Practical and clinical utility of non-invasive vagus nerve stimulation (nVNS) for the acute treatment of migraine. A post hoc analysis of the randomized, sham-controlled, double-blind PRESTO trial

Background: The PRESTO study of non-invasive vagus nerve stimulation (nVNS; gammaCore®) featured key primary and secondary end points recommended by the International Headache Society to provide Class I evidence that for patients with an episodic migraine, nVNS significantly increases the probability of having mild pain or being pain-free 2 h post stimulation. Here, we examined additional data from PRESTO to provide further insights into the practical utility of nVNS by evaluating its ability to consistently deliver clinically meaningful improvements in pain intensity while reducing the need for rescue medication. Methods: Patients recorded pain intensity for treated migraine attacks on a 4-point scale. Data were examined to compare nVNS and sham with regard to the percentage of patients who benefited by at least 1 point in pain intensity. We also assessed the percentage of attacks that required rescue medication and pain-free rates stratified by pain intensity at treatment initiation. Results: A significantly higher percentage of patients who used acute nVNS treatment (n = 120) vs sham (n = 123) reported a ≥ 1-point decrease in pain intensity at 30 min (nVNS, 32.2%; sham, 18.5%; P = 0.020), 60 min (nVNS, 38.8%; sham, 24.0%; P = 0.017), and 120 min (nVNS, 46.8%; sham, 26.2%; P = 0.002) after the first attack. Similar significant results were seen when assessing the benefit in all attacks. The proportion of patients who did not require rescue medication was significantly higher with nVNS than with sham for the first attack (nVNS, 59.3%; sham, 41.9%; P = 0.013) and all attacks (nVNS, 52.3%; sham, 37.3%; P = 0.008). When initial pain intensity was mild, the percentage of patients with no pain after treatment was significantly higher with nVNS than with sham at 60 min (all attacks: nVNS, 37.0%; sham, 21.2%; P = 0.025) and 120 min (first attack: nVNS, 50.0%; sham, 25.0%; P = 0.018; all attacks: nVNS, 46.7%; sham, 30.1%; P = 0.037). Conclusions: This post hoc analysis demonstrated that acute nVNS treatment quickly and consistently reduced pain intensity while decreasing rescue medication use. These clinical benefits provide guidance in the optimal use of nVNS in everyday practice, which can potentially reduce use of acute pharmacologic medications and their associated adverse events. Trial registration: ClinicalTrials.gov identifier: NCT02686034

Towards structure-independent stabilization for uncertain underactuated Euler–Lagrange systems

Available control methods for underactuated Euler–Lagrange (EL) systems rely on structure-specific constraints that may be appropriate for some systems, but restrictive for others. A generalized (structure-independent) control framework is to a large extent missing, especially in the presence of uncertainty. This paper introduces an adaptive-robust control framework for a quite general class of uncertain underactuated EL systems. Compared to existing literature, the important attributes of the proposed solution are: (i) avoiding structure-specific restrictions, namely, symmetry condition property of the mass matrix, and a priori bounds on non-actuated states or state derivatives; (ii) considering Coriolis, centripetal, friction and gravity terms to be unknown, while only requiring the knowledge of maximum perturbation around a nominal value of the mass matrix; (iii) handling state-dependent uncertainties irrespective of their linear or nonlinear in parameters structure. These features significantly widen the range of underactuated EL systems the proposed solution can handle in comparison to the available methods. Stability is studied analytically and the performance is verified in simulation using offshore boom crane dynamics.Accepted Author ManuscriptShip Design, Production and OperationsTeam DeSchutte

A simultaneous adaptation law for a class of nonlinearly-parametrized switched systems

This letter proposes a new adaptive control method for a class of nonlinearly-parametrized switched systems that includes Monod kinetics and Euler-Lagrange systems with nonlinear in parameters form as special cases. As compared to the adaptive switched frameworks proposed in literature, the proposed adaptation framework has the distinguishing feature of updating the gains of the active and inactive subsystems simultaneously: by doing this it avoids high gains for the active subsystems or vanishing gains for the inactive ones. The design is studied analytically and its performance is validated in simulation with a robotic manipulator example.Accepted Author ManuscriptShip Design, Production and OperationsTeam DeSchutte

An iterative Sum-of-Squares optimization for static output feedback of polynomial systems

This work proposes an iterative procedure for static output feedback of polynomial systems based on Sum-of-Squares optimization. Necessary and sufficient conditions for static output feedback stabilization of polynomial systems are formulated, both for the global and for the local stabilization case. Since the proposed conditions are bilinear with respect to the decision variables, an iterative procedure is proposed for the solution of the stabilization problem. Every iteration is shown to improve the performance with respect to the previous one, even if convergence to a local minimum might occur. Since polynomial Lyapunov functions and control laws are considered, a Sum-of-Squares optimization approach is adopted. A numerical example illustrates the results.Accepted Author ManuscriptHybrid, Adaptive and Nonlinea

Cooperative output regulation of heterogeneous unknown systems via passification-based adaptation

While several robust cooperative output regulation approaches for heterogeneous systems have been proposed (with fixed-gain distributed controllers), the design of adaptive-gain distributed controllers becomes relevant in dealing with larger uncertainty than robust approaches. This letter addresses the adaptive cooperative output regulation problem for heterogeneous systems with unknown linear dynamics, where possibly large system uncertainty would make fixed-gain robust approaches not applicable. A passification method is adopted to design adaptive-gain distributed controllers solving the problem. The proposed method includes two steps: in the first step, a distributed observer of the exogenous signal is designed for those systems that cannot access the exosystem, and a reference model is designed whose output can converge to the exogenous signal; in the second step, command generator tracking is achieved via adaptive laws that make the output of each system converge to the output of the reference model, and thus to the exogenous signal. Stability analysis is provided via a Lyapunov approach, and a numerical example illustrates the effectiveness of the approach.Accepted Author ManuscriptTeam DeSchutte

Adaptive synchronization of unknown heterogeneous agents: An adaptive virtual model reference approach

This work deals with state synchronization of heterogeneous linear agents with unknown dynamics. The problem is solved by formulating the synchronization problem as a special model reference adaptive control where each agent tries to converge to the model defined by its neighbors. For those agents that do not know the reference signal that drives the flock, a fictitious reference is estimated in place of the actual one: the estimation of such reference is distributed and requires measurements from neighbors. By using a matching condition assumption, which is imposed so that the agents can converge to the same behavior, the fictitious reference estimation leads to adaptive laws for the feedback and the coupling gains arising from distributed matching conditions. In addition, the coupling connection is not scalar as in most literature, but possibly vector-valued. The proposed approach is applicable to heterogeneous agents with arbitrarily large matched uncertainties. A Lyapunov-based approach is derived to show analytically asymptotic convergence of the synchronization error: robustification in the presence of bounded errors or unknown (constant) leader input is also discussed. Finally, a motivational example is presented in the context of Cooperative Adaptive Cruise Control and numerical examples are provided to demonstrate the effectiveness of the proposed method.Team DeSchutte

An integrated control-oriented modelling for HVAC performance benchmarking

Energy efficiency in building heating, ventilating and air conditioning (HVAC) equipment requires the development of accurate models for testing HVAC control strategies and corresponding energy consumption. In order to make the HVAC control synthesis computationally affordable, such control-oriented models are typically a simplified version of more elaborate building simulation environments (e.g. EnergyPlus, Modelica, TRNSYS). Despite their simplicity, control-oriented models must effectively catch all the interactions between HVAC equipment, in order achieve system integration and avoid fragmentation in HVAC modelling and control synthesis, which is one of the main causes of suboptimal performance in the building sector. In this work we propose an integrated control-oriented modelling for HVAC performance benchmarking. The following HVAC equipment and their interaction are modelled: condensing boiler, radiator, air handling unit, heat pump, chiller, fan, pump, pipe, duct, and multiple thermal zones. The proposed modelling approach is modular so that the user can add and remove as many components as desired, depending on the building to be modelled. Appropriate procedures for synthesis of control strategies and benchmarking are proposed. Extensive simulations demonstrate the effectiveness of the proposed methodology, which can lead to improvements in occupants' thermal comfort while at the same time consistently attaining energy savings.Accepted Author ManuscriptTeam DeSchutte

Stability margins in adaptive mixing control via a Lyapunov-based switching criterion

This paper proposes a Lyapunov-based switching logic within the framework of adaptive mixing control (AMC), where a weighted combination of a family of candidate controllers can be inserted in the loop to regulate the output of an uncertain plant. The proposed AMC scheme employs a bank of parallel estimators, or multiple estimators, together with a switching logic that orchestrates which estimate should be evaluated by the mixer. The switching logic is driven by input/output data and uses Lyapunov-based criteria to assess the best estimate among the bank of parallel estimates. The resulting scheme guarantees convergence of the switching signal in finite time to a controller that satisfies a Lyapunov inequality implying a prescribed stability margin. The problem of convergence to the desired controller is addressed both analytically and numerically. In contrast, most classes of continuous tuning adaptive control or switching adaptive control schemes do not guarantee that after the switching stops or the adaptation is switched off the resulting closed loop linear time-invariant (LTI) system is stable, unless there is sufficient plant excitation that guarantees convergence to the desired fixed parameter controller. The proposed scheme guarantees that if the desired controller is switched on, it will never be switched off thereafter. Furthermore, simulations demonstrate that while alternative adaptation methods can converge to an LTI unstable feedback loop, the proposed scheme consistently converges to the desired controller.Accepted Author ManuscriptTeam DeSchutte

Monitoring energy efficiency of condensing boilers via hybrid first-principle modelling and estimation

The operating principle of condensing boilers is based on exploiting heat from flue gases to pre-heat cold water at the inlet of the boiler: by condensing into liquid form, flue gases recover their latent heat of vaporization, leading to 10–12% increased efficiency with respect to traditional boilers. However, monitoring the energy efficiency of condensing boilers is complex due to their nonlinear dynamics: currently, (static) nonlinear efficiency curves of condensing boilers are calculated at quasi-stationary regime and ‘a posteriori’, i.e. from data collected during chamber tests: therefore, with this static approach, it is possible to monitor the energy efficiency only at steady-state regime. In this work we propose a novel model-based monitoring approach for condensing boilers that extends the operating regime for which monitoring is possible: the approach is based on a hybrid dynamic model of the condensing boiler, where state-dependent switching accounts for dynamically changing condensing/non condensing proportions. Monitoring the energy efficiency over the boiler's complete dynamic regime is possible via switching estimators designed for the different condensing/non condensing modes. By using real-world boiler efficiency data we show that the proposed approach results in a (dynamic) nonlinear efficiency curve which gives a more complete description of the condensing boilers operation than static nonlinear efficiency curves: in addition, the dynamic curve can be derived ‘a priori’, i.e. from first principles, or from data collected during normal boiler operation (without requiring special chamber tests).Team DeSchutte