Command Filter Research Articles

Bionic tracking-containment control based on smooth transition in communication

In this paper, we propose the bionic tracking-containment control based on smooth transition in communication, which is inspired by wolf hunting. To realize the hunting target process, we concentrate on the transition from tracking control to containment control of the swarm system by using backstepping method. The smooth transition of switching communication topology is introduced to realize bionic switching. We design a smooth switching function, which can avoid the negative influence of instant switch. Due to the input saturation and smooth switching function, it is challenging to design the tracking-containment controller with nonlinear dynamics and external disturbances. To overcome these difficulties, we design the tracking-containment control based on the adaptive backstepping method, which includes n command filters and one adaptive neural network to improve the control performance. The swarm system is proved stable under the Lyapunov stability criterion. Finally, simulation is carried out to verify the feasibility of the proposed method.

Adaptive neural control for nonlinear systems with actuator faults and unknown control directions via command filter

AbstractThis article studies the issue of command filter‐based adaptive fault‐tolerant control for a class of nonlinear systems subject to unknown control directions and disturbance. First, the neural network is employed to deal with the nonlinear functions, and the explosion of the complexity problem is handled by the command filter approach. Second, the bound estimation method and the Nussbaum function are utilized to compensate for the influence of the actuator faults and the unknown directions, respectively. Finally, the tracking error signals are guaranteed to converge into bounded compact sets around the origin, and all closed‐loop signals are bounded. The effectiveness of the proposed method is illustrated by three simulations.

Design of singularity-free fixed-time fault-tolerant control for HFVs with guaranteed asymmetric time-varying flight state constraints

This article solves the fixed-time trajectory tracking problem for hypersonic flight vehicles (HFVs) encountered with diverse actuator faults and asymmetric envelope constraints. In contrast to the state of the art, the crucial characteristics of our design lie in obviating the explosion of complexity of the conventional recursive design, and in realizing satisfactory preselected tracking qualities for flight states in the sense of guaranteeing asymmetric envelope constraints. More precisely, by exploiting the fixed-time command filters to produce certain command signals and their derivatives, a modified command-filtered control algorithm is formulated to circumvent heavy computation burden caused by repetitive derivative of intermediate control laws. A two-step control methodology is devised based on an auxiliary compensating dynamics, which is capable of compensating for the actuator faults completely without the need for prior knowledge about the lumped disturbances and the actuator faults. Time-varying asymmetric barrier Lyapunov functions are introduced to confine the flight state tracking errors within the corresponding time-varying compact sets all the time provided their initial values remain therein. The effectiveness of the proposed method is validated by comparative simulation results.

Distributed consensus tracking control for nonlinear multiagent systems with state delays and unknown control coefficients

AbstractIn this article, the distributed consensus tracking problem is investigated for a group of heterogeneous nonlinear multiagent systems (MASs). The dynamic of each follower is subject to multiple time‐varying state delays and unknown non‐identical control coefficients. Most existing results for MASs with unknown non‐identical control coefficients are on the condition that only the specific Nussbaum‐type function can be used. This constraint is removed by employing the enhanced Nussbaum functions. Some appropriate Lyapunov–Krasovskii functionals are constructed to compensate the delayed nonlinear functions. By applying the finite‐time command filters to backstepping technique, a novel distributed adaptive consensus tracking control law is developed, which is independent of multiple state delays. It is proved that each follower's output can track the leader. Finally, the validness of the proposed control algorithm is illustrated by two simulation examples.

Attitude stabilization of rigid spacecraft with angular velocity and torque limitations

An adaptive backstepping control scheme has been put forward to investigate the attitude stabilization problem for a spacecraft with modeling uncertainties, external disturbances, actuator failures, angular velocity limitations and actuator limitations simultaneously. Based on the active disturbance rejection concept (ADRC), a positive definite diagonal matrix is selected by the designer to separate a control item from the system. Then, an extended state observer is constructed to deal with the total uncertain item including actuator failure. In order to deal with the limitation of torques, a saturation coefficient is introduced and its adaptive law is obtained. Meanwhile, a command filter and the compensation signal are constructed to handle the angular velocity limitations. Finally, the stability of the closed-loop system is analyzed. Simulation results are given to verify the effectiveness of the proposed scheme.

Finite‐time adaptive fuzzy command filtering control for stochastic nonlinear systems with input quantization

SummaryThis article focuses on the finite‐time adaptive fuzzy control problem based on command filtering for stochastic nonlinear systems subject to input quantization. Fuzzy logic systems are employed to estimate unknown nonlinearities. In the control design, the hysteretic quantized input is decomposed into two bounded nonlinear functions, which solves the chattering problem. Meanwhile, an adaptive fuzzy controller is presented by the combination of command filter technique and backstepping control, which eliminates the computational complexity existing in traditional backstepping design. Under the proposed adaptive mechanism, all the closed‐loop signals remain bounded while the desired system performance can be realized within finite time. The main significance of this work is that (1) the filtering error can be solved on the basis of the designed compensating signals; (2) the requirement of adaptive parameters is decreased to only one, which simplifies the controller design process and may improve the control performance. Two simulation examples are used to validity of the developed scheme.

Command filtered event‐triggered adaptive control for MIMO stochastic multiple time‐delay systems

AbstractIn this article, the command filter based adaptive event‐triggered control problem for multiple‐input and multiple‐output multiple time‐delay stochastic nonlinear systems is considered. First, a state observer is constructed to estimate the unmeasured states of systems. Then, in the framework of backstepping design, the command filtered and event‐triggered techniques are employed to avoid the problem of “explosion of complexity” and save the communication resources, respectively. Meanwhile, by utilizing the command filters, a novel variable separation method is constructed to address the algebraic‐loop problem, which caused by the nonstrict‐feedback item. The boundedness of the whole signals in systems can be remained, and the given desired trajectories can be followed by the system outputs. Finally, a numerical example is shown to demonstrate the effectiveness of the proposed control method.

Robust adaptive neural network control for dynamic positioning of marine vessels with prescribed performance under model uncertainties and input saturation

This paper presents a dedicated robust adaptive neural network control (RANNC) scheme for dynamic positioning (DP) of marine vessels with a prescribed performance under model uncertainties, external disturbances and input saturation. To guarantee that the transient performance is always within the prescribed performance constraints, a novel error transfer function is firstly proposed to transfer the original dynamic positioning system with the constrained error behavior into an equivalent unconstrained one. Next, the RANNC scheme is developed with the backstepping technique, and the method of command filter is introduced to avoid the ”dimension disaster” problem. Considering the ship’s inertial matrix and damping matrix are not constant in practice, the adaptive control technique and RBF neural networks are adopted to design the model adaptive controller, which only requires the actuator matrix rather than a completely accurate model. Moreover, minimal learning parameter technique is introduced to minimize the computational burden triggered by weight update of neural networks. Finally, comparison simulation results are provided to illustrate the performance of the proposed RANNC scheme.

Finite‐time adaptive fuzzy control for a class of output constrained nonlinear systems with dead‐zone

SummaryThe article investigates the finite‐time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead‐zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite‐time control theory, a novel adaptive state‐feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite‐time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed‐loop are proved to be semi‐globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.

Global adaptive neural backstepping control of a flexible hypersonic vehicle with disturbance estimation

PurposeThis paper aims to discuss the precise altitude and velocity tracking control of a hypersonic vehicle, a global adaptive neural backstepping controller was studied based on a disturbance observer (DOB).Design/methodology/approachThe DOB combined with a radial basis function (RBF) neural network (NN) was used to estimate the disturbance terms that are generated by the flexible modes of the hypersonic vehicle system. A global adaptive neural method was introduced to approximate the unknown system dynamics, with robust control terms pulling the system transient states back into the neural approximation domain externally.FindingsThe globally uniformly ultimately bounded for all signals of a closed-loop system can be guaranteed by the proposed control algorithm. Additionally, the command filtered backstepping methods can avoid the explosion of the complexity problem caused by the backstepping design process. In addition, the effectiveness of the proposed controller can be verified by the simulation used in this study.Research limitations/implicationsNormally lateral dynamics issue should be discussed in the process of control system designed, the lateral dynamics are not included in the nonlinear dynamic model of hypersonic vehicle used in this paper, merely the longitudinal flight dynamics are discussed in this paper.Originality/valueThe flexible states in rigid modes are considered as the disturbance of the system, which is estimated by structuring DOB with NN approximations. The compensating tracking error and prediction error are used in the update law of RBF NN weight. The differential explosions complexity derived from the backstepping procedure is dealt with by using command filters.

Event-triggered compound learning tracking control of nonstrict-feedback nonlinear systems in sensor-to-controller channel

This paper investigates the event-triggered tracking control of the nonstrict-feedback nonlinear system with time-varying disturbances. While the fuzzy logic systems (FLSs) approximate the unknown dynamics, an event-triggered compound learning algorithm is originally developed to accurately estimate the total uncertainties. By referring to an event-triggered adaptive model, the control laws are derived without provoking the problem of “algebraic loop,” seeing Remark 3. The command filters are employed to generate the continuous substitutes for both the virtual control laws and their derivatives, so as to solve the recently proposed problem of “jumps of virtual control laws” arising in the backstepping-based event-triggered control (ETC). The triggering condition is constructed to guarantee the similarity between the adaptive model and the original system. Estimation of optimal fuzzy weights and compound disturbances follows from the event-triggered update laws. While the satisfactory learning performance is achieved, the proposed control scheme can guarantee the semi-globally uniformly ultimate boundedness (SGUUB) of all the tracking errors. Finally, a numerical experiment verifies the effectiveness of the proposed control scheme.

Distributed finite-time adaptive consensus tracking control for multiple AUVs with state constraints

Aiming at the consensus tracking control problem of multiple autonomous underwater vehicles (AUVs) with state constraints, a new neural network (NN) and barrier Lyapunov function based finite-time command filtered backstepping control scheme is proposed. The finite-time command filter is utilized to filtering the virtual control signal, the error compensation signal is constructed to eliminate filtering error due to the use of filter, and the NN approximation technology is used to deal with the unknown nonlinear dynamics. The control scheme can guarantee that the consensus tracking errors of position states converge into the desired neighborhood of the origin in finite-time while not exceeding the predefined constraints. Finally, simulation studies prove the feasibility of proposed control algorithm.

Adaptive event‐triggered control for MIMO nonlinear systems with asymmetric state constraints based on unified barrier functions

AbstractThe topic of adaptive event‐triggered control for multi‐input‐multi‐output nonlinear systems with asymmetric state constraints is considered in this article. First, by introducing unified barrier functions method, the initial system is transformed to a non‐constraints system, which brings that the requirement of feasibility conditions could be eliminated and the constraint functions could be relaxed effectively. Then, an adaptive tracking controller is designed by combining some excellent technology, where command filter is utilized to overcome the explosion of complexity, neural network is introduced to approximate unknown nonlinear function, and event‐triggered mechanism is proposed to save communication resources. The designed control scheme can make the outputs of the system to track the target trajectories within a small bounded error range, all signals in the closed‐loop system are bounded, and all states do not escape the state constraints. Finally, practical and comparative examples are given to verify the effectiveness of the method.

Velocity-free attitude tracking for rigid spacecraft via bounded control

This article investigates the attitude tracking control problem for a rigid spacecraft without angular velocity feedback, in which external disturbances, parametric uncertainties, and input saturation are considered. Initially, an angular velocity observer is developed incorporated with adaptive technique, which could tackle the unmeasurable angular velocity and system uncertainties simultaneously. By introducing adaptive updating law into the proposed observer, the synchronized uncertainties are handled such that robustness of the observer is enhanced, even in the presence of external disturbances. Further, for solving the input constraints problem, command filter and backstepping method are utilized; thus, a bounded attitude tracking control law is derived. Finally, the attitude tracking performance is evaluated by numerical examples.

Backstepping Control Based on Constrained Command Filter for Hypersonic Flight Vehicles with AOA and Actuator Constraints

An antisaturation backstepping control scheme based on constrained command filter for hypersonic flight vehicle (HFV) is proposed with the consideration of angle of attack (AOA) constraint and actuator constraints of amplitude and rate. Firstly, the HFV system model is divided into velocity subsystem and height subsystem. Secondly, to handle AOA constraint, a constrained command filter is constructed to limit the amplitude of the AOA command and retain its differentiability. And the constraint range is set in advance via a prescribed performance method to guarantee that the tracking error of the AOA meets the constraint conditions and transient and steady performance. Thirdly, the proposed constrained command filter is combined with the auxiliary system for actuator constraints, which ensures that the control input meets the limited requirements of amplitude and rate, and the system is stable. In addition, the tracking errors of the system are proved to be ultimately uniformly bounded based on the Lyapunov stability theory. Finally, the effectiveness of the proposed method is verified by simulation.

Adaptive finite‐time output feedback control for Markov jumping nonlinear systems

SummaryIn this article, the problem of output feedback tracking control for uncertain Markov jumping nonlinear systems is studied. A finite‐time control scheme based on command filtered backstepping and adaptive neural network (NN) technique is given. The finite‐time command filter solves the problem of differential explosions for virtual control signals, the NN is utilized to approximate the uncertain nonlinear dynamics and the adaptive NN observer is applied to restructure the state of system. The finite‐time error compensation mechanism is established to compensate the errors brought by filtering process. The proposed finite‐time tracking control algorithm can ensure that the solution of the closed‐loop system is practically finite‐time stable in mean square. Two simulation examples are employed to demonstrate the effectiveness of the proposed control algorithm.

Command filtered adaptive fuzzy control of fractional-order nonlinear systems

The standard backstepping control scheme has inherently computational complexity explosion problem, and consequently, becomes prohibitive as the order increases. This paper contributes to command filtered adaptive fuzzy control (AFC) of fractional-order nonlinear systems (FNSs) by using fractional backstepping control method. To approximate the virtual input, a fractional-order command filter (FCF) is proposed. Filtering approximation errors that affect the performance of the controller during the filtering process are solved by an error compensation mechanism (ECM). The simulation results verify the validity of the theoretical results.

Event-based adaptive fuzzy fixed-time control for nonlinear interconnected systems with non-affine nonlinear faults

This article studies the event-based adaptive practical fixed-time decentralized control problem for a class of large-scale uncertain nonlinear systems subject to non-affine nonlinear faults. By fusing the techniques of fixed-time control and command filter, the problems such as singular-value and computational explosion in fixed-time control based on backstepping design framework are solved. Based on the fuzzy approximation theory and Butterworth low-pass filter (BLPF) technique, the non-affine nonlinear fault terms are processed and fault-tolerant controllers are designed to realize fault compensation. In order to relieve the communication the pressure between system components, a novel switching event-triggering mechanism (SETM) based on user-set threshold parameters is proposed. This switching threshold design the scheme combines the advantages of the traditional fixed threshold and relative threshold design strategies, providing greater flexibility in balancing system performance and network constraints. By combining the practical fixed-time stability criterion with the Lyapunov stability theory, it is demonstrated that both the tracking performance and the closed-loop stability can be ensured in a fixed-time. Finally, two simulation examples are given to verify the effectiveness of the proposed fixed-time switching event-triggered control (SETC) scheme.

Fuzzy synchronization of fractional-order chaotic systems using finite-time command filter

For conventional backstepping control, the analytical calculation of certain virtual controller is required in each step, so when system order increases, the computational burden also increases. An adaptive command filtered fuzzy synchronization approach is implemented for strict feedback fractional-order chaotic systems (FCSs) in this paper. The computational explosion in the backstepping is solved through a fractional-order command filter (FCF). The filtering approximation errors arising from the FCF are overcame by a error compensation mechanism (ECM). In every step, a fuzzy system is introduced to process system uncertainties. The stability of synchronization errors of a strict feedback FCS is ensured based on fractional Lyapunov stability criteria. Finally, numerical simulation examples illustrate the effectiveness of the proposed scheme.

Command filtered adaptive backstepping control for high-accuracy motion tracking of hydraulic systems with extended state observer

High-accuracy motion tracking of hydraulic systems is of great significance in industrial applications. Nevertheless, dynamic nonlinearity, modeling uncertainty, generalized disturbance, and measurement noise are inevitably existed in hydraulic systems, which severely deteriorates the practical control performance. Aimed at enhancing the motion-tracking accuracy of hydraulic systems, a novel command filtered adaptive backstepping controller with extended state observer is proposed in this article. On the basis of the established system’s nonlinear model, the extended state observer utilizing only position output feedback information is first designed to estimate the system’s unmeasurable states, and time-varying disturbances of the hydraulic system are also obtained for subsequent active disturbance compensation. Next, a second-order command filter is constructed to generate specific command signals and their derivatives, which significantly simplifies the controller design process by avoiding complicated analytical differential calculations in contrast to traditional adaptive backstepping algorithm. Subsequently, with consideration of system’s nonlinearity, parametric uncertainty, and time-varying disturbance, the developed extended state observer and command filter are introduced into the adaptive backstepping design process of the proposed controller, and theoretical stability of the proposed controller is guaranteed via Lyapunov analysis. Finally, the effectiveness and superiority of the proposed controller are demonstrated by comparative experimental results.