Binary Decision Diagrams (BDDs) have been used to represent logic models in a variety of research contexts, such as software product lines, circuit testing, and plasma confinement, among others. Although BDDs have proven to be very useful, the main problem with this technique is that synthesizing BDDs can be a frustratingly slow or even unsuccessful process, due to its heuristic nature. We present an extension of propositional logic to tackle one recurring phenomenon in logic modeling, namely groups of variables related by an exclusive-or relationship, and also consider two other extensions: one in which at least n variables in a group are true and another one for in which at most n variables are true. We add XOR, atLeast-n and atMost-n primitives to logic formulas in order to reduce the size of the input and also present algorithms to efficiently incorporate these constructions into the building of BDDs. We prove, among other results, that the number of nodes created during the process for XOR groups is reduced from quadratic to linear for the affected clauses. the XOR primitive is tested against eight logical models, two from industry and six from Kconfig-based open-source projects. Results range from no negative effects in models without XOR relations to performance gains well into two orders of magnitude on models with an abundance of this kind of relationship.

The potential benefits of networked control systems are tremendous, as they can be easily upgraded by just including new components (i.e., sensors, actuators, or controllers), avoiding any further modifications to their structure. A critical approach to unleash such potential benefits is event-based control, where the system output turns to be sampled on demand, instead of being sampled constantly at rigid periods of time. This paper analyzes from a bibliometric point of view the literature published for the last twenty years on event-based control, identifying the most relevant articles, authors, institutions, and journals. Moreover, the principal topics, motivations, and problems faced by the researchers are discussed, identifying distinct challenges and opportunities for future research.

This work presents a closed-loop position control of a mobile robot, which is capable of moving from its current position to a target point by manipulating its linear and angular velocities. The main objective of this paper is to modify an existing control law based on the kinematic model to improve the response when the robot is backwards oriented and to reach the destination point in less time and with a shorter trajectory. Stability of the proposed control law is validated by Lyapunov Criterion. Some procedures are implemented to test this approach both in simulation with MATLAB, and experimentally with the Khepera IV robot.

In this paper we present a real application of computational intelligence. Fuzzy control of a non-linear rotary chain pendulum is proposed and implemented on real prototypes. The final aim is to obtain a larger region of attraction for the stabilization of this complex system, that is, a more robust controller. As it is well-known, fuzzy logic exploits...

We study the problem of periodic event-triggered targeted formation control for multi-agent Lagrangian systems. We assume that the equations of motion of each agent are derived from a Lagrangian function. Besides, each agent has information about a predefined convex set as a targeted set. The goal of the agents is to achieve the desired formation in the targeted sets, while the information is asynchronously shared by a periodic event-triggering specification, and there is also a time-delay in their communication. A novel distributed control law is proposed for the agents to reach the goal while their velocities are driven to zero. Applications and simulations are provided to validate the theoretical results. (C) 2021 ISA. Published by Elsevier Ltd. All rights reserved.