Reference governors: Theoretical Extensions and Practical Applications.

As systems become downsized and operate at the limits of performance, control systems must be designed to ensure that system state and control constraints are satisfied; however, conventional control schemes are often designed without taking constraints into account. Reference governors and the related, more flexible, extended command governors are add-on, constraint enforcement schemes that modify reference signals to conventionally designed, closed-loop systems for the purpose of enforcing output constraints. The focus of this dissertation is on theoretical and methodological extensions of reference and extended command governors, and on their practical applications. Various theoretical results are presented. The first is the development of reduced-order reference and extended command governors, which enables constraint enforcement schemes using simplified models. The second, related development is that of reference governors for decentralized systems that may or may not communicate over a network. The third considers command governors with penalty functions that are used to enforce prioritized sets of constraints, as well as reference governors that are applied to a sequence of prioritized references. The fourth considers the often overlooked case of applying reference governors to linear systems subject to nonlinear constraints; various formulations of constraints are considered, including quadratic constraints and mixed logical-dynamic constraints. The final theoretical development considers using contractive sets to design reference governors for systems with time-varying reference inputs or subject to time-dependent constraints. Numerical simulations are used throughout to illustrate the theoretical advances. The design of reference governor schemes for three systems arising in practical applications is also presented. The first scheme enforces compressor surge constraints for turbocharged gasoline engines, ensuring that the compressor does not surge. The second scheme is designed for an airborne wind energy system that is subject to various flight constraints including constraints on altitude and angle of attack. The third and final scheme is designed for the constrained control of spacecraft attitude, whose discrete-time dynamics evolve on the configuration space SO(3). In the case of the first application, experimental vehicle results are reported that show successful avoidance of surge. For the other two applications, nonlinear model simulation results are reported that show enforcement of system constraints.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113518/1/kalabic_1.pd

Reduced Order and Prioritized Reference Governors for Limit Protection in Aircraft Gas Turbine Engines

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140424/1/6.2014-1149.pd

Incorporating Risk into Control Design for Emergency Operation of Turbo-Fan Engines

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90650/1/AIAA-2011-1591-262.pd

Reference Governors for Time-varying Systems and Constraints

Control systems are often subject to constraints imposed by physical limitations or safety considerations, and require means of constraint management to ensure the stability and safety of the system. For real-time implementation, constraint management schemes must not carry a heavy computational burden; however many of the current solutions are computationally unattractive, especially those with robust formulations. Thus, the design of constraint management schemes with low computational loads is an important and practical problem for control engineers. Reference Governor (RG) is an efficient constraint management scheme that is attractive for real-time implementation due to its low computational complexity and ease of implementation. However, in theory, RG is only able to enforce constant constraints for systems with time-invariant models. In this thesis, we extend the capabilities of RG to solve two separate problems. The solution to the first problem presented in this thesis is a novel RG scheme for overshoot mitigation in tracking control systems. The proposed scheme, referred to as the Reference Governor with Dynamic Constraint (RG-DC), recasts the overshoot mitigation problem as a constraint management problem. The outcome of this reformulation is a dynamic Maximal Admissible Set (MAS), which varies in real-time as a function of the reference signal and the tracking output. RG-DC employs the dynamic MAS to modify the reference signal to mitigate or, if possible, prevent overshoot. The second solution presented in this thesis is a RG scheme for constraint management of parameter-varying systems with slowly time-varying constraints. The solution, known as the Adaptive-Contractive Reference Governor (RG-AC) utilizes a contractive characterization of MAS that changes in real-time as a function of the system\u27s time-varying parameters in a computationally attractive manner. This adaptive set is based off a first-order Taylor approximation of the parameter dependent matrices that describe the time-varying MAS. The work in this thesis is supported by simulation results which demonstrate the efficacy of both approaches, and also highlight their limitations

Coordinated Model Predictive Control of Aircraft Gas Turbine Engine and Power System

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143088/1/1.G002562.pd

Model predictive emissions control of a diesel engine airpath: Design and experimental evaluation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163480/2/rnc5188.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163480/1/rnc5188_am.pd

The Iteration Domain Reference Governor, a Constraint Management Scheme for Batch Processes

In this work, a novel combination of Reference Governors (RG) and Iterative Learning Control (ILC) to address the issue of simultaneous learning and constraint management in systems that perform a task repeatedly is proposed. The proposed control strategy leverages the measured output from the previous iterations to improve tracking, while guaranteeing constraint satisfaction during the learning process. To achieve this, the plant is modeled by a linear system with uncertainties. An RG solution based on a robust Maximal Admissible Set (MAS) is proposed that endows the ILC algorithm with constraint management capabilities. The proposed method is applied to the Scalar Reference Governor (SRG), the Vector Reference Governor (VRG) and the Command Governor (CG). An update law on the MAS is proposed to further improve performance

Reference Governors: From Theory to Practice

Control systems that are subject to constraints due to physical limitations, hardware protection, or safety considerations have led to challenging control problems that have piqued the interest of control practitioners and theoreticians for many decades. In general, the design of constraint management schemes must meet several stringent requirements, for example: low computational burden, performance, recovery mechanisms from infeasibility conditions, robustness, and formulation simplicity. These requirements have been particularly difficult to meet for the following three classes of systems: stochastic systems, linear systems driven by unmodeled disturbances, and nonlinear systems. Hence, in this work, we develop three constraint management schemes, based on Reference Governor (RG), for these classes of systems. The first scheme, which is referred to as Stochastic RG, leverages the ideas of chance constraints to construct a Stochastic Robustly Invariant Maximal Output Admissible set (SR-MAS) in order to enforce constraints on stochastic systems. The second scheme, which is called Recovery RG (RRG), addresses the problem of recovery from infeasibility conditions by implementing a disturbance observer to update the MAS, and hence recover from constraint violations due to unmodeled disturbances. The third method addresses the problem of constraint satisfaction on nonlinear systems by decomposing the design of the constraint management strategy into two parts: enforcement at steady-state, and during transient. The former is achieved by using the forward and inverse steady-state characterization of the nonlinear system. The latter is achieved by implementing an RG-based approach, which employs a novel Robust Output Admissible Set (ROAS) that is computed using data obtained from the nonlinear system. Added to this, this dissertation includes a detailed literature review of existing constraint management schemes to compare and highlight advantages and disadvantages between them. Finally, all this study is supported by a systematic analysis, as well as numerical and experimental validation of the closed-loop systems performance on vehicle roll-over avoidance, turbocharged engine control, and inverted pendulum control problems

Developments in Stochastic Fuel Efficient Cruise Control and Constrained Control with Applications to Aircraft.

This dissertation presents contributions to fuel-efficient control of vehicle speed and constrained control with applications to aircraft. In the first part of this dissertation a stochastic approach to fuel-efficient vehicle speed control is developed. This approach encompasses stochastic modeling of road grade and traffic speed and uses the application of stochastic dynamic programming to generate vehicle speed control policies that are optimized for the trade-off between fuel consumption and travel time. It is shown that the policies lead to the emergence of time-varying vehicle speed patterns, often referred to as pulse and glide (PnG). Through simulations and experiments it is confirmed that these time-varying vehicle speed profiles are more fuel-efficient than driving at a comparable constant speed. A practical implementation strategy of these patterns is then developed and demonstrated. Also, several additional contributions are made to approaches for stochastic modeling of road grade and vehicle speed that include the use of Kullback-Liebler divergence and divergence rate and a stochastic jump-like model for the behavior of the road grade. In the second part of the dissertation, contributions to constrained control with applications to aircraft are described. Recoverable sets and integral safe sets of initial states of constrained closed-loop systems are introduced first and computational procedures of such sets based on linear discrete-time models are given. An approach to constrained flight planning based on chaining recoverable sets or integral safe sets is described and illustrated with a simulation example. Finally, two control schemes that exploit integral safe sets are proposed. The first scheme, referred to as the controller state governor (CSG), resets the controller state (typically an integrator) to enforce the constraints and enlarge the set of plant states that can be recovered without constraint violation. The second scheme, referred to as the controller state and reference governor (CSRG), combines the controller state governor with the reference governor control architecture and provides the capability of simultaneously modifying the reference command and the controller state to enforce the constraints. Theoretical results that characterize the response properties of both schemes are presented. Examples are reported that illustrate the operation of these schemes.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111399/1/kevinmcd_1.pd

Development of an electronic control unit for the T63 gas turbine

Includes bibliographical references.Fundamental research has been undertaken at the SASOL Advanced Fuels Laboratory to investigate the effects of the chemistry and physical properties of both conventional and synthetic jet fuels on threshold combustion. This research was undertaken using a purpose built low pressure continuous combustion test facility. Researchers at the laboratory now wish to examine these effects on an aviation gas turbine in service for which “off-map” scheduling of fuel to the engine would be required. A two phase project was thus proposed to develop this capability; the work of this thesis embodies Phase I of that project