Non-fragile switching tracking control for a flexible air-breathing hypersonic vehicle based on polytopic LPV model

This article proposes a linear parameter varying (LPV) switching tracking control scheme for a flexible air-breathing hypersonic vehicle (FAHV). First, a polytopic LPV model is constructed to represent the complex nonlinear longitudinal model of the FAHV by using Jacobian linearization and tensor-product (T-P) model transformation approach. Second, for less conservative controller design purpose, the flight envelope is divided into four sub-regions and a non-fragile LPV controller is designed for each parameter sub-region. These non-fragile LPV controllers are then switched in order to guarantee the closed-loop FAHV system to be asymptotically stable and satisfy a specified performance criterion. The desired non-fragile LPV switching controller is found by solving a convex constraint problem which can be efficiently solved using available linear matrix inequality (LMI) techniques, and robust stability analysis of the closed-loop FAHV system is verified based on multiple Lypapunov functions (MLFs). Finally, numerical simulations have demonstrated the effectiveness of the proposed approach.     

Robust control for an unmanned helicopter with constrained flapping dynamics

In this paper, a neural network based adaptive prescribed performance control scheme is proposed for the altitude and attitude tracking system of the unmanned helicopter in the presence of state and output constraints. For handling the state constraints, the barrier Lyapunov function and the saturation function are employed. And, the prescribed performance method is used to deal with the flapping angle constraints for the unmanned helicopter. It is proved that the proposed control approach can ensure that all the signals of the resulting closed-loop system are bounded, and the tracking errors are within the prescribed performance bounds for all time. The numerical simulation is given to illustrate the performance of the proposed scheme.     

Virtual target guidance-based distributed model predictive control for formation control of multiple UAVs

The paper proposes a Virtual Target Guidance (VTG)-based distributed Model Predictive Control (MPC) scheme for formation control of multiple Unmanned Aerial Vehicles (UAVs). First, a framework of distributed MPC scheme is designed in which each UAV only shares the information with its neighbors, and the obtained local Finite-Horizon Optimal Control Problem (FHOCP) can be solved by swarm intelligent optimization algorithm. Then, a VTG approach is developed and integrated into the distributed MPC scheme to achieve trajectory tracking and obstacle avoidance. Further, an event-triggered mechanism is proposed to reduce the computational burden for UAV formation control, which takes into consideration the predictive state errors as well as the convergence of cost function. Numerical simulations show that the proposed VTG-based distributed MPC scheme is more computationally efficient to achieve formation control of multiple UAVs in comparison with the traditional distributed MPC method.     

Adaptive event-triggered distributed optimal guidance design via adaptive dynamic programming

In this paper, the multi-missile cooperative guidance system is formulated as a general nonlinear multi-agent system. To save the limited communication resources, an adaptive eventtriggered optimal guidance law is proposed by designing a synchronization-error-driven triggering condition, which brings together the consensus control with Adaptive Dynamic Programming(ADP) technique. Then, the developed event-triggered distributed control law can be employed by finding an approximate solution of eve...     

Event-triggered and consensus-based attitude tracking alignment for discrete-time multiple spacecraft system exploiting interference

This paper presents a discrete-time attitude control strategy with equi-global practical stabilizability for aligning the attitude of multiple spacecraft to a predesigned configuration according to a time-variant reference. By utilizing the interference of the wireless channel, the communication scheme designed in this paper can save communication resources, amount of computation, and energy proportionally to the number of spacecraft. The exact discrete-time model and approximate discrete-time model of the consensus-based spacecraft tracking system are given. Then the framework for the design of an event-triggered control scheme for the exact discrete-time system via its approximate models is developed, which avoids the periodic actuation, and Zeno behavior is proved to be excluded. Furthermore, the control scheme can handle the presence of the unknown fading channel. Finally, simulation results are presented to demonstrate the effectiveness of the control strategy.     

飞行模拟转台高精度数字重复控制器的设计

从工程的角度讨论了离散重复控制系统的设计,所提出的重复控制方法可保证速度跟踪误差快速收敛为零。在重复控制器中采用了高阶低通滤波器和动态补偿器,改善了跟踪精度,保证了系统的稳定性,减少了周期性扰动误差。将所提出的方法应用于飞行模拟转台伺服系统的速度控制中,仿真结果表明,针对周期指令信号和周期干扰信号可保证较高的跟踪精度和较强的稳定性和鲁棒性。     

Event-triggered cooperative target tracking in wireless sensor networks

Since the issues of low communication bandwidth supply and limited battery capacity are very crucial for wireless sensor networks, this paper focuses on the problem of event-triggered cooperative target tracking based on set-membership information filtering. We study some fundamental properties of the set-membership information filter with multiple sensor measure-ments. First, a sufficient condition is derived for the set-membership information filter, under which the boundedness of the outer ellipsoidal approximation set of the estimation means is guaranteed. Second, the equivalence property between the parallel and sequential versions of the set-membership information filter is presented. Finally, the results are applied to a 1D event-triggered target tracking scenario in which the negative information is exploited in the sense that the measurements that do not satisfy the triggering conditions are modelled as set-membership mea-surements. The tracking performance of the proposed method is validated with extensive Monte Carlo simulations.     

基于新型终端滑模的航天器执行器故障容错姿态控制

针对受干扰的刚体航天器冗余执行器存在故障与控制受限的姿态跟踪控制问题,提出一类基于新型指数形式的非奇异快速滑模面（ENFTSM）与趋近律的姿态容错控制器设计方法。当部分推力器发生故障时,假设剩余推力器具有输出饱和特性且能提供足够推力保证航天器执行任务,相比一般终端滑模控制器,本文设计的控制器不仅能使系统状态以更快的速度到达平衡点,且不需要在线对执行器故障信息进行检测和分离。基于Lyapunov方法证明本文设计的控制器能保证闭环系统稳定,且能有效地抑制外部干扰、控制受限和执行器故障等约束。最后对提出的控制算法进行了数值仿真,其结果表明了该控制器的有效性。     

Event-triggered control for containment maneuvering of second-order MIMO multi-agent systems with unmatched uncertainties and disturbances

This paper is concerned with distributed containment maneuvering of second-order Multi-Input Multi-Output (MIMO) multi-agent systems with non-periodic communication and actuation. The agent is subject to unmatched nonlinear dynamics and external disturbances. Event-triggered containment maneuvering control methods is developed based on a modular design. Specifically, an estimator module is constructed based on neural networks and the non-periodic obtained follower information through event-triggered communication. Next, a controller module is designed by using the identified information from the estimator module and a third-order linear tracking differentiator. An event-triggered mechanism is introduced for updating the actuator. Then, a path update law is designed based on the non-periodic leader information through event-triggered communication. The closed-loop system cascaded by the estimation subsystem and control subsystem is proved to be input-to-state stable, and Zeno behavior is excluded in the control process. The proposed method is capable of reducing the consumption of communication and actuation. A simulation example is provided to substantiate the effectiveness of the proposed event-triggered control method for distributed containment maneuvering of second-order MIMO multi-agent systems.     

Friction compensation for low velocity control of hydraulic flight motion simulator: A simple adaptive robust approach

Low-velocity tracking capability is a key performance of flight motion simulator (FMS), which is mainly affected by the nonlinear friction force. Though many compensation schemes with ad hoc friction models have been proposed, this paper deals with low-velocity control without friction model, since it is easy to be implemented in practice. Firstly, a nonlinear model of the FMS middle frame, which is driven by a hydraulic rotary actuator, is built. Noting that in the low velocity region, the unmodeled friction force is mainly characterized by a changing-slowly part, thus a simple adaptive law can be employed to learn this changing-slowly part and compensate it. To guarantee the boundedness of adaptation process, a discontinuous projection is utilized and then a robust scheme is proposed. The controller achieves a prescribed output tracking transient performance and final tracking accuracy in general while obtaining asymptotic output tracking in the absence of modeling errors. In addition, a saturated projection adaptive scheme is proposed to improve the globally learning capability when the velocity becomes large, which might make the previous proposed projection-based adaptive law be unstable. Theoretical and extensive experimental results are obtained to verify the high-performance nature of the proposed adaptive robust control strategy.     

Event-triggered adaptive control for attitude tracking of spacecraft

Plug-and-play technology is an important direction for future development of spacecraft and how to design controllers with less communication burden and satisfactory performance is of great importance for plug-and-play spacecraft. Considering attitude tracking of such spacecraft with unknown inertial parameters and unknown disturbances, an event-triggered adaptive backstepping controller is designed in this paper. Particularly, a switching threshold strategy is employed to design the event-triggering mechanism. By introducing a new linear time-varying model, a smooth function, an integrable auxiliary signal and a bound estimation approach, the impacts of the network-induced error and the disturbances are effectively compensated for and Zeno phenomenon is successfully avoided. It is shown that all signals of the closed-loop system are globally uniformly bounded and both the attitude tracking error and the angular velocity tracking error converge to zero. Compared with conventional control schemes, the proposed scheme significantly reduces the communication burden while providing stable and accurate response for attitude maneuvers. Simulation results are presented to illustrate the effectiveness of the proposed scheme.     

Novel adaptive neural control of flexible air-breathing hypersonic vehicles based on sliding mode differentiator

A novel adaptive neural control strategy is exploited for the longitudinal dynamics of a generic flexible air-breathing hypersonic vehicle(FAHV).By utilizing functional decomposition method, the dynamics of FAHV is decomposed into the velocity subsystem and the altitude subsystem.For each subsystem, only one neural network is employed for the unknown function approximation.To further reduce the computational burden, minimal-learning parameter(MLP)technology is used to estimate the norm of ideal weight vectors rather than their elements.By introducing sliding mode differentiator(SMD) to estimate the newly defined variables, there is no need for the strict-feedback form and virtual controller.Hence the developed control law is considerably simpler than the ones derived from back-stepping scheme.Finally, simulation studies are made to illustrate the effectiveness of the proposed control approach in spite of the flexible effects, system uncertainties and varying disturbances.     

Periodic event-triggered formation control for multi-UAV systems with collision avoidance

In this paper, periodic event-triggered formation control problems with collision avoidance are studied for leader–follower multiple Unmanned Aerial Vehicles (UAVs). Firstly, based on the Artificial Potential Field (APF) method, a novel sliding manifold is proposed for controller design, which can solve the problem of collision avoidance. Then, the event-triggered strategy is applied to the distributed formation control of multi-UAV systems, where the evaluation of the event condition is continuous. In addition, the exclusion of Zeno behavior can be guaranteed by the inter-event time between two successive trigger events have a positive lower bound. Next, a periodic event-triggered mechanism is developed for formation control based on the continuous event-triggered mechanism. The periodic trigger mechanism does not need additional hardware circuits and sophisticated sensors, which can reduce the control cost. The stability of the control system is proved by the Lyapunov function method. Finally, some numerical simulations are presented to illustrate the effectiveness of the proposed control protocol.     

STOCHASTIC NEURAL NETWORK AND ITS APPLICATION TO MULTI－MANEUVERING TARGET TRACKING

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快速模型预测控制用于微型直升机航迹跟踪

为实现微型共轴无人直升机(MCUH)的航迹跟踪,考虑系统的状态和输入约束,利用非线性模型预测控制(NMPC)技术设计一种快速在线的控制器。首先,简化MCUH的非线性模型,利用系统的微分平坦特性生成满足直升机动力学的可行航迹,沿着该航迹对系统进行线性化,得到近似直升机非线性动力学的线性时变(LTV)模型。然后,将传统输出航迹跟踪NMPC问题转化为LTV-MPC优化问题,降低问题的复杂度,为确保航迹跟踪误差系统的指数渐近稳定,分别设计终端域和终端罚值。最后,通过数值仿真,验证快速在线NMPC策略的可行性。结果表明:设计的预测控制器误差控制精度高、求解速度快,可实现对有约束的时变航迹的跟踪。     

考虑进气约束的高超声速飞行器预定性能控制

针对高超声速飞行器跟踪误差瞬态性能约束与发动机进气条件约束问题,提出约束预定性能控制方案。首先,设计新型设定时间性能函数用于限定跟踪误差的瞬态与稳态性能。相比传统方法,新型方案可保证性能函数在设定时刻精确收敛至稳态值,同时可灵活调整函数初始收敛速率,避免控制饱和。其次,将速度与高度受约束跟踪误差进行无约束转换,通过控制转化误差有界满足原始跟踪误差的预定性能约束。在高度子系统中,通过结合预定性能控制限定攻角变化范围,能够满足发动机进气需求。最后,以考虑参数摄动的吸气式高超声速飞行器为对象执行对比仿真,结果表明所提方法能够有效满足跟踪误差的性能约束与发动机进气约束。     

基于新型终端滑模的航天器执行器故障容错姿态控制简

 针对受干扰的刚体航天器冗余执行器存在故障与控制受限的姿态跟踪控制问题,提出一类基于新型指数形式的非奇异快速滑模面（ENFTSM）与趋近律的姿态容错控制器设计方法。当部分推力器发生故障时,假设剩余推力器具有输出饱和特性且能提供足够推力保证航天器执行任务,相比一般终端滑模控制器,本文设计的控制器不仅能使系统状态以更快的速度到达平衡点,且不需要在线对执行器故障信息进行检测和分离。基于Lyapunov方法证明本文设计的控制器能保证闭环系统稳定,且能有效地抑制外部干扰、控制受限和执行器故障等约束。最后对提出的控制算法进行了数值仿真,其结果表明了该控制器的有效性。     

Linear time-varying eigenstructure assignment with flight control application

This work is concerned with the assignment of a desired PD-eigenstructure for linear time-varying systems. Despite its well-known limitations, gain scheduling control appeared to be a focus of the research efforts. Scheduling of frozen-time, frozen-state controllers for fast time-varying dynamics is known to be mathematically fallacious, and practically hazardous. Therefore, recent research efforts are being directed towards applying time-varying controllers. In this paper we: 1) introduce a differential algebraic eigenvalue theory for linear time-varying systems; and 2) propose a PD-eigenstructure assignment scheme via a differential Sylvester equation and a command generator tracker (CGT) for linear time-varying systems. The PD-eigenstructure assignment is utilized as a regulator. A feedforward gain for tracking control is computed by using the command generator tracker. The whole design procedures of the proposed PD-eigenstructure assignment scheme are systematic in nature. The scheme could be used to determine the stability of linear time-varying systems easily as well as to provide a new horizon of designing controllers for the linear time-varying systems. A missile flight control application is presented to validate the proposed schemes.     

Distributed event-triggered adaptive control for second-order nonlinear uncertain multi-agent systems

In this paper, the event-triggered consensus control problem for nonlinear uncertain multi-agent systems subject to unknown parameters and external disturbances is considered. The dynamics of subsystems are second-order with similar structures, and the nodes are connected by undirected graphs. The event-triggered mechanisms are not only utilized in the transmission of information from the controllers to the actuators, and from the sensors to the controllers within each agent, but also in the communication between agents. Based on the adaptive backstepping method, extra estimators are introduced to handle the unknown parameters, and the measurement errors that occur during the event-triggered communication are well handled by designing compensating terms for the control signals. The presented distributed event-triggered adaptive control laws can guarantee the boundness of the consensus tracking errors and the Zeno behavior is avoided. Meanwhile, the update frequency of the controllers and the load of communication burden are vastly reduced. The obtained control protocol is further applied to a multi-input multi-output second-order nonlinear multi-agent system, and the simulation results show the effectiveness and advantages of our proposed method.     

Quantitative speed control for SRM drive using fuzzy adapted inverse model

Quantitative and robust speed control for a switched reluctance motor (SRM) drive is considered to be rather difficult and challenging owing to its highly nonlinear dynamic behavior. A speed control scheme having two-degree-of-freedom (2DOF) structure is developed here to improve the speed dynamic response of an SRM drive. In the proposed control scheme, the feedback controller is quantitatively designed to meet the desired regulation control requirements first. Then a reference model and a command feedforward controller based on an inverse plant model are employed to yield the desired tracking response at nominal case. As the variations of system parameters and operating conditions occur, the prescribed control specifications may not be satisfied any more. To improve this, the inverse model is adaptively tuned by a fuzzy control scheme so that the model-following tracking error is significantly reduced. In addition, a simple disturbance cancellation robust controller is added to improve the tracking and regulation control performances further.