Robust Excitation Force Estimation and Prediction for Wave Energy Converter M4 Based on Adaptive Sliding-Mode Observer

The wave excitation force estimation and prediction play an important role in improving the performance of causal and noncausal controllers for wave energy converters (WECs). This article proposes a robust adaptive sliding-mode observer (ASMO) to estimate the wave excitation force subject to unknown disturbances and parametric uncertainties for a multimotion multifloat WEC, called M4. Both the convergence time and the estimation error can be explicitly bounded within expected limits by tuning the ASMO parameters, which are essentially beneficial for causal controllers to maintain the control performance. A fixed-time convergent sliding variable is designed to drive the estimation error into a small region within a fixed time. Due to the adaptive law, the overall system is proven to be finite-time stable, which allows explicit formulations of the convergence time and the estimation error. Moreover, based on the wave force estimation by the ASMO, an improved auto-regressive (AR) model whose coefficients are updated by online training is developed to predict the wave excitation force. The prediction errors can also be explicitly estimated to achieve guaranteed control performance for the noncausal controller requiring future excitation force. From the comparison based on a realistic sea wave gathered from Cornwall, U.K., it can be found that compared with the conventional Kalman filter, the ASMO achieves a smaller steady-state estimation error and has satisfactory robustness performance against 30% model mismatch.</p

Non-causal Linear Optimal Control with Adaptive Sliding Mode Observer for Multi-Body Wave Energy Converters

As a non-causal optimal control problem, the performance of wave energy converter (WEC) control relies on the accuracy of the future incoming wave prediction. However, the inevitable prediction errors can degrade WEC performance dramatically especially when a long prediction horizon is needed by a WEC non-causal optimal controller. This paper proposes a novel non-causal linear optimal control with adaptive sliding mode observer (NLOC+ASMO) scheme, which can effectively mitigate the control performance degradation caused by wave prediction errors. This advantage is achieved by embedding the following enabling techniques into the scheme: (i) an adaptive sliding mode observer (ASMO) to estimate current excitation force in real-time with explicitly formulated boundary of estimation error, (ii) an auto-regressive (AR) model to predict the incoming excitation force with explicitly formulated boundary of prediction error using a set of latest historical data of ASMO estimations from (i), and (iii) a compensator to compensate for both the estimation error and the prediction error of excitation force. Moreover, the proposed NLOC+ASMO scheme does not cause heavy computational load enabling its real-time implementation on standard computational hardware, which is especially critical for the control of WECs with complicated dynamics. The proposed NLOC+ASMO framework is generic and can be applied to a wide range of WECs, and in this paper we demonstrate the efficacy by using a multi-float and multi-motion WEC called M4 as a case study, whose control problem is more challenging than the widely studied point absorbers. Simulation results show the effectiveness of the proposed control scheme in a wide range of sea states, and it is also found that the controller is not sensitive to change of ASMO parameters

Empowering wave energy with control technology: Possibilities and pitfalls

With an increasing focus on climate action and energy security, an appropriate mix of renewable energy technologies is imperative. Despite having considerable global potential, wave energy has still not reached a state of maturity or economic competitiveness to have made an impact. Challenges include the high capital and operational costs associated with deployment in the harsh ocean environment, so it is imperative that the full energy harnessing capacity of wave energy devices, and arrays of devices in farms, is realised. To this end, control technology has an important role to play in maximising power capture, while ensuring that physical system constraints are respected, and control actions do not adversely affect device lifetime. Within the gamut of control technology, a variety of tools can be brought to bear on the wave energy control problem, including various control strategies (optimal, robust, nonlinear, etc.), data-based model identification, estimation, and forecasting. However, the wave energy problem displays a number of unique features which challenge the traditional application of these techniques, while also presenting a number of control ‘paradoxes’. This review articulates the important control-related characteristics of the wave energy control problem, provides a survey of currently applied control and control-related techniques, and gives some perspectives on the outstanding challenges and future possibilities. The emerging area of control co-design, which is especially relevant to the relatively immature area of wave energy system design, is also covered

Advances in Rotating Electric Machines

It is difficult to imagine a modern society without rotating electric machines. Their use has been increasing not only in the traditional fields of application but also in more contemporary fields, including renewable energy conversion systems, electric aircraft, aerospace, electric vehicles, unmanned propulsion systems, robotics, etc. This has contributed to advances in the materials, design methodologies, modeling tools, and manufacturing processes of current electric machines, which are characterized by high compactness, low weight, high power density, high torque density, and high reliability. On the other hand, the growing use of electric machines and drives in more critical applications has pushed forward the research in the area of condition monitoring and fault tolerance, leading to the development of more reliable diagnostic techniques and more fault-tolerant machines. This book presents and disseminates the most recent advances related to the theory, design, modeling, application, control, and condition monitoring of all types of rotating electric machines

Hydrodynamic excitation force estimation and forecasting for wave energy applications

Ocean waves represent a significant energy resource which can complement other renewable energy technologies during the transition to a low-carbon energy mix. Despite the large number of concepts suggested for the conversion of wave energy, none of the technologies has yet demonstrated economic viability. To this end, several solutions have been proposed in the literature, such as deploying Wave Energy Converters (WECs) in large arrays or optimal control of WECs. The majority of WEC optimal control strategies require knowledge of the previous, current, and future excitation force acting on the device. However, for the WEC case, the excitation force is an unmeasurable quantity and, therefore, must first be estimated, based on available measurements, and then predicted in the future. The main objective of this thesis is to analyse the estimation/prediction techniques proposed for wave energy applications and to evaluate whether such techniques are ready to be applied for real WEC control strategies. To this end, a critical comparison of the available excitation force estimators is presented. Additionally, the performance of the autoregressive model as a predictor is analysed, showing that, the obtained prediction accuracy can get close to the theoretically best achievable prediction accuracy. Based on the errors observed from the analysis of excitation force estimation/prediction techniques, a sensitivity analysis of an optimal control strategy to such errors is performed. As a result, this thesis provides an overview of the aspects which should be considered at the stage of tuning estimation/prediction techniques, to not affect the controller performance. Since the estimation/prediction problem becomes more challenging for WEC arrays, due to the hydrodynamic interactions, an important question is whether the extra measurements from the array are sufficient to compensate for the greater complexity of the wave field. Thus, a global estimator/predictor, considering information from all the devices of the array, is developed and compared to a set of independent estimators/predictors. Finally, this thesis introduces an identification strategy to obtain a parametric model of both the force-to-motion dynamics and/or the radiation force convolution term of the device. The strategy allows for the identification of low-order parametric models of WECs, which will simplify the implementation of optimal control strategies in real-time. Additionally, the proposed strategy is compared to the other approaches available in the literature

Optimal Control of Wave Energy Converters

In this dissertation, we address the optimal control of the Wave Energy Converters. The Wave Energy Converters introduced in this study can be categorized as the single body heaving device, the single body pitching device, the single body three degrees of freedoms device, and the Wave Energy Converters array. Different types of Wave Energy Converters are modeled mathematically, and different optimal controls are developed for them. The objective of the optimal controllers is to maximize the energy extraction with and without the motion and control constraints. The development of the unconstrained control is first introduced which includes the implementation of the Singular Arc control and the Simple Model Control. The constrained optimal control is then introduced which contains the Shape-based approach, Pseudospectral control, the Linear Quadratic Gaussian optimal control, and the Collective Control. The wave estimation is also discussed since it is required by the controllers. Several estimators are implemented, such as the Kalman Filter, the Extended Kalman Filter, and the Kalman-Consensus Filter. They can be applied for estimating the system states and the wave excitation force/wave excitation force field. Last, the controllers are validated with the Discrete Displacement Hydraulic system which is the Power Take-off unit of the Wave Energy Converter. The simulation results show that the proposed optimal controllers can maximize the energy absorption when the wave estimation is accurate. The performance of the unconstrained controllers is close to the theoretical maximum (Complex Conjugate Control). Furthermore, the energy extraction is optimized and the constraints are satisfied by applying the constrained controllers. However, when the proposed controllers are further validated with the hydraulic system, they extract less energy than a simple Proportional-derivative control. This indicates the dynamics of the Power take-off unit needs to be considered in designing the control to obtain the robustness

Advances in Intelligent Vehicle Control

This book is a printed edition of the Special Issue Advances in Intelligent Vehicle Control that was published in the journal Sensors. It presents a collection of eleven papers that covers a range of topics, such as the development of intelligent control algorithms for active safety systems, smart sensors, and intelligent and efficient driving. The contributions presented in these papers can serve as useful tools for researchers who are interested in new vehicle technology and in the improvement of vehicle control systems

Model-Based Robot Control and Multiprocessor Implementation

Model-based control of robot manipulators has been gaining momentum in recent years. Unfortunately there are very few experimental validations to accompany simulation results and as such majority of conclusions drawn lack the credibility associated with the real control implementation

Modeling and Control of a Multibody Hinge-BargeWave Energy Converter

Wave Energy Converters (WECs) are devices used to extract energy from the waves. The particular WEC considered in this thesis is a three-body hinge-barge WEC, which is an articulated floating structure composed of 3 rectangular bodies interconnected by hinges, and it operates longitudinally to the direction to the incoming wave. The relative motion between each pair of bodies drives a Power Take-Off (PTO) system, which extracts the energy from the waves. The objective of this thesis is to increase the energy that can be extracted by a three-body hinge-barge WEC using an optimal control strategy, which computes the optimal loads applied by the PTOs driven by the relative motion between the bodies. The optimal control is formulated in the time domain, and computes the PTO loads in a coordinated way, so that the total energy extracted by the device is maximized. The optimal control strategy is formulated for a three-body hinge-barge WEC that is equipped with either passive or active PTOs. In this thesis, an optimal control strategy, for the maximization of the energy extracted by a three-body hinge-barge WEC, is derived with Pseudo-Spectral (PS) methods, which are a subset of the class of techniques used for the discretisation of integral and partial differential equations known as mean weighted residuals. In particular, PS methods based on Fourier basis functions, are used to derive an optimal control strategy, for a finite time horizon. Therefore, an optimal control strategy, with PS methods based on Fourier basis functions, cannot be applied for realtime control of the WEC, as Fourier basis functions can only represent the steady-state response of the WEC. However, PS methods based on Fourier basis functions provide a useful framework for the evaluation of the achievable power absorption performance of the WEC, with both active and passive PTOs. The Receding Horizon (RH) real-time optimal control of a three-body hingebarge WEC is derived with PS methods based on Half-Range Chebyshev-Fourier (HRCF) basis functions. The RH optimal real-time controller, with PS methods based on HRCF basis functions, maximizes the energy extracted by the WEC at each time step over a moving control horizon. In contrast to Fourier basis functions, HRCF basis functions are well suited for the approximation of non-periodic signals, allowing the representation of both the transient and steady-state response of the WEC. The optimal control strategy, with PS methods based on either Fourier or HRCF basis functions, is based on a dynamic model of the device, which is derived with two different modeling methodologies, that can be also applied to other types of multiple body WECs. The modeling methodologies are validated against wave-tank tests carried out on a 1/7th scale two-body hingebarge device, and a 1/25th and 1/20th scale three-body hinge-barge device