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

Direct data-driven control of constrained linear parameter-varying systems: A hierarchical approach

In many nonlinear control problems, the plant can be accurately described by a linear model whose operating point depends on some measurable variables, called scheduling signals. When such a linear parameter-varying (LPV) model of the open-loop plant needs to be derived from a set of data, several issues arise in terms of parameterization, estimation, and validation of the model before designing the controller. Moreover, the way modeling errors affect the closed-loop performance is still largely unknown in the LPV context. In this paper, a direct data-driven control method is proposed to design LPV controllers directly from data without deriving a model of the plant. The main idea of the approach is to use a hierarchical control architecture, where the inner controller is designed to match a simple and a-priori specified closed-loop behavior. Then, an outer model predictive controller is synthesized to handle input/output constraints and to enhance the performance of the inner loop. The effectiveness of the approach is illustrated by means of a simulation and an experimental example. Practical implementation issues are also discussed.Comment: Preliminary version of the paper "Direct data-driven control of constrained systems" published in the IEEE Transactions on Control Systems Technolog

Explicit Reference Governor for Continuous Time Nonlinear Systems Subject to Convex Constraints

This paper introduces a novel closed-form strategy that dynamically modifies the reference of a pre-compensated nonlinear system to ensure the satisfaction of a set of convex constraints. The main idea consists of translating constraints in the state space into constraints on the Lyapunov function and then modulating the reference velocity so as to limit the value of the Lyapunov function. The theory is introduced for general nonlinear systems subject to convex constraints. In the case of polyhedric constraints, an explicit solution is provided for the large and highly relevant class of nonlinear systems whose Lyapunov function is lower-bounded by a quadratic form. In view of improving performances, further specializations are provided for the relevant cases of linear systems and robotic manipulators.Comment: Submitted to: IEEE Transactions on Automatic Contro

Intermittent predictive control of an inverted pendulum

Intermittent predictive pole-placement control is successfully applied to the constrained-state control of a prestabilised experimental inverted pendulum

Value of thermostatic loads in future low-carbon Great Britain system

This paper quantifies the value of a large population of heterogeneous thermostatically controlled loads (TCLs). The TCL dynamics are regulated by means of an advanced demand side response model (DSRM). It optimally determines the flexible energy/power consumption and simultaneously allocates multiple ancillary services. This model explicitly incorporates the control of dynamics of the TCL recovery pattern after the provision of the selected services. The proposed framework is integrated in a mixed integer linear programming formulation for a multi-stage stochastic unit commitment. The scheduling routine considers inertia-dependent frequency response requirements to deal with the drastic reduction of system inertia under future low-carbon scenarios. Case studies focus on the system operation cost and CO2 emissions reductions for individual TCLs for a) different future network scenarios, b) different frequency requirements, c) changes of TCL parameters (e.g. coefficient of performance, thermal insulation etc.)