A computational method for reduced-order observers in linear systems
A computationally efficient stable dual-mode type nonlinear predictive control algorithm
A continuation method for motion-planning problems
We apply the well-known homotopy continuation method to address the motion planning problem (MPP) for smooth driftless control-affine systems. The homotopy continuation method is a Newton-type procedure to effectively determine functions only defined implicitly. That approach requires first to characterize the singularities of a surjective map and next to prove global existence for the solution of an ordinary differential equation, the Wazewski equation. In the context of the MPP, the aforementioned...
A continuation method for motion-planning problems
We apply the well-known homotopy continuation method to address the motion planning problem (MPP) for smooth driftless control-affine systems. The homotopy continuation method is a Newton-type procedure to effectively determine functions only defined implicitly. That approach requires first to characterize the singularities of a surjective map and next to prove global existence for the solution of an ordinary differential equation, the Wazewski equation. In the context of the MPP, the aforementioned...
A double window state observer for detection and isolation of abrupt changes in parameters
The paper presents a new method for diagnosis of a process fault which takes the form of an abrupt change in some real parameter of a time-continuous linear system. The abrupt fault in the process real parameter is reflected in step changes in many parameters of the input/output model as well as in step changes in canonical state variables of the system. Detection of these state changes will enable localization of the faulty parameter in the system. For detecting state changes, a special type of...
A family of model predictive control algorithms with artificial neural networks
This paper details nonlinear Model-based Predictive Control (MPC) algorithms for MIMO processes modelled by means of neural networks of a feedforward structure. Two general MPC techniques are considered: the one with Nonlinear Optimisation (MPC-NO) and the one with Nonlinear Prediction and Linearisation (MPC-NPL). In the first case a nonlinear optimisation problem is solved in real time on-line. In order to reduce the computational burden, in the second case a neural model of the process is used...
A fast algorithm for scalar Nevanlinna-Pick interpolation.
A federated approach to parallel and distributed simulation of complex systems
The paper describes a Java-based framework called ASimJava that can be used to develop parallel and distributed simulators of complex real-life systems. Some important issues associated with the implementation of parallel and distributed simulations are discussed. Two principal paradigms for constructing simulations today are considered. Particular attention is paid to an approach for federating parallel and distributed simulators. We describe the design, performance and applications of the ASimJava...
A general on-the-fly algorithm for modifying the kinematic tree hierarchy
When conducting a dynamic simulation of a multibody mechanical system, the model definition may need to be altered during the simulation course due to, e.g., changes in the way the system interacts with external objects. In this paper, we propose a general procedure for modifying simulation models of articulated figures, particularly useful when dealing with systems in time-varying contact with the environment. The proposed algorithm adjusts model connectivity, geometry and current state, producing...
A geometric approach for testing regularity of multi-dimensional polynomial matrices and a pencil of -matrices
A homotopy approach to rational covariance extension with degree constraint
The solutions to the Rational Covariance Extension Problem (RCEP) are parameterized by the spectral zeros. The rational filter with a specified numerator solving the RCEP can be determined from a known convex optimization problem. However, this optimization problem may become ill-conditioned for some parameter values. A modification of the optimization problem to avoid the ill-conditioning is proposed and the modified problem is solved efficiently by a continuation method.
A method for computing quadratic Brunovsky forms.
A multishift algorithm for the numerical solution of algebraic Riccati equations.
A multivariable multiobjective predictive controller
Predictive control of MIMO processes is a challenging problem which requires the specification of a large number of tuning parameters (the prediction horizon, the control horizon and the cost weighting factor). In this context, the present paper compares two strategies to design a supervisor of the Multivariable Generalized Predictive Controller (MGPC), based on multiobjective optimization. Thus, the purpose of this work is the automatic adjustment of the MGPC synthesis by simultaneously minimizing...
A new optimal algorithm for a time-dependent scheduling problem
A note on the numerical solution of complex Hamiltonian and skew-Hamiltonian eigenvalue problems.
A novel interval arithmetic approach for solving differential-algebraic equations with VALENCIA-IVP
The theoretical background and the implementation of a new interval arithmetic approach for solving sets of differentialalgebraic equations (DAEs) are presented. The proposed approach computes guaranteed enclosures of all reachable states of dynamical systems described by sets of DAEs with uncertainties in both initial conditions and system parameters. The algorithm is based on VALENCIA-IVP, which has been developed recently for the computation of verified enclosures of the solution sets of initial...
A robust computational technique for a system of singularly perturbed reaction-diffusion equations
A simple recursive estimator with on-line orthogonalization of the input sequence
A simple scheme for semi-recursive identification of Hammerstein system nonlinearity by Haar wavelets
A simple semi-recursive routine for nonlinearity recovery in Hammerstein systems is proposed. The identification scheme is based on the Haar wavelet kernel and possesses a simple and compact form. The convergence of the algorithm is established and the asymptotic rate of convergence (independent of the input density smoothness) is shown for piecewiseLipschitz nonlinearities. The numerical stability of the algorithm is verified. Simulation experiments for a small and moderate number of input-output...