Deadlock-free supervisory control for automated manufacturing systems (AMSs) has been a popular research subject. However, for numerous researchers, their studies are merely practicable on the assumption that resources cannot fail. In practice, resource failures can occur unexpectedly. In this study, the authors take into consideration deadlock and blocking problems in systems with assembly operations embedded in flexible routes. Their objective is to develop a robust supervisor that controls resource allocation and selects flexible routes such that stagnant parts requiring failed resources do not block the movement of parts not necessarily requiring failed resources. That is to say, it must ensure that parts not necessarily requiring any failed resource can continue their operations. The proposed policy tries to take full advantage of the shared resource capacity to improve systems' performance. By modelling AMSs with Petri nets, their robust supervisor predicts in advance whether the currently-available resources are sufficient to support a token to advance into the desired destination in a single process. The method is achieved in an online and distributed way and avoids enumerating states. At last, several simulation examples show the correctness of their proposed method.

This study investigates the problem of global finite-time attitude tracking for spacecraft subject to actuator constraints and attitude measurements only. A velocity-free saturated hybrid proportional–derivative (PD) plus spacecraft dynamics (PD+) control is proposed. Benefiting from the hybrid control technique, the unwinding phenomenon is completely avoided and the global stability is achieved. Lyapunov stability theory and homogeneous method are employed to show global finite-time tracking. Advantages of the proposed control include simple and intuitive structure and the absence of velocity measurements, and thus it is ready to implement. An additive feature is that the proposed control is explicitly upper bounded and hence it can assure that actuator constraints will not be violated by selecting the control gains a priori. Simulations are performed to illustrate the effectiveness and improved performance of the proposed approach.

This study considers the consensus tracking problem of singular multi-agent systems by using an iterative learning control approach. Here, the communication among the followers is described by a directed graph, and only a portion of the followers can receive the leader's information. For such singular multi-agent systems, a unified iterative learning algorithm is proposed in both continuous-time domain and discrete-time domain. Furthermore, the convergence condition of the algorithm is presented and analysed. In this study, the main contribution is to extend the iterative learning control theory from multi-agent systems to singular multi-agent systems. It is shown that the algorithm can guarantee the outputs of the followers converge to the leader's trajectory on a finite time interval along the iteration axis. Finally, the provided examples illustrate the effectiveness of the theoretical results.

Due to the long-range data communication and complex Mars environment, the Mars lander needs to promote the ability to autonomously adapt uncertain situations ensuring high precision landing in future Mars missions. Based on the analysis of multiple disturbances, this study demonstrates an enhanced predictor–corrector guidance method to deal with the effect of atmospheric uncertainties during the entry phase of the Mars landing. In the proposed method, the predictor–corrector guidance algorithm is designed to autonomously drive the Mars lander to the parachute deployment. Meanwhile, the disturbance observer is designed to onboard estimate the effect of fiercely varying atmospheric uncertainties resulting from rapidly height decreasing. Then, with the estimation of atmospheric uncertainties compensated in the feed-forward channel, the composite guidance method is put forward such that both anti-disturbance and autonomous performance of the Mars lander guidance system are improved. Convergence of the proposed composite method is analysed. Simulations for a Mars lander entry guidance system demonstrates that the proposed method outperforms the baseline method in consideration of the atmospheric uncertainties.

This study addresses the consensus problem for linear multi-agent systems subject to external disturbances under the leaderless framework. A novel distributed dynamic output feedback control protocol is proposed, which utilises not only relative output information of neighbouring agents but also relative state information of neighbouring controllers. Through model transformation, the consensus control problem of multi-agents network is reduced to a set of independent stabilisation subproblems for n-dimensional linear systems. Sufficient analysis conditions are derived using the Lyapunov method. An important contribution of this work lies in that the leaderless output-feedback consensus synthesis conditions are convexified without introducing any conservatism and formulated as linear matrix inequalities, which can be solved efficiently via convex optimisation. This is achieved by using a novel dynamic output-feedback controller structure. A numerical example has been used to demonstrate the advantage of theoretical results.