Asynchronous networked MPC with ISM for uncertain nonlinear systems

A model-based event-triggered control scheme for nonlinear constrained continuous-time uncertain systems in networked configuration is presented in this paper. It is based on the combined use of Model Predictive Control (MPC) and Integral Sliding Mode (ISM) control, and it is oriented to reduce the packets transmission over the network both in the direct path and in the feedback path, in order to avoid network congestion. The key elements of the proposed control scheme are the ISM local control law, the MPC remote controller, a smart sensor and a smart actuator, both containing a copy of the nominal model of the plant. The role of the ISM control law is to compensate matched uncertainties, without amplifying the unmatched ones. The MPC controller with tightened constraints generates the control component oriented to comply with state and control requirements, and is asynchronous since the underlying constrained optimization problem is solved only when a triggering event occurs. In the paper, the robustness properties of the controlled system are theoretically analyzed, proving the regional input-tostate practical stability of the overall control scheme

Deployable Vibration Control Systems for Lightweight Structures

The recent push towards lightweight, efficient, and innovative structural designs has brought forth a range of vibration control issues related to implementation, effectiveness, and control system design that are not fully addressed by existing strategies. In many cases, these structures are capable of withstanding day-to-day loads and only experience excessive vibrations during predictable peak-loading events such as large crowds or wind storms. At the same time, the use of lightweight material coupled with innovative construction methods has given rise to temporary structures which are designed to facilitate rapid implementation and intended for short-term applications. Both scenarios point towards a vibration control system that is suitable for immediate, short-term applications which motivates the concept of deployable autonomous control systems (DACSs). The deployability aspect implies the control system is capable of being readily implemented on a range of structures with only minor customization to the structure or device while the autonomy aspect refers to the ability of the system to react to changes in the dynamic response and effectively control different structural modes of vibration. A prototype device, consisting of an electromagnetic mass damper (EMD) mounted on an unmanned ground vehicle (UGV) equipped with vision sensors and on-board computational hardware, is developed to study the vibration control performance and demonstrate the advantages of the DACS concept. Both numerical and experimental modelling techniques are used to identify system models for each component of the prototype device. Given the system models, the dynamic interaction between the device and underlying structure is derived theoretically and validated experimentally. The use of an EMD and UGV introduce a number of practical challenges associated with controller design. These challenges arise due to the presence of physical operating constraints as well as uncertainty in the controller model. Three different candidate controllers, based on linear-quadratic Gaussian (LQG), model-predictive control (MPC), and robust H-infinity control theory, are formulated for the prototype device and comparatively assessed with respect to their ability to address these challenges. The MPC framework provides a systematic approach to incorporate physical operating constraints directly in the control formulation while robust synthesis of an H-infinity controller is well suited for addressing uncertainty in both the controller and structure models. A key property of the prototype device is the ability to reposition itself at different locations on the structure. To study the impact of this mobility on the overall control performance, a simultaneous localization and mapping (SLAM) solution is implemented for bridge structures. The SLAM solution generates a map of the structure that can later be used for autonomous navigation of the prototype device. In achieving autonomous mobility, the location of the control force can be added as an additional parameter in the controller formulation. The overall performance of the prototype device is evaluated through a combination of numerical simulations and experimental studies. Real-time hybrid simulation (RTHS) is used extensively to study the dynamic interaction effects and evaluate the control performance of the prototype device on various structures. A full-scale modular aluminum pedestrian bridge is used to demonstrate autonomous navigation and assess the advantages of a mobile control device. The results from each study point towards DACSs as being a favourable alternative to existing control systems for immediate, short-term vibration control applications

Modeling and Intelligent Control for Spatial Processes and Spatially Distributed Systems

Dynamical systems are often characterized by their time-dependent evolution, named temporal dynamics. The space-dependent evolution of dynamical systems, named spatial dynamics, is another important domain of interest for many engineering applications. By studying both the spatial and temporal evolution, novel modeling and control applications may be developed for many industrial processes. One process of special interest is additive manufacturing, where a three-dimensional object is manufactured in a layer-wise fashion via a numerically controlled process. The material is printed over a spatial domain in each layer and subsequent layers are printed on top of each other. The spatial dynamics of the printing process over the layers is named the layer-to-layer spatial dynamics. Additive manufacturing provides great flexibility in terms of material selection and design geometry for modern manufacturing applications, and has been hailed as a cornerstone technology for smart manufacturing, or Industry 4.0, applications in industry. However, due to the issues in reliability and repeatability, the applicability of additive manufacturing in industry has been limited. Layer-to-layer spatial dynamics represent the dynamics of the printed part. Through the layer-to-layer spatial dynamics, it is possible to represent the physical properties of the part such as dimensional properties of each layer in the form of a heightmap over a spatial domain. Thus, by considering the spatial dynamics, it is possible to develop models and controllers for the physical properties of a printed part. This dissertation develops control-oriented models to characterize the spatial dynamics and layer-to-layer closed-loop controllers to improve the performance of the printed parts in the layer-to-layer spatial domain. In practice, additive manufacturing resources are often utilized as a fleet to improve the throughput and yield of a manufacturing system. An additive manufacturing fleet poses additional challenges in modeling, analysis, and control at a system-level. An additive manufacturing fleet is an instance of the more general class of spatially distributed systems, where the resources in the system (e.g., additive manufacturing machines, robots) are spatially distributed within the system. The goal is to efficiently model, analyze, and control spatially distributed systems by considering the system-level interactions of the resources. This dissertation develops a centralized system-level modeling and control framework for additive manufacturing fleets. Many monitoring and control applications rely on the availability of run-time, up-to-date representations of the physical resources (e.g., the spatial state of a process, connectivity and availability of resources in a fleet). Purpose-driven digital representations of the physical resources, known as digital twins, provide up-to-date digital representations of resources in run-time for analysis and control. This dissertation develops an extensible digital twin framework for cyber-physical manufacturing systems. The proposed digital twin framework is demonstrated through experimental case studies on abnormality detection, cyber-security, and spatial monitoring for additive manufacturing processes. The results and the contributions presented in this dissertation improve the performance and reliability of additive manufacturing processes and fleets for industrial applications, which in turn enables next-generation manufacturing systems with enhanced control and analysis capabilities through intelligent controllers and digital twins.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169635/1/baltaefe_1.pd

Wirelessly Enabled Control of Cyber-Physical Infrastructure with Applications to Hydronic Systems.

Civil infrastructure systems, such as transportation networks, pipe networks, electrical grids, and building environments, are typically managed and controlled with outdated, inefficient, and minimally automated legacy controllers. This is apparent from documented oil pipeline leaks, broad electrical outages, and power plant failures. The relatively recent advents of small inexpensive microcontrollers and low-power wireless networking technologies has revealed opportunities for better managing the operational effectiveness of civil infrastructure systems. Academic research in this field is maturing, yet the field remains in its nascent years of commercial viability, focusing mainly on low data-rate sensing with centralized processing. Little focus has been on distributed wireless control systems for civil infrastructure. This dissertation follows the development and utilization of a new cyber-physical system (CPS) architecture for civil infrastructure. Embedded computing power is distributed throughout the physical systems and global objectives are met with the aid of wireless information exchange. The Martlet wireless controller node was conceived during the first part of this thesis to enable this objective of wirelessly distributed CPS. Once produced, the Martlet was used to realize such a controller, motivated by an application in hydronic cooling systems. The design of the proposed controller began with a study concerning models and objective functions for the control of bilinear systems, like those found in hydronics, when constrained by the resources of a wireless control node. The results showed that previous work with linear quadratic controllers could be improved by using nonlinear models and explicit objective functions. An agent-based controller utilizing the proposed bilinear model-predictive control algorithm, was then developed accounting for the limitation of, and leveraging the advantages of, wireless control nodes in order to regulate a hydronic system with hybrid dynamics. The resulting Martlet based control system was compared to traditional benchmark controllers and shown to achieve adequate performance, with the added benefits of a wireless CPS. These developments in wirelessly distributed control of complex systems are presented not only with the tested hydronic systems in mind, but with the goal of extending this technology to improve the performance and reliability of a wide variety of controlled cyber-physical civil infrastructure systems.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107310/1/mbkane_1.pd