This book on complexity science comprises a collection of chapters on methods and principles from a wide variety of disciplinary fields — from physics and chemistry to biology and the social sciences. In this two-part volume, the first part is a collection of chapters introducing different aspects in a coherent fashion, and providing a common basis and the founding principles of the different complexity science approaches; the next provides deeper discussions of the different methods of use in complexity science, with interesting illustrative applications. The fundamental topics deal with self-organization, pattern formation, forecasting uncertainties, synchronization and revolutionary change, self-adapting and self-correcting systems, and complex networks. Examples are taken from biology, chemistry, engineering, epidemiology, robotics, economics, sociology, and neurology.@en

A better understanding in the biological clock is important to help reduce stress on shift workers. Moreover, in the field of medication it will allow for more effective treatments as certain types of medication are more effective when applied at certain moments in the 24-hour cycle. The mammalian biological clock is controlled by a tiny area in the brain called the suprachiasmatic nucleus (SCN). The neurons in the SCN are able to synchronize their clock gene expression to each other through coupling. However, it is unclear how different types of coupling affect the synchronizing property of the SCN. This research explores how two types of coupling, namely gap junction coupling and neuromodulator diffusion shape the synchronous behaviour of a network of SCN neurons. Since data collection in the biological system is challenging, this research is done using a modeling approach. A mathematical single SCN neuron model was used and scaled to a network representation. The individual neuron models were coupled using a gap junction and neuromodulator models. In this research, it was found that gap junction coupling is a precise and strictly local form of coupling. It can synchronize phase errors on the level of action potentials. However in a network there is a maximum number of neurons that can be synchronized, assuming that the number of gap junctions per neuron is limited. Therefore, it was concluded that in large SCN networks gap junction coupling is not able to completely synchronize the network. Neuromodulator coupling is imprecise, slow and global. It can effectively synchronize large phase errors, however, as phase errors become small, neuromodulator coupling loses its synchronizing ability. Therefore, it can only synchronize the daily pattern and cannot synchronize on the level of action potentials. Furthermore, it was shown that neuromodulator diffusion can synchronize SCN networks of arbitrary size.
As a final conclusion, the combination between gap junctions and neuromodulator diffusion is able to synchronize a network completely, perfectly, and rapidly. The neuromodulator component ensures complete synchronization while the gap junctions guarantee perfect synchronization (in the absence of noise). Furthermore, the combination ensures effective synchronization for both small and large phase errors. Therefore, the combination of these two types of coupling is vital in the establishment of network with versatile synchronization properties.

The primary objective of this work is to research and develop a dynamic model and an advanced control strategy for a reversible solid oxide fuel cell in a grid to ensure load tracking whilst maintaining fuel utilisation and temperature dynamics within a safe range. This report presents the successful development of the dynamic model and corresponding controller. To do so, modeling and control are discussed in two separate chapters where model requirements, specifications and conception are presented followed by the control techniques, control objectives and controller synthesis. A RSOFC model has successfully been developed and thoroughly validated against other literature. To do so, a set of fitting parameters has been distilled from literature to create a good overlap with other studies and are combined in a manner that they can be implemented in other work. Steady state dynamics and the transient dynamics have shown a good match to the available literature. Additionally, the model offers useful insights into RSOFC (transient) dynamics with relation to temperature effects, fuel composition and cell support structure, which have not been documented before. At last the RSOFC stack, together with the developed model has been built in a plug-and-play manner that it can be implemented and adjusted by others, to be used in combination with other models. For control an output-feedback adaptive nonlinear model predictive controller has been developed, which is an advanced version of the well established (non)linear model predictive controller. The development of the temperature controller is given wherein the structure of the MPC is presented together with its trajectory, adaptive constraints and tuning variables. After completing the development of the controller, the controller was simulated together with the dynamic model as part of a micro-grid. The simulations were split up into short and long term scenarios and showed satisfactory results as all the set control objectives were achieved.

A relatively new and not rather common technique in construction industry is the use of 3D printers to print architectural structures and buildings. Nowadays, parts of the printed object are build in inside environments, where after the parts have to be transported to their desired location, which is very costly and time consuming. A solution could be to bring the printer to the construction site. However, current printers are not designed to be mobile or to be used directly at construction sites. This is what leads to the topic of this thesis: develop a robust tracking mechanism for the 3D concrete printer nozzle that is able to cope with disturbances that arise when having a mobile printer that is used in outside environments. Current printers have placed a mixing unit next to the construction area, pumping the concrete mixture to the nozzle. In this research, a new design concept is proposed which should displace the whole mixing unit together with the nozzle over the construction area while still ensuring high tracking accuracy of the printing trajectory. This is done by means of a dual staged manipulator. Horizontally spanned cables and an industrial crane account for the coarse displacement, whereas a Stewart-Gough platform accounts for the fine control of the nozzle. Both stages are assumed to be decoupled and by using the Euler-Lagrange approach, two separate models are derived with the corresponding equations of motion. This model is implemented in a fully parametrizable simulation environment in order to test the later developed controllers. Subsequently, a control strategy for the coarse stage is developed. Three control strategies are combined in order to guarantee a robust tracking: robustness by an \hinf controller, anticipation by a feed-forward controller, and slight tracking improvement by additional PI control. The disturbances that are taken into account are: wind, misalignment and support structure deflection. It turned out that the control strategy is able to reject these uncertainties in the simulation. The residuary error is compensated by the fine stage by using a PI control approach. The results show that the Stewart-Gough platform significantly reduces the tracking error to within a range of the desired accuracy. A high accuracy is beneficial for the reliability of the concrete structure and savings on finishing processes.

Objects floating on or near the water surface (e.g. vessels, and floating wind-turbines) suffer from motions induced by waves of varying height, direction, and frequency. This not only causes unpleasantness for passengers and crew of ships but also it limits the accessibility to the offshore platforms. Bosch Rexroth with their partner Barge Master have developed the so-called Motion Compensated Gangway that provides a safe passage for cargo and personnel to offshore structures.
In order to maintain a motionless connection with the offshore structure, once the tip of the gangway is pushed against the offshore structure. The gangway system actively compensates for the sea-induced motion that acts on the vessel.
However, the docking procedure is still manually attained, where accidents may occur due to human error (i.e. insufficient training, loss of concentration). One way to improve the current control scheme is to enable an automated docking scheme.
Accordingly, the main of this project focuses on eliminating the human factor from the control loop, so the overall process is accomplished automatically and more efficiently in terms of safety and performance.
Inspired by how the operator estimates the relative motion between the Gangway and the target (i.e. the offshore platform). In this thesis, a measurement system is proposed to measure this relative motion. This measurement system comprises a vision sensor, force tip measurements, and Motion Reference Unit (MRU). In this thesis, the proposed automated docking scheme is developed around a nonlinear MPC scheme. For the simulation environment and for the MPC scheme employs, a nonlinear model of the gangway system is derived. This model embeds an approximation of the joint-level control loop of the Gangway system. Also, this model comprises the open-chain kinematic model of the Gangway system and the proposed measurement system including a perspective projection model of the vision sensor. Due to modelling the vision sensor as such and the MPC’s capability in handling various constraints, the proposed control scheme enjoys a singularity-free solution.
The proposed control scheme detects and tracks the target in the 2D image plane. To safeguard against visual measurements discontinuity (i.e. cluttering, target outside the field of view), a linear Kalman filter is designed to predict the target position in the image plane.
To gain higher performance, the disturbance anticipatory property in MPC is enabled by forecasting the sea-induced motion. Where a neural network with the NARX topology was designed and trained to acquire a multi-step-ahead prediction model of the induced motion.
Several numerical experiments were carried to evaluate the performance of the proposed control scheme for automated docking. Where for the nominal case scenarios all the control requirements are fulfilled. Also, more extreme scenarios are performed to evaluates the overall performance under plant model mismatch and against various sea-induced motion conditions. Evidently, the proposed control scheme is prone to camera calibrations error.
In terms of the efficiency, the proposed automated docking scheme performs the docking in 4 to 10 seconds (based on the initial conditions and sea state). Whereas the time it takes the operator to perform the docking is up to 3 minutes which depends on his/her experience.

Correction techniques, such as tangential iterative projections (TIP), were developed to reconstruct the image for the whole field of view. However, due to the three dimensional nature of biological tissues, induced aberrations are different throughout the field of view. This Master of Science thesis shows the development of four algorithms. These algorithms apply TIP to deconvolve images locally. Thereafter, the local results are combined in order to restore images from anisoplanatic aberrations. The difference between the the algorithms developed during this research is the complexity in the spatial domain and in the Fourier domain. It was found that adaptive limited support in the spatial domain increases the im- age quality of the estimated object. A novel approach for multi-frame deconvolution in the Fourier domain has shown to be a promising modification. The use of weighted multi-frame deconvolution in the Fourier domain has lead to improved image quality.

The world of molecular biology is composed by a complex network of interactions that are analogous to electric circuits. They govern the functions required for life, from metabolism to locomotion. In these networks, the presence of network motifs were identified, recurring elements supposedly kept by evolution. One of them is called the feedforward loop and has the function of a sign-sensitive delay element or noise-filter. Moreover, different combinations of several types of feedforward loops were identified in the transcription networks of Escherichia coli and Saccharomyces cerevisiae, called complex feedforward loops. From this finding a question arises: do different types of combined feedforward loops have a specific function? Would this identified function be useful in synthetic biology applications? Answering these questions is the ultimate goal of a research direction in systems biology, studied at the Institute of Complex Molecular Systems at Eindhoven University of Technology. However, biological experiments are difficult to setup and conduct in a suitable manner to generate relevant results. Therefore, it would be highly effective to be able to predict the nonlinear dynamical behaviour of these (combined) feedforward loops. Nevertheless, in order to be able to achieve this, first a single feedforward loop must be fully modelled, calibrated and analysed. This master thesis focuses on this goal and is composed of three main elements: modelling, parameter estimation and structural analysis. The modelling section comprises of the methodology derived in order to transpose the biochemical reactions into equations and perform model reduction on the feedforward loop built at the ICMS. Then, a hybrid parameter estimation method was applied successfully and made it possible to perform numerical simulations of the system. Lastly, the focus was directed to structural analysis and obtaining insights about the behaviour of the network without knowledge of the parameters. This included the adaptation of metabolic network analysis tools, elementary flux mode analysis and flux balance analysis to be used on gene expression networks. As a result, it was possible to link the nonlinearity of the steady-states observed in the experimental data with the accumulation of certain compounds.

Proton therapy is an increasingly popular form of radiotherapy that uses high energy protons for the treatment of cancer. It results in a lower integral dose than the classical photon radiotherapy. This makes it suitable for the treatment of tumors close to critical organs such as in the head and neck. To minimize alignment errors the head and neck are immobilized during treatment. Current immobilization methods are uncomfortable and unable to correct local misalignments between the head and the body. Therefore, an adaptive immobilization device is designed that can correct the local misalignments of the head and neck.

A challenging task in synchronization of multi-agent systems is steering the network towards a coherent solution when the dynamics of the constituent systems are heterogeneous and residing in a possibly large uncertainty set. In this situation, synchronization can be achieved via adaptive protocols (with adaptive feedback gains, or adaptive coupling gains, or both). However, as state-of-the-art synchronization methods adopt a distributed observer architecture, they require to communicate extra local observer variables among neighbors, in addition to the neighbors' states (or outputs). The distinguishing feature of this work is to show that synchronization in heterogeneous and uncertain multi-agent systems is possible without the need for any distributed observer. This can be achieved by designing adaptive distributed synchronization protocols, based on homogenization reasoning. Specifically, ideal gains are defined (feedback and coupling gains) that could lead all the heterogeneous agents to a desired homogeneous behavior and thus synchronization. However, since these gains are unknown in view of the unknown dynamics, we design adaptive laws for these gains that lead the agents toward synchronization. In this thesis, different control protocols are designed to address both leaderless and leader-follower synchronization of linear multi-agent systems. The protocols are then extended to achieve synchronization over a special class of nonlinear multi-agent systems, whose units are modeled as Kuramoto-like systems. Throughout this work, convergence of the synchronization error to zero is shown via Lyapunov analysis, and numerical examples demonstrate the effectiveness of the proposed protocols.

The ZeBRo (Dutch abbreviation: Zesbenige Robot, six-legged robot), is a walking robot designed by the TU Delft, with its foundations on the RHex. The current version of the ZeBRo project, the DeciZebro, is made for the research to swarming in robotics, and is about the size of an A4-paper.
To counter these shortcomings of CPG (a method to determine gait movement), Max-Plus algebra can be used for the timing of the legs of walking robots. This can be done by modeling a walking cycle as two discrete events. These events are the times of the lift-off and touchdown and can be determined by using a Max-Plus Discrete Event System (DES) framework. The main purpose of these events is to determine two separate periods; the stance period, and the swing or flight period.
Max-Plus algebra is defined as a semi-ring over the union of real numbers and minus infinity. The standard binary operations are taking the maximum and addition which can be used for scalar and matrix operations.
The Max-Plus linear system contain the gait matrix A, and the vector v(k) containing the lift-off and touchdown times of vector instance k. One of the strengths of this method is the ability to change gaits, by simply changing the A-matrix. This then results in the switching Max-Plus linear (SMPL) system:
This SPML system determined in only contains gaits with successive recirculating leg-groups, where the synchronization of the lift-off of a certain leg-group I relies on the touchdown of the leg-group i-1. This allows for gaits like walking for humans, or a slow trot for horses, where a leg-group remains on the ground until the previous leg-group has recirculated.
To increase the number of possible gaits, the synchronization of successive leg-groups is extended to not only contain the previous leg-groups' touchdown times, but also their lift-off times. This extension allows for gaits containing multiple rotation leg-groups at the same time, making gaits like the gallop possible. Because of the desired stable situation of grounded legs, the synchronization is chosen to not extend the timing of the touchdown, as delays should not hinder the return of the legs to their grounded position.
The performance of different gaits is tested on different surfaces, to determine the influence of the amount of legs on the ground and determining whether gait changes could influence the success rate of the system regarding traversing rough terrain. Inertia measurement units (IMU) are used for detecting rough terrain, and tests show that the body movement of a ZeBRo on both flat and rough terrain are heavily influenced by the gaits used.
Because of several limitations regarding the actuation of the legs, gaits containing moments of static instability could not be tested. However, the framework for implementation regarding the Max-Plus is lain and tested using simulations.

Because of the increasing e-commerce volume, resulting in increasing demands on the speed of delivery, logistical processes become more and more automated. Order picking is one of the last tasks that is done by humans in warehouses, because humans are flexible with respect to the large variability and changeability in items. However, it is a labour intensive and monotonous task, resulting in fatigue and a shortage of order picking personnel. This motivates the development of automated pick-and-place systems.
One of the challenges for such systems is the heterogeneity of items. In warehouses there is a big diversity in items so the system has to be able to deal with all of them. Another challenge is dealing with items that are deformable. Current systems often make use of suction cups but integrating sensors that can be used to handle deformable items is hard. Fingered robotic grippers have more potential in grasping these kind of items, but grasping deformable items is one of the least addressed topics in robotics. Therefore, the objective of this thesis is to design a control strategy for a fingered robotic gripper to grasp and hold deformable items in a pick-and-place task.
Inspired by the underlying principles that humans use to execute a pick-and-place task, a multi-level controller is proposed for a three-fingered gripper with capacitive pressure pads. The multi-level controller consists of a low-level computed torque controller and a high-level numerical optimisation based extremum seeking controller. The computed torque controller uses an internal model of the kinematics and dynamics, which is derived with screw theory, to compute the torques required to comply with the fundamental grasping constraint and the setpoint on the gripping force. The controller is tuned in such a way that the grasp quality is maximised, given a constant reference gripping force. Because of the fact that the properties of the items are unknown, an intelligent control system has to be able to determine the gripping force setpoint autonomously. This is the task of the high-level controller, that uses tactile sensors to derive the slip. This slip is used to determine the setpoint on the gripping force that the low-level controller has to follow, while maximising the grasp quality and not damaging the products as a result of applying excessive gripping force.
The proposed control strategy is tested and tuned in a simulation environment. The pick-and-place task is executed for the products from a virtual product inventory. The controller is optimised with respect to the control goal on a wide variety of deformable items. Designing controllers according to the proposed principle will increase the diversity of items that can be handled in a pick-and-place environment, while increasing the quality of the grasp and minimising the risk of damaged products.