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:

**2004 (Volume 14)**

Number 1

**Second - order linear state space systems: Computing the transfer function using the DFT**

George E. Antoniou(State University Montclair, USA) |

**keywords:** linear systems, second-order systems, Fourier transform, transfer function.

**Relationship between Smith zeros and invariant zeros in linear systems**

Jerzy Tokarzewski(Military University of Technology, Poland) |

*S(E,A,B,C,D)*(in particular, at

*E=I*, of a standard linear system

*S(A,B,C,D)*) can be generalized and related to the state-space methods is discussed. Nothing is assumed about the relationship of the number of inputs to the number of outputs nor about the normal rank of the underlying system matrix. The aforementioned generalization treats zeros (called further the invariant zeros) as the triples (complex number, nonzero state-zero direction, input-zero direction). Such treatment is strictly connected with the output-zeroing problem and in that spirit the zeros can be easily interpreted even in the degenerate case (i.e., when any complex number is such zero).

**keywords:** linear systems, zeros, state-space methods.

**Stable indirect adaptive fuzzy control for a class of SISO nonlinear systems**

Salim Labiod, Mohamed Seghir Boucherit and Omar Bouhali(Ecole Nationale Polytechnique, Algeria) |

**keywords:** fuzzy control, fuzzy systems, nonlinear systems, adaptive control.

**A new adaptive least-squares estimation algorithm with generalized internal feedback**

Krzysztof J. Latawiec(Technical University of Opole, Poland) |

*a*daptive

*l*east-

*s*quares parameter estimator are shown to generalize and extend the use of internal information feedback in various robustness/alertness-oriented modifications to the standard ALS estimation algorithm. In the cascade estimation structure it is possible to `naturally' stabilize, rather than maximize, the information matrix so that the covariance zeroing and blowup are effectively eliminated and the celebrated square root update of the covariance matrix is no longer needed. Consequently, a new, partly heuristic ALS MIMO estimation algorithm, enabling to effectively track both slow and jump parameter variations, is presented. The algorithm is coupled with a simple but robust predictive control scheme, offering a new adaptive MIMO control strategy.

**keywords:** adaptive systems, least-squares estimation, robust estimation, time-varying systems, identification, adaptive control, predictive control.

**-Synthesis: an algebraic approach**

Marek Dlapa and Roman Prokop(Tomas Bata University in Zlin, Czech Republic) |

**keywords:** structured singular value, algebraic synthesis, time delay, PID controllers, linear fractional transformation.

**Adaptive stabilization of infinite-dimensional undamped second order systems without velocity feedback**

Toshihiro Kobayashi and Masahiro Oya(Kyushu Institute of Technology, Japan) |

**keywords:** adaptive stabilization, undamped second order dynamical systems, parallel compensators.

**A controllability problem for a class of uncertain - parameters linear dynamic systems**

Krzysztof Oprzedkiewicz(University of Mining and Metallurgy, Poland) |

**keywords:** linear uncertain parameters dynamic systems, controllability.

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