To reduce CO2 emissions and tackle increasing fuel costs, the aviation industry is swiftly moving toward the electrification of aircraft. From the viewpoint of systems and control, a key challenge brought by this transition corresponds to the management and safe operation of the propulsion system's onboard electrical power distribution network. Motivated by this transition, in this work, we propose a distributed adaptive controller for regulating the voltage of a DC bus in a class of DC power distribution networks inspired by a series-hybrid-electric propulsion system. The proposed controller-whose design is based on principles of backstepping, adaptive, and passivity-based control techniques-also enables the proportional sharing of the electric load among multiple converter-interfaced sources, which reduces the likelihood of overstressing individual sources. Compared to existing control strategies, our method ensures stable, convergent, and accurate voltage regulation and load sharing even if the effects of power lines of unknown resistances and inductances are considered. The performance of the proposed control scheme is experimentally validated and compared to state-of-the-art controllers in a power hardware-in-the-loop (PHIL) environment.

We consider the problem of active fault-tolerant control in cyber-physical systems composed of strictly passive linear-time invariant dynamic subsystems. We cast the problem as a constrained optimization problem and propose an augmented primal-dual gradient dynamics-based fault-tolerant control framework that enforces network-level constraints and provides optimality guarantees for the post-fault steady-state operation. By suitably interconnecting the primal-dual algorithm with the cyber-physical dynamics, we provide sufficient conditions under which the resulting closed-loop system possesses a unique and exponentially stable equilibrium point that satisfies the Karush–Kuhn–Tucker (KKT) conditions of the constrained problem. The framework's effectiveness is illustrated through numerical experiments on a DC microgrid.

Continuous-time primal-dual gradient dynamics (PDGD) is an ubiquitous approach for dynamically solving constrained distributed optimization problems. Yet, the distributed nature of the dynamics makes it prone to communication uncertainties, especially time delays. To mitigate this effect, we propose a delay-robust continuous-time PDGD. The dynamics is obtained by augmenting the standard PDGD with an auxiliary state coupled through a gain matrix, while preserving the optimal solution. Then, we present sufficient tuning conditions for this gain matrix in the form of linear matrix inequalities, which ensure uniform asymptotic stability in the presence of bounded, time-varying delays. The criterion is derived via the Lyapunov-Krasovskii method. A numerical example illustrates the improved delay robustness of our approach compared to the standard PDGD under large, time-varying delays.

We develop a novel switching dynamics that converges to the Karush-Kuhn-Tucker (KKT) point of a nonlinear optimisation problem. This new approach is particularly notable for its lower dimensionality compared to conventional primal-dual dynamics, as it focuses exclusively on estimating the primal variable. Our method is successfully illustrated on general quadratic optimisation problems, the minimisation of the classical Rosenbrock function, and a nonconvex optimisation problem stemming from the control of energy-efficient buildings.

To reduce CO2 emissions and tackle increasing fuel costs, the aviation industry is swiftly moving towards the electrification of aircraft. From the viewpoint of systems and control, a key challenge brought by this transition corresponds to the management and safe operation of the propulsion system's onboard electrical power distribution network. In this work, for a series-hybrid-electric propulsion system, we propose a distributed adaptive controller for regulating the voltage of a DC bus that energizes the electricity-based propulsion system. The proposed controller – whose design is based on principles of back-stepping, adaptive, and passivity-based control techniques – also enables the proportional sharing of the electric load among multiple converter-interfaced sources, which reduces the likelihood of over-stressing individual sources. Compared to existing control strategies, our method ensures stable, convergent, and accurate voltage regulation and load-sharing even if the effects of power lines of unknown resistances and inductances are considered. The performance of the proposed control scheme is experimentally validated and compared to state-of-the-art controllers in a power hardware-in-the-loop (PHIL) environment.

We propose an input-output data-driven framework for certifying the stability of interconnected multiple-input-multiple-output linear time-invariant discrete-time systems via QSR-dissipativity. That is, by using measured input-output trajectories of each subsystem, we verify dissipative properties and extract local passivity indices without requiring an explicit model identification.These passivity indices are then used to derive conditions under which the equilibrium of the interconnected system is stable. In particular, the framework identifies how the lack of passivity in some subsystems can be compensated by surpluses in others. The proposed approach enables a compositional stability analysis by combining subsystem-level conditions into a criterion valid for the overall interconnected system. We illustrate via a numerical case study, how to compute channel-wise passivity indices and infer stability guarantees directly from data with the proposed method.

In this work we present a cost-optimal energy management scheme for sector-coupled energy plants, focusing on systems that enable gas-to-electricity, gas-to-heat, and power-to-heat conversions. To capture realistic operational challenges, the considered system model incorporates dynamic constraints, including start-up delays and off-time-dependent start-up costs. By accounting for the impact of these factors, we demonstrate on a case study that they can significantly reduce overall operational costs. The energy management problem is cast as a mixed-integer nonlinear programming (MINLP) problem, which is then solved within a model predictive control (MPC) framework. The proposed approach provides a structured methodology for real-time energy management, enhancing energy efficiency while minimizing costs. Copyright (c) 2025 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

A fundamental precondition for the operation of district heating networks (DHNs) is a stable hydraulic behavior. However, the ongoing transition toward a sustainable heat supply, especially the rising integration of distributed heat sources and the increasingly meshed topologies, introduces complex and potentially destabilizing hydraulic dynamics. In this work, we propose a unifying, equilibrium-independent passivity (EIP)-based control framework, which guarantees asymptotic stability of any feasible, hydraulic DHN equilibrium for a wide range of DHN setups covering different DHN generations, meshed, time-varying topologies, and multiple, dynamically interacting distributed heat sources. The obtained results hold for the state of the art as well as future DHN generations featuring, for example, multiple distributed heat sources, asymmetric pipe networks, and multiple temperature layers.

In these lecture notes, we delve into the models of the most commonly used DC-DC power converters: namely, the buck converter and the boost converter. Furthermore, we derive models for a DC microgrid consisiting of multiple buck and/or boost converters interconnected via (dynamic) resistive-inductive power lines and supplying the so-called ZIP loads, which are characterized by the parallel combination of constant impedance (Z), current (I), and power (P) load components. Furthermore, we introduce the primary control objectives in DC microgrids, focusing on voltage regulation and current sharing. Finally, we explore the most advanced control techniques to achieve these objectives. Importantly, these lecture notes are not intended to advocate total replacement of Alternating Current (AC) power systems with their Direct Current (DC) counterparts, but rather aim to offer a balanced perspective between them, acknowledging the historical dominance of AC power systems while underscoring the contemporary relevance of DC microgrids, which, with their inherent advantages, represent a viable complement to the existing infrastructure, fostering innovation and resilience in modern power networks.

To reduce CO 2 emissions and tackle increasing fuel costs, the aviation industry is swiftly moving towards the electrification of aircraft. From the viewpoint of systems and control, a key challenge brought by this transition corresponds to the management and safe operation of the propulsion system's onboard electrical power distribution network. In this work, for a series-hybrid-electric propulsion system, we propose a distributed adaptive controller for regulating the voltage of a DC bus that energizes the electricity-based propulsion system. The proposed controller-whose design is based on principles of back-stepping, adaptive, and passivity-based control techniques-also enables the proportional sharing of the electric load among multiple converter-interfaced sources, which reduces the likelihood of over-stressing individual sources. Compared to existing control strategies, our method ensures stable, convergent, and accurate voltage regulation and load sharing even if the effects of power lines of unknown resistances are considered. The performance of the proposed control scheme is illustrated via numerical simulations of an exemplary propulsion architecture.

The transformation of fossil fuel-based district heating grids (DHGs) to CO$_2$-neutral DHGs requires the development of novel operating strategies. Model predictive control (MPC) is a promising approach, as knowledge about future heat demand and heat supply can be incorporated into the control, operating constraints can be ensured and the stability of the closed-loop system can be guaranteed. In this paper, we employ MPC for DHGs to control the system mass flows and injected heat flows. Following common practice, we derive terminal ingredients to stabilize given steady state temperatures and storage masses in the DHG. To apply MPC with terminal ingredients, it is crucial that the system under control is stabilizable. By exploiting the particular system structure, we give a sufficient condition for the stabilizability in terms of the grid topology and hence, for the applicability of the MPC scheme to DHGs. Furthermore, we demonstrate the practicability of the application of MPC to an exemplary DHG in a numerical case study.

In this paper, using tools from graph theory we provide verifiable necessary and sufficient conditions for the existence of a unique hydraulic equilibrium in district heating systems of meshed topology and containing multiple heat sources. Even though numerous publications have addressed the design of efficient algorithms for numerically finding hydraulic equilibria in the general context of water distribution networks, this is not the case for the analysis of existence and uniqueness. Moreover, most of the existing work dealing with these aspects exploit the equivalence between the nonlinear algebraic equations describing the hydraulic equilibria and the KKT conditions of a suitably defined nonlinear convex optimization problem. Differently, this paper proposes necessary and sufficient graph-theoretic conditions on the actuator placement for the existence and uniqueness of a hydraulic equilibrium, independent of the actuators' control objective. An example based on a representative district heating network is considered to illustrate the key aspects of our contribution, and an explicit formulation of the steady state solution is given for the case in which pressure drops through pipes are linear with respect to the flow rate.

This letter studies nonlinear dynamic control design for a class of bilinear systems to asymptotically stabilize a given equilibrium point while fulfilling constraints on the control input and state. We design a controller based on integral actions on the system input and output. As special cases, the proposed controller contains a dynamic controller with an integral action of either input or output only and a static controller. Stability analysis of the closed-loop system is performed based on a Lyapunov function. Level sets of the Lyapunov function are utilized to estimate a set of initial states and inputs such that the corresponding state and input trajectories are within specified compact sets. Finally, the proposed control technique is applied to a heat exchanger under constraints on the temperature of each cell (state) and the mass flow rate (input), and simulations show the effectiveness of the proposed approach.

This paper addresses the problem of achieving current sharing and voltage balancing in DC microgrids when the filter parasitic resistances of the Distributed Generation Units (DGUs) are unknown and potentially time-varying. Two schemes are proposed for current sharing and voltage balancing, which use only generated current and voltage measurements. The first scheme is a novel distributed adaptive control utilising the principles of back-stepping and passivity-based control design, intended for the case of constant parasitic resistances. The second scheme alters an existing stabilising controller for current sharing and voltage balancing by incorporating the estimation of the unknown, possibly time-varying, parasitic resistance. A Super-Twisting Sliding Mode Algorithm (STA) estimates the parasitic resistance and its bounded variations in finite-time. The simulation results using a DC microgrid composed of 4 DGUs demonstrate the performance of the proposed schemes.

In this paper, we use elements of graph theory and port-Hamiltonian systems to develop a modular dynamic model describing the hydraulic behavior of 4th generation district heating networks. In contrast with earlier generation networks with a single or few heat sources and pumps, newer installations will prominently feature distributed heat generation units, bringing about a number of challenges for the control and stable operation of these systems, e.g., flow reversals and interactions among pumps controllers, which may lead to severe oscillations. We focus thus on flexible system setups with an arbitrary number of distributed heat sources and end-users interconnected through a meshed, multi-layer distribution network of pipes. Moreover, differently from related works on the topic, we incorporate dynamic models for the pumps in the system and explicitly account for the presence of pressure holding units. By inferring suitable (power-preserving) interconnection ports, we provide a number of claims about the passivity properties of the overall, interconnected system, which proves to be highly beneficial in the design of decentralized control schemes and stability analyses.

Modern district heating technologies have a great potential to make the energy sector more flexible and sustainable due to their capabilities to use energy sources of varied nature and to efficiently store energy for subsequent use. Central control tasks within these systems for the efficient and safe distribution of heat refer to the stabilization of overall system temperatures and the regulation of storage units state of charge. These are challenging goals when the networked and nonlinear nature of district heating system models is taken into consideration. In this letter, for district heating systems with multiple, distributed heat producers, we propose a decentralized control scheme to provably meet said tasks stably.

This paper explores a Passivity-based Control scheme for islanded AC microgrids with detailed power converter dynamics. In contrast to the usual practice, it is proposed to include in the controller design the required power of the loads and the available power of the Distributed Energy Resources by means of a dynamical system whose trajectories asymptotically converge to the solution of the power flow equations. The stability properties of the closed-loop system are formally proved while its usefulness is illustrated numerically.

These lecture notes provide an overview of recent research on the modeling and control of smart grids using distributed algorithms. In particular, energy-based modeling of general AC power networks using the framework of port-Hamiltonian systems theory is presented, and the relevance of such a formulation for stability analysis and control design is discussed. Low-level control design aspects (at a physical layer) for DC microgrids are also considered, achieving objectives such as fair load sharing among distributed generation units and (average) voltage regulation using limited data and measurements from the system. Finally, general frameworks for the optimal control of smart grids are introduced to consider both physical and economic constraints and exploit the flexibility brought up by storage devices and demand response from the grid’s prosumers.

Flow and storage volume regulation is essential for the adequate transport and management of energy resources in district heating systems. In this letter, we propose a novel and suitably tailored-decentralized-adaptive control scheme addressing this problem whilst offering closed-loop stability guarantees. We focus on a system configuration comprising multiple heat producers, consumers and storage tanks exchanging energy through a common distribution network, which are features of modern and prospective district heating installations. The proposed controller is based on passivity, backstepping and (indirect) adaptive control theory.