Class Of Piecewise Affine Systems Research Articles

Duality of controllability and observability in proportional equal conflict timed continuous Petri Nets

Controllability and observability properties have been widely studied in Timed Continuous Petri Nets (TCPNs), a class of piecewise affine systems, in order to analyze and control crowded discrete event systems. This work studies the concept of duality applied to TCPNs as a vehicle to establish links between controllability and observability, i.e., a synergy to improve the understanding of these properties and to enlarge the class of nets that can be analyzed. To achieve this, we study the concepts of rank-controllability and rank-observability. They capture structural conditions for controllability and observability. Afterwards, the computation of dual nets for Fork-Attribution (FA), Choice-Free (CF), Join-Free (JF), and Proportional Equal Conflict (PEQ) TCPNs subclasses are presented. By using the dual definition, several relations between the primal’s controllability and its dual’s observability are stated. Particularly, in FA rank-controllability and rank-observability are dual properties. In consistent and strongly connected CF, JF, and PEQ nets, the rank-observability of the dual is sufficient for the rank-controllability of the primal. The opposite implication holds for CF and PEQ if the self-loop places, added by the dual construction methodology, are measurable.

Dimension of the repeller for a piecewise expanding affine map

In this paper, we study the dimension theory of a class of piecewise affine systems in euclidean spaces suggested by Michael Barnsley, with some applications to the fractal image compression. It is a more general version of the class considered in the work of Keane, Simon and Solomyak [The dimension of graph directed attractors with overlaps on the line, with an application to a problem in fractal image recognition. {\it Fund. Math.}, {\bf 180}(3):279-292, 2003] and can be considered as the continuation of the works [On the dimension of self-affine sets and measures with overlaps. {\it Proc. Amer. Math. Soc.}, {\bf 144}(10):4427-4440, 2016], [On the dimension of triangular self-affine sets. {\it Erg. Th. \& Dynam. Sys.}, to appear.] by the authors. We also present some applications of our results for the generalized Takagi functions and fractal interpolation functions.

Discontinuous Lyapunov functions for a class of piecewise affine systems

In this paper, a Lyapunov-based method is provided to study the local asymptotic stability of planar piecewise affine systems with continuous vector fields. For such systems, the state space is supposed to be partitioned into several bounded convex polytopes. A piecewise affine function, not necessarily continuous on the boundaries of the polytopic partitions, is proposed as a candidate Lyapunov function. Then, sufficient conditions for the local asymptotic stability of the system, including a monotonicity condition at switching instants, are formulated as a linear programming problem. In addition, when the problem does not have a feasible solution based on the original partitions of the system, a new partition refinement algorithm is presented. In this way, more flexibility can be provided in searching for the Lyapunov function. Owing to relaxation of the continuity condition imposed on the system boundaries, the proposed method reaches to less conservative results, compared with the previous methods based on continuous piecewise affine Lyapunov functions. Simulation results illustrate the effectiveness of the proposed method.

Efficient online solution of multi-parametric mixed-integer quadratic problems

This paper considers model predictive control of a class of piecewise affine systems and introduces a method to reduce the complexity of the optimisation problem which is solved online. The optimisation problem is a mixed-integer quadratic program which is parameterised by the initial state of the system dynamics. The complexity of the problem solved online is reduced by moving part of the computational burden offline. In the offline computations, the structure of the mixed-integer problem is explored to determine a polytopic partition of the set of initial states. Each polytope of the partition is then considered and it is determined which integer combinations can/cannot be optimal, given that the initial state is contained in the current polytope. The result of the offline computations is that each polytope is associated with the set of potentially optimal integer combinations. The online solution of the mixed-integer problem consists of a two-step procedure: first, it is determined which polytope contains the initial state. Then, the mixed-integer problem is solved, taking into account only those integer combinations associated with the current polytope. The solution approach is shown to give a significant complexity reduction when applied to hybrid control of switched-mode power converters.

Stability of stationary solutions of piecewise affine differential equations describing gene regulatory networks

We study stability properties of a class of piecewise affine systems of ordinary differential equations arising in the modeling of gene regulatory networks. Our method goes back to the concept of a Filippov stationary solution (in the narrow sense) to a differential inclusion corresponding to the system in question. The main result of the paper justifies a reduction principle in the stability analysis enabling to omit the variables that are not singular, i.e. that stay away from the discontinuity set of the system. We suggest also “the first approximation method” to study asymptotic stability of stationary solutions based on calculating the principal part of the system, which is 0-homogeneous rather than linear. This leads to an efficient algorithm of how to check asymptotic stability without calculating the eigenvalues of the systemʼs Jacobian. In Appendix A we discuss and compare two other concepts of stationary solutions to the system in question.

Lebesgue piecewise affine approximation of nonlinear systems

This paper addresses a piecewise affine (PWA) approximation problem, i.e., a problem of finding a PWA system model which approximates a given nonlinear system. First, we propose a new class of PWA systems, called the Lebesgue PWA approximation systems, as a model to approximate nonlinear systems. Next, we derive an error bound of the PWA approximation model, and provide a technique for constructing the approximation model with specified accuracy. Finally, the proposed method is applied to a gene regulatory network with nonlinear dynamics, which shows that the method is a useful approximation tool.

A NEW DUAL-MODE HYBRID MPC ALGORITHM WITH A ROBUST STABILITY GUARANTEE

This paper employs the Input-to-State Stability (ISS) framework to investigate the robustness of discrete-time Piece-Wise Affine (PWA) systems in closed-loop with Model Predictive Controllers (MPC), or hybrid MPC for short. We show via an example taken from literature that stabilizing hybrid MPC can generate MPC values functions that are not ISS Lyapunov functions for arbitrarily small additive disturbances. As a consequence, it is not easy to prove that nominally stabilizing hybrid MPC schemes are robust. This motivates the need to design MPC schemes for hybrid systems with an a priori robust stability guarantee. A possible solution to this problem was recently developed by the authors for a particular class of PWA systems, i.e. when the origin lies in the interior of one of the regions in the partition. The main contribution of this paper is a novel dual-mode MPC algorithm for hybrid systems with an a priori ISS guarantee. This MPC scheme is applicable to general PWA systems, i.e. when the origin may lie on the boundaries of multiple regions in the partition.

Identification of piecewise affine systems based on statistical clustering technique

This paper is concerned with the identification of a class of piecewise affine systems called a piecewise affine autoregressive exogenous (PWARX) model. The PWARX model is composed of ARX sub-models each of which corresponds to a polyhedral region of the regression space. Under the temporary assumption that the number of sub-models is known a priori, the input–output data are collected into several clusters by using a statistical clustering algorithm. We utilize support vector classifiers to estimate the boundary hyperplane between two adjacent regions in the regression space. In each cluster, the parameter vector of the sub-model is obtained by the least squares method. It turns out that the present statistical clustering approach enables us to estimate the number of sub-models based on the information criteria such as CAIC and MDL. The estimate of the number of sub-models is performed by applying the identification procedure several times to the same data set, after having fixed the number of sub-models to different values. Finally, we verify the applicability of the present identification method through a numerical example of a Hammerstein model.

Identification of piecewise affine systems based on statistical clustering technique

This paper is concerned with the identification of a class of piecewise affine systems called a piecewise affine autoregressive exogenous model by using a statistical clustering algorithm based on a Gaussian mixture model. It is shown that the present statistical clustering approach enables us to estimate the number of sub-models based on the information criteria such as CAIC and MDL.

Development of a Simulator of a Class of Piecewise Affine Systems

This paper treats the simulation problem of multi-modal piecewise affine systems with binary-switches. First, it is pointed out by numerical examples that some problems on the event detection occur in the existing simulators when a solution of the system crosses an intersection of multiple switching hyperplanes. Next, a new simulation algorithm is proposed under the switch-based transition rule.

A GEOMETRIC APPROACH TO REACHABILITY COMPUTATIONS FOR CONSTRAINED DISCRETE-TIME SYSTEMS

The problem of reachability computations for systems with simultaneous constraints on the states, control inputs and disturbances is treated. A problem formulation is provided for the general case and, for the special case where the disturbance constraints are independent of the states and inputs, it is discussed how the solution can be approached using standard geometric concepts. It is also discussed how the procedure can be implemented for a class of piecewise affine systems with polyhedral constraints using computational geometry software.