Robust missile autopilot design based on dynamic surface control

Since the dynamical system and control system of the missile are typically nonlinear, an effective acceleration tracking autopilot is designed using the dynamic surface control(DSC)technique in order to make the missile control system more robust despite the uncertainty of the dynamical parameters and the presence of disturbances. Firstly, the nonlinear mathematical model of the tail-controlled missile is decomposed into slow acceleration dynamics and fast pitch rate dynamics based on the naturally existing time scale separation. Secondly, the controller based on DSC is designed after obtaining the linear dynamics characteristics of the slow and fast subsystems. An extended state observer is used to detect the uncertainty of the system state variables and aerodynamic parameters to achieve the compensation of the control law. The closed-loop stability of the controller is derived and rigorously analyzed. Finally, the effectiveness and robustness of the design is verified by Monte Carlo simulation considering different initial conditions and parameter uptake. Simulation results illustrate that the missile autopilot based DSC controller achieves better performance and robustness than the other two well-known autopilots.The method proposed in this paper is applied to the design of a missile autopilot, and the results show that the acceleration tracking autopilot based on the DSC controller can ensure accurate tracking of the required commands and has better performance.

Adaptive Dynamic Surface Control for Integrated Missile Guidance and Autopilot

Integrated guidance and control for homing missiles utilizing adaptive dynamic surface control approach is considered based on the three channels independence design idea. A time-varying integrated guidance and control model with unmatched uncertainties is first formulated for the pitch channel, and an adaptive dynamic surface control algorithm is further developed to deal with these unmatched uncertainties. It is proved that the proposed feedback controller can ensure not only the accuracy of target interception, but also the stability of the missile dynamics. Then, the same control approach is further applied to the control design of the yaw and roll channels. The 6-degree-of-freedom （6-DOF） nonlinear missile simulation results demonstrate the feasibility and advantage of the proposed integrated guidance and control design scheme.

Adaptive dynamic surface control for air-breathing hypersonic vehicle

This paper describes an adaptive control approach for an air-breathing hypersonic vehicle. The control objective is to provide robust altitudes and velocity tracking in the presence of model uncertainties and varying disturbances. A fuzzy-neural disturbance observer is developed to estimate uncertainties and disturbances, and the adaptive controller is synthesized by the dynamic surface approach combing with the observer. The tracking error at the steady state can be guaranteed to converge to inside of a small residue set which the size of the set can be an arbitrary small value. Simulation results demonstrate the effectiveness of the presented approach.

Adaptive Fuzzy Dynamic Surface Control of Flexible-Joint Robot Systems With Input Saturation

In this paper, we propose an adaptive fuzzy dynamic surface control(DSC) scheme for single-link flexible-joint robotic systems with input saturation. A smooth function is utilized with the mean-value theorem to deal with the difficulties associated with input saturation. An adaptive DSC design with an auxiliary first-order filter is used to solve the "explosion of complexity"problem. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood around zero. The main advantage of the proposed method is that only one adaptation parameter needs to be updated,which reduces the computational burden significantly. Simulation results demonstrate the feasibility of the proposed scheme and the comparison results show that the improved DSC method can reduce the computational burden by almost two thirds in comparison with the standard DSC method.

Integrated guidance and control of guided projectile with multiple constraints based on fuzzy adaptive and dynamic surface

Based on fuzzy adaptive and dynamic surface(FADS),an integrated guidance and control(IGC)approach was proposed for large caliber naval gun guided projectile,which was robust to target maneuver,canard dynamic characteristics,and multiple constraints,such as impact angle,limited measurement of line of sight(LOS)angle rate and nonlinear saturation of canard deflection.Initially,a strict feedback cascade model of IGC in longitudinal plane was established,and extended state observer(ESO)was designed to estimate LOS angle rate and uncertain disturbances with unknown boundary inside and outside of system,including aerodynamic parameters perturbation,target maneuver and model errors.Secondly,aiming at zeroing LOS angle tracking error and LOS angle rate in finite time,a nonsingular terminal sliding mode(NTSM)was designed with adaptive exponential reaching law.Furthermore,combining with dynamic surface,which prevented the complex differential of virtual control laws,the fuzzy adaptive systems were designed to approximate observation errors of uncertain disturbances and to reduce chatter of control law.Finally,the adaptive Nussbaum gain function was introduced to compensate nonlinear saturation of canard deflection.The LOS angle tracking error and LOS angle rate were convergent in finite time and whole system states were uniform ultimately bounded,rigorously proven by Lyapunov stability theory.Hardware-in-the-loop simulation(HILS)and digital simulation experiments both showed FADS provided guided projectile with good guidance performance while striking targets with different maneuvering forms.

Output-feedback Dynamic Surface Control for a Class of Nonlinear Non-minimum Phase Systems

In this paper, an output-feedback tracking controller is proposed for a class of nonlinear non-minimum phase systems.To keep the unstable internal dynamics bounded, the method of output redefinition is applied to let the stability of the internal dynamics depend on that of redefined output, thus we only need to consider the new external dynamics rather than internal dynamics in the process of designing control law. To overcome the explosion of complexity problem in traditional backstepping design, the dynamic surface control(DSC) method is firstly used to deal with the problem of tracking control for the nonlinear non-minimum phase systems. The proposed outputfeedback DSC controller not only forces the system output to asymptotically track the desired trajectory, but also drives the unstable internal dynamics to follow its corresponding bounded and causal ideal internal dynamics, which is solved via stable system center method. Simulation results illustrate the validity of the proposed output-feedback DSC controller.

Output Feedback Dynamic Surface Controller Design for Airbreathing Hypersonic Flight Vehicle

This paper addresses issues related to nonlinear robust output feedback controller design for a nonlinear model of airbreathing hypersonic vehicle. The control objective is to realize robust tracking of velocity and altitude in the presence of immeasurable states, uncertainties and varying flight conditions.A novel reduced order fuzzy observer is proposed to estimate the immeasurable states. Based on the information of observer and the measured states, a new robust output feedback controller combining dynamic surface theory and fuzzy logic system is proposed for airbreathing hypersonic vehicle. The closedloop system is proved to be semi-globally uniformly ultimately bounded(SUUB), and the tracking error can be made small enough by choosing proper gains of the controller, filter and observer. Simulation results from the full nonlinear vehicle model illustrate the effectiveness and good performance of the proposed control scheme.

Adaptive Neural Network Dynamic Surface Control for Perturbed Nonlinear Time-delay Systems

This paper proposes an adaptive neural network control method for a class of perturbed strict-feedback nonlinear systems with unknown time delays. Radial basis function neural networks are used to approximate unknown intermediate control signals. By constructing appropriate Lyapunov-Krasovskii functionals, the unknown time delay terms have been compensated. Dynamic surface control technique is used to overcome the problem of ＂explosion of complexity＂ in backstepping design procedure. In addition, the semiglobal uniform ultimate boundedness of all the signals in the closed-loop system is proved. A main advantage of the proposed controller is that both problems of ＂curse of dimensionality＂ and ＂explosion of complexity＂ are avoided simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the approach.

Adaptive Fuzzy Dynamic Surface Control for Uncertain Nonlinear Systems

In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of ＂explosion of complexity＂ in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globally uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller （SMC）. Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.

Dynamic Surface Control with Nonlinear Disturbance Observer for Uncertain Flight Dynamic System

A new robust control method of a nonlinear flight dynamic system with aerodynamic coefficients and external disturbance has been proposed.The proposed control system is a combination of the dynamic surface control(DSC)and the nonlinear disturbance observer(NDO).DSC technique provides the ability to overcome the″explosion of complexity″problem in backstepping control.NDO is adopted to observe the uncertainties in nonlinear flight dynamic system.It has been proved that the proposed design method can guarantee uniformly ultimately boundedness of all the signals in the closed-loop system by Lyapunov stability theorem.Finally,simulation results show that the proposed controller provides better performance than the traditional nonlinear controller.

Adaptive integral dynamic surface control based on fully tuned radial basis function neural network

An adaptive integral dynamic surface control approach based on fully tuned radial basis function neural network （FTRBFNN） is presented for a general class of strict-feedback nonlinear systems,which may possess a wide class of uncertainties that are not linearly parameterized and do not have any prior knowledge of the bounding functions.FTRBFNN is employed to approximate the uncertainty online,and a systematic framework for adaptive controller design is given by dynamic surface control. The control algorithm has two outstanding features,namely,the neural network regulates the weights,width and center of Gaussian function simultaneously,which ensures the control system has perfect ability of restraining different unknown uncertainties and the integral term of tracking error introduced in the control law can eliminate the static error of the closed loop system effectively. As a result,high control precision can be achieved.All signals in the closed loop system can be guaranteed bounded by Lyapunov approach.Finally,simulation results demonstrate the validity of the control approach.

Adaptive Synchronization of Rssler System Based on Dynamic Surface Control

A synchronization scheme for R6ssler system based on Dynamic Surface Control （DSC） is proposed in this paper. The DSC method is a recursive design procedure like conventional backstepping methods. Different from the backstepping design, a first-order fdter is introduced in every DSC design step. For this introduced fdter, the derivative of the selected virtual control is avoided and then the drawback of ＂explosion of complexity＂ existing in backstepping design is overcome. Moreover, adaptive method is used for controller design when the system parameters are unknown. Finally, a numerical example is given to illustrate the effectiveness and performance of the proposed method.

Backstepping adaptive control of hydraulic Stewart platform using dynamic surface

Hydraulic Stewart platform is characterized by nonlinearity for driving system in essence,severe load coupling among the legs,which bring a great difficulty for controller design and performance improvement.Afore controller research is either low in tracking performance and movement smoothness when it ignores the nonlinearity and dynamics coupling,or complex in algorithm and has the need of acceleration feedback or observer when the dynamics coupling and nonlinearity is included.To solve the dilemma,a new controller,backstepping adaptive control of hydraulic Stewart platform using dynamic surface is put forward based on the complete dynamics including the upper platform dynamics and hydraulic nonlinearity in driving system.Asymptotic stability of the whole system is proved by Lyapunov method.The proposed algorithm is simple by avoiding the use of acceleration.The simulation results indicate that the control algorithm performs better than the normal PID controller in control precision,dynamic response and depression of the cross coupling.

Self-erasable dynamic surface patterns via controllable elastic modulus boosting multi-encoded and tamper-proof information storage

Dynamic surface patterns(DSPs)have attracted significant interest in anti-counterfeiting,enabling information to be stored,encrypted and decrypted in response to external stimuli.However,creating dynamic surface patterns,capable of controlling wrinkling time and independently modulating different information in both wrinkled and fluorescent states,remains a tremendous challenge.These limit DSPs to further enhance tamper-proofing capacity and extend the information storage density.Here,a rationally designed patterning strategy based on controllable elastic modulus was demonstrated to fabricate self-erasable dynamic surface patterns(S-DSPs)that increase information storage density.These novel S-DSPs strategically integrated amino co-oligomers(ACOs)with the 9-anthracenemethanol(9-AM)as skin layers,designing a bilayer multi-encoding system which could carry several different types of information with wrinkled and fluorescent patterns.The ACOs with relatively low molecular weight can endow the elastic modulus of skin layers with a wide range of regulation.As a result,the difference between the compressive strain and the critical wrinkle strain in the bilayer system would be precisely modulated by photo-dimerization to form quick-response(minimum<1 min)and self-erasable(3 min–8 days)wrinkled patterns for S-DSPs.Meanwhile,the fluorescence pattern could be independently erased and reprogrammed without affecting the change in the wrinkle pattern under modulus-controlled conditions.Moreover,controllable self-erasure in S-DSPs significantly develops tamper-proof capabilities in a supply chain.This original strategy could provide a new approach to the tamper-proof,high-density,and multi-encoded information storage in the product security or inkless printing.

Adaptive dynamic surface control for quadrotor-slung load transportation system with uncertainties

Quadrotors play a significant role in our lives and are transforming our lives.Transporting cable-suspended loads is an unavoidable quadrotor application trend and a hot research topic in the control field.Nonetheless,the load swing and unpredictability pose significant challenges to the quadrotor's stability.In this paper,an anti-swing controller with an inner-outer control strategy for the quadrotor-slung load transportation system is presented.To facilitate the controller design,the outer position dynamics are restructured in the form of cascades.Then,a virtual controller is created to force the underactuated states to the dynamic surface to ensure the position subsystem's stability.To improve robustness,an adaptive law is used to eliminate the effects of uncertain cable length.Lastly,a dynamic surface controller for the inner attitude subsystem is presented to drive the actual force to the virtual force.It is demonstrated that the control strategy can stabilize the quadrotor despite mass and cable length uncertainties.Comparative results are provided to demonstrate the efficacy and durability of the proposed method.

Morphodynamic signatures derived from daily surface elevation dynamics can explain the morphodynamic development of tidal flats

Understanding the sensitivity of tidal flats to environmental changes is challenging.Currently,most studies rely on process-based models to systematically explain the morphodynamic evolution of tidal flats.In this study,we proposed an alternative empirical approach to explore tidal flat dynamics using statistical indices based on long-term time series of daily surface elevation development.Surface elevation dynamic(SED)indices focus on the magnitude and period of surface elevation changes,while morphodynamic signature(MDS)indices relate sediment dynamics to environmental drivers.The statistical analyses were applied to an intervention site in the Netherlands to determine the effect of recently constructed groynes on the tidal flat.Using these analyses,we were able to(1)detect a reduction in the daily SED and(2)determine that the changes in the daily SED were predominantly caused by the reduction in wave impact between the groynes rather than the reduction in tidal currents.Overall,the presented results showed that the combination of novel statistical indices provides new insights into the trajectories of tidal flats,ecosystem functioning,and sensitivity to physical drivers(wind and tides).Finally,we suggested how the SED and MDS indices may help to explore the future trajectories and climate resilience of intertidal habitats.

Adaptive block dynamic surface control for integrated missile guidance and autopilot

A novel integrated guidance and autopilot design method is proposed for homing missiles based on the adaptive block dynamic surface control approach. The fully integrated guidance and autopilot model is established by combining the nonlinear missile dynamics with the nonlinear dynamics describing the pursuit situation of a missile and a target in the three-dimensional space. The integrated guidance and autopilot design problem is further converted to a state regulation problem of a time-varying nonlinear system with matched and unmatched uncertainties. A new and simple adaptive block dynamic surface control algorithm is proposed to address such a state regulation problem. The stability of the closed-loop system is proven based on the Lyapunov theory. The six degrees of freedom （6DOF） nonlinear numerical simulation results show that the proposed integrated guidance and autopilot algorithm can ensure the accuracy of target interception and the robust stability of the closed-loop system with respect to the uncertainties in the missile dynamics.

Adaptive dynamic surface control of NSVs with input saturation using a disturbance observer

Abstract An adaptive dynamic surface control （DSC） scheme is proposed for the multiinput and multioutput （MIMO） attitude motion of nearspace vehicles （NSVs） in the presence of external dis turbance, system uncertainty and input saturation. The external disturbance and the system uncer tainty are efficiently tackled using a Nussbaum disturbance observer （NDO）, and the adaptive controller is constructed by combining the dynamic surface control technique to handle the problem of ＂explosion of complexity＂ inherent in the conventional backstepping methodl For handling the input saturation, an auxiliary system is designed with the same order as that of the studied MIMO attitude system. Using the error between the saturation input and the desired control input as the input of the designed auxiliary system, a series of signals are generated to compensate for the effect of the saturation in the dynamic surface control design. It is proved that the developed control scheme can guarantee that all signals of the closedloop control system are semiglobally uniformly bounded. Finally, simulation results illustrate that the proposed control scheme can achieve satis factory tracking performance under the composite effects of the input saturation and the external disturbance.

Robust dynamic surface control of flexible joint robots using recurrent neural networks

A robust neuro-adaptive controller for uncertain flexible joint robots is presented. This control scheme integrates H^infinity disturbance attenuation design and recurrent neural network adaptive control technique into the dy- namic surface control framework. Two recurrent neural networks are used to adaptively learn the uncertain functions in a flexible joint robot. Then, the effects of approximation error and filter error on the tracking performance are attenuated to a prescribed level by the embedded H-infinity controller, so that the desired H-infinity tracking performance can be achieved. Finally. simulation results verifv the effectiveness of the nronosed control scheme.

Adaptive Neural Network Dynamic Surface Control for a Class of Nonlinear Systems with Uncertain Time Delays

This paper presents a solution to tracking control problem for a class of nonlinear systems with unknown parameters ana uncertain time-varying delays. A new adaptive neural network （NN） dynamic surface controller （DSC） is developed. Some assumptions on uncertain time delays, which were required to be satisfied in previous works, are removed by introducing a novel indirect neural network algorithm into dynamic surface control framework. Also, the designed controller is independent of the time delays. Moreover, the dynamic compensation terms are introduced to facilitate the controller design. It is shown that the closed-loop tracking error converges to a small neighborhood of zero. Finally, a chaotic circuit system is initially bench tested to show the effectiveness of the proposed method.