An iterative algorithm for solving ill-conditioned linear least squares problems

Linear Least Squares（LLS） problems are particularly difficult to solve because they are frequently ill-conditioned, and involve large quantities of data. Ill-conditioned LLS problems are commonly seen in mathematics and geosciences, where regularization algorithms are employed to seek optimal solutions. For many problems, even with the use of regularization algorithms it may be impossible to obtain an accurate solution. Riley and Golub suggested an iterative scheme for solving LLS problems. For the early iteration algorithm, it is difficult to improve the well-conditioned perturbed matrix and accelerate the convergence at the same time. Aiming at this problem, self-adaptive iteration algorithm（SAIA） is proposed in this paper for solving severe ill-conditioned LLS problems. The algorithm is different from other popular algorithms proposed in recent references. It avoids matrix inverse by using Cholesky decomposition, and tunes the perturbation parameter according to the rate of residual error decline in the iterative process. Example shows that the algorithm can greatly reduce iteration times, accelerate the convergence,and also greatly enhance the computation accuracy.

Lateral Stability Improvement of Car-Trailer Systems Using Active Trailer Braking Control

An active trailer braking controller to improve the lateral stability of car-trailer systems is presented. The special and complex structures of these types of vehicles exhibit unique unstable motion behavior, such as the trailer swing, jack-knifing and rollover. These unstable motion modes may lead to fatal accidents. The effects of passive mechanical parameters on the stability of car-trailer systems have been thoroughly investigated. Some of the passive parameters, such as the center of gravity of the trailer, may be drastically varied during various operating conditions. Even for an optimal design of a car-trailer system, based on a specific passive parameter set, the lateral stability cannot be guaranteed. In order to improve the lateral stability of car-trailer systems, an active trailer braking controller is designed using the Linear Quadratic Regular （LQR） technique. To derive the controller, a vehicle model with 3 Degrees Of Freedom （DOF） is developed to represent the car-trailer system. A single lane-change maneuver has been simulated to examine the performance of the controller and the numerical results are compared with those of the baseline design. The benchmark investigation indicates that the optimal controller based on the LQR technique can effectively improve the high-speed lateral stability of the car-trailer system.

On Regular Linear Relations

For a closed linear relation in a Banach space the concept of regularity is introduced and studied. It is shown that many of the results of Mbekhta and other authors for operators remain valid in the context of multivalued linear operators. We also extend the punctured neighbourhood theorem for operators to linear relations and as an application we obtain a characterization of semiFredholm linear relations which are regular.

Sufcient Conditions for Error Bounds and Linear Regularity in Banach Spaces

In this paper, we study error bounds for lower semicontinuous functions defined on Banach space and linear regularity for finitely many closed subset in Banach spaces. By using Clarke＇s subd- ifferentials and Ekeland variational principle, we establish several sufficient conditions ensuring error bounds and linear regularity in Banach spaces.

Stock price index analysis of four OPEC members:a Bayesian approach

This study examines the relationship between macroeconomic variables and stock price indices of four prominent OPEC oil-exporting members.Bayesian model averaging(BMA)and regularized linear regression(RLR)are employed to address uncertainties arising from different estimation models and variable selection.Jointness is utilized to determine the nature of relationships among variable pairs.The case study spans macroeconomic variables and stock prices from 1996 to 2018.BMA findings reveal a strong positive association between stock price indices and both consumer price index(CPI)and broad money growth in each analyzed OPEC country.Additionally,the study suggests a weak negative correlation between OPEC oil prices and the stock price index.RLR results align with BMA analysis,offering insights valuable for policymakers and international wealth managers.