Command-filtered Backstepping Research Articles

Photovoltaics literature survey (no. 149)

Photovoltaics literature survey (no. 149)

Command Filtered Model-Free Robust Control for Aircrafts With Actuator Dynamics

In this paper, a command filtered model-free robust (CFMFR) controller is proposed to regulate attitude angles of an aircraft with parameter uncertainties and disturbances to track the given reference signals. For the first subsystem of the controlled plant, the incremental nonlinear dynamic inversion (INDI) is applied to design incremental virtual control law. While the time-delayed control (TDC) method is used to design the control law by integrating sliding-mode technique considering the nominal value of the control effectiveness matrix is unknown. The adaption laws of the control gain are constructed by Lyapunov control theorem. Not only the actuator dynamics of the control surfaces are considered, but also the noises, biases, and time delays of the measurements of the control surface deflection angles are taken into account. Therefore, the command-filtered backstepping is utilized to compensate for the actuator dynamics and filtered errors, and the modified stable linear filter is developed to handle the measurement errors. The stability of the whole closed-loop system, including the compensated signals which are the outputs of the stable linear filters, is analyzed by using Lyapunov theory. The numerical simulation results demonstrate effectiveness of the proposed CFMFR control approach with updating matrix.

A novel adaptive command-filtered backstepping sliding mode control for PV grid-connected system with energy storage

In order to solve the problems of power fluctuation in the photovoltaic (PV) grid-connected system and the nonlinearity in the model of inverters, a projection-based adaptive backstepping sliding mode controller with command-filter is designed in the system to adjust the DC-link voltage and the AC side current in the PV grid-connected system. Firstly, the mathematical model of the inverter in PV system is established, then backstepping control method is applied to control it, and the command filter is added to the controller to eliminate the differential expansion of the backstepping controller. Furthermore, the adaptive law based on Lyapunov stability theory is designed to estimate the uncertain parameters in the grid-connected inverter. A projection algorithm is introduced into the adaptive controller due to the demand of guaranteeing the bounded estimated value. Additionally, a sliding mode controller is increased to improve its robustness in this system. Considering the influence of irradiation and temperature changes, a battery energy storage system (BESS) is applied on the DC side to suppress the fluctuation of the output power of the PV system. Finally, the simulation results demonstrate that the presented strategy can control precisely the grid-connected inverter.

Learning from neural control for non-affine systems with full state constraints using command filtering

ABSTRACT This paper focusses on learning from command filtering-based adaptive neural control for non-affine nonlinear systems with full state constraints. This paper utilises a novel transformed function to convert the origin full-state constrained problem into an equivalent unconstrained one. By combining command-filtered backstepping, a novel adaptive neural control scheme is proposed to guarantee that all closed-loop signals are uniformly ultimately bounded and all states stay in the predefined bounded regions. Subsequently, by verifying the partial persistent excitation condition of the radial basis function neural network, neural weight estimates are proven to converge to the ideal weights and the convergent weights are stored in the constant values. Using the stored knowledge, a neural learning control scheme is developed for similar control tasks, which can improve control performances without the violation of full state constraints. Simulation studies are performed to illustrate the validity of the proposed scheme.

Adaptive command-filtered fuzzy backstepping control for linear induction motor with unknown end effect

In this paper, the problem of the speed control is considered for linear induction motor with the end effects, uncertain system parameters, and external load disturbance. Firstly, the proposed controller is based on backstepping method, and the adaptive laws are designed.The fuzzy logic modeling approach is used to deal with the unknown nonlinear functions and uncertain parameters. Secondly, a constrained command filter is employed to overcome the problem of differential expansion and controller saturation in the backstepping method, and a filter’s compensating signal is used to mitigate the error caused by the constrained command filter. Thirdly, the projection operator introduced in the adaptive laws guarantees boundedness of the estimated functions and robustness of the designed controller in the presence of time-varying disturbances and uncertainties. Thus, the proposed control controller can ensure that all response signals in the closed-loop system are bounded. Finally, the effectiveness of the proposed controller is verified by simulation and comparison with command-filtered backstepping controller.

Design of the Nonlinear Cruise Controllers for Hypersonic Vehicle

When the hypersonic vehicle is cruising, they face the aerothermoelastic, as well as the matching, unmatched uncertainty and the disturbance. This paper presents a control method of command filter Backstepping sliding in order to cope with the problems above. First, this method does the problem of calculation expands to Backstepping using the command filter. Then, introducing sliding control settles the matching problem and disturbance; Consideration to decline the shake of sliding control and deal with the unmatched uncertainty, using the idea of higher order sliding mode control, this paper augments an addition virtual control state equation in each control loop and makes the output of the control system act on an integral, which not only declines the shake of sliding control, but also deals with the unmatched uncertainty using adaptive Backstepping. However, introducing an additional virtual control equation of state increases the system order, which has a growing in complexity when using the adaptive Backstepping to design the control system. Nevertheless the problem could be resolved by the method of dynamic surface. At last, the global stability of the proposed method is proved in theory and the effectiveness and robust of this method are verified by the simulation.

Immersion and invariance adaptive control with σ-modification for uncertain nonlinear systems

A novel adaptive control with σ-modification for uncertain nonlinear systems is proposed in the paper. The application of conventional adaptive control is severely limited by the problems of construction of Lyapunov function and parameter drift because of non-parametric uncertainties. The proposed adaptive control that is on the basis of the immersion and invariance theory and σ-modification can be used to deal with these problems to some extent. It turns out to be a structured design method without requiring a Lyapunov function in the design level and robust to non-parametric uncertainties. Moreover, constrained command filter backstepping is adopted to meet the amplitude and rate constraints on the states and actuators. The uniformly ultimately bounded stability of the closed-loop system has been analyzed by Lyapunov theory with parametric and non-parametric uncertainties of the controlled model. To demonstrate the design flexibility, the method is applied to the position tracking control system design of a mass-damper-spring system and the flight control system design of a scramjet-powered air-breathing hypersonic vehicle. Finally, the effectiveness of the proposed adaptive control method is illustrated by numerical simulations.

Robust Command Filtered Adaptive Backstepping Control for a Quadrotor Aircraft

This paper addresses a robust trajectory tracking controller for an underactuated quadrotor with external bounded disturbances and unknown inertia parameters. Different from most of the existing control algorithms, the proposed method does not adopt the dual-loop scheme in which the design is divided into position control and attitude control. Instead, command filter backstepping is employed to design the controller based on the integrated motion model such that the stability can be guaranteed strictly for the flight control system. Furthermore, adaptive compensation and robust compensation are introduced to deal with the uncertainty of the inertia parameters and the external bounded disturbances, respectively. Finally, a similar skew symmetric structure is chosen as the desired structure of the closed-loop system to facilitate the analysis of the stability of the integrated system. Stability and robust performance of the designed controller are verified by Lyapunov stability theorem. Simulations are provided to validate the proposed controller.

Distributed Fuzzy Adaptive Backstepping Optimal Control for Nonlinear Multi-missile Guidance Systems with Input Saturation

This paper investigates the distributed optimal tracking control problem for nonlinear multiagent systems with a fixed directed graph. The dynamics of followers are in strict-feedback form with unknown nonlinearities and input saturation. Fuzzy logic systems and auxiliary system are introduced to identify the unknown nonlinearities and compensate the effect of input saturation, respectively. Then, by using the command-filtered backstepping technique, the distributed optimal tracking control problem is transformed into a distributed optimal regulation problem of tracking error dynamics in affine form. Subsequently, the distributed optimal feedback controller is derived via adaptive dynamic programming technique, in which a critic network is constructed to approximate the associated cost function online with a designed weight update law. Therefore, the whole controller, consisting of distributed adaptive feedforward tracking controller and distributed optimal feedback controller, not only guarantees that all signals in the closed-loop system are uniformly ultimately bounded, but also guarantees that the cooperative cost function is minimized. The effectiveness of the proposed method is demonstrated by simulation on the cooperative guidance problem of multimissile systems.

Composite learning from adaptive backstepping neural network control

In existing neural network (NN) learning control methods, the trajectory of NN inputs must be recurrent to satisfy a stringent condition termed persistent excitation (PE) so that NN parameter convergence is obtainable. This paper focuses on command-filtered backstepping adaptive control for a class of strict-feedback nonlinear systems with functional uncertainties, where an NN composite learning technique is proposed to guarantee convergence of NN weights to their ideal values without the PE condition. In the NN composite learning, spatially localized NN approximation is employed to handle functional uncertainties, online historical data together with instantaneous data are exploited to generate prediction errors, and both tracking errors and prediction errors are employed to update NN weights. The influence of NN approximation errors on the control performance is also clearly shown. The distinctive feature of the proposed NN composite learning is that NN parameter convergence is guaranteed without the requirement of the trajectory of NN inputs being recurrent. Illustrative results have verified effectiveness and superiority of the proposed method compared with existing NN learning control methods.

Containment Control of Underactuated Ships with Environment Disturbances and Parameter Uncertainties

An implementable robust containment control algorithm is proposed for a group of underactuated ships in the presence of hydrodynamic parameter uncertainties and external disturbances. The control objective is to drive all the followers into the convex hull spanned by the virtual leaders, whose state information is available only to a subset of the followers. For this purpose, the ship model is primarily transformed to a strict-feedback form. In the kinematic design, a virtual containment controller, requiring the state information from its neighbors, is presented based on the results obtained from graph theory. In the dynamic design, a robust containment controller is developed through utilizing upper-to-up sliding mode control. In addition, in order to simplify the implementations of the control law, the command filtered backstepping (CFBP) method is introduced to prevent the analytic differentiations of the virtual law from each design step of the backstepping (BP) method. Subsequently, it is well proven that all the tracking errors could converge to and remain small neighborhoods of the equilibrium point. Finally, several simulation experiments are conducted to demonstrate the performance of the proposed control algorithm.

Nonlinear Control of Back-to-Back VSC-HVDC System via Command-Filter Backstepping

This paper proposed a command-filtered backstepping controller to improve the dynamic performance of back-to-back voltage-source-converter high voltage direct current (BTB VSC-HVDC). First, the principle and model of BTB VSC-HVDC in abc and d-q frame are described. Then, backstepping method is applied to design a controller to maintain the voltage balance and realize coordinated control of active and reactive power. Meanwhile, command filter is introduced to deal with the problem of input saturation and explosion of complexity in conventional backstepping, and a filter compensation signal is designed to diminish the adverse effects caused by the command filter. Next, the stability and convergence of the whole system are proved via the Lyapunov theorem of asymptotic stability. Finally, simulation results are given to demonstrate that proposed controller has a better dynamic performance and stronger robustness compared to the traditional PID algorithm, which also proves the effectiveness and possibility of the designed controller.

Adaptive Command-Filtered Backstepping Control for Linear Induction Motor via Projection Algorithm

A theoretical framework of the position control for linear induction motors (LIM) has been proposed. First, indirect field-oriented control of LIM is described. Then, the backstepping approach is used to ensure the convergence and robustness of the proposed control scheme against the external time-varying disturbances via Lyapunov stability theory. At the same time, in order to solve the differential expansion and the control saturation problems in the traditional backstepping, command filter is designed in the control and compensating signals are presented to eliminate the influence of the errors caused by command filters. Next, unknown total mass of the mover, viscous friction, and load disturbances are estimated by the projection-based adaptive law which bounds the estimated function and simultaneously guarantees the robustness of the proposed controller against the parameter uncertainties. Finally, simulation results are given to illustrate the validity and potential of the designed control scheme.

Visual Servoing of Fixed - Wing Unmanned Aerial Vehicle Using Command Filtered Backstepping

Visual Servoing of Fixed - Wing Unmanned Aerial Vehicle Using Command Filtered Backstepping

Robust NSV Fault-Tolerant Control System Design Against Actuator Faults and Control Surface Damage Under Actuator Dynamics

In this paper, a decentralized fault-tolerant control (FTC) system is proposed for near-space vehicle (NSV) attitude dynamics. First, NSV reentry attitude dyna mic models with an uncertainty, actuator failure models, and a control surface damage model are described. Next, a new local fault identification algorithm is proposed to iden tify different types of actuator faults, which is based on multiobserver techniques. The local fault identification is constituted by a fault detection observer, fault parameter identification observers, and a decision-making mechanism. Then, a global adaptive sliding-mode observer is used to design the command filter backstepping fault- tolerant controller. Our focus is on the accommodation for actuator faults, control surface damage, uncertainties, and the resulting disturbances of the NSV. Finally, simulation results are given to demonstrate the effectiveness and poten tial of the proposed FTC scheme.

Design of three-dimensional nonlinear guidance law with bounded acceleration command

This paper concentrates on the problem of designing a three-dimensional nonlinear guidance law accounting for saturation nonlinearity and the dynamics of missile autopilot based on a command filtered backstepping (CFBS) scheme. In the design, the nonlinear kinematics of target–missile engagement is considered in the spherical coordinate system and the dynamics of the autopilot is considered as a second-order term. The CFBS scheme is utilized to blend the command filtering approach into standard backstepping method to avoid the complex computation of the analytic derivatives of the intermediate control signals. A command filter with a saturation limiter embedded and some auxiliary filters are combined together to address acceleration command saturation. Simulation results show that even though subject to saturation constraint, the proposed guidance law achieves excellent guidance performance in terms of missed distance.

Model Free Command Filtered Backstepping Control for Marine Power Systems

In order to retrain chaotic oscillation of marine power systems which are excited by periodic electromagnetism perturbation, two novel model free command-filtered backstepping control methods are designed in this paper. Firstly, the dynamic model of marine power system based on the two parallel nonlinear models is established. Secondly, extended state observer (ESO) and adaptive neural network observer (NNO) are designed to estimate the velocity signal and the unknown dynamic model. Moreover, the uniform form of ESO and NNO is given. Next, the model free command-filtered backstepping controller is put forward based on the uniform observer form. Finally, the simulation results indicate that the two proposed control algorithms can quickly retrain chaotic oscillation and their effectiveness and potential are amply demonstrated.

Adaptive neural observer‐based backstepping fault tolerant control for near space vehicle under control effector damage

In this study, a theoretical framework for reconfigurable flight control is developed and applied to near space vehicle (NSV) attitude dynamics. First, NSV reentry mode is described. Second, an adaptive neural network observer is proposed, which ensures asymptotic convergence of the state observer error to zero under control effector damage and uncertainty. Next, a reconfigurable command-filter backstepping controller is designed based on the adaptive neural network observer. The authors focus is on the accommodation of the control effector damage, uncertainty and resulting disturbances. It is shown that the presented new control design results in asymptotic convergence of the attitude tracking error to zero. Finally, simulation results are given to demonstrate the effectiveness and potential of the proposed fault tolerant control scheme.

Command Filtered Adaptive Fuzzy Neural Network Backstepping Control for Marine Power System

In order to retrain chaotic oscillation of marine power system which is excited by periodic electromagnetism perturbation, a novel command-filtered adaptive fuzzy neural network backstepping control method is designed. First, the mathematical model of marine power system is established based on the two parallel nonlinear model. Then, main results of command-filtered adaptive fuzzy neural network backstepping control law are given. And the Lyapunov stability theory is applied to prove that the system can remain closed-loop asymptotically stable with this controller. Finally, simulation results indicate that the designed controller can suppress chaotic oscillation with fast convergence speed that makes the system return to the equilibrium point quickly; meanwhile, the parameter which induces chaotic oscillation can also be discriminated.

Adaptive command filtered backstepping tracking controller design for quadrotor unmanned aerial vehicle

This paper discusses the design of an adaptive command-filtered backstepping flight control law with uncertain parameters for a quadrotor unmanned aerial vehicle (UAV). The control law is tasked with tracking reference trajectories with a constrained velocity, attitude, and attitude rate. Thruster misalignment is included in the formulation of the quadrotor dynamics. Online parameter update laws are used to compensate for the uncertain parameters, namely mass, inertia, actuator gain, and thruster misalignment. Command filters are used to implement the vehicle’s actuator and state constraints. Stability of the control law with parameter update laws during periods of saturation is guaranteed by using a modified tracking error in the Lyapunov function, in which the effect of the saturation is smoothed into the other internal control steps. The controller and its performance are evaluated using a non-linear, six-degree-of-freedom dynamic model of a quadrotor UAV in simulations. The results show that the proposed control law enhances the tracking performance by controlling internal states even with parameter uncertainties and thruster misalignment errors.