Communication free leader–follower formation control of unmanned aircraft systems

This paper proposes a formation control strategy for unmanned aircraft under which there is no need to information exchange among aircraft. Based on the measurement of relative information such as distances and orientations obtained from practical sensors, the formation is realized by employing the feedback linearization approach. By considering the leader maneuver to be unknown, a nonlinear estimator is designed and the stability of the combined controller–estimator is guaranteed. Simulation results confirm the effectiveness of the proposed formation flight control strategy.     

On disturbance propagation in leader–follower systems with limited leader information

This paper studies the problem of disturbance propagation in a string of vehicles aiming to proceed along a given trajectory while keeping a constant distance between each vehicle and its successor. It is assumed that each vehicle can control its position based on the spacing error with respect to the preceding vehicle in the string, as well as on coded information transmitted by the lead vehicle. Using information-theoretic techniques, this paper establishes a lower bound to the integral of the sensitivity function of spacing errors with respect to a stochastic disturbance acting on the lead vehicle. The derived bound depends on the open-loop poles and zeros of the vehicles’ dynamics as well as on the (possibly nonlinear) controller used at each vehicle. The lower bound is shown to be tight for a specific class of systems and controllers.     

An adaptive control architecture for leader–follower multiagent systems with stochastic disturbances and sensor and actuator attacks

In this paper, we develop a novel distributed adaptive control architecture for addressing networked multiagent systems subject to stochastic exogenous disturbances with compromised sensor and actuators. Specifically, for a class of linear leader–follower multiagent systems, we develop a new structure of the neighbourhood synchronisation error for the control design protocol of each follower. The proposed control algorithm addresses time-varying multiplicative sensor attacks on the leader state measurements. In addition, the framework addresses time-varying multiplicative actuator attacks on the followers that do not have a communication link with the leader and additive actuator attacks on all follower agents in the network. The proposed adaptive controller guarantees uniform ultimate boundedness of the state tracking error for each agent in a mean-square sense.     

A distributed model predictive control scheme for leader–follower multi-agent systems

In this paper, we present a novel receding horizon control scheme for solving the formation problem of leader–follower configurations. The algorithm is based on set-theoretic ideas and is tuned for agents described by linear time-invariant (LTI) systems subject to input and state constraints. The novelty of the proposed framework relies on the capability to jointly use sequences of one-step controllable sets and polyhedral piecewise state-space partitions in order to online apply the ‘better’ control action in a distributed receding horizon fashion. Moreover, we prove that the design of both robust positively invariant sets and one-step-ahead controllable regions is achieved in a distributed sense. Simulations and numerical comparisons with respect to centralised and local-based strategies are finally performed on a group of mobile robots to demonstrate the effectiveness of the proposed control strategy.     

Leader–follower fixed-time consensus of multi-agent systems with high-order integrator dynamics

The leader–follower fixed-time consensus of high-order multi-agent systems with external disturbances is investigated in this paper. A novel sliding manifold is designed to ensure that the tracking errors converge to zero in a fixed-time during the sliding motion. Then, a distributed control law is designed based on Lyapunov technique to drive the system states to the sliding manifold in finite-time independent of initial conditions. Finally, the efficiency of the proposed method is illustrated by numerical simulations.     

Leader–follower tracking control with guaranteed consensus performance for interconnected systems with linear dynamic uncertain coupling

This paper considers the leader–follower tracking control problem for linear interconnected systems with undirected topology and linear dynamic coupling. Interactions between the systems are treated as linear dynamic uncertainty and are described in terms of integral quadratic constraints (IQCs). A consensus-type tracking control protocol is proposed for each system based on its state relative to its neighbours. In addition, a selected set of subsystems is used to control their relative states with respect to the leader. Two methods are proposed for the design of this control protocol. One method uses a coordinate transformation to recast the protocol design problem as a decentralised robust control problem for an auxiliary interconnected large-scale system. Another method is direct; it does not employ coordinate transformation, rather it also allows for more general linear uncertain interactions. Using these methods, sufficient conditions are obtained which guarantee that the system tracks the leader. These conditions guarantee a suboptimal bound on the system consensus and tracking performance. The proposed methods are compared using a simulation example, and their effectiveness is discussed. Also, algorithms are proposed for computing suboptimal controllers.     

Distributed event-triggered cooperative attitude control of multiple rigid bodies with leader–follower architecture

In this note, the distributed event-triggered cooperative attitude control of multiple rigid bodies with leader–follower architecture is investigated, where both the cases of static and dynamic leaders are all considered. Two distributed triggering procedures are first introduced for the followers and leaders, and then the distributed cooperative controllers are designed under the proposed triggering schemes. Under the designed controllers with the event-triggered strategies, it is shown that the orientations of followers converge to the convex hull formed by the desired leaders’ orientations with zero angular velocities. Moreover, the communication pressure in network is reduced and the energy of each agent is saved. Simulation results show the effectiveness of the proposed method.     

Adaptive control of Hammerstein–Wiener nonlinear systems

The Hammerstein–Wiener model is a block-oriented model, having a linear dynamic block sandwiched by two static nonlinear blocks. This note develops an adaptive controller for a special form of Hammerstein–Wiener nonlinear systems which are parameterized by the key-term separation principle. The adaptive control law and recursive parameter estimation are updated by the use of internal variable estimations. By modeling the errors due to the estimation of internal variables, we establish convergence and stability properties. Theoretical results show that parameter estimation convergence and closed-loop system stability can be guaranteed under sufficient condition. From a qualitative analysis of the sufficient condition, we introduce an adaptive weighted factor to improve the performance of the adaptive controller. Numerical examples are given to confirm the results in this paper.     

Manipulability of leader–follower networks with the rigid-link approximation

This paper introduces the notion of manipulability to mobile, multi-agent networks as a tool to analyze the instantaneous effectiveness of injecting control inputs at certain, so-called leader nodes in the network. Effectiveness is interpreted to characterize how the movements of the leader nodes translate into responses among the remaining follower nodes. This notion of effectiveness is a function of the interaction topologies, the agent configurations, and the particular choice of inputs used to influence the network. In fact, classic manipulability is an index used in robotics to analyze the singularity and efficiency of configurations of robot-arm manipulators. To define similar notions for leader–follower networks, we use a rigid-link approximation of the follower dynamics and, under this assumption, we prove that the instantaneous follower velocities can be uniquely determined from that of the leaders’, which allows us to define a meaningful and computable manipulability index for the leader–follower networks. This paper examines the property of the proposed index in simulation and with real mobile robots, and demonstrates how the index can be used to find effective interaction topologies.     

Adaptive output feedback stabilisation for planar nonlinear systems with unknown control coefficients

The paper is concerned with the global adaptive stabilisation via output feedback for a class of uncertain planar nonlinear systems. Remarkably, the unknowns in the systems are rather serious: the control coefficients are unknown constants which do not belong to any known interval, and the growth of the systems heavily depends on the unmeasured states and has the rate of unknown polynomial of output. First, a delicate state transformation is introduced to collect the unknown control coefficients, and subsequently, a suitable state observer is successfully designed with two different dynamic gains. Then, an adaptive output feedback controller is proposed by flexibly combining the universal control idea and the backstepping technique. Meanwhile, an appropriate estimation law is constructed to overcome the negative effect caused by the unknown control coefficients. It is shown that, with the appropriate choice of the design parameters, all the states of the resulting closed-loop system are globally bounded, and furthermore, the states of the original system converge to zero.     

Adaptive control of stochastic Hammerstein–Wiener nonlinear systems with measurement noise

This paper deals with the adaptive control of a class of stochastic Hammerstein–Wiener nonlinear systems with measurement noise. Despite the fundamental progress achieved so far, a general theory framework about adaptive control of Hammerstein–Wiener models is still absent. Such situation is mainly due to the lack of an appropriate parameterisation model. To this end, this paper presents a novel parameterisation model that is to replace unmeasurable internal variables with their estimations. Then, the adaptive control algorithm to be applied is derived on the basis of self-tuning control. In addition, due to the use of the internal variable estimations, the stability and convergence properties are different from the self-tuning control. Our aim, in theoretical analysis, is to discover what limitations are in using the estimations instead of the true values in a control algorithm. Representative numerical examples are given and the simulation results verify the theoretical analysis.     

Adaptive robust control of nonholonomic systems with stochastic disturbances

Based on the Brockett’s necessary condition for feedback asymptotic stabilization[1], nonholonomic systems fail to be stabilized at the origin by any static continuous state feedback though they are open loop controllable. There are two novel approaches …     

Adaptive dynamic surface control for a class of output-feedback nonlinear systems with guaranteed ℒ∞ tracking performance

In this article, an output-feedback adaptive dynamic surface control (DSC) is proposed for a class of nonlinear systems. It is proved that, by using the new scheme, the explosion of the complexity problem in a traditional backstepping design can be eliminated, the semi-global stability of a closed-loop system can be guaranteed and, in particular, by choosing the design parameters and initialising the filters and the update law properly, we show that the ?_∞ performance of the system-tracking error can be achieved without over-parametrisation. Another advantage of the proposed scheme compared with those traditional backstepping control and current adaptive DSC schemes, whose adaptive control law is obtained through a series of steps recursively, is that the adaptive law is needed only at the first design step, and therefore significantly reduces the design procedure.     

An output formation consensus control for leader–follower networked multi-agent systems under communication constraints and switching topologies

In this paper, the formation consensus problem for a class of leader–follower networked multi-agent systems under communication constraints and switching topologies is investigated. A networked predictive control scheme is proposed to achieve stability and output formation consensus with the switching topology, capable of compensating for data loss and time delays in the network. By equating the whole closed-loop networked multi-agent system with the proposed control scheme to the corresponding switched system, the sufficient and necessary condition of output formation consensus and stability for agents is given. Finally, using three-degree-of-freedom air-bearing spacecraft simulators as the control objects, the proposed scheme is demonstrated to be able to actively compensate for the communication constraints through numerical simulations, and it is also verified to have a good control performance by further realizing the formation task of the simulators through practical experiments.     

Adaptive practical output tracking of a class of nonlinear systems

Focus is hid on the adaptive practical output-tracking problem of a chss of nonlinear systems with high-order lower-triangular structure and uncontrollable unstable linearization. Using the modified adaptive addition of a power integrator technique as a basic tool, a new smooth adaptive state feedback controller is designed. This controller can ensure all signals of the closed-loop systems are globally bounded and output tracking error is arbitrary small.     

Adaptive H2/H∞ tracking control for a class of uncertain robotic systems

This paper addresses the problem of designing mixed H₂/H_∞ tracking control for a large class of uncertain robotic systems. Nonlinear H_∞ control theory, H₂ control theory and intelligent adaptive control algorithm are combined to construct a hybrid adaptive/robust H₂/H_∞ tracking control scheme. One adaptive neural network system is constructed to approximate the behaviour of uncertain robot dynamics, and the other adaptive control algorithm is designed to estimate the behaviour of the modelled disturbance. Moreover, a robust H_∞ control algorithm is designed to attenuate the effects of the unmodelled disturbance. Only a set of algebraic matrix Riccati-like equations is required to implement the proposed mixed H₂/H_∞ tracking controller, and so an explicit and closed-form solution is obtained. Consequently, the mixed H₂/H_∞ adaptive/robust tracking controller developed here can be analytically computed and easily implemented. Finally, simulations are presented to illustrate the effectiveness of the proposed control algorithm.     

Distributed robust control for synchronised tracking of networked Euler–Lagrange systems

In this paper, we propose a distributed robust control method for synchronised tracking of networked Euler–Lagrange systems, where the time-varying reference trajectory is sent to only a subset of the agents. It is assumed that the agents can exchange information with their local neighbours on a bidirectionally connected communication graph. In the local controller equipped in each generalised coordinate of the agents, a disturbance observer is introduced to compensate for the low-passed-coupled uncertainties, and a sliding mode control term is employed to handle the uncertainties that the disturbance observer cannot compensate for sufficiently. By some damping terms, the boundedness of the signals of the overall networked nonlinear systems is first ensured. Then we show how the disturbance observer and sliding mode control term play in a cooperative way in each local generalised coordinate to achieve an excellent synchronised tracking performance. Simulation results are provided to support the theoretical results.     

Adaptive control of linear multivariable systems with high frequency gain matrix hurwitz

A new adaptive control scheme is proposed for multivariable model reference adaptive control （MRAC） systems based on the nonlinear backstepplng approach with vector form. The assumption on a priori knowledge of the high frequency gain matrix in existing results is relaxed and the new required condition for the high frequency gain matrix can be easily checked for certain plants so that the proposed method is widely applicable. This control scheme guarantees the global stability of the closed-loop systems and the tracking error can be arbitrary small. The simulation result for an application example shows the validity of the proposed nonlinear adaptive scheme.     

Neural model-based adaptive control for systems with unknown Preisach-type hysteresis

An adaptive control scheme is presented for systems with unknown hysteresis. In order to handle the case where the hysteresis output is unmeasurale, a novel model is firstly developed to describe the characteristic of hysteresis. This model is motivated by Preisach model but implemented by using neural networks (NN). The main advantage is that it is easily used for controller design. Then, the adaptive controller based on the proposed model is presented for a class of SISO nonlinear systems preceded by unknown hysteresis, which is estimated by the proposed model. The hws for model updating and the control hws for the neural adaptive controller are derived from Lyaptmov stability theorem, therefore the semi - global stability of the closed-loop system is guaranteed. At last, the simulation results are illuswated.     

Error-based adaptive optimal tracking control of nonlinear discrete-time systems

In this paper,for the output tracking problem of nonlinear discrete-time systems,a performance index is newly defined using the adaptive dynamic programming(ADP) technique to completely eliminate tracking errors in theory.In contrast to traditional definitions of performance indices in other ADP-based methods,the proposed performance index is not only designed from the perspective of output tracking errors but also introduced errors of system states and control inputs at adjacent stages,which is...