Robust energy-maximising control of wave energy systems under input uncertainty

Motivated by the ubiquitous presence of input uncertainty in the wave energy control problem, we propose, in this paper, a robust energy-maximising framework which explicitly considers potential wave excitation force deviations in the computation of the optimal control law, while systematically respecting state and input constraints. In particular, this is achieved by a suitable moment-based characterisation for the input uncertainty, taking into consideration an appropriate convex uncertainty set. The concept of moments is combined with well-known robust optimisation principles, by proposing a worst-case performance approach. We show that this novel moment-based robust optimal control framework always admits a unique global energy-maximising solution, hence leading to a computationally efficient robust solution. The performance of the proposed controller is illustrated by means of a case study, considering a heaving point absorber WEC

Time-varying damping coefficient to increase power extraction from a notional wave energy harvester

Energy efficiency and renewable energy generation is attracting increasing attention, due to the established understanding that a new sustainable approach to power human activities is compulsory, on the one hand, and thanks to technological advances, on the other hand. Energy harvesters, at different scales, are promising tools, but their performance and economic viability depend on advanced energy-maximisation control techniques. This paper borrows a control strategy from the vibration energy harvesting field, and implements it to a notional wave energy conversion application. A linear time variant damping coefficient of the power take-off unit is considered, oscillating at twice sinusoidal excitation force frequency, inducing parametric resonance in the system and significantly expanding the response bandwidth. Active and semi-active solutions are investigated, allowing or preventing bi-directional power flow, comparing results with traditional passive and impedance-matching control. Results show that, although both active and semi-active control successfully increase the mean power extraction, much larger than passive control, semi-active control ensures better power quality and lower control forces

One-loop effective potential in M4 x T2 with and without 't Hooft flux

We review the basic notions of compactification in the presence of a background flux. In extra-dimentional models with more than five dimensions, Scherk and Schwarz boundary conditions have to satisfy 't Hooft consistency conditions. Different vacuum configurations can be obtained, depending whether trivial or non-trivial 't Hooft flux is considered. The presence of the "magnetic" background flux provide, in addition, a mechanism for producing four-dimensional chiral fermions. Particularizing to the six-dimensional case, we calculate the one-loop effective potential for a U(N) gauge theory on M4 x T2. We firstly review the well known results of the trivial 't Hooft flux case, where one-loop contributions produce the usual Hosotani dynamical symmetry breaking. Finally we applied our result for describing, for the first time, the one-loop contributions in the non-trivial 't Hooft flux case

Nonlinear energy-maximising optimal control of wave energy systems: A moment-based approach

Linear dynamics are virtually always assumed when designing optimal controllers for wave energy converters (WECs), motivated by both their simplicity and computational convenience. Nevertheless, unlike traditional tracking control applications, the assumptions under which the linearization of WEC models is performed are challenged by the energy-maximizing controller itself, which intrinsically enhances device motion to maximize power extraction from incoming ocean waves. \GSIn this article, we present a moment-based energy-maximizing control strategy for WECs subject to nonlinear dynamics. We develop a framework under which the objective function (and system variables) can be mapped to a finite-dimensional tractable nonlinear program, which can be efficiently solved using state-of-the-art nonlinear programming solvers. Moreover, we show that the objective function belongs to a class of generalized convex functions when mapped to the moment domain, guaranteeing the existence of a global energy-maximizing solution and giving explicit conditions for when a local solution is, effectively, a global maximizer. The performance of the strategy is demonstrated through a case study, where we consider (state and input-constrained) energy maximization for a state-of-the-art CorPower-like WEC, subject to different hydrodynamic nonlinearities

Optimal control of wave energy systems considering nonlinear Froude–Krylov effects: control-oriented modelling and moment-based control

Motivated by the relevance of so-called nonlinear Froude–Krylov (FK) hydrodynamic effects in the accurate dynamical description of wave energy converters (WECs) under controlled conditions, and the apparent lack of a suitable control framework effectively capable of optimally harvesting ocean wave energy in such circumstances, we present, in this paper, an integrated framework to achieve such a control objective, by means of two main contributions. We first propose a data-based, control-oriented, modelling procedure, able to compute a suitable mathematical representation for nonlinear FK effects, fully compatible with state-of-the-art control procedures. Secondly, we propose a moment-based optimal control solution, capable of transcribing the energy-maximising optimal control problem for WECs subject to nonlinear FK effects, by incorporating the corresponding data-based FK model via moment-based theory, with real-time capabilities. We illustrate the application of the proposed framework, including energy absorption performance, by means of a comprehensive case study, comprising both the data-based modelling, and the optimal moment-based control of a heaving point absorber WEC subject to nonlinear FK force

On the approximation of moments for nonlinear systems

Model reduction by moment-matching relies upon the availability of the so-called moment. If the system is nonlinear, the computation of moments depends on an underlying specific invariance equation, which can be difficult or impossible to solve. This note presents four technical contributions related to the theory of moment matching: first, we identify a connection between moment-based theory and weighted residual methods. Second, we exploit this relation to provide an approximation technique for the computation of nonlinear moments. Third, we extend the definition of nonlinear moment to the case in which the generator is described in explicit form. Finally, we provide an approximation technique to compute the moments in this scenario. The results are illustrated by means of two examples

Energy-maximising moment-based constrained optimal control of ocean wave energy farms

Successful commercialisation of wave energy technology inherently incorporates the concept of an array of wave energy converters (WECs). These devices, which constantly interact via hydrodynamic effects, require optimised control that can guarantee maximum energy extraction from incoming ocean waves while ensuring, at the same time, that any physical limitations associated with device and actuator systems are being consistently respected. This paper presents a moment-based energy-maximising optimal control framework for WECs arrays subject to state and input constraints. The authors develop a framework under which the objective function (and system variables) can be mapped to a finite-dimensional tractable quadratic program (QP), which can be efficiently solved using state-of-the-art solvers. Moreover, the authors show that this QP is always concave, i.e. existence and uniqueness of a globally optimal solution is guaranteed under this moment-based framework. The performance of the proposed strategy is demonstrated through a case study, where (state and input constrained) energy-maximisation for a WEC farm composed of CorPower-like WEC devices is considered

Model reduction by moment matching: beyond linearity a review of the last 10 years

We present a review of some recent contributions to the theory and application of nonlinear model order reduction by moment matching. The tutorial paper is organized in four parts: 1) Moments of Nonlinear Systems; 2) Playing with Moments: Time-Delay, Hybrid, Stochastic, Data-Driven and Beyond; 3) The Loewner Framework; 4) Applications to Optimal Control and Wave Energy Conversion