Andrea Serrani

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In this work, a distributed indirect adaptive controller is designed for a group of robotic agents cooperatively manipulating a common payload. Uncertainty on the model of the manipulated object and the limited actuation capabilities of the single agents can significantly impact the overall behavior of the control system. An indirect adaptive control scheme is proposed in this article to address these shortcomings. In particular, model uncertainty and loss of effectiveness of the actuators are handled in a unifying fashion by an adaptive control architecture that preserves physical consistency of the estimated inertial parameters of the manipulated object, while simultaneously providing an antiwindup mechanism for the estimated inertial parameters in case of actuator saturation. In addition, a dynamic input allocation strategy is proposed to distribute the control effort among the agents in such a way that the intrinsic input redundancy of the overall setup is exploited for dynamic optimization of additional performance criteria, including optimization of the control efforts on each agent. The stability of the closed-loop system is proven theoretically, and the performance and robustness of the control system are validated by means of comparative simulations with respect to a baseline state-of-the-art controller.

This article addresses the output regulation problem for linear systems whose model is not known a priori but are internally stable or have achieved internal stability through feedback. The article provides a perspective that complements classical internal model-based methodologies. The paradigm we follow emphasizes adaptive feedforward control, signifying all those design methodologies that position a model of the signal to be tracked or rejected by a controlled system outside the primary feedback loop responsible for system stabilization.

This article examines the properties of output-redundant systems, that is, systems possessing a larger number of outputs than inputs, through the lense of the geometric approach of Wonham et al. We begin by formulating a simple output allocation synthesis problem, which involves “concealing” input information from a malicious eavesdropper having access to the system output, while still allowing for a legitimate user to reconstruct it. It is shown that the solvability of this problem requires the availability of a redundant set of outputs. This very problem is instrumental to unveiling the fundamental geometric properties of output-redundant systems, which form the basis for our subsequent constructions and results. As a direct application, we demonstrate how output allocation can be employed to effectively protect the input information from certain output eavesdroppers with guaranteed results.

This paper examines the properties of output-redundant systems, that is, systems possessing a larger number of outputs than inputs, through the lenses of the geometric approach of Wonham et al. We begin by formulating a simple output allocation synthesis problem, which involves ``concealing" input information from a malicious eavesdropper having access to the system output, while still allowing for a legitimate user to reconstruct it. It is shown that the solvability of this problem requires the availability of a redundant set of outputs. This very problem is instrumental to unveiling the fundamental geometric properties of output-redundant systems, which form the basis for our subsequent constructions and results. As a direct application, we demonstrate how output allocation can be employed to effectively protect the information of input information from certain output eavesdroppers with guaranteed results.

The sixth IEEE Conference on Control Technology and Applications (CCTA 2022) took place at the Stazione Marittima, Trieste, Italy, from August 23 to 25, 2022, with technical workshops held on August 22, 2022. This event was conducted as a hybrid format, offering both in-person and virtual participation, marking the first hybrid conference sponsored by the IEEE Control Systems Society (CSS), since the COVID-19 pandemic. The CCTA 2022 was organized in collaboration with the Society for Instrument and Control Engineers and co-sponsored by the European Control Association. The CCTA 2022 is the premier event of the CSS focusing on advancements in systems and control technologies and applications. This peculiar focus of the conference establishes a natural connection with the IEEE Transactions on Control Systems Technology (TCST). Two initiatives were introduced in the CCTA 2022 to nourish this kindred relationship between the premier application-oriented journal and conference of the CSS. Authors of recently published papers in TCST that have not been previously presented at the CCTA were encouraged to give oral presentations of their work at the conference. Furthermore, the authors of the selected articles presented at the CCTA 2022 were invited to submit extended versions of their work for consideration in this special section of the September 2024 Issue of the TCST dedicated to the conference.

This letter presents a predictor-based adaptive augmentation scheme to recover the designed behavior of a baseline linear controller in presence of parametric uncertainty. Remarkably, the proposed scheme achieves the recovery of the baseline closed-loop performance without the need for explicit knowledge of the baseline controller states and structure; rather, the adaptive mechanism relies solely on the output of the baseline controller and plant states. We showcase how the proposed adaptive design seamlessly integrates into inner-outer loop control architectures, enhancing the overall performance and robustness while simultaneously reducing the control law complexity compared to available solutions.