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Several designs of recurrent neural networks have been proposed in the literature involving different clock times. However, the stability and synchronization of this kind of system have not been studied. In this paper, we consider that each neuron or group of neurons of a switched recurrent neural network can have a different sampling period for its activation, which we call switched multi-rate recurrent neural networks, and we propose a dynamical model to describe it. Through Lyapunov methods, sufficient conditions are provided to guarantee the exponential stability of the network. Additionally, these results are extended to the synchronization problem of two identical networks, understanding the synchronization as the agreement of both of them in time. Numerical simulations are presented to validate the theoretical results. The proposed method might help to design more efficient and less computationally demanding neural networks.

This paper revisites the direct synthesis tuning method of continuous-time low-order controllers, and specially PID controllers, for control of time-delayed single-input single-output processes. A setpoint prefilter is included to improve the servo response and integrating load disturbances are accounted for. Robustness is addressed by the feedback controller to obtain the desired maximum sensitivity value. Similar results in step disturbance compensation are obtained with simpler analytical tuning rules when compared to recently reported methods. However, the proposed procedure enables to compensate integrating load disturbances, which are not handled in the other methods.

This article 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 article 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 work, the load disturbance rejection problem is studied. Specifically, the feedforward compensators are considered to reduce the effect of the disturbance in the process' performance. The authors propose simple tuning rules that can be easily applied to a wide range of processes improving the response against the disturbance. The improvement of the proposed method is measured through different performance indices in several simulation examples.

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 studies the control problem of an air levitation system with limited sensing capabilities. We propose a simple but considerably robust switched controller. We prove that the output of the system is globally uniformly ultimately bounded with a bound as small as we desire and we show through simulations and real experiments the robustness of the controller in the presence of disturbances, model uncertainties and parameter tuning.

In this paper, feedforward and feedback controllers are studied considering decoupled periodic event-triggering mechanisms for output and disturbance sensors. Stability and robustness conditions for linear systems are obtained considering transportation delays and actuator saturation following the Lyapunov-Krasovskii procedure. A numerical example shows that the proposed control strategy reduces the communication between sensors and controller significantly, while the system performance is not deteriorated.

Because of online laboratories (labs), students can perform experimental activities from their mobile devices and/or computers. This article proposes an experimentation environment (EE) that extends the capabilities of interactive online labs with scripting language support. Thus, control engineering students can specify complex experiments, avoid routine tasks, and empirically test controllers they made themselves.

This paper proposes a new method for the analysis of continuous and periodic event-based state-feedback plus static feed-forward controllers that regulate linear time invariant systems with time delays. Measurable disturbances are used in both the control law and triggering condition to provide better disturbance attenuation. Asymptotic stability and L2-gain disturbance rejection problems are addressed by means of Lyapunov–Krasovskii functionals, leading to performance conditions that are expressed in terms of linear matrix inequalities. The proposed controller offers better disturbance rejection and a reduction in the number of transmissions with respect to other robust event-triggered controllers in the literature.

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.

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.

[Resumen] En este artículo se estudia el problema del control de formaciones para sistemas multi-agente gober- nados por una dinámica lagrangiana. Cada agente observa un conjunto convexo, el cual debe alcan- zar, siendo el objetivo del grupo alcanzar la forma- ci´on deseada en estos conjuntos cuando la comu- nicación entre los agentes est´a sujeta a retardos. Se propone una nueva ley de control para alcanzar la formación en los conjuntos objetivo, mientras que la velocidad de los agentes converge a cero. Finalmente, se han validado los resultados teóri- cos mediante un ejemplo de simulación. [Abstract] We study the problem of targeted formation control for multi-agent systems which evolves under the dynamics provided by a Lagrangian function. Each agent observes a convex set as a target and the goal of the swarm is to achieve the desired formation within these sets while the measurements from other agents are received with delay. A novel control law is proposed to achieve the formation in all targeted sets while the velocities of the agents are driven to zero. Applications and simulation results are given to validate the theoretical results. Ministerio de Ciencia, Innovación y Universidades; DPI2017-84259-C2-1-R Ministerio de Ciencia, Innovación y Universidades; DPI2017-84259-C2-2-R Fundación “La Caixa”; (ID 1000104344), LCF/BQ/PI19/11690016 Ministerio de Ciencia, Innovación y Universidades; MTM2016-76072-P, ILink Proyecto LINKA20079

Event-triggered control is a control strategy which allows the savings of communication resources in networked control systems. In this paper, we are interested in periodic event-triggering mechanisms in the sense that the triggering condition is only verified at predefined periodic sampling instants, which automatically ensures that Zeno behavior does not occur. We consider the case where both the output measurement and the control input are transmitted asynchronously using two independent triggering conditions. The developed result is dedicated to a class of nonlinear systems, where both the plant model and the feedback law can be described by polynomial functions. The overall problem is modeled and analyzed in the framework of time-delay systems, which allows to derive sum-of-squares (SOS) conditions to guarantee the global asymptotic stability in terms of the sampling period and the parameters of the triggering conditions. The approach is illustrated on a nonlinear numerical example.

This paper presents a library of MATLAB classes developed to provide a framework to allow performing easy and scalable process control simulations. The proposed object-oriented tool features the basic components of a control loop including: processes, controllers, sensors, actuators and connection links. The simulator can be configured to carry out simulations with continuous and/or discrete elements, and/or include event-triggered capabilities in a straightforward manner. The benefits of the proposed library are shown with the rapid development and simulation of a quadruple-tank system that is controlled by means of a PI controller.

This work considers the coverage of underwater areas with a mobile robot with constrained control and communication capabilities. While underwater, the robot can control its depth but it is subject to flow in the other directions. While on the surface, it can move (essentially) freely. The aim of the work is the coverage of the areas with the minimum waste of resources. For that, we propose a two-part algorithm, where one part is a genetic algorithm and the other part is an algorithm based on Netwton's method. Numerical simulations are provided to illustrate the efficiency of the algorithm.

In this paper, a novel strategy for swinging up an inverted pendulum is proposed. The strategy combines an energy-based control law with an event triggering condition to minimize transmissions, protect actuators and save energy. In addition, the strategy is periodic event-triggered, which provides two main advantages: An analytical way to determine a priori the sampling period to guarantee the appropriate behavior and an easy implementation in real prototypes.

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 the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost when dealing with complex systems. In this case, the control strategy is based on a Takagi-Sugeno fuzzy model of the strongly non-linear multivariable system. Simulation and experimental results on the real plant have been obtained and tested in a rotary inverted pendulum and in a double rotary inverted pendulum. They have been compared to other feedback control strategies such as Full State Feedback or Linear Quadratic Regulator with encouraging results. Fuzzy control allows to enlarge the stability region of control. Indeed, the region of attraction and therefore the stabilization has been enlarged up to over 17% for the real system.

In this paper, periodic event-triggered controllers are proposed for the rotary inverted pendulum. The control strategy is divided in two steps: swing-up and stabilization. In both cases, the system is sampled periodically but the control actions are only computed at certain instances of time (based on events), which are a subset of the sampling times. For the stabilization control, the asymptotic stability is guaranteed applying the Lyapunov–Razumikhin theorem for systems with delays. This result is applicable to general linear systems and not only to the inverted pendulum. For the swing-up control, a trigger function is provided from the derivative of the Lyapunov function for the swing-up control law. Experimental results show a significant improvement with respect to periodic control in the number of control actions.

The design of event-based controllers for systems with unknown states is investigated in this paper. The case of general quadratic triggering conditions that depend on the estimated state given by a Luenberger observer is studied. Novel frameworks are proposed for continuous and periodic event-based control providing criteria for asymptotic stability with the form of Linear Matrix Inequalities (LMIs). The frameworks are tested in simulation through a challenging system, such as the double rotary inverted pendulum.

This paper is concerned with periodic event-triggered control, which avoids the continuous monitoring of the state of the system while reducing the number of control updates. A new form of quadratic event-triggering condition is proposed to enlarge the inter-event times. The asymptotic stability criteria is analyzed by means of Lyapunov-Krasovskii functionals and the stability condition is expressed in terms of linear matrix inequalities. Simulation and experimental results are given to show the effectiveness of the proposed method.

This paper studies the problem of distributed targeted distance-based formation control for mechanical systems. The problem consists on finding a distributed control law such that if each agent targets a convex set, and also measures the relative position of their nearest neighbors, then the agents achieve the desired formation in these sets while its velocities are driven to zero. We study the problem for agents with a time-delay communication in the measurements of the relative positions and where the motion of each agent is determined by a Lagrangian function. Simulation are given to validate the theoretical result.