2017 (vol. 27) - Number 4

*M. Kaczmarek, W. Domski, A. Mazur:*

Position-force control of mobile manipulator - nonadaptive and adaptive case

*Zhong Cao, Wenjing Zhao, Xiaorong Hou:*

Adaptive robust simultaneous stabilization controller with tuning parameters design for two dissipative Hamiltonian systems

*J. Duda:*

A Lyapunov functional for a system with both lumped and distributed delay

*Sundarapandian Vaidyanathan, Aceng Sambas, Mustafa Mamat, Mada Sanjaya WS:*

A new three-dimensional chaotic system with a hidden attractor, circuit design and application in wireless mobile robot

*J. Ratajczak, K. Tchoñ:*

On dynamically consistent Jacobian inverse for non-holonomic robotic systems

*D. Krokavec, A. Filasova:*

Stabilization of discrete-time LTI positive systems

*P. Tatjewski:*

Offset-free nonlinear Model Predictive Control with state-space process models

ACS Abstract:

**2006 (Volume 16)**

Number 2

**Principles of constraint systems and constraint solvers**

Thom Frühwirth(Faculty of Computer Science, University of Ulm, Germany) | Slim Abdennadher(Department of Computer Science, German University Cairo, Egypt) |

**keywords:** computational logic, executable specifications, rule-based programming, program analysis, algorithms

**An introduction to interval-based constraint processing**

Gerrit Renker, Hatem Ahriz(School of Computing, The Robert Gordon University, Aberdeen, UK) |

Constraint programming is often associated with solving problems over finite domains. Many applications in engineering, cad and design, however, require solving problems over continuous (real-valued) domains. While simple constraint solvers can solve linear constraints with the inaccuracy of floating-point arithmetic, methods based on interval arithmetic allow exact (interval) solutions over a much wider range of problems. Applications of interval-based programming extend the range of solvable problems from non-linear polynomials up to those involving ordinary differential equations.

In this text, we give an introduction to current approaches, methods and implementations of interval-based constraint programming and solving. Special care is taken to provide a uniform and consistent notation, since the literature in this field employs many seemingly different, but yet conceptually related, notations and terminology.

**keywords:** constraint programming, interval-based computation, interval consistency techniques

**Filtering algorithms for the Same and UsedBy constraints**

Nicolas Beldiceanu(Ecole des Mines de Nantes, Nantes Cedex, France) | Irit Katriel, Sven Thiel(Max-Planck-Institut fur Informatik, Saarbrucken, Germany) |

*X*and

*Z*such that

*|X| > |Z|*and assigns values to them such that the multiset of values assigned to the variables in

*Z*is contained in the multiset of values assigned to the variables in

*X*. Same is the special case of UsedBy in which

*|X|=|Z|*. We show algorithms that achieve arc-consistency and bound-consistency for these constraints.

**keywords:** arc-consistency, bound-consistency, constraint programming, filtering algorithm, global constraint, network flow, strongly connected component

**Message delay and asynchronous DisCSP search**

Roie Zivan, Amnon Meisels(Department of Computer Science, Ben-Gurion University of the Negev, Israel) |

**keywords:** distributed constraint satisfaction, search, distributed AI

<< Back