Asymptotic stability of sampled-data piecewise affine slab systems

This paper addresses stability analysis of closed-loop sampled-datapiecewiseaffine (PWA) slabsystems. In particular, we study the case in which a PWA plant is in feedback with a discrete-time emulation of a PWA controller. We consider the sampled-datasystem as a continuous-time system with a variable time delay. The contributions of this work are threefold. First, we present a modified Lyapunov–Krasovskii functional (LKF) for studying PWA systems with time delays that is less conservative when compared to previously suggested alternatives. Second, based on the new LKF, sufficient conditions are provided for asymptoticstability of sampled-data PWA slabsystems to the origin. These conditions become Linear Matrix Inequalities (LMIs) in the case of a piecewise linear (PWL) controller. Finally, we present an algorithm for finding a lower bound on the maximum delay that preserves asymptoticstability. Therefore, the output of the algorithm provides an upper bound on the minimum sampling frequency that guarantees asymptoticstability of the sampleddatasystem. The new results are successfully applied to a unicycle example

Convex Formulation of Controller Synthesis for Piecewise-Affine Systems

This thesis is divided into three main parts. The contribution of the first part is to present a controller synthesis method to stabilize piecewise-affine (PWA) slab systems based on invariant sets. Inspired by the theory of sliding modes, sufficient stabilization conditions are cast as a set of Linear Matrix Inequalities (LMIs) by proper choice of an invariant set which is a target sliding surface. The method has two steps: the design of the attractive sliding surface and the design of the controller parameters. While previous approaches to PWA controller synthesis are cast as Bilinear Matrix Inequalities (BMIs) that can, in some cases, be relaxed to LMIs at the cost of adding conservatism, the proposed method leads naturally to a convex formulation. Furthermore, the LMIs obtained in this work have lower dimension when compared to other methods because the dimension of the closed-loop state space is reduced. In the second part of the thesis, it is further shown that the proposed approach is less conservative than other approaches. In other words, it will be shown that for every solution of the LMIs resulting from previous approaches, there exists a solution for the LMIs obtained from the proposed method. Furthermore, it will be shown that while previous convex controller synthesis methods have no solutions to their LMIs for some examples of PWA systems, the approach proposed in this thesis yields a solution for these examples. The contribution of the last part of this thesis is to formulate the PWA time-delay synthesis problem as a set of LMIs. In order to do so, we first define a sliding surface, then control laws are designed to approach the specified sliding surface and ensure that the trajectories will remain on that surface. Then, using Lyapunov-Krasovskii functionals, sufficient conditions for exponential stability of the resulting reduced order system will be obtained. Several applications such as pitch damping of a helicopter (2nd order system), rover path following example (3rd order system) and active flutter suppression (4th order system) along with some other numerical examples are included to demonstrate the effectiveness of the approaches

Stability analysis and controller synthesis for a class of piecewise smooth systems

This thesis deals with the analysis and synthesis of piecewise smooth (PWS) systems. In general, PWS systems are nonsmooth systems, which means their vector fields are discontinuous functions of the state vector. Dynamic behavior of nonsmooth systems is richer than smooth systems. For example, there are phenomena such as sliding modes that occur only in nonsmooth systems. In this thesis, a Lyapunov stability theorem is proved to provide the theoretical framework for the stability analysis of PWS systems. Piecewise affine (PWA) and piecewise polynomial (PWP) systems are then introduced as important subclasses of PWS systems. The objective of this thesis is to propose efficient computational controller synthesis methods for PWA and PWP systems. Three synthesis methods are presented in this thesis. The first method extends linear controllers for uncertain nonlinear systems to PWA controllers. The result is a PWA controller that maintains the performance of the linear controller while extending its region of convergence. However, the synthesis problem for the first method is formulated as a set of bilinear matrix inequalities (BMIs), which are not easy to solve. Two controller synthesis methods are then presented to formulate PWA and PWP controller synthesis as convex problems, which are numerically tractable. Finally, to address practical implementation issues, a time-delay approach to stability analysis of sampled-data PWA systems is presented. The proposed method calculates the maximum sampling time for a sampled-data PWA system consisting of a continuous-time plant and a discrete-time emulation of a continuous-time PWA state feedback controller

Posterior computation with the Gibbs zig-zag sampler

An intriguing new class of piecewise deterministic Markov processes (PDMPs) has recently been proposed as an alternative to Markov chain Monte Carlo (MCMC). In order to facilitate the application to a larger class of problems, we propose a new class of PDMPs termed Gibbs zig-zag samplers, which allow parameters to be updated in blocks with a zig-zag sampler applied to certain parameters and traditional MCMC-style updates to others. We demonstrate the flexibility of this framework on posterior sampling for logistic models with shrinkage priors for high-dimensional regression and random effects and provide conditions for geometric ergodicity and the validity of a central limit theorem.Comment: 29 pages, 4 figure

Stability of uncertain piecewise affine systems with time delay: delay-dependent Lyapunov approach

This article addresses the problem of robust stability of piecewise affine (PWA) uncertain systems with unknown time-varying delay in the state. It is assumed that the uncertainty is norm bounded and that upper bounds on the state delay and its rate of change are available. A set of linear matrix inequalities (LMIs) is derived providing sufficient conditions for the stability of the system. These conditions depend on the upper bound of the delay. The main contributions of the article are as follows. First, new delay-dependent LMI conditions are derived for the stability of PWA time-delay systems. Second, the stability conditions are extended to the case of uncertain PWA time delay systems. Numerical examples are presented to show the effectiveness of the approach

Optimal control and robust estimation for ocean wave energy converters

This thesis deals with the optimal control of wave energy converters and some associated observer design problems. The first part of the thesis will investigate model predictive control of an ocean wave energy converter to maximize extracted power. A generic heaving converter that can have both linear dampers and active elements as a power take-off system is considered and an efficient optimal control algorithm is developed for use within a receding horizon control framework. The optimal control is also characterized analytically. A direct transcription of the optimal control problem is also considered as a general nonlinear program. A variation of the projected gradient optimization scheme is formulated and shown to be feasible and computationally inexpensive compared to a standard nonlinear program solver. Since the system model is bilinear and the cost function is not convex quadratic, the resulting optimization problem is shown not to be a quadratic program. Results are compared with other methods like optimal latching to demonstrate the improvement in absorbed power under irregular sea condition simulations. In the second part, robust estimation of the radiation forces and states inherent in the optimal control of wave energy converters is considered. Motivated by this, low order H∞ observer design for bilinear systems with input constraints is investigated and numerically tractable methods for design are developed. A bilinear Luenberger type observer is formulated and the resulting synthesis problem reformulated as that for a linear parameter varying system. A bilinear matrix inequality problem is then solved to find nominal and robust quadratically stable observers. The performance of these observers is compared with that of an extended Kalman filter. The robustness of the observers to parameter uncertainty and to variation in the radiation subsystem model order is also investigated. This thesis also explores the numerical integration of bilinear control systems with zero-order hold on the control inputs. Making use of exponential integrators, exact to high accuracy integration is proposed for such systems. New a priori bounds are derived on the computational complexity of integrating bilinear systems with a given error tolerance. Employing our new bounds on computational complexity, we propose a direct exponential integrator to solve bilinear ODEs via the solution of sparse linear systems of equations. Based on this, a novel sparse direct collocation of bilinear systems for optimal control is proposed. These integration schemes are also used within the indirect optimal control method discussed in the first part.Open Acces

Design, Construction and Control of a Quadrotor Helicopter Using a New Multirate Technique

This thesis describes the design, development, analysis and control of an autonomous Quadrotor Uninhabited Aerial Vehicle (UAV) that is controlled using a novel approach for multirate sampled-data systems. This technique uses three feedback loops: one loop for attitude, another for velocity and a third loop for position, yielding a piece-wise affine system. Appropriate control actions are also computed at different rates. It is shown that this technique improve the system's stability under sampling rates that are significantly lower than the ones required with more classical approaches. The control strategy, that uses sensor data that is sampled at different rates in different nodes of a network, is also applied to a ground wheeled vehicle. Simulations and experiments show very smooth tracking of set-points and trajectories at a very low sampling frequency, which is the main advantage of the new technique