for trajectory tracking of a quadrotor with complex unknowns and cascade constraints arising from constrained actuator dynamics, including saturations and dead zones. The entire quadrotor system including actuator dynamics is decomposed into five cascade subsystems connected by intermediate saturated nonlinearities. By virtue of the cascade structure, backpropagating constraints (BCs) on intermediate signals are derived from constrained actuator dynamics suffering from nonreversible rotations and nonnegative squares of rotors, and decouple subsystems with saturated connections. Combining with sliding-mode errors, BC-based virtual controls are individually designed by addressing underactuation and cascade constraints. In order to remove smoothness requirements on intermediate controls, first-order filters are employed, and thereby contributing to backstepping-like subcontrollers synthesizing in a recursive manner. Moreover, universal adaptive compensators are exclusively devised to dominate intermediate tracking residuals and complex unknowns. Eventually, the closed-loop BCTTC system stability can be ensured by the Lyapunov synthesis, and trajectory tracking errors can be made arbitrarily small. Simulation studies demonstrate the effectiveness and superiority of the proposed BCTTC scheme for a quadrotor with complex constrains and unknowns

Adaptive backstepping sliding mode control for heavy-weight airdrop operations

This paper proposes an adaptive backstepping sliding mode flight control method that is compatible with heavyweight cargo airdrop. The goal is to maintain the plane states during cargo extraction process, in the presence of uncertainties of both constant and time-varying types, as well as matched and unmatched types. A backstepping sliding mode flight control law with parameter adaptation is presented based on the plane-cargo dynamics in strict-feedback form. The control approach consists in having an adaptation law that approximates the disturbance and uncertain aerodynamic function, which is separated from the complex nonlinearities. Also, the adaptation algorithm with projection can bound the estimated function. This ensures the robustness of the controller against time-varying disturbance and uncertainty. The convergence performance and robustness property of the control law are proved by the Lyapunov theory. The control effect is evaluated on a transport plane performing a maximum load airdrop task in a number of simulation scenarios

Adaptive backstepping controller design of quadrotor biplane for payload delivery

Performance of the UAVs for a particular application can be enhanced by hybrid design, where take-off, hover, and landing happen like rotary-wing UAVs, and flies like fixed-wing UAVs. A backstepping controller and an adaptive backstepping controller are designed for trajectory tracking and payload delivery in a medical emergency or medical substance delivery like vaccine delivery in the presence of wind gust. Simulation results show that the backstepping controller effectively tracks the trajectory during the entire flight envelope, including take-off, hovering, the transition phase, level flight mode, and landing. A comparison between Backstepping, Integral Terminal Sliding Mode (ITSMC) and Adaptive Backstepping controllers for payload delivery show that the adaptive backstepping controller effectively tracks the altitude and attitude. ITSMC is capable of tracking the desired trajectory for a change in the mass but has sluggish response. The backstepping controller generates a steady-state error in altitude during the mass change in biplane-quadrotor.The publication of this article was funded by Qatar National Library.Scopu

Neural network control design for an unmanned aerial vehicle with a suspended payload

Unmanned aerial vehicles (UAVs) demonstrate excellent manoeuvrability in cluttered environments, which makes them a suitable platform as a data collection and parcel delivering system. In this work, the attitude and position control challenges for a drone with a package connected by a wire is analysed. During the delivering task, it is very difficult to eliminate the external unpredictable disturbances. A robust neural network-based backstepping sliding mode control method is designed, which is capable of monitoring the drone's flight path and desired attitude with a suspended cable attached. The convergence of the position and attitude errors together with the Lyapunov function are employed to attest to the robustness of the nonlinear transportation platform. The proposed control system is tested with a simulation and in an outdoor environment. The simulation and open field test results for the UAV transportation platform verify the controllers' reliability

Neural network control design for an unmanned aerial vehicle with a suspended payload

Unmanned aerial vehicles (UAVs) demonstrate excellent manoeuvrability in cluttered environments, which makes them a suitable platform as a data collection and parcel delivering system. In this work, the attitude and position control challenges for a drone with a package connected by a wire is analysed. During the delivering task, it is very difficult to eliminate the external unpredictable disturbances. A robust neural network-based backstepping sliding mode control method is designed, which is capable of monitoring the drone's flight path and desired attitude with a suspended cable attached. The convergence of the position and attitude errors together with the Lyapunov function are employed to attest to the robustness of the nonlinear transportation platform. The proposed control system is tested with a simulation and in an outdoor environment. The simulation and open field test results for the UAV transportation platform verify the controllers' reliability