This thesis contains two main parts. The first part presents a database compiling 137 landslide-triggering earthquakes (LTEs) worldwide, with magnitudes greater than the minimum observed threshold for causing landslides (M4.5), for the period of 1998 -2009. Our data sources include a comprehensive review of the existing literature on earthquake-triggered landslides (ETLs), and also a USGS-based earthquake catalog (PAGER-CAT) that contains information on earthquake-triggered secondary events. Only 14 earthquakes out of the 137 seismic events induced significant numbers of landslides (>250). We compared the number of ETLs with the total number of earthquakes with M ≥ 4.5 (n=68,734) during the same period of time. The results show that only 0.2 % of ETLs and only 4.5% of earthquakes of M > 6 resulted in landslide. In addition, we compiled a database of 37 large-scale landslides, involving initial failure volumes of greater than 20 Mm3 that occurred worldwide between 1900 to 2010. The database contains large-scale earthquake-triggered (n ETLs=18) and non-earthquake-triggered landslides (n NETLs=20), i.e., ca. 50% of large-scale landslides were induced by seismic activity. Surprisingly, the volume-temporal frequency curves of ETLs and NETLs show almost identical slopes and intercepts. Thus, for a given volume, the annual frequency of ETLs is almost identical to that of NETLs in the 110 year period. In contrast to previous studies, this thesis found that the volume of the largest landslide triggered by a given landslide-triggering earthquake is not a function of earthquake magnitude. Peak ground motions (PGA, PGV, and PSA) were calculated for the 18 large-scale ETLs at the site of each occurrence and the resulting values show a correlation with the volume of landslides below the threshold of ca. 80 Mm3. Above this threshold, the relationship between peak ground motions and ETL volume shows complex and nonlinear behavior. The results suggest that 1) other special conditions are required for significant earthquake-triggered landslides to occur, and 2) that very large earthquake-triggered landslides (volume greater than 80 Mm3) result from complex progressive failure mechanisms initiated by seismic shaking (i.e., above this threshold volume, landslide volume is independent of PGA, PGV, and PSA). A detailed analysis of the two 1985 Nahanni earthquakes and the North Nahanni rockslide triggered by the first main shock is carried out in the second part of the study. The North Nahanni rockslide, Northwest Territories, Canada was triggered by the earthquake of M=6.6 on October 5th, 1985. The slide occurred in a Palaeozoic carbonate sequence along a thrust fault, which partly follows bedding and partly cuts across bedding. The sliding surface within the limestone consisted of two planes; the lower plane dipped at 20° while the upper plane dipped at 35°. Slope stability analysis is performed using discontinuum numerical modeling. Static slope stability analyses indicate that the sliding rock was marginally safe for the sliding surface friction angles of 24o or higher. Dynamic analyses of the co-seismic movements are conducted by applying a series of sinusoidal waves to the base of the model. The amplitudes of the October earthquake's seismic waves are estimated using strong motion data available from the second main shock. The results, from the dynamic analysis indicate that the slope becomes unstable for given seismic inputs at a specific range of friction angles (24o to 30o) for the sliding surface and the deformation behavior of the North Nahanni rock masses is dependent on the frequency of the seismic signals. Because the static slope stability analysis showed that the slope was close to instability prior to the seismic shaking, we suggest that the 1985 Nahanni earthquake operated as a trigger event that accelerated the occurrence of the slide. This finding supports our earlier results of the global scale study, which showed that the triggering event does not change the general trend of the frequency-volume distribution of landslides; however, it can accelerate the occurrence of slope failure.

Stochastic model predictive control (MPC) is a fascinating field for research and of increasing practical importance since optimal control techniques have been intensively investigated in modern control system design. With the development of computer technologies and communication networks, networked control systems (NCSs) or cyber-physical systems (CPSs) have become an interest of research due to the comprehensive integration of physical systems, such as sensors, actuators and plants, with intricate cyber components, possessing information communication and computation. In CPSs, advantages of low installation cost, high reliability, flexible modularity, improved efficiency, and greater autonomy can be obtained by the tight coordination of physical and cyber components. Several sectors, including robotics, transportation, health care, smart buildings, and smart grid, have witnessed the successful application of CPSs design. The integration of extensive cyber capability and physical plants with ubiquitous uncertainties also introduces concerns over communication efficiency, robustness and stability of the CPSs. Thus, to achieve satisfactory performance metrics of efficiency, robustness and stability, a detailed investigation into control synthesis of CPSs under the stochastic model predictive control framework is of importance. The stochastic model predictive control synthesis plays a vital role in CPSs design since the multivariable stochastic system subject to probabilistic constraints can be controlled in an optimized way. On the other hand, aperiodically sampled, or event-based, model predictive control has also been applied to CPSs extensively to improve communication efficiency. In this thesis, the control synthesis and analysis of aperiodically sampled stochastic model predictive control for CPSs is considered. Chapter 1 provides an introductory literature review of the current development of stochastic MPC, distributed stochastic MPC and event-based MPC. Chapter 2 presents a stochastic self-triggered model predictive control scheme for linear systems with additive uncertainty and with the states and inputs being subject to chance constraints. In the proposed control scheme, the succeeding sampling time instant and current control inputs are computed online by solving a formulated optimization problem. Chapter 3 discusses a stochastic self-triggered model predictive control algorithm with an adaptive prediction horizon. The communication cost is explicitly considered by adding a damping factor in the cost function. Sufficient conditions are provided to guarantee closed-loop chance constraints satisfactions. Furthermore, the recursive feasibility of the algorithm is analyzed, and the closed-loop system is shown to be stable. Chapter 4 proposes a distributed self-triggered stochastic MPC control scheme for CPSs under coupled chance constraints and additive disturbances. Based on the assumptions on stochastic disturbances, both local and coupled probabilistic constraints are transformed into the deterministic form using the tube-based method, and improved terminal constraints are constructed to guarantee the recursive feasibility of the control scheme. Theoretical analysis has shown that the overall closed-loop CPSs are quadratically stable. Numerical examples illustrate the efficacy of the proposed control method in terms of data transmission reductions. Chapter 5 concludes the thesis and suggests some promising directions for future research. / Graduate / 2022-01-15

The feedback control system is defined as the sampling of an output signal and feeding it back to the input, resulting in an error signal that drives the overall system. This dissertation focuses on the stabilization and performance of state feedback control systems. Chapters 3 and 4 focus on the feedback control protocol approaching in the multi-agents system. In particular, the global regulation of distributed optimization problems has been considered. Firstly, we propose a distributed optimization algorithm based on the proportional-integral control strategy and the exponential convergence rate has been delivered. Moreover, a decentralized mechanism has been equipped to the proposed optimization algorithm, which enables an arbitrarily chosen agent in the system can compute the value of the optimal solution by only using the successive local states. After this, we consider the cost function follows the restricted secant inequality. A dynamic event-triggered mechanism design has been proposed. By ensuring the global regulation of the distributed proportional-integral optimization algorithm, the dynamic event-triggered mechanism efficiently reduces the communication frequency among agents. Chapter 5 focuses on the feedback control protocol approaching the single-agent system. Specifically, we investigate the truncated predictor feedback control of the regulation of linear input-delayed systems. For the purpose of improving the closed-loop performance, we propose a design of the truncated predictor feedback method with time-varying feedback parameters and give the potential range of choosing the time-varying feedback parameters to replace the traditional constant low gain parameters.

Yes / Advanced drug delivery systems, such as ultrasound-mediated drug delivery, show great promise for increasing the therapeutic index. Improvements in delivery by altering the ultrasound parameters have been studied heavily in vitro but relatively little in vivo. Here, the same therapeutic microbubble and tumour type are used to determine whether altering ultrasound parameters can improve drug delivery. Liposomes were loaded with SN38 and attached via avidin: biotin linkages to microbubbles. The whole structure was targeted to the tumour vasculature by the addition of anti-vascular endothelial growth factor receptor 2 antibodies. Tumour drug delivery and metabolism were quantified in SW480 xenografts after application of an ultrasound trigger to the tumour region. Increasing the trigger duration from 5 s to 2 min or increasing the number of 5 s triggers did not improve drug delivery, nor did changing to a chirp trigger designed to stimulate a greater proportion of the microbubble population, although this did show that the short tone trigger resulted in greater release of free SN38. Examination of ultrasound triggers in vivo to improve drug delivery is justified as there are multiple mechanisms at play that may not allow direct translation from in vitro findings. In this setting, a short tone burst gives the best ultrasound parameters for tumoural drug delivery. / This research was funded by the EPSRC (EP/I000623/1, EP/L504993/1 and EP/P023266/1). S.D.E. is supported by the National Institute for Health Research infrastructure at Leeds. J.R.M. is supported by an EPSRC UKRI Innovation Fellowship (EP/S001069/1).

Networked control systems, commonly employed in domains such as space exploration and robotics utilize network communication for efficient and coordinated control among distributed components. In these scenarios, effectively managing communication to prevent network overload poses a critical challenge. Previous research has explored the use of reinforcement learning methods combined with event-triggered control to autonomously have agents learn efficient policies for control and communication. Nevertheless, these approaches have encountered limitations in terms of performance and scalability when applied in multiagent scenarios. This thesis examines the underlying causes of these challenges and propose potential solutions. With the findings suggesting that training agents in a decentralized manner, coupled with modeling of the missing communication, can improve agent performance. This allows the agents to achieve performance levels comparable to those of agents trained with full communication, while reducing unnecessary communication

In modern cyber-physical systems (CPSs) where the control signals are generally transmitted via shared communication networks, there is a desire to balance the closed-loop control performance with the communication cost necessary to achieve it. In this context, aperiodic real-time scheduling of control tasks comes into being and has received increasing attention recently. It is well known that model predictive control (MPC) is currently widely utilized in industrial control systems and has greatly increased profits in comparison with the proportional integral-derivative (PID) control. As communication and networks play more and more important roles in modern society, there is a great trend to upgrade and transform traditional industrial systems into CPSs, which naturally requires extending conventional MPC to communication-efficient MPC to save network resources. Motivated by this fact, we in this thesis propose robust MPC and scheduling co-design algorithms to networked CPSs possibly affected by both parameter uncertainties and additive disturbances. In Chapter 2, a dynamic event-triggered robust tube-based MPC for constrained linear systems with additive disturbances is developed, where a time-varying pre-stabilizing gain is obtained by interpolating multiple static state feedbacks and the interpolating coefficient is determined via optimization at the time instants when the MPC-based control is triggered. The original constraints are properly tightened to achieve robust constraint optimization and a sequence of dynamic sets used to test events are derived according to the optimized coefficient. We theoretically show that the proposed algorithm is recursively feasible and the closed-loop system is input-to-state stable (ISS) in the attraction region. Numerical results are presented to verify the design. In Chapter 3, a self-triggered min-max MPC strategy is developed for constrained nonlinear systems subject to both parametric uncertainties and additive disturbances, where the robust constraint satisfaction is achieved by considering the worst case of all possible uncertainty realizations. First, we propose a new cost function that relaxes the penalty on the system state in a time period where the controller will not be invoked. With this cost function, the next triggering time instant can be obtained at current time instant by solving a min-max optimization problem where the maximum triggering period becomes a decision variable. The proposed strategy is proved to be input-to-state practical stable (ISpS) in the attraction region at triggering time instants under some standard assumptions. Extensions are made to linear systems with additive disturbances, for which the conditions reduce to a linear matrix inequality (LMI). Comprehensive numerical experiments are performed to verify the correctness of the theoretical results. / Graduate

<p>Day by day, we are witnessing a considerable increase in number and range of applications which entail the use of embedded computer systems. This increase is closely followed by the growth in complexity of applications controlled by embedded systems, often involving strict timing requirements, like in the case of safety-critical applications. Efficient design of such complex systems requires powerful and accurate tools that support the designer from the early phases of the design process.</p><p>This thesis focuses on the study of real-time distributed embedded systems and, in particular, we concentrate on a certain aspect of their real-time behavior and implementation: the time-triggered (TT) and event-triggered (ET) nature of the applications and of the communication protocols. Over the years, TT and ET systems have been usually considered independently, assuming that an application was entirely ET or TT. However, nowadays, the growing complexity of current applications has generated the need for intermixing TT and ET functionality. Such a development has led us to the identification of several interesting problems that are approached in this thesis. First, we focus on the elaboration of a holistic schedulability analysis for heterogeneous TT/ET task sets which interact according to a communication protocol based on both static and dynamic messages. Second, we use the holistic schedulability analysis in order to guide decisions during the design process. We propose a design optimisation heuristic that partitions the task-set and the messages into the TT and ET domains, maps and schedules the partitioned functionality, and optimises the communication protocol parameters. Experiments have been carried out in order to measure the efficiency of the proposed techniques.</p> / Report code: LiU-Tek-Lic-2003:21.

Networked control over wireless sensor and actuator systems is of growing importancein many application domains. Energy and communication bandwidth are scarce resources in such systems. Despite that feedback control might only be needed occasionally, sensor and actuator communications are often periodic and with high frequency in today’s implementations. In this thesis, resource-constrained wireless networked control systems with an adaptive sampling period are considered. Our first contribution is a system architecture for aperiodic wireless networked control. As the underlying data transmission is performed over a shared wireless network, we identify scheduling policies and medium access controls that allow for an efficient implementation of sensor communication. We experimentally validate three proposed mechanisms and show that best performance is obtained by a hybrid scheme, combining the advantages of event- and self-triggered control as well as the possibilities provided by contention-based and contention-free medium accesscontrol. In the second contribution, we propose an event-triggered PI controller for wireless process control systems. A novel triggering mechanism which decides the transmission instants based on an estimate of the control signal is proposed. It addresses some side-effects that have been discovered in previous PI proposals, which trigger on the state of the process. Through simulations we demonstrate that the new PI controller provides setpoint tracking and disturbance rejection close to a periodic PI controller, while reducing the required network resources. The third contribution proposes a co-design of feedback controllers and wireless medium access. The co-design is formulated as a constrained optimization problem, whereby the objective function is the energy consumption of the network and the constraints are the packet loss probability and delay, which are derived from the performance requirements of the control systems. The design framework is illustrated in a numerical example. / QC 20111004

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Day by day, we are witnessing a considerable increase in number and range of applications which entail the use of embedded computer systems. This increase is closely followed by the growth in complexity of applications controlled by embedded systems, often involving strict timing requirements, like in the case of safety-critical applications. Efficient design of such complex systems requires powerful and accurate tools that support the designer from the early phases of the design process. This thesis focuses on the study of real-time distributed embedded systems and, in particular, we concentrate on a certain aspect of their real-time behavior and implementation: the time-triggered (TT) and event-triggered (ET) nature of the applications and of the communication protocols. Over the years, TT and ET systems have been usually considered independently, assuming that an application was entirely ET or TT. However, nowadays, the growing complexity of current applications has generated the need for intermixing TT and ET functionality. Such a development has led us to the identification of several interesting problems that are approached in this thesis. First, we focus on the elaboration of a holistic schedulability analysis for heterogeneous TT/ET task sets which interact according to a communication protocol based on both static and dynamic messages. Second, we use the holistic schedulability analysis in order to guide decisions during the design process. We propose a design optimisation heuristic that partitions the task-set and the messages into the TT and ET domains, maps and schedules the partitioned functionality, and optimises the communication protocol parameters. Experiments have been carried out in order to measure the efficiency of the proposed techniques.