A modular adaptive control design with ISS analysis for nonminimum phase hypersonic vehicle models

Air‐breathing hypersonic vehicles typically exhibit a nonminimum phase behavior when altitude is controlled via lift generation. This phenomenon prohibits the use of classical inversion‐based control techniques. Dynamic models of these vehicles are also subject to parametric uncertainties and unmodeled dynamics related to flexible effects of the fuselage. In this paper, we present a modular adaptive control method that achieves asymptotic setpoint tracking in both airspeed and altitude using thrust and elevator deflection as the only control inputs for a generic longitudinal model of a hypersonic cruise. The nonminimum phase problem is overcome through output redefinition, with altitude controlled by pitching moment. The internal dynamics, flight path angle, and altitude are then stabilized by saturating the interconnections and exploiting local stability properties. A new technique for the use of saturation functions in error coordinate is presented. The adaptive controller for altitude uses a pitch rate observer combined with projection. This control augmentation decouples the parameter estimation errors from internal dynamics, allowing for the use of small‐gain arguments. Simulation results from a vehicle model with flexible effects and parametric uncertainty are included to demonstrate control effectiveness.     

基于自适应模糊控制的飞机自动着陆系统

为了更好地完成着陆任务,引入自适应模糊控制算法应用于飞机自动着陆时下降以及改平的纵向控制中,利用变论域收缩因子来优化模糊控制器的量化因子,同时配合模糊规则对比例因子的自适应调整,从而使飞机更精确地跟踪下滑道.通过仿真表明该控制系统具有良好的动态性能,有效地提高了飞机自动着陆的精度.     

Direct adaptive neural tracking control for a class of stochastic pure‐feedback nonlinear systems with unknown dead‐zone

This paper considers the problem of adaptive neural tracking control for a class of nonlinear stochastic pure‐feedback systems with unknown dead zone. Based on the radial basis function neural networks' online approximation capability, a novel adaptive neural controller is presented via backstepping technique. It is shown that the proposed controller guarantees that all the signals of the closed‐loop system are semi‐globally, uniformly bounded in probability, and the tracking error converges to an arbitrarily small neighborhood around the origin in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the suggested control scheme. Copyright © 2012 John Wiley & Sons, Ltd.     

Finite-time adaptive control for nonlinear systems with uncertain parameters based on the command filters

The trajectory tracking control problem for a class of nonlinear systems with uncertain parameters is considered in this article. A new adaptive finite-time tracking control is designed based on the adaptive backstepping method via the command filters. The command filter mechanism can avoid the calculation of partial derivatives and solve the “explosion of complexity” in the backstepping design. The compensation signals are introduced to eliminate errors produced by the command filters. The proposed adaptive backstepping control can guarantee the tracking error remains in a small neighborhood of the origin in finite time, while the practical finite-time stability of the control systems with uncertain parameters is proven by the stability criterion. The effectiveness of the proposed scheme is verified by some simulation results.     

Adaptive neural network command filtered backstepping control of pure‐feedback systems in presence of full state constraints

An adaptive neural network (NN) command filtered backstepping control is proposed for the pure‐feedback system subjected to time‐varying output/stated constraints. By introducing a one‐to‐one nonlinear mapping, the obstacle caused by full stated constraints is conquered. The adaptive control law is constructed by command filtered backstepping technology and radial basis function NNs, where only one learning parameter needs to be updated online. The stability analysis via nonlinear small‐gain theorem shows that all the signals in closed‐loop system are semiglobal uniformly ultimately bounded. The simulation examples demonstrate the effectiveness of the proposed control scheme.     

Adaptive saturation compensation for strict-feedback systems with unknown control coefficient and input saturation

This work presents an adaptive saturation compensation scheme for the strict-feedback uncertain systems with unknown control coefficient and input saturation. An adaptive saturation dynamic filter that does not require the a priori information of the completely unknown control coefficient is incorporated to correct position errors online to reduce the saturation effect. A Nussbaum-type function is employed to handle the unknown control coefficient and avoid the control singularity. The adaptive command-filtered backstepping is employed to derive the adaptive controller. The repeated differential operations of stabilizing functions required in the traditional backstepping are obviated due to command filters. It is analyzed that the designed adaptive controller achieves the system output tracking and the closed-loop uniform ultimate stability. A simulation example is provided to validate the scheme.     

Decentralized adaptive multi‐dimensional Taylor network tracking control for a class of large‐scale stochastic nonlinear systems

This paper investigates the problem of adaptive multi‐dimensional Taylor network (MTN) decentralized tracking control for large‐scale stochastic nonlinear systems. Minimizing the influence of randomness and complex nonlinearity, which increases computational complexity, and improving the controller's real‐time performance for the stochastic nonlinear system are of great significance. With combining adaptive backstepping with dynamic surface control, a decentralized adaptive MTN tracking control approach is developed. In the controller design, MTNs are used to approximate nonlinearities, the backstepping technique is employed to construct the decentralized adaptive MTN controller, and the dynamic surface control technique is adopted to avoid the “explosion of computational complexity” in the backstepping design. It is proven that all the signals in the closed‐loop system remain bounded in probability, and the tracking errors converge to a small residual set around the origin in the sense of a mean quartic value. As the MTN contains only addition and multiplication, the proposed control method is more simplified and of good real‐time performance, compared with the existing control methods for large‐scale stochastic nonlinear systems. Finally, a numerical example is presented to illustrate the effectiveness of the proposed design approach, and simulation results demonstrate that the method presented in this paper has good real‐time performance and control quality, and the dynamic performance of the closed‐loop system is satisfactory.     

Adaptive control for switched uncertain nonlinear systems with time‐varying output constraint and input saturation

This paper is concerned with adaptive tracking control for switched uncertain nonlinear systems, which contain the time‐varying output constraint (TVOC) and input asymmetric saturation characteristic. In response to the unknown functions, the fuzzy logic systems are adopted. The controller is constructed by the backstepping technique. Based on the Tangent Barrier Lyapunov Function (BLF‐Tan), an adaptive switched control scheme is designed. It is demonstrated that all signals in the resulted system are semiglobally uniformly ultimately bounded with TVOC under arbitrary switchings. Furthermore, the effectiveness of presented control method is validated via the simulation example.     

Output‐feedback adaptive tracking control of stochastic nonlinear systems using multi‐dimensional Taylor network

In this paper, an adaptive multi‐dimensional Taylor network (MTN) control scheme based on the backstepping and dynamic surface control (DSC) is developed to solve the tracking control problem for the stochastic nonlinear system with immeasurable states. The MTNs are used to approximate the unknown nonlinearities, and then based on the multivariable analog of circle criterion, an observer is first introduced to estimate the immeasurable states. By combining the adaptive backstepping technique and the DSC technique, an adaptive MTN output‐feedback backstepping DSC approach is developed. It is shown that the proposed controller ensures that all signals of the closed‐loop system are remain bounded in probability, and the tracking error converges to an arbitrarily small neighborhood around the origin in the sense of probability. Finally, the effectiveness of the design approach is illustrated by simulation results.     

Fault‐tolerant control using command‐filtered adaptive back‐stepping technique: Application to hypersonic longitudinal flight dynamics

In this paper, the adaptive back‐stepping controller is investigated for a class of strict‐feedback systems using the command filter technique. Adaptive laws are designed for updating the controller parameters when both the plant parameters and actuator‐failure parameters are unknown. Furthermore, the auxiliary dynamics is developed to deal with the input constraints. Closed‐loop stability and asymptotic‐state tracking are ensured. The method is applied to the longitudinal dynamics of a generic hypersonic aircraft in the presence of actuator faults and input constraints. Based on the parameter estimation, the command‐filtered adaptive back‐stepping control is presented. Simulation results on the control‐oriented model show that the proposed approach achieves good tracking performance. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive asymptotical tracking controller design for uncertain nonaffine nonlinear system with high‐order mismatched disturbances

In this paper, the problem of anti‐disturbance asymptotical tracking control is studied for nonaffine systems with high‐order mismatched disturbances. The disturbances can be described as polynomial functions, which are first estimated by constructing generalized extended state filter. The nonaffine system is changed into an augmented affine system via introducing an auxiliary integrator. A novel adaptive anti‐disturbance tracking controller is recursively designed, where the disturbance estimation is used for feedforward compensation at each step. A sliding mode differentiator is applied to reduce the computational burden taken by the backstepping method. The boundedness of the closed‐loop system is proved based on Lyapunov stability theory and zero error tracking performance is ensured. Finally, a numerical example is provided to show the effectiveness of the proposed scheme.     

Adaptive robust output‐feedback motion control of hydraulic actuators

Most previous advanced motion control of hydraulic actuators used full‐state feedback control techniques. However, in many cases, only position feedback is available, and thus, there are imperious demands for output‐feedback control for hydraulic systems. This paper firstly transforms a hydraulic model into an output feedback–dependent form. Thus, the K‐filter can be employed, which provides exponentially convergent estimates of the unmeasured states. Furthermore, this observer has an extended filter structure so that online parameter adaptation can be utilized. In addition, it is a well‐known fact that any realistic model of a hydraulic system suffers from significant extent of uncertain nonlinearities and parametric uncertainties. This paper constructs an adaptive robust controller with backstepping techniques, which is able to take into account not only the effect of parameter variations coming from various hydraulic parameters but also the effect of hard‐to‐model nonlinearities such as uncompensated friction forces, modeling errors, and external disturbances. Moreover, estimation errors that come from initial state estimates and uncompensated disturbances are dealt with via certain robust feedback at each step of the adaptive robust backstepping design. After that, a detailed stability analysis for the output‐feedback closed‐loop system is scrupulously checked, which shows that all states are bounded and that the controller achieves a guaranteed transient performance and final tracking accuracy in general and asymptotic output tracking in the presence of parametric uncertainties only. Extensive experimental results are obtained for a hydraulic actuator system and verify the high‐performance nature of the proposed output‐feedback control strategy.     

飞机着陆下滑道与输电线路垂直防护间距分析

飞机着陆下滑过程中，应与穿越或接近机场飞行区端净空的架空输电线路保持一定的垂直间距，防止对机载导航电子设备干扰。根据不同类别飞机着陆系统的性能和防护指标，分析了无线电干扰程度，并验算了干扰防护率；结合下滑道净空特点和相关标准规定，计算出了下滑道关键点净空要求及防护间距。结果表明：对于双信标着陆系统，下滑道应与架空输电线路保持不小于150m的垂直间距；对于当前主流使用的仪表着陆系统，应根据下滑信标发射方向和飞行程序计算确定垂直间距，150m的垂直间距有很大裕度。     

Adaptive finite‐time formation tracking control for multiple nonholonomic UAV system with uncertainties and quantized input

An adaptive finite‐time formation tracking control approach is proposed for multiple unmanned aerial vehicle (UAV) system with quantized input signals in this paper. The UAVs are described by nonholonomic kinematic model and autopilot model with uncertainties. An enhanced hysteretic quantizer is introduced to avoid chattering, and some restrictions are released by using a new quantization decomposition method. Based on backstepping technique and finite‐time Lyapunov stability theory, the adaptive finite‐time controller is designed for the trajectory tracking of the multi‐UAV formation. The nonholonomic constraints are solved by a transverse function. A transformation is introduced to the control input signals to eliminate the quantization effect. Stability analysis proves that the tracking errors can converge to a small neighborhood of the origin within finite time and all the closed‐loop signals are semiglobally finite‐time bounded. The effectiveness of the proposed control approach is validated by simulation and experiment.     

Adaptive backstepping trajectory tracking controller for a miniature helicopter

An adaptive backstepping controller is proposed to achieve the asymptotically stable trajectory tracking for a miniature helicopter. The helicopter model is firstly decomposed into a cascaded structure between the position and attitude loops with unmodeled dynamics. The backstepping technique is applied to exploit this cascaded structure and to streamline the controller design procedure. Hyperbolic tangent functions, instead of traditional sign functions, are adopted to complete adaptive algorithms for adjusting the upper bounds of the unmodeled dynamics. Further, the controller introduces an auxiliary dynamic system to ensure the thrust constraint and to obviate singularity during the command attitude extraction. The stability analysis demonstrates that, the asymptotical stability of the auxiliary dynamic system warrants the asymptotically stable tracking of the miniature helicopter system. Simulations verify the theoretical results and analyze the tracking performance. Copyright © 2016 John Wiley & Sons, Ltd.     

Adaptive output feedback actuator failure compensation for a class of non‐linear systems

An adaptive compensation control scheme using output feedback is designed and analysed for a class of non‐linear systems with state‐dependent non‐linearities in the presence of unknown actuator failures. For a linearly parameterized model of actuator failures with unknown failure values, time instants and pattern, a robust backstepping‐based adaptive non‐linear controller is employed to handle the system failure, parameter and dynamics uncertainties. Robust adaptive parameter update laws are derived to ensure closed‐loop signal boundedness and small tracking errors, in general, and asymptotic regulation, in particular. An application to controlling the angle of attack of a non‐linear hypersonic aircraft dynamic model in the presence of elevator segment failures is studied and simulation results show that the developed adaptive control scheme has desired actuator failure compensation performance. Copyright © 2004 John Wiley & Sons, Ltd.     

Adaptive preview control with deck motion compensation for autonomous carrier landing of an aircraft

In this article, an autonomous carrier landing problem of an aircraft is addressed by developing an autonomous carrier landing system (ACLS) composed of previewable guidance and control systems. In the guidance system, an appropriate touchdown point is estimated by predicting the seakeeping motion of the deck by unscented Kalman filtering technique, which is then utilized to adjust the reference glide path and produce an effective deck motion compensation, indispensable for a safe landing. The adaptive preview control (APC) scheme is proposed, which utilizes future reference information. The feedback and feedforward adaptive gains are derived through the Lyapunov stability theorem ensuring better tracking response and disturbance rejection. Hence, the asymptotic stability of the closed-loop system is guaranteed. The simulation results depict better performance of the proposed ACLS in the presence of deck fluctuations and airwake disturbance compared with PID and LMI based preview control schemes.     

Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

Cooperative adaptive neural partial tracking errors constrained control for nonlinear multi‐agent systems

This paper considers the problem of partial tracking errors constrained for high‐order nonlinear multi‐agent systems in strict‐feedback form. In the control design, radial‐based function neural networks are utilized to identify uncertain nonlinear functions, and a cooperative adaptive dynamic surface control is proposed to avoid the explosion of complexity in the backstepping technique. Based on the minimal learning parameter technique and the predefined performance approach, a novel cooperative adaptive neural network control method is developed. The proposed controller is able to guarantee that all the closed‐loop network signals are cooperative semi‐globally uniformly ultimately bounded, and partial tracking errors confine all times within the predefined bounds. Finally, simulation example and comparative example with previous methods are given to verify and clarify the effectiveness of the new design procedure. Copyright © 2016 John Wiley & Sons, Ltd.     

Robust adaptive control for non‐linear systems in generalized output‐feedback canonical form

Design of global robust adaptive output‐feedback dynamic compensators for stabilization and tracking of a class of systems that are globally diffeomorphic into systems in generalized output‐feedback canonical form is investigated. This form includes as special cases the standard output‐feedback canonical form and various other forms considered previously in the literature. Output‐dependent non‐linearities are allowed to enter both additively and multiplicatively. The system is allowed to contain unknown parameters multiplying output‐dependent non‐linearities and, also, unknown non‐linearities satisfying certain bounds. Under the assumption that a constant matrix can be found to achieve a certain property, it is shown that a reduced‐order observer and a backstepping controller can be designed to achieve practical stabilization of the tracking error. If this assumption is not satisfied, it is shown that the control objective can be achieved by introducing additional dynamics in the observer. Sufficient conditions under which asymptotic tracking and stabilization can be achieved are also given. This represents the first robust adaptive output‐feedback tracking results for this class of systems. Copyright © 2003 John Wiley & Sons, Ltd.