Flapping-wing flying robots, as a newly emerging research hotspot, have attracted more and more researchers' attention. Compared with traditional aircraft, flapping-wing flying robots have the characteristics of high flight efficiency, good concealment, and have a wide range of application prospects. As an important power mechanism of aircraft, the research of wing is very important. In this paper, we design a wing structure that can realize the active bending of wings, which can well imitate the bending pattern of wings of birds in the natural flight process. At the same time, a wind tunnel test was carried out to measure the lift resistance of the single wing and the folded wing under the same power. The results show that the folded wing has higher flight efficiency under the same power.

The issue of modeling and fault-tolerant control (FTC) design for a class of flexible air-breathing hypersonic vehicles (FAHVs) with actuator faults is investigated in this article. Different from previous research, the shear deformation of the fuselage is considered, and an ordinary differential equations-partial differential equations (ODEs-PDEs) coupled model is established for the FAHVs. A feedback control is proposed to ensure flight stable and an adaptive FTC method is designed to deal with actuator faults while suppressing the system's vibrations. Besides, the stability analysis of the closed-loop system is given via the Lyapunov direct method and an algorithm that transfers the bilinear matrix inequalities (BMIs) feasibility problem to the linear matrix inequalities (LMIs) feasibility problem is provided for determining the control gains. Finally, the numerical simulation results show that the proposed controller can stabilize the flight states and suppresses the vibration of the fuselage efficiently.

This article considers the design of an adaptive iterative learning controller for high-rise buildings with active mass dampers (AMDs). High-rise buildings in this article are seen as distributed parameter systems, in which the characteristics of every point in buildings should be considered. Two partial differential equations (PDEs) and several ordinary differential equations are used to describe the model of buildings. To achieve the control target that is to suppress the vibration induced by high winds, an adaptive iterative learning controller is proposed for the flexible building system with boundary disturbance. The convergency of the adaptive iterative learning control (AILC) approach is proven by serious theory analysis. In simulations and experiments, this article uses both the analysis of figures and quantitative analysis (root-mean-square values) to illustrate the efficiency of the AILC scheme.

For a mobile dual flexible manipulator (MDFM) system, this article focuses on the problem of cooperative trajectory tracking under unknown dynamics and time-varying trajectories. The dynamic model of the wheeled mobile manipulator system in 2-D space is established. Taking into account the unmodeled dynamics of the system, unknown terms of the system are approximated by integrating the radial basis function neural network (RBFNN) structure. By introducing the servo system, the cooperative trajectory tracking control (CTTC) strategy is designed, which realizes the system's cooperative operation, time-varying trajectory tracking, and vibration suppression. The performance of the proposed control scheme is verified through theoretical analysis and numerical simulations.

In this article, a boundary control scheme is proposed to suppress 2-D vibration of Euler–Bernoulli beam with output constraints and input saturation. The original partial differential equations (PDEs) model is transformed to a new form containing virtual control. Then a boundary controller is designed via the backstepping method to suppress the coupled vibration. The hyperbolic tangent function and Nussbaum function are employed to deal with the input saturation. A barrier Lyapunov function with time adjusting function is introduced to suppress the structural vibration of Euler–Bernoulli beam with arbitrary initial conditions. The disturbance observer is designed to deal with the unknown boundary disturbance. Finally, the simulation results show the effectiveness of the proposed vibration controller.

This article discusses cooperative control of a mobile dual flexible manipulator system with asymmetric time-varying output constraints and actuator failures. The shift function and a barrier Lyapunov function (BLF) are used to guarantee output constraints when the initial states of the system violate the prescribed constraints. Moreover, an adaptive fault-tolerant control scheme is developed to deal with actuator failures, while suppressing system’s vibration and achieving cooperative operation. Finally, theoretic analysis proves the uniform bounded stability of the system and numerical simulation verifies the effectiveness of the proposed control method. Note to Practitioners—The purpose of this article is to develop a cooperative dual flexible manipulator system with performance limitations and actuator failures. The system can realize the task of stably grasping and moving a rigid object. The existing research on the grasping task of flexible manipulators only focuses on coordinated operation, which limits the application of the dual flexible manipulator system in practical engineering. To further study the problem, this article considers the output constraints and actuator failures of the dual flexible manipulator system in the actual process and proposes a cooperative fault-tolerant control framework. The control framework uses shift function and BLF to deal with output constraints and adopts adaptive technology to deal with actuator failures. In addition, the cooperative operation task of grasping object with dual flexible manipulators is realized. Simulation shows that this control strategy is feasible.

As a kind of large flexible structure, high-rise buildings need to consider wind-resistant and anti-seismic problems for the safety of occupants and properties, especially in coastal areas. This article proposes an infinite dimensional model and an adaptive boundary control law for an active mass damper (AMD) on this question. The dynamic model of the high-rise building is a combination of some storeys which have flexible walls and rigid floors under a series of physical conditions. Then the adaptive boundary controller is acted on an AMD which is equipped on the top floor, in order to suppress the vibration of every floor and guarantee the comfort of residents. Moreover, simulations and experiments are carried out on a two-floor flexible building to illustrate the effectiveness of the proposed control strategy.

This article involves the adaptive inverse control of a coupled vessel-riser system with input backlash and system uncertainties. By introducing an adaptive inverse dynamics of backlash, the backlash control input is divided into a mismatch error and an expected control command, and then a novel adaptive inverse control strategy is established to eliminate vibration, tackle backlash, and compensate for system uncertainties. The bounded stability of the controlled system is analyzed and demonstrated by exploiting the Lyapunov's criterion. The simulation comparison experiments are finally presented to verify the feasibility and effectiveness of the control algorithm.

This paper examines the boundary disturbance observer-based control for a vibrating single-link flexible manipulator system possessing external disturbances. Two new boundary anti-disturbance control strategies are presented to eliminate vibration, track disturbance, and determine angle position for the flexible manipulator system. Achieving rigorous analysis with no model reduction, the derived control can ensure the angle positioning and bounded stability in the controlled system. By appropriately designing parameters, the resulting simulation results can demonstrate the control performance.

Boundary control strategy is developed to analyze the vibration problem of the offshore ocean thermal energy conversion (OTEC) system as well as to constrain the bottom tension and top motion. To provide an accurate dynamic behavior for the OTEC system, this distributed parameter system is modeled and formulated with a governing equation and boundary conditions (PDE-ODEs model). Two robust adaptive boundary controllers are designed and disposed at the endpoints of the system, and the stability of the controlled system under unknown disturbances is achieved. After selecting the relevant parameters appropriately, the offset of the offshore OTEC system can be suppressed to equilibrium position. Finally, the effectiveness of the proposed control is illustrated by simulation.

This paper addresses a flexible micro aerial vehicle (MAV) under spatiotemporally varying disturbances, which is composed of a rigid body and two flexible wings. Based on Hamilton's principle, a distributed parameter system coupling in bending and twisting, is modeled. Two iterative learning control (ILC) schemes are designed to suppress the vibrations in bending and twisting, reject the distributed disturbances and regulate the displacement of the rigid body to track a prescribed constant trajectory. At the basis of composite energy function, the boundedness and the learning convergence are proved for the closed-loop MAV system. Simulation results are provided to illustrate the effectiveness of the proposed ILC laws.

The vibration offsets reduction is studied for an industrial axially moving accelerated string subjected to the external disturbances and input saturation. A boundary control strategy is put forward to reduce the vibration offsets and an auxiliary term is introduced to handle the restriction of the input saturation. In addition, both infinite-dimensional observer and finite-dimensional observer are, respectively, designed to track unknown disturbances. Under the developed control strategy, the existence, uniqueness, and convergence of the solution of the closed-loop string system are discussed without resorting to model reduction methods. By choosing the proper control parameters, the simulations are given to verify the performance of the developed control strategy.

This paper focuses on adaptive robust vibration control for flexible riser systems affected by input nonlinearities and unknown external disturbances. An auxiliary system is constructed and adjusted to develop a boundary adaptive robust control for restraining the vibrational offset and eliminating the effect of input nonlinearities. Besides, an adaptive law of boundary disturbance upper-bound is constructed together with the vibration control strategy to estimate the magnitude of unknown boundary disturbance. Further, the convergence of states and stability of the system are ensured with the developed control scheme. By choosing the proper control parameters, the control performance is verified with the obtained simulation results.

This paper presents a framework of output feedback stabilization of an axially moving accelerated system influenced by exogenous disturbances. Based on the flexible-rigid coupled dynamical model of the system, a boundary output feedback control is developed to reduce the vibration and estimate the boundary disturbance by fusing Lyapunov's synthetic approach, disturbance rejection theory, and observer technique. Under the developed control, the exponential convergence of system state observer errors and uniformly ultimately bounded stability of the controlled system can be demonstrated adopting rigorous theoretical analysis, and the control performance of the developed control method is verified by simulation results.

In this paper, we study the control problems of distributed parameter systems, and discuss the limitations of traditional control methods. In recent years, social factors have gradually become an essential parameter of system modeling. For complex distributed parameter systems, the accurate modeling becomes difficult. With the rapid development of the network and the technology of big data and cloud computing, based on the advanced control theory of large-scale computing, we introduce the idea of parallel control to the control of distributed parameter systems. Parallel control is a method to accomplish tasks through the interaction of virtual and actual. Its core is to model the complex distributed parameter system on artificial society or artificial system, then analyze and evaluate it by computational experiment, and finally control and manage the distributed parameter system by parallel execution. Data-driven control and computational control are used in this method, which is a control idea that adapts to the rapid development of society.