IFAC Journal of Systems and Control最新文献

This paper deals with simultaneous credible bands (SCBs) for transfer function estimates based on Gaussian posteriors of the impulse response vector derived from identification of high-order FIR models, where SCBs quantify estimation errors of functions over their entire domain. Though conservative, SCBs for step responses and gain/phase functions are obtained by maximizing and minimizing them over the uncertainty sets specified by critical values of ${\chi }^2$ statistics associated with the Gaussian posterior. This procedure also applies to deriving (exact) pointwise credible bands (PCBs) using relevant critical values. In numerical studies, we compute the failure rates that SCBs fail to include the true step response or gain function over their respective domains; thereby an empirical method for computing less conservative SCBs is developed.

One of the most important decisions in any manufacturing company is how to schedule the operations on the available machines. In several industries, the nature of the job imposes certain constraints to operations scheduling. In a no-wait flowshop, once a job starts on the first machine, it has to continue being processed on the next ones, without any interruptions. As an extension of the flowshop scheduling problem, the no-wait version is also very difficult to be solved to optimality within a reasonable time, and many heuristics have been proposed for it. This paper aims to classify existing solution algorithms proposed to solve the no-wait flowshop scheduling problem with setup times and some of its variants. Our classification is based on the type of setup considered; we also review all available performance measures in the literature. We show how combining a heuristic to generate a good initial solution, local search procedures, insertion and swapping of job positions and techniques developed originally to solve transportation problems are among the popular and efficient techniques for this problem. We identify the main available benchmark instance sets and propose several promising avenues to guide future research.

To obtain fixed-time stability and finite-time convergence of altitude and yaw motions of a mini-quadrotor subjected to perturbations, this paper proposes a new altitude/yaw motion finite-time tracking control. First, a nonsingular terminal sliding manifold is proposed for both subsystems whose states converge to their desired values in finite-time. To address the uncertainties of the system, a robust fixed-time switching controller is proposed whose stability is proposed and its settling-time depends only on control of the parameters and not the initial conditions. The validation of the proposed approach is presented based on a real mini-quadrotor.

This paper considers the problem of expanding and reducing Laman graphs, of which each vertex has at most four neighbors. To this end, several simple algorithms that can be repeatedly applied to construct or degenerate a given four-degree limited Laman graph are proposed. The correctness of the proposed algorithms is asserted based on Laman’s criterion. Numerous examples and discussions are provided to demonstrate the applicability and impact of these algorithms.

The study investigates two categories of perfusion-based pulmonary blood flow analysis: model-based and model-less methods. The model-based approach yields plausible results, but requires strict parameter settings and presents challenges in handling. On the other hand, the model-less approach is simpler but limited to a single input analysis, necessitating an inverse problem to estimate the impulse response from input–output relationships. To overcome these limitations, this article proposes a model-less method that combines simplicity and accuracy, enabling multi-input system analysis and aiming for standardized analysis. They leverage deep learning convolution to directly estimate the impulse response, allowing for multi-input analysis. Comparative experiments demonstrate that the proposed method is easy to implement and exhibits a low estimation error within the measured signal-to-noise ratio (SNR) range, even though it is sensitive to noise. Furthermore, the proposed method is evaluated through waveform analysis, specifically Delay and Dispersion in Experiment 1, where it is compared with conventional methods. In Experiment 2, blood flow analysis is performed on a patient with a defect in the left pulmonary artery. The results indicate high convergence, independence from input waveforms, and effective analysis of cases with vascular stenosis. Moreover, the method enables multi-input system analysis, consistently yielding results consistent with medical findings, even for patients with left pulmonary artery defects.

In vehicle dynamics control, many variables of interest cannot be directly measured, as sensors might be costly, fragile or even not available. Therefore, real-time estimation techniques need to be used. The previous approach suffers from two main drawbacks: (i) the approximations due to model mismatch might jeopardize the performance of the final estimation-based control; (ii) each new estimator requires the calibration from scratch of a dedicated model. In this paper, we propose a twin-in-the-loop scheme, where the ad-hoc model is replaced by an accurate full-fledged simulator of the vehicle, typically available to vehicles manufacturers and suitable for the estimation of any on-board variable, coupled with a compensator within a closed-loop observer scheme. Given the black-box nature of the digital twin, a data-driven methodology for observer tuning is developed, based on Bayesian optimization. The effectiveness of the proposed estimation method for the estimation of vehicle states and forces, as compared to traditional model-based Kalman filtering, is experimentally shown on a dataset collected with a sport car. In summary, the proposed approach achieves, in the most aggressive driving scenarios, an average improvement of $0.5°$ for the side-slip angle estimation, and of more than $500$ N for the front lateral forces estimation.

Autonomous guidance and control (G&C) is vital for planetary surface exploration missions. The challenge of space applications is to find computational efficient algorithms that can be employed on-board while giving optimal and feasible solutions. Addressing this issue, this article presents a G&C solution for planetary surface relocations using thrust steering based on analytical suboptimal algorithms. The proposed solution is an alternative to on-board optimization using feedback linearization, time-optimal trajectories for each individual axis and a novel snap-based control, which considers the limits of the spacecraft design. The robustness of the G&C solution to model uncertainties is demonstrated using Monte Carlo simulations on the nonlinear surface dynamics of 67P/Churyumov–Gerasimenko (67P). Compared to other G&C approaches, the algorithms can easily be implemented on-board, reduce verification & validation costs, and minimize computational effort.

We study a pursuit-evasion differential game in which three agents move with simple motion on the Euclidean plane. Two of them, the cutters (pursuers), aim to capture a fugitive ship (the evader) as soon as possible. Having an opposite goal, the fugitive ship seeks to avoid capture for as long as possible. The game ends when the distance between the fugitive and at least one of the cutters is smaller than a given value. We have divided the game into two cases: case 1, when all players have the same speed, and case 2, when the evader is faster than the pursuers. Unlike previous work, our main innovations are as follows. For case 1, we present a solution obtained using exclusively differential game techniques. The game of kind is solved by establishing a study of the barrier that defines the winner of the game. In addition, we obtained time-optimal strategies for all players, proving that they do not switch controls. For case 2, we obtain the primary solution and exhibit an example showing the existence of control switches.

In this paper, we focus on the periodic output regulation for a one-dimensional wave equation where the performance output is non-collocated with the control input. The exosystems considered here are multi-periodic time-varying, capable of generating periodic reference signals and disturbances within the domain and at the boundaries, each with distinct periods. Initially, a backstepping-based state feedback regulator is designed by tackling an ill-posed periodic regulator equation. Subsequently, leveraging an external matrix, we design a novel time-varying observer tailored for the transformed wave equation and the exosystems. An output feedback regulator is then obtained by replacing the states with their estimations. The tracking error is shown to decay exponentially and the closed-loop system is proved to be bounded. Some numerical simulations are presented to validate the results.

The control theory is one of the most fundamental branches of engineering as it implicates solving abilities of numerous non-linear engineering design problems efficiently. Again, Pontryagin’s maximum principle is one of the most salient topics of control theory as it is involved in solving various important problems. However, in the current highly complex situation, most of such real-life problems appear to be highly uncertain/imprecise in nature. Consequently, in order to analyse such problems accurately, uncertainty/flexibility of such problems cannot be overestimated. Motivating from this fact and as a necessity, in this study, the Pontryagin’s maximum principles are extended in interval environment for interval valued control problems (IVCPs). In this context, an IVCP is defined along with different formal terminologies. Further, the necessary and sufficient optimality conditions (i.e., Pontryagin’s maximum principles) are extended for IVCPs using existing interval ranking proposed by Bhunia and Samanta (2014). Further, in the second part of this work, in order to test the effectiveness of the proposed theories, an economic order quantity (EOQ) model is developed by considering dynamic servicing strategies in interval environment. With the help of numerical example, the proposed extension of Pontryagin’s maximum principles for IVCPs is well validated.