Development and evaluation of methods for control and modelling of multiple-input multiple-output systems

In control, a common type of system is the multiple-input multiple-output (MIMO) system, where the same input may affect multiple outputs, or conversely, the same output is affected by multiple inputs. In this thesis two methods for controlling MIMO systems are examined, namely linear quadratic Gaussian (LQG) control and decentralized control, and some of the difficulties associated with them.One difficulty when implementing decentralized control is to decide which inputs should control which outputs, also called the input-output pairing problem. There are multiple ways to solve this problem, among them using gramian based measures, which include the Hankel interaction index array, the participation matrix and the Σ2 method.\ua0 These methods take into account system dynamics as opposed to many other methods which only consider the steady-state system. However, the gramian based methods have issues with input and output scaling. Generally, this is handled by scaling all inputs and outputs to have equal range. However, in this thesis it is demonstrated how this can cause an incorrect pairing. Furthermore, this thesis examines other methods of scaling the gramian based measures, using either row or column sums, or by utilizing the Sinkhorn-Knopp algorithm. It is shown that there are considerable benefits to be gained from the alternative scaling of the gramian based measures, especially when using the Sinkhorn-Knopp algorithm. The use of this method also has the advantage that the results are completely independent of the original scaling of the inputs and outputs.An expansion to the decentralized control structure is the sparse control, in which a decentralized controller is expanded to include feed-forward or MIMO blocks. In this thesis we explore how to best use the gramian based measures to find sparse control structures, and propose a method which demonstrates considerable improvement compared to existing methods of sparse control structure design.A prerequisite to implementing control configuration methods is an understanding of the processes in question. In this thesis we examine the pulp refining process and design both static and dynamic models for pulp and paper properties such as shives width, fiber length and tensile index, and various available inputs. We demonstrate that utilizing internal variables (primarily consistencies) estimated from temperature measurements yields improved results compared to using solely measured variables. The measurement data from the refiners is noisy, sometimes sparse and generally irregularly sampled. This thesis discusses the challenges posed by these constraints and how they can be resolved.\ua0\ua0 An alternative way to control a MIMO system is to implement an LQG controller, which yields a single control structure for the entire system using a state based controller. It has been proposed that LQG control can be an effective control scheme to be used on networked control systems with wireless channels. These channels have a tendency to be unreliable with packet delays and packet losses. This thesis examines how to implement an LQG controller over such unreliable communication channels, and derives the optimal controller minimizing the cost function expressed in actuated controls.When new methods of control system design and analysis are introduced in the control engineering field, it is important to compare the new results with existing methods. Often this requires application of the methods on examples, and for this purpose benchmark processes are introduced. However, in many areas of control engineering research the number of examples are relatively few, in particular when MIMO systems are considered. For a thorough assessment of a method, however, as large number of relevant models as possible should be used. As a remedy, a framework has been developed for generating linear MIMO models based on predefined system properties, such as model type, size, stability, time constants, delays etc. This MIMO generator, which is presented in this thesis, is demonstrated by using it to evaluate the previously described scaling methods for the gramian based pairing methods

Web Browser Based Ladder-Editor

The goal for this master thesis is the creation of a graphical ladder-editor in JavaScript and HTML5. The editor is made in such a manner that the user inserts blocks by selecting them from a menu. Then the block is inserted simply by them clicking where the block should be inserted. The editor itself should handle the required lines. The editor also contains a menu with custom made buttons which allows the user to easily browse through the different possibilities and options. Most common ladder blocks are included in the editor, and it is easy to add more if desired. Furthermore, the editor described here contains the possibility for the user to delete the blocks added and it also contains undo and redo functionality. Menus have been designed and implemented that allows the user to change the attributes of the contacts, coils and function blocks that he or she has inserted. There is also the possibility to copy a block from one part of the system and insert it somewhere else. The system that the user edits graphically using the editor is described in code using the Json format. This in turn allows the program the user is working on to be saved and loaded. This is also implemented, in this case by establishing communication with B&Rs program Automation Studios which then handles the saving and loading from and to file

Stochastic optimal control over unreliable communication links

In this paper LQG control over unreliable communication links is derived. That is to say, the communication channels between the controller and the actuators and between the sensors and the controller are unreliable. This is of growing importance as networked control systems and use of wireless communication in control are becoming increasingly common. The problem of how to optimize LQG control in this case is examined in the situation where communication between the components is done with acknowledgments. Previous solutions to finite horizon discrete time hold-input LQG control for this case do not fully utilize the available information. Here a new solution is presented which resolves this limitation. The solution is linear and covers communication channels subject to both packet losses and delays. The new control scheme is compared with previous solutions for LQG control in simulations, which demonstrates that a significant improvement in the cost can be achieved by fully utilizing the available information

Finding feedforward configurations using gramian based interaction measures

A sparse control structure can be seen as a decentralised controller that is expanded to include feedforward or MIMO blocks. Here, use of the gramian based interaction measures to determine a sparse control structure with feedforward is examined. A modification to the method used today is proposed and it is demonstrated that it results in a considerable improvement. Furthermore, recently proposed modifications to scaling gramian based measures are expanded to also cover sparse control structures. We show that the method that yields the best result is when two different scaling methods are combined, using one to design a decentralized controller and another to find feedforward connections

ANT-Maps: Visualising Perspectives of Business and Information Systems

In the IS-literature, graphical representations often accompany Actor-Network Theory (ANT) analyses of IS-initiatives, serving as tools for improving visibility of the case and interest and power of actors. Building on a comprehensive literature survey, we identify a gap in existing visualisation approaches, as these mainly focus on offering visual support of the case. We present a visualisation approach and a generic, precise and well defined notation that is directly mapped to key concepts of ANT, highlighting the process of translating actors to commit to the implementation initiative. The approach is illustrated by an actor-network analysis of a particular IS-initiative in a Swedish media organisation

Stimulation within the cuneate nucleus suppresses synaptic activation of climbing fibers.

Several lines of research have shown that the excitability of the inferior olive is suppressed during different phases of movement. A number of different structures like the cerebral cortex, the red nucleus, and the cerebellum have been suggested as candidate structures for mediating this gating. The inhibition of the responses of the inferior olivary neurons from the red nucleus has been studied extensively and anatomical studies have found specific areas within the cuneate nucleus to be target areas for projections from the magnocellular red nucleus. In addition, GABA-ergic cells projecting from the cuneate nucleus to the inferior olive have been found. We therefore tested if direct stimulation of the cuneate nucleus had inhibitory effects on a climbing fiber field response, evoked by electrical stimulation of the pyramidal tract, recorded on the surface of the cerebellum. When the pyramidal tract stimulation was preceded by weak electrical stimulation (5-20 μA) within the cuneate nucleus, the amplitude of the climbing fiber field potential was strongly suppressed (approx. 90% reduction). The time course of this suppression was similar to that found after red nucleus stimulation, with a peak suppression occurring at 70 ms after the cuneate stimulation. Application of CNQX (6-cyano-7-nitroquinoxaline-2,3-dione, disodium salt) on the cuneate nucleus blocked the suppression almost completely. We conclude that a relay through the cuneate nucleus is a possible pathway for movement-related suppression of climbing fiber excitability

UE Antenna Properties and Their Influence on Massive MIMO System Performance

The use of large-scale antenna arrays can bring substantial improvements both in energy and spectral efficiency. This paper presents an initial study of user equipment (UE) antenna performance based on prototypes for a massive MIMO test bed. Most publications in the massive MIMO area have assumed isotropic or dipole antenna behavior at the UE side. It is, however, of greatest interest to evaluate the impact of realistic antenna implementations and user loading on such systems. Antennas are integrated into realistic UE form factors. Simulations are carried out to evaluate system performance using the UE antenna behavior measured in a Satimo StarGate 64. Comparisons are made with ideal isotropic un-correlated antennas. The presented UEs are designed for the 3.7 GHz band used by the LuMaMi massive MIMO test bed at Lund University

Development and evaluation of methods for control of multiple-input multiple output systems

In control, the most common type of system is the multiple-input multiple-output(MIMO) system, where the same input may affect multiple outputs, orconversely, the same output is affected by multiple inputs. In thisthesis two methods for controlling MIMO systems are examined, namelylinear quadratic Gaussian (LQG) control and decentralized control,and some of the difficulties associated with them. One difficulty when implementing decentralized control is to decidewhich inputs should control which outputs, that is the input-outputpairing problem. There are multiple ways to solve this problem, amongthem using gramian based measures, which include the Hankel interactionindex array, the participation matrix and the Sigma2 method.These methods take into account system dynamics as opposed to manyother methods which only consider the steady-state system. However,the gramian based methods have issues with input and output scaling.Generally, this is resolved by scaling all inputs and outputs to haveequal range. However, in this thesis it is demonstrated how this canresult in an incorrect pairing. Furthermore this thesis examines othermethods of scaling the gramian based measures, using either row orcolumn sums, or by utilizing the Sinkhorn-Knopp algorithm. This thesisshows that there are considerable benefits to be gained from the alternativescaling of the gramian based measures, especially when using the Sinkhorn-Knoppalgorithm. The use of this method also has the advantage that theresults are completely independent of the original scaling of theinputs and outputs.An alternative way to control a MIMO system is to implement an LQGcontroller, which yields a single control structure for the entiresystem using a state based controller. It has been proposed that LQGcontrol can be an effective control scheme to be used on networkedcontrol systems with wireless channels. These channels have a tendencyto be unreliable with package delays and package losses. This licentiatethesis examines how to implement an LQG controller over such unreliablecommunication channels, and proposes an optimal controller which minimizesthe cost function.When new methods of control system design and analysis are introducedin the control engineering field, it is important to compare the newresults with existing methods. Often this requires application ofthe methods on examples, and for this purpose benchmark processesare introduced. However, in many areas of control engineering researchthe number of examples are relatively few, in particular when MIMOsystems are considered. For a thorough assessment of a method, however,as large number of relevant models as possible should be used. Asa remedy, a framework has been developed for generating linear MIMOmodels based on predefined system properties, such as model type,size, stability, time constants, delays etc. This MIMO generator,which is presented in this thesis, is demonstrated by using it toevaluate the previously described scaling methods for the gramianbased pairing methods