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Aiming at the positioning accuracy control problem in the running of the assembly machine for assembled camshaft, a kind of position controller based on the feedforward‐feedback control of speed and acceleration is designed.

It combines feedforward‐feedback control with the quartic displacement curve acceleration/deceleration algorithm.

The axial dimension and the phase angle of the cam obtained after being assembled is checked. The result shows that for each type of camshaft, the error of the axial dimension of the cam is less than ±0.2mm and the error of the phase angle of the cam is less than ±30′. In addition, production efficiency is greatly improved (the assembling time is 90‐120S/piece).

The paper combines feedforward‐feedback control with the quartic displacement curve acceleration/deceleration algorithm for the first time.

Points out that the topic of performance measurement (PM) has received a lot of attention in recent years, with many competing PM models vying for management attention, and recently much of the literature on PM has been summarized in a taxonomic framework by Ballantine and Brignall (1995). Drawing on this taxonomy, describes research which updates the original model for PM in services developed by Fitzgerald et al. (1991), as summarized by Brignall et al. in the November 1991 issue of Management Accounting (UK). Shows that the new model considers PM at all levels of a business, not just at the strategic business unit (SBU) level, and makes propositions relevant to PM system design including information technology (IT) aspects.

This research aims to present a novel cooperative control architecture designed specifically for roads with variations in height and curvature. The primary objective is to enhance the longitudinal and lateral tracking accuracy of the vehicle.

In addressing the challenges posed by time-varying road information and vehicle dynamics parameters, a combination of model predictive control (MPC) and active disturbance rejection control (ADRC) is employed in this study. A coupled controller based on the authors’ model was developed by utilizing the capabilities of MPC and ADRC. Emphasis is placed on the ramifications of road undulations and changes in curvature concerning control effectiveness. Recognizing these factors as disturbances, measures are taken to offset their influences within the system. Load transfer due to variations in road parameters has been considered and integrated into the design of the authors’ synergistic architecture.

The framework's efficacy is validated through hardware-in-the-loop simulation. Experimental results show that the integrated controller is more robust than conventional MPC and PID controllers. Consequently, the integrated controller improves the vehicle's driving stability and safety.

The proposed coupled control strategy notably enhances vehicle stability and reduces slip concerns. A tailored model is introduced integrating a control strategy based on MPC and ADRC which takes into account vertical and longitudinal force variations and allowing it to effectively cope with complex scenarios and multifaceted constraints problems.

Large optical mirror processing systems (LOMPSs) consist of multiple subrobots, and correlated disturbance terms between these robots often lead to reduced processing accuracy. This abstract introduces a novel approach, the nonlinear subsystem adaptive dispersed fuzzy compensation control (ADFCC) method, aimed at enhancing the precision of LOMPSs.

The ADFCC model for LOMPS is developed through a nonlinear fuzzy adaptive algorithm. This model incorporates control parameters and disturbance terms (such as those arising from the external environment, friction and correlation) between subsystems to facilitate ADFCC. Error analysis is performed using the subsystem output parameters, and the resulting errors are used as feedback for compensation control.

Experimental analysis is conducted, specifically under the commonly used concentric circle processing trajectory in LOMPS. This analysis validates the effectiveness of the control model in enhancing processing accuracy.

The ADFCC strategy is demonstrated to significantly improve the accuracy of LOMPS output, offering a promising solution to the problem of correlated disturbances. This work holds the potential to benefit a wide range of practical applications.

The purpose of this paper is to investigate the time-varying finite-time formation tracking control problem for multiple unmanned aerial vehicle systems under switching topologies, where the states of the unmanned aerial vehicles need to form desired time-varying formations while tracking the trajectory of the virtual leader in finite time under jointly connected topologies.

A consensus-based formation control protocol is constructed to achieve the desired formation. In this paper, the time-varying formation is specified by a piecewise continuously differentiable vector, while the finite-time convergence is guaranteed by utilizing a non-linear function. Based on the graph theory, the finite-time stability of the close-loop system with the proposed control protocol under jointly connected topologies is proven by applying LaSalle’s invariance principle and the theory of homogeneity with dilation.

The effectiveness of the proposed protocol is verified by numerical simulations. Consequently, the proposed protocol can successfully achieve the predefined time-varying formation in finite time under jointly connected topologies while tracking the trajectory generated by the leader.

This paper proposes a solution to simultaneously solve the control problems of time-varying formation tracking, finite-time convergence, and switching topologies.

This paper aims to present a cooperative adaptive cruise control, called stable smart driving model (SSDM), for connected and autonomous vehicles (CAVs) in mixed traffic streams with human-driven vehicles.

Considering the linear stability, SSDM is able to provide smooth deceleration and acceleration in the vehicle platoons with or without cut-in. Besides, the calibrated Virginia tech microscopic energy and emission model is applied in this study to investigate the impact of CAVs on the fuel consumption of the vehicle platoon and traffic flows. Under the cut-in condition, the SSDM outperforms ecological SDM and SDM in terms of stability considering different desired time headways. Moreover, single-lane vehicle dynamics are simulated for human-driven vehicles and CAVs.

The result shows that CAVs can reduce platoon-level fuel consumption. SSDM can save the platoon-level fuel consumption up to 15%, outperforming other existing control strategies. Considering the single-lane highway with merging, the higher market penetration of SSDM-equipped CAVs leads to less fuel consumption.

The proposed rule-based control method considered linear stability to generate smoother deceleration and acceleration curves. The research results can help to develop environmental-friendly control strategies and lay the foundation for the new methods.

Computer production management systems are far more common than they were even five years ago, as a result of reductions in the costs of computer hardware and the growing use of package software by both large and small firms. However, there are still many problems associated with such computer systems. Though the symptoms are somewhat different depending on whether we are concerned with large or small companies, the root cause is the same: a lack of any clear philosophy of what production management systems do and how they should be designed. In addition companies face a need to integrate hardware from many different suppliers and the ability to do this would also be helpful to smaller firms. At the moment such integration is difficult to carry out.

This special “Anbar Abstracts” issue of the Journal of Management in Medicine is split into six sections covering abstracts under the following headings: General Management; Personnel and Training; Quality in Health Care; Health Care Marketing; Financial Management; Information Technology.

The purpose of this paper is to improve the control precision of the station-keeping control for a stratosphere airship through the feedforward-feedback PID controller which is designed by the wind speed prediction based on the incremental extreme learning machine (I-ELM).

First of all, the online prediction of wind speed is implemented by the I-ELM with rolling time. Second, the feedforward-feedback PID controller is designed through the position information of the airship and the predicted wind speed. In the end, the one-dimensional dynamic model of the stratosphere airship is built, and the controller is applied in the numerical simulation.

Based on the conducted numerical simulations, some valuable conclusions are obtained. First, through the comparison between the predicted value and true value of the wind speed, the wind speed prediction based on I-ELM is very accurate. Second, the feedforward-feedback PID controller designed in this paper is very effective.

This paper is very valuable to the research of a high-accuracy station-keeping control of stratosphere airship.

The purpose of this paper is to present a neural network approach to control performance assessment.

The performance index under study is based on the minimum variance control benchmark, a radial basis function network (RBFN) is used as the pre‐whitening filter to estimate the white noise sequence, and a stable filtering and correlation analysis method is adopted to calculate the performance index by estimating innovations sequence using the RBFN pre‐whitening filter. The new approach is compared with the auto‐regressive moving average model and the Laguerre model methods, for both linear and nonlinear cases.

Simulation results show that the RBFN approach works satisfactorily for both linear and nonlinear examples. In particular, the proposed scheme shows merits in assessing controller performance for nonlinear systems and surpasses the Laguerre model method in parameter selection.

A RBFN approach is proposed for control performance assessment. This new approach, in comparison with some well‐known methods, provides satisfactory performance and potentials for both linear and nonlinear cases.