A max-plus algebra predictive approach to a battery assembly system control

This paper is an updated and extended version of the paper "The QR Decomposition and the Singular Value Decomposition in the Symmetrized Max-Plus Algebra" (B. De Schutter and B. De Moor, SIAM J. Matrix Anal. Appl., 19 (1998), pp. 378--406). The max-plus algebra, which has maximization and addition as its basic operations, can be used to describe and analyze certain classes of discrete-event systems, such as flexible manufacturing systems, railway networks, and parallel processor systems. In contrast to conventional algebra and conventional (linear) system theory, the max-plus algebra and the max-plus-algebraic system theory for discrete-event systems are at present far from fully developed, and many fundamental problems still have to be solved. Currently, much research is going on to deal with these problems and to further extend the max-plus algebra and to develop a complete max-plus-algebraic system theory for discrete-event systems. In this paper we address one of the remaining gaps in the max-plus algebra by considering matrix decompositions in the symmetrized max-plus algebra. The symmetrized max-plus algebra is an extension of the max-plus algebra obtained by introducing a max-plus-algebraic analogue of the $-$-operator. We show that we can use well-known linear algebra algorithms to prove the existence of max-plus-algebraic analogues of basic matrix decompositions from linear algebra such as the QR decomposition, the singular value decomposition, the Hessenberg decomposition, the LU decomposition, and so on. These max-plus-algebraic matrix decompositions could play an important role in the max-plus-algebraic system theory for discrete-event systems.

The class of model-based predictive controllers (MBPCs) has been quite successful at overcoming many of the well-known difficulties inherent in nonminimum phase (NMP) systems, e.g., flexible structures, and among the various MBPCs, Unified Predictive Control (UPC) was selected for the control tasks in this paper. Two methods are used to model the tip force of a flexible manipulator. Modal expansion (summation) is a pole but not zero preserving approach, while Infinite Product Expansion preserves both poles and zeros of a system. It is shown that in a flexible structure framework the difference between the exact and modal expansion zeros is significant. The effect of transmission zero mismatch will be observed in a closed loop system, especially when a model based controller is used. Simulation results show that when a UPC is designed based on the modal expansion model, it destabilizes the closed loop system when an exact model is used as the plant. This suggests a severe problem in implementing the designed UPC experimentally. The use of an exact model in a model-based controller design procedure, such as UPC, is therefore suggested. (Author)

Wind power intermittency represents one of the major challenges facing the future growth of grid-connected wind energy projects. The integration of wind turbines and energy storage systems (ESS) provides a viable approach to mitigate the unfavorable impact on grid stability and power quality. In this study, an economic model predictive control (MPC) framework is presented for an integrated wind turbine and flywheel energy storage system (FESS). The control objective is to smooth wind power output and mitigate tower fatigue load. The optimal control problem within the model predictive control framework has been formulated as a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control algorithm is compared to that of a baseline wind turbine controller. The effect of the proposed control actions on the fatigue loads acting on the tower and blades is investigated. The simulation results, with various wind scenarios, showed the ability of the proposed control algorithm to achieve the aforementioned objectives in terms of smoothing output power and mitigating tower fatigue load with negligible effect on the wind energy harvested.

In this paper, a model predictive control (MPC) framework for building energy system setpoint optimization is developed and tested. The performance of the MPC framework is presented in comparison to a baseline case, where a fixed setpoint schedule is used. To simulate the MPC procedure, an EnergyPlus building model is used to represent the actual building that the optimal setpoints are applied to, and a Gaussian process (GP) regression meta-model is used in the MPC procedure that generates the optimal setpoints. The performance outputs that are used for evaluation are total heating, ventilation and air conditioning (HVAC) energy usage and the Fanger predicted mean vote (PMV) thermal comfort measure. The inputs for the GP regression meta-models are selected to be representative of data points that could be obtained by modern supervisory control and data acquisition (SCADA) systems to support data-driven building models. The supervisory MPC framework is capable of reducing the total energy usage with minor adjustments in thermal comfort.

Given the growing number of electronic services and their applications in many existing and evolving domains, such as e-tail and e-medicine, much recent attention has been focused on the collection, maintenance, and dissemination of personal information by electronic service providers (ESPs). Often, information is gathered without the active involvement of the consumers, who may be unaware of the nature of the data collected or the purposes for which these data will be used. Techniques such as cookies generally are implemented on the browsers without permission from the targeted consumer. In this paper, we propose a new framework for information dissemination to ESPs using secure communication of consumer-controlled information via trusted information distribution (TID) services. A TID service gathers information based on consumer consent and consumer-controlled profile then disseminates relevant information to targeted groups of ESPs. Using encryption and a group key management scheme, our communications mechanism securely and discriminately disseminates information to dynamic groups of ESPs that subscribe to the TID service.

In this article, we present a client/server augmented reality (AR) system for viewing complex assembly models on mobile phones. Complex model information is located on a PC which takes care of all of the heavy AR tracking and rendering computation. A camera phone is used as a client to show this information, augmented on still images as animated view. The mobile phone interface also supports correct masking of the assembly pieces as they come together, as well as a graphics only viewing mode intended for better understanding of the assembly process. In addition to describing the mobile augmented assembly system we present results from two pilot user studies evaluating elements of the user interface. INTRODUCTION In order to remain competitive, today’s industry is employing a growing number of product variations with shorter and shorter life cycles, requiring efficient ways to handle the production planning and processing. Assembly line workers face more and more complex tasks and an increasing memory load is posed by the new production needs. Experienced workers may be able to handle several product variants at the same time, but new workers require training and guidance to handle the work tasks. Related activities such as maintenance and repair also require a lot of know-how of complex products. Guidance in assembly tasks is commonly provided by using printed blueprints or other documents. However, these are mainly two dimensional images or text while the real assembly task is three dimensional, making the relationship between parts hard to understand. Computer based technologies have been developed such as electronic guides, multimedia training material and interactive documents. However, these typically require the user to turn away from the assembly task to study a computer screen separate from the workspace. In our research we explore how augmented reality (AR) technology can be used to provide more intuitive guides to assist with assembly, repair and training tasks. With AR technology, synthetic objects can be merged with the user’s view of the real world so that the user can perform the assembly task without needing to look at a separate screen. The virtual objects appear in the correct position so that AR enables the creation of realistic looking 3D animated assembly “manuals”. Other researchers have developed prototype AR systems for supporting assembly tasks. These are typically based on head mounted displays (HMDs) connected to desktop or wearable computers. However, wearable computers are relatively expensive, they have a short battery life, and taking them into a harsh industrial environment is not always possible. Head mounted displays can also be bulky, they involve safety issues, and many workers are reluctant to wear them. To overcome these disadvantages, we are interested in developing a reliable mobile phone based AR assembly system. Today’s mobile phones have fast processors, significant memory, 3D graphics support, and high resolution displays. They contain various accessories that can be used for developing mobile AR applications such as good quality cameras, connectivity by Bluetooth, WLAN and GPRS, and various SAM.700.003.1155

This paper reports an application of an max-plus algebra fault-tolerant control to a system of cubes' packing <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . Such systems belong to the class of discrete event systems for which the evolution of the states depends on the occurrence of events. The essential problem concerns a control of independent, parallel conveyor belts transporting cubes to processing units. The contribution of this paper is a mathematical description of a set of multiple conveyor belts. The proposed solution guarantees cube handling by conveyor belts according to a reference sequence. This sequence is provided by the Manufacturing Execution System (MES). In addition, the proposed approach has to deal with both synchronization (in particular the one based on mutual exclusion mode), concurrency issues as well as faults. Subsequently, all necessary constraints are developed and incorporated within the transportation strategy. As a result, the predictive fault-tolerant control strategy is developed. The final part of the paper exhibits an illustrative example, which shows the performance of the proposed approach.

ABSTRACTIn this paper, a new model predictive control framework is proposed for positive systems subject to input/state constraints and interval/polytopic uncertainty. Instead of traditional quadratic performance index, simple linear performance index, linear Lyapunov function, cone invariant set with linear form and linear computation tool are first adopted. Then, a control law that can handle the constraints and robustly stabilise the systems is proposed. The advantages of the new framework lie in the following facts: (1) an equivalent linear problem is formulated that can be easily solved than other problems including the quadratic ones, (2) simple linear index and linear tool can be used based on the essential property of positive systems to achieve the desired control performance and (3) a general model predictive control law without sign restriction is designed. Finally, an attempt of application on mitigating viral escape is provided to verify the effectiveness of the proposed approach.

Modern challenges of the economy are an adaptation to the changes taking place in the world community. New forms of interaction in human society, transferred to the digital space, are gaining increasing importance. Economic entities must respond fully to the demands of the digital environment. At the same time, the state mustn't reduce its fiscal control over such digital operations. The purpose of the article is to analyze the legislative regulation of taxation of business entities that work in areas related to IT technologies and activities carried out on the Internet. This study covers difficulties and debatable issues arising in the taxation of business entities due to the implementation of digitalization. The authors systematized the features of taxation of the activities of Diya City residents following the current tax legislation of Ukraine. The article contains detailed explanations of which electronic services are subject to VAT and which transactions are not electronic services. The main key points for non-residents and providers of electronic services regarding VAT payment have been systematized. Attention is paid to issues related to the taxation of transactions with cryptocurrency. The authors performed a detailed analysis of the Draft Law of Ukraine “On Amendments to the Code of Criminal Procedure and Some Other Laws of Ukraine Regarding Transactions with Cryptocurrency”, and individual tax consultations of the State Tax Service of Ukraine. It was established that when taxing operations with virtual assets, particularly cryptocurrency, it is necessary to be guided by the norms of the Tax Code of Ukraine. In individual conflicting situations that arise due to various types of operations with cryptocurrency, it is recommended to contact the State Tax Service for individual clarifications.

A novel topology-aware model predictive control (MPC) framework is presented for navigating off-road wheeled vehicles with extreme mobility on 3-D terrains. Prior studies have oversimplified the problem by either treating it solely as a path-planning problem or disregarding the terrain topology. To bridge this gap, this article presents a one-layer model predictive planning and control framework that considers terrain topology for off-road vehicles at operationally relevant speeds. The algorithm is tested in various simulated scenarios with comparisons to benchmarks. The proposed algorithm demonstrates superior performance by capturing the dynamic constraints, while the benchmarks either fail to complete tasks or exhibit inferior performance due to inaccurate representation of the dynamic limitations of the vehicle. Furthermore, the algorithm is tested for robustness to demonstrate its ability to handle uncertainties in terrain topology.

Data-driven nonlinear model predictive control for AUV trajectory tracking under oceanic disturbances.

This paper proposes a model predictive control approach for coordinated secondary voltage control of on-load tap changing transformers and battery energy storage systems in a distribution system to maintain the bus voltage levels in the presence of photovoltaic generation. Optimal control actions are obtained based on a quadratic objective function with linear constraints. The control actions are implemented in a case study using a modified CIGRE European low voltage distribution network with corresponding models of the constituent devices and their local controllers. The results indicate that battery energy storage system could aid the system voltages and reduce the number of transformer tap operations if the control is performed in a coordinated manner enabled by the model predictive control framework.

A novel machine learning-based model predictive control framework for improving the energy efficiency of air-conditioning systems

This work investigates the event‐driven model predictive control problem for perturbed nonlinear systems with input and state constraints. Firstly, a new event‐driven triggering condition, considering the gradient and accumulation of the error between the optimal and actual states at adjacent moments with a state‐dependent relative threshold is designed with a guaranteed positive inter‐event time to avoid Zeno behaviour. Secondly, an error gradient and accumulation type event‐driven model predictive control framework is designed based on the new triggering condition and the dual‐mode strategy, for effectively reducing the calculation and communication burden of the model predictive control controller while ensuring desired control performance. Furthermore, the feasibility and the input‐to‐state practical stability (ISpS) of gradient and accumulation‐type event‐driven model predictive control are rigorously guaranteed theoretically. At last, the simulation results are provided to validate the this algorithm.

Chemtex will build US biofuels plant