This paper presents a sliding mode-based filter for estimating the oscillation amplitude of non-stationary signals. The proposed algorithm makes use of the structure of sliding mode observers to ensure the estimation of the orthogonal component of a non-stationary signal, when the frequency of the trigonometric function varies over time. A stability analysis is provided to show the filter’s ability to remove the DC components, and numerical simulations illustrate its performance under noisy conditions.

Traffic management of multi-AGV fleets through improved dynamic resource reservation (IDRR) has been recently proven to be an interesting alternative within zone control-based approaches in terms of time completion efficiency in in-house transportation tasks. In this paper, preliminary results show that the combination of IDRR with PRIM allocation, a classical market-based task allocation strategy, yields a significant reduction of finishing times in a standard benchmark problem. Hence, further improvements are to be expected from deeper suitability analyses plus better tailored adaptations of optimal task allocation algorithms to zone control-based fleet management systems, and in particular to IDRR.

The deployment and coordination of mobile sensor networks for coverage control applications can present several practical challenges, including how to efficiently share limited communication resources and how to reduce the use of localization devices (e.g., radars and lidars). One potential solution to these challenges is to reduce the frequency at which agents communicate or sample each other's position. In this article, we present a distributed asynchronous self-triggered control policy for centroidal Voronoi coverage control that is shown to decrease the sampling or communication instants among agents without degrading the performance of the mobile sensor network. Each agent independently decides when to sample the position of nearby agents and uses outdated information of its neighbors until new information is required. We prove that the locational cost function describing the distribution of agents monotonically decreases everywhere outside of a bounded neighborhood around the group's optimal configuration and that the agents asymptotically converge to their Voronoi centroids if the data-sampled centroid errors approach zero. In addition, we show that the sampling intervals are always positive and lower bounded and, as illustrated by simulations and experiments, they tend to stabilize at a large value as the mobile sensor network comes to a steady state. Simulations and experiments with ground vehicles validate the control strategy and show that the proposed policy can achieve similar level of performance as a continuous or fast periodic implementation.

This paper presents an adaptive control-based strategy to regulate the output voltage of a a magnetically coupled multiport dc-dc converter aimed at automotive applications. The proposed algorithm renders robustness to resistive load uncertainty and to the presence of unknown constant power loads. The theoretical analysis, which uses Lyapunov stability theory, is validated via realistic numerical simulations.

This paper presents a feedback linearization-based control strategy for a a magnetically coupled multiport dc-dc converter aimed at automotive applications. Essentially, a transformation of control and state variables is proposed in such a way that the resulting system becomes linear and decoupled. Then, a conventional PI controller is devised that renders asymptotic stability, as well as robustness to resistive load uncertainty and presence of constant power loads. The inversion of the control transformation, which involves nonlinear terms, is carried out using linear approximations with no significant performance decay. Hence, simplicity and efficiency are the main features of the control design. The proposal is validated via realistic numerical simulations.

In this paper we present a state feedback-based adaptive cruise control strategy for an autonomous vehicle able to operate in an effective and safe manner between speed regulation and position control, depending on the velocity of the precedent vehicle and its relative distance. The algorithm is shown to be stable in each operating mode, and design criteria for the controller parameters are used in order to meet the required performance features. Additionally, the control system is numerically tested in an heterogeneous fleet mixing human drivers and autonomous vehicles, and it is shown how the presence of a limited number of autonomous vehicles equipped with the proposed controller improves the traffic flow in terms of stop-and-go waves reduction.

The tracking/rejection of periodic disturbances in linear systems is achievable via internal model principle-based techniques, such as repetitive control. However, when the frequency of the signal to track/reject is uncertain or time-varying, the performance of these controllers decays dramatically. This article discusses the basics of Model Reference Adaptive Control with Minimal Controller Synthesis, and assesses its applicability to this problem from a comparative study of the performance of this type of controllers and a repetitive controller, both designed to regulate the speed of a DC motor subject to periodic disturbances. The study is supported by experimental results.

The use of DC-DC boost-based switched converters for DC-AC step-up inversion applications has been long handicapped by the fact that it requires non-offset, periodic current reference profiles that satisfy an Abel differential equation of the 2nd kind, and this is a challenging problem because the corresponding vector field becomes nonsmooth in zero-crossing points. As a consequence, the proposals made so far considered either offset inversion, which is much less interesting from a practical point of view, or theoretically unsupported approximate non-offset inversion schemes. However, sufficient conditions for the existence of periodic solutions with nonconstant sign in Abel equations of the 2nd kind have been recently reported. In this communication we review these results, and we use them to achieve exact inversion with a boost DC-AC power converter. The proposal is validated via numerical simulations.

As other Internal Model Principle based strategies, digital repetitive control uses an internal model which provides infinite gain at specific frequencies. In systems subject to actuator saturation, a controller with this characteristics is highly prone to windup effect. Since linear design does not consider the actuator saturation this non linear behaviour may compromise the performance and even the stability of the system. One way to deal with this problem is to avoid saturation by selecting an actuator with larger capacity but it increases the implementation cost. In other cases, an anti-windup scheme is necessary. The main goal of the anti-windup strategy is threefold: to obtain a faster recovery of the system after saturation, to achieve less performance degradation and to preserve stability. In this paper three different anti-windup schemes have been selected from the available literature to address the windup problem in digital repetitive control. The design and implementation issues are discussed. A simulation example compares the results when saturation is reached either during the transient response or in steady state.

Digital repetitive control is a technique which allows to track periodic references and/or reject periodic disturbances. Repetitive controllers are usually designed assuming a fixed frequency for the signals to be tracked/rejected, its main drawback being a dramatic performance decay when this frequency varies. A usual approach to overcome the problem consists of an adaptive change of the sampling time according to the reference/disturbance period variation. However, this sampling period adaptation implies parametric changes affecting the closed-loop system behavior, that may compromise the system stability. This article presents a design strategy which allows to compensate for the parametric changes caused by sampling period adjustment. Stability of the digital repetitive controller working under time-varying sampling period is analyzed. Theoretical developments are illustrated with experimental results.

Time-dependent sliding surfaces are used in the generation of signals at the load resistance of a buck converter. Restrictions on these signals are derived from the condition of existence of sliding regime. The use of two sliding zones in the generation of a specified signal is studied.>