The primary importance of the paper is the application of the efficient formulation for the simulation of open-loop lightweight robotic manipulator. The framework employed in the paper makes use of the spatial operator algebra and the associated equations are expressed in joint space. This compact representation of the manipulator dynamics makes it possible to solve the robot forward and inverse dynamics problems in a recursive and fast manner. In the current form, the presented algorithm can be applied for the dynamics simulation of an open-loop chain system possessing any number of joints. Specifically, the formulation has been successfully applied for the analysis of the 7DOF KUKA LWR robot. Results from a number of test cases for the robot demonstrate the verification of the calculations.
The optimal design of excitation signal is a procedure of generating an informative input signal to extract the model parameters with maximum pertinence during the identification process. The fractional calculus provides many new possibilities for system modeling based on the definition of a derivative of noninteger-order. A novel optimal input design methodology for fractional-order systems identification is presented in the paper. The Oustaloup recursive approximation (ORA) method is used to obtain the fractional-order differentiation in an integer order state-space representation. Then, the presented methodology is utilized to solve optimal input design problem for fractional-order system identification. The fundamental objective of this approach is to design an input signal that yields maximum information on the value of the fractional-order model parameters to be estimated. The method described in this paper was verified using a numerical example, and the computational results were discussed.
We consider the downlink of an orthogonal frequency division multiplexing (OFDM) based cell that accommodates calls from different service-classes with different resource requirements. We assume that calls arrive in the cell according to a quasi-random process, i.e., calls are generated by a finite number of sources. To calculate the most important performance metrics in this OFDM-based cell, i.e., congestion probabilities and resource utilization, we model it as a multirate loss model, show that the steady-state probabilities have a product form solution (PFS) and propose recursive formulas which reduce the complexity of the calculations. In addition, we study the bandwidth reservation (BR) policy which can be used in order to reserve subcarriers in favor of calls with high subcarrier requirements. The existence of the BR policy destroys the PFS of the steady-state probabilities. However, it is shown that there are recursive formulas for the determination of the various performance measures. The accuracy of the proposed formulas is verified via simulation and found to be satisfactory.
This paper presents a novel sideslip angle estimator based on the pseudo-multi-sensor fusion method. The
kinematics-based and dynamics-based sideslip angle estimators are designed for sideslip angle estimation.
Also, considering the influence of ill-conditioned matrix and model uncertainty, a novel sideslip angle estimator
is proposed based on the wheel speed coupling relationship using a modified recursive least squares
algorithm. In order to integrate the advantages of above three sideslip angle estimators, drawing lessons
from the multisensory information fusion technology, a novel thinking of sideslip angle estimator design is
presented through information fusion of pseudo-multi-sensors. Simulations and experiments were carried
out, and effectiveness of the proposed estimation method was verified.
A class of Xorshift Random Number Generators (RNGs) are introduced by Marsaglia. We have proposed an algorithm which constructs a primitive Xorshift RNG from a given prim- itive polynomial. We also have shown a weakness present in those RNGs and suggested its solution. A separate algorithm also proposed which returns a full periodic Xorshift generator with desired number of Xorshift operations.