Assembly operations are common in automated manufacturing systems (AMSs). AMSs with assembly operations belong to complex systems due to their complicated structures. The traditional supervisory control techniques (SCTs) are generally not suitable for such large-scale systems. In this article, we propose a distributed control technique for AMSs with assembly operations to achieve a near-optimal liveness enforcement. Specifically, we define a type of decomposable system modeled by decomposable augmented marked graphs (AMGs) and create buffer-linked AMGs (BAMGs) by connecting each subsystem through buffers with specified capacities. Next, we construct the complemented subsystems to ensure structural completeness and simplify their structures to condense their reachability graphs. By conducting liveness analysis of BAMGs employing siphons, we demonstrate that the liveness of BAMGs depends solely on that of each individual subsystem. Finally, we design monitors for simplified subsystems utilizing reachability analysis and achieve distributed control of AMGs. Since the scale of reachable states is greatly reduced in simplified subsystems compared with the original AMGs, our method can save a significant amount of computation. An experimental study demonstrates the effectiveness of the proposed method.

In supervisory control of Petri nets (PNs), the place-invariant ($P$-invariant) control principle is the most typical and principal method to deal with the siphon control problem. Although it has a relatively narrow application, this principle is widely acknowledged due to its simplicity and efficiency. In this article, we first propose the extended$P$-invariant control principle in order to extend the application of$P$-invariants and provide a general methodology for the control of siphons. Second, three types of$P$-invariants, from the special to the general, are developed to implicitly or explicitly invariant control the siphons. In the most general case, the virtual$P$-invariants are constructed in the PNs. Third, the extended principle is further applied to the supervisor simplification. In the paradigm of the extended principle, it presents the redundancy from a structural perspective in contrast to several typical methods, and shows the significant importance of structural analysis in PNs, especially the important role of$P$-invariants. As a consequence, the extended$P$-invariant control principle can be considered as the fundamental principle of siphon control as well as its supervisor simplification.

Although supervisor simplification in the framework of automated manufacturing systems has been studied in many literatures, there is still an intense demand for essential and general techniques. Basically, supervisors can be synthesized by specifications which are expressed by generalized mutual exclusion constraints (GMECs). In this paper, we propose static and dynamic partitions on GMECs to remove redundant ones while retain necessary ones. These two partitions are distinctly different in the utilization of system information. Static partition separates inequalities into independent and dependent ones without doing any structure analysis. While dynamic partition divides inequalities into active and inactive ones necessarily with the aid of system information. Nevertheless, mathematical analysis shows that statically dependent inequalities are essentially dynamically inactive while dynamically active ones are substantially statically independent. Thus, these partitions are contradictory in theory whereas compatible in practice. Since static partition is more general while its dynamic counterpart is more precise, they together complementarily explain many simplification principles. Furthermore, they are applicable to both ordinary and general systems. Experimental results show the effectiveness and efficiency of supervisor simplification based on static and dynamic inequality partitions.

As an important branch of production facilities, automated manufacturing systems are a promising perspective of modern factories which become increasingly complex and flexible. From the perspective of development, time variable is a significant concern. In this paper, we propose a class of time-varying systems, Tv-S4R. After involving a global time information loop, it can represent realistic system whose manufacturing process varies with time variables. Event-based control is introduced for serving two important purposes. First, it exerts time-varying specifications on the system, i.e., different processes are executed at different time stages. Second, it prevents the system from reaching any first-met bad marking which will eventually result in deadlocks. We will show that the event-based control can enhance our specifications' expressivity capability compared to their state-based counterparts in terms of generalized mutual exclusion constraints. At last, supervisors are simplified according to the identification of dependence and independence of inequalities. An experimental study illustrates the application of Tv-S4R and the effectiveness of event-based control method.

Supervisory control techniques (SCTs), as one of the fundamental researches in the domain of automated manufacturing systems, implement specifications upon a plant model, leading the system to tendentiously desired behaviors. Generalized Mutual Exclusion Constraints (GMECs) are a typical kind of SCTs which correspond to a linear supervisory specification in the context of Petri nets (PNs). Given a set of admissible GMECs, supervisor simplification is needed to reduce implementation cost and mitigate fabrication complexity. In this paper, two methods are proposed and improved in the paradigm of arbitrary GMECs simplification. For the method based on P-invariant control, it develops in the semantics of PN structure analysis, exhibiting drawbacks like low computational efficiency, high failure probability, and definite failure to control weakly L1-dependent inequalities. On the contrary, for the method based on inequality analysis, it germinates on the ground of algebra theory, tackling both L1- and L2-dependent inequalities. Experimental results show the effectiveness and efficiency of supervisor simplification based on inequality analysis.

Most contemporary manufacturing systems appear as complex event-driven automation facilities. Supervisor synthesis and simplification are fundamental in automated manufacturing systems (AMSs). From design and implementation standpoints, it is preferable to decrease supervisor scales so as to mitigate their realization expense. Ordinary and general Petri nets are considered as powerful formalisms to describe, analyze, and control AMSs. The former is concise while the latter is compact. By considering both cases, our approach shows some properties so as to disclose their rationales with regard to liveness enforcement. Many control methodologies are developed in the context of the ordinary ones. They are straightforward but might be unadaptable to the general ones. This work develops new theory in this perspective. Some comparison and contrast survey has been demonstrated in order to clarify their common theoretical basis and distinct supervisory effect. In accordance to a thorough study, a novel simplification method is developed so as to unify both cases and facilitate their application. Experimental results show that the developed strategy is effective and efficient when simplifying supervisors.

Colored Petri nets are widely used to model Automated Manufacturing Systems thanks to their compactness to describe complex networked systems. Compared to general Petri nets, they allow many folding techniques so as to condense the system model. With them, many control synthesis problems are reduced to the solution of matrix operations. Supervisory control techniques can be realized in a computationally efficient way. In this work, these matrices are further distinguished by independent and dependent ones. A method is proposed to identify these independent ones while removing those dependent ones. As a result, a supervisor can be significantly simplified. In practice, this implies the significant reduction of cost, increase of reliability, and improvement of performance. Examples are presented to illustrate the effectiveness and efficiency of this method.

Due to the competition for limited resources by many concurrent processes in large scale automated manufacturing systems (AMS), one has to resolve a deadlock issue in order to reach their production goal without disruption and downtime. Monolithic resolution is a conventional approach for optimal or acceptable solutions, but suffers from computational difficulty. On the other hand, some decentralized methods are more powerful in finding approximate solutions, but most are application-dependent. By modeling AMS as Petri nets, we develop an innovative distributed control approach, which can create a trajectory leading to a desired destination and are adaptable to different kinds of constraints. Control strategies are applied to processes locally such that they can concurrently proceed efficiently. Global destinations are always reachable through the local observation upon processes without knowing external and extra information. Efficient algorithms are proposed to find such distributed controllers.