Terminal Angular Constraint Integrated Guidance and Control for Flexible Hypersonic Vehicle with Dead-Zone Input Nonlinearity

This paper presents an integrated guidance and control model for a flexible hypersonic vehicle with terminal angular constraints.The integrated guidance and control model is bounded and the dead-zone input nonlinearity is considered in the system dynamics.The line of sight angle,line of sight angle rate,attack angle and pitch rate are involved in the integrated guidance and control system.The controller is designed with a backstepping method,in which a first order filter is employed to avoid the differential explosion.The full tuned radial basis function(RBF)neural network(NN)is used to approximate the system dynamics with robust item coping with the reconstruction errors,the exactitude model requirement is reduced in the controller design.In the last step of backstepping method design,the adaptive control with Nussbaum function is used for the unknown dynamics with a time-varying control gain function.The uniform ultimate boundedness stability of the control system is proved.The simulation results validate the effectiveness of the controller design.

Adaptive feedback control for nonlinear triangular systems subject to uncertain asymmetric dead-zone input

In this paper,an adaptive control strategy is proposed to investigate the issue of uncertain dead-zone input for nonlinear triangular systems with unknown nonlinearities.The considered system has no precise priori knowledge about the dead-zone feature and growth rate of nonlinearity.Firstly,a dynamic gain is introduced to deal with the unknown growth rate,and the dead-zone characteristic is processed by the adaptive estimation approach without constructing the dead-zone inverse.Then,by virtue of hyperbolic functions and sign functions,a new adaptive state feedback controller is proposed to guarantee the global boundedness of all signals in the closed-loop system.Moreover,the uncertain dead-zone input problem for nonlinear upper-triangular systems is solved by the similar control strategy.Finally,two simulation examples are given to verify the effectiveness of the control scheme.

Tracking Control of Uncertain High-Order Nonlinear Systems with Odd Rational Powers and the Dead-Zone Input:A Direct Fuzzy Adaptive Control Method

This work studies the tracking issue of uncertain nonlinear systems.The existence of odd rational powers,multiple unknown parameters and the dead-zone input add many difficulties for control design.During procedures of the control design,by introducing an appropriate Lyapunov function,utilizing recursive control method and the inequality technique,some appropriate intermediate auxiliary control laws are designed under the hypothesis that nonlinear terms in the system are known.When those nonlinear terms are unknown,by employing the powerful approximation ability of fuzzy systems,the intermediate auxiliary control laws are approximated recursively and used to construct the virtual control.Finally,a new fuzzy adaptive tracking controller is constructed to ensure a small tracking error and the boundedness of all states.In this paper,the overparameterization problem is significantly avoided since only two adaptive laws are adopted.Numerical and practical examples are used to verify the raised theory.

A Fractional-Order Ultra-Local Model-Based Adaptive Neural Network Sliding Mode Control of n-DOF Upper-Limb Exoskeleton With Input Deadzone

This paper proposes an adaptive neural network sliding mode control based on fractional-order ultra-local model for n-DOF upper-limb exoskeleton in presence of uncertainties,external disturbances and input deadzone.Considering the model complexity and input deadzone,a fractional-order ultra-local model is proposed to formulate the original dynamic system for simple controller design.Firstly,the control gain of ultra-local model is considered as a constant.The fractional-order sliding mode technique is designed to stabilize the closed-loop system,while fractional-order time-delay estimation is combined with neural network to estimate the lumped disturbance.Correspondingly,a fractional-order ultra-local model-based neural network sliding mode controller(FO-NNSMC) is proposed.Secondly,to avoid disadvantageous effect of improper gain selection on the control performance,the control gain of ultra-local model is considered as an unknown parameter.Then,the Nussbaum technique is introduced into the FO-NNSMC to deal with the stability problem with unknown gain.Correspondingly,a fractional-order ultra-local model-based adaptive neural network sliding mode controller(FO-ANNSMC) is proposed.Moreover,the stability analysis of the closed-loop system with the proposed method is presented by using the Lyapunov theory.Finally,with the co-simulations on virtual prototype of 7-DOF iReHave upper-limb exoskeleton and experiments on 2-DOF upper-limb exoskeleton,the obtained compared results illustrate the effectiveness and superiority of the proposed method.

Vibration Control of A Flexible Marine Riser System Subject to Input Dead Zone and Extraneous Disturbances

An observer-based adaptive backstepping boundary control is proposed for vibration control of flexible offshore riser systems with unknown nonlinear input dead zone and uncertain environmental disturbances.The control algorithm can update the control law online through real-time data to make the controller adapt to the environment and improve the control precision.Specifically,based on the adaptive backstepping framework,virtual control laws and Lyapunov functions are designed for each subsystem.Three direction interference observers are designed to track the timevarying boundary disturbance.On this basis,the inverse of the dead zone and linear state transformation are used to compensate for the original system and eliminate the adverse effects of the dead zone.In addition,the stability of the closed-loop system is proven by Lyapunov stability theory.All the system states are bounded,and the vibration offset of the riser converges to a small area of the initial position.Finally,four examples of flexible marine risers are simulated in MATLAB to verify the effectiveness of the proposed controller.

Influence of heat input on microhardness and microstructure across the welding interface between stainless steel and low alloy steel

The welding interface is crucial to the service safety of dissimilar metal weld(DMW)joints between stainless steel(SS)and low alloy(LA)steel.Different status of welding interfaces was prepared by cladding SS consumables to LA steel substrates with different heat inputs via tungsten inert gas arc welding(TIG),followed by a series of microstructural characterizations and hardness tests.Results showed that a hardening and transition layer(TL)would be generated along the welding interface,and the width and hardening degree of the TL would increase with the heat input.Meanwhile,heavy load hardness tests showed that highly severe inhomogeneous plastic deformation and the microcrack would be generated in the interfacial region and the welding interface respectively in the highest heat input sample(1.03 kJ/mm).These results indicate that the increase in heat input would deteriorate the bonding performance of DMW joints.Further microstructural observations showed that the higher hardening degree of the highest heat input sample was mainly attributed to the stronger grain boundary,solution,and dislocation strengthening effects.

Dynamic Event-Triggered Consensus Control for Input Constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first designed.Then,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale networks.It is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event time.In addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable parameter.Furthermore,the results are extended to regional consensus of the MASs with the bounded control protocol.Numerical simulations show the effectiveness of the proposed approach.

Adaptive Sensor-Fault Tolerant Control of Unmanned Underwater Vehicles With Input Saturation

This paper investigates the tracking control problem for unmanned underwater vehicles(UUVs)systems with sensor faults,input saturation,and external disturbance caused by waves and ocean currents.An active sensor fault-tolerant control scheme is proposed.First,the developed method only requires the inertia matrix of the UUV,without other dynamic information,and can handle both additive and multiplicative sensor faults.Subsequently,an adaptive fault-tolerant controller is designed to achieve asymptotic tracking control of the UUV by employing robust integral of the sign of error feedback method.It is shown that the effect of sensor faults is online estimated and compensated by an adaptive estimator.With the proposed controller,the tracking error and estimation error can asymptotically converge to zero.Finally,simulation results are performed to demonstrate the effectiveness of the proposed method.

Exact controllability of rational expectations model with multiplicative noise and input delay

This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.

Estimating the Input Power of a Power Plant Using the Efficiency of the Inverter

The study focuses on estimating the input power of a power plant from available data, using the theoretical inverter efficiency as the key parameter. The paper addresses the problem of missing data in power generation systems and proposes an approach based on the efficiency formula widely documented in the literature. In the absence of input data, this method makes it possible to estimate the plant’s input power using data extracted from the site, in particular that provided by the Ministry of the Environment. The importance of this study lies in the need to accurately determine the input power in order to assess the overall performance of the energy system.

Adaptive Variable Structure Control of MIMO Nonlinear Systems with Time-varying Delays and Unknown Dead-zones

In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output （MIMO） nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The unknown time-varying delay uncer- tainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The approach removes the assumption of linear function outside the deadband without necessarily constructing a dead-zone inverse as an added contribution. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation term for the upper bound of the residual and optimal approximation error as well as the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. In addition, a modified adaptive control algorithm is given in order to avoid the high-frequency chattering phenomenon. Simulation results demonstrate the effectiveness of the approach.

ADAPTIVE CONTROL OF FLEXIBLE BEAM WITH UNKNOWN DEAD-ZONE IN THE DRIVING MOTOR

Adaptive control of a flexible beam system preceded by an unknown dead-zonein the driving motor is investigated in state space form. By introducing an important lemma forsimplifying error equation between the flexible beam model and the matching reference model, arobust adaptive control scheme is developed by involving the dead-zone inverse terms. The newadaptive control law ensures global stability of the entire system and achieves desired trackingprecision even when the slopes of the dead-zone are not equal. Simulations performed on a typicalflexible beam system illustrate and clarify the validity of this approach.

Anti-Dead-Zone Integral Sliding Control and Active Vibration Suppression of a Free-floating Space Robot with Elastic Base and Flexible Links

Under the conditions of joint torque output dead-zone and external disturbance,the trajectory tracking and vibration suppression for a free-floating space robot(FFSR)system with elastic base and flexible links were discussed.First,using the Lagrange equation of the second kind,the dynamic model of the system was derived.Second,utilizing singular perturbation theory,a slow subsystem describing the rigid motion and a fast subsystem corresponding to flexible vibration were obtained.For the slow subsystem,when the width of deadzone is uncertain,a dead-zone pre-compensator was designed to eliminate the impact of joint torque output dead-zone,and an integral sliding mode neural network control was proposed.The integral sliding mode term can reduce the steady state error.For the fast subsystem,an optimal linear quadratic regulator(LQR)controller was adopted to damp out the vibration of the flexible links and elastic base simultaneously.Finally,computer simulations show the effectiveness of the compound control method.

Adaptive Attitude Control for Multi-MUAV Systems With Output Dead-Zone and Actuator Fault

Many mechanical parts of multi-rotor unmanned aerial vehicle(MUAV)can easily produce non-smooth phenomenon and the external disturbance that affects the stability of MUAV.For multi-MUAV attitude systems that experience output dead-zone,external disturbance and actuator fault,a leader-following consensus anti-disturbance and fault-tolerant control(FTC)scheme is proposed in this paper.In the design process,the effect of unknown nonlinearity in multi-MUAV systems is addressed using neural networks(NNs).In order to balance out the effects of external disturbance and actuator fault,a disturbance observer is designed to compensate for the aforementioned negative impacts.The Nussbaum function is used to address the problem of output dead-zone.The designed fault-tolerant controller guarantees that the output signals of all followers and leader are synchronized by the backstepping technique.Finally,the effectiveness of the control scheme is verified by simulation experiments.

Design of Observer-based Adaptive Controller for Nonlinear Systems with Unmodeled Dynamics and Actuator Dead-zone

This paper presents an up-to-date study on the observer-based control problem for nonlinear systems in the presence of unmodeled dynamics and actuator dead-zone.By introducing a dynamic signal to dominate the unmodeled dynamics and using an adaptive nonlinear damping to counter the effects of the nonlinearities and dead-zone input,the proposed observer and controller can ensure that the closed-loop system is asymptotically stable in the sense of uniform ultimate boundedness.Only one adaptive parameter is needed no matter how many unknown parameters there are.The system investigated is more general and there is no need to solve Linear matrix inequality （LMI）.Moreover,with our method,some assumptions imposed on nonlinear terms and dead-zone input are relaxed.Finally,simulations illustrate the effectiveness of the proposed adaptive control scheme.

Adaptive variable structure control for large-scale time-delayed systems with unknown nonlinear dead-zone

The problem of adaptive fuzzy control for a class of large-scale, time-delayed systems with unknown nonlinear dead-zone is discussed here. Based on the principle of variable structure control, a design scheme of adaptive, decentralized, variable structure control is proposed. The approach removes the conditions that the dead-zone slopes and boundaries are equal and symmetric, respectively. In addition, it does not require that the assumptions that all parameters of the nonlinear dead-zone model and the lumped uncertainty are known constants. The adaptive compensation terms of the approximation errors axe adopted to minimize the influence of modeling errors and parameter estimation errors. By theoretical analysis, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded, with tracking errors converging to zero. Simulation results demonstrate the effectiveness of the approach.

Parameter estimation for dual-rate sampled Hammerstein systems with dead-zone nonlinearity

The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.

Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison

Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state responses.This paper presents a deep observation on and a comparison between two of those methods:the generalized extended-state observer(GESO)and the equivalent input disturbance(EID)from assumptions,system configurations,stability conditions,system design,disturbance-rejection performance,and extensibility.A time-domain index is introduced to assess the disturbance-rejection performance.A detailed observation of disturbance-suppression mechanisms reveals the superiority of the EID approach over the GESO method.A comparison between these two methods shows that assumptions on disturbances are more practical and the adjustment of disturbance-rejection performance is easier for the EID approach than for the GESO method.

Stabilization of fractional bilinear systems with multiple inputs

In this paper,we study in a constructive way the stabilization problem of fractional bilinear systems with multiple inputs.Using the quadratic Lyapunov functions and some additional hypotheses on the unit sphere,we construct stabilizing feedback laws for the considered fractional bilinear system.A numerical example is given to illustrate the efficiency of the obtained result.

Input Structure Design for Structural Controllability of Complex Networks

This paper addresses the problem of the input design of large-scale complex networks.Two types of network components,redundant inaccessible strongly connected component(RISCC)and intermittent inaccessible strongly connected component(IISCC)are defined,and a subnetwork called a driver network is developed.Based on these,an efficient method is proposed to find the minimum number of controlled nodes to achieve structural complete controllability of a network,in the case that each input can act on multiple state nodes.The range of the number of input nodes to achieve minimal control,and the configuration method(the connection between the input nodes and the controlled nodes)are presented.All possible input solutions can be obtained by this method.Moreover,we give an example and some experiments on real-world networks to illustrate the effectiveness of the method.