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The purpose of this paper is to propose a novel serial structure repetitive control scheme for shunt active power filter (SAPF) to improve the steady-state accuracy and dynamic performance of SAPF. The novelty of this scheme lies in the reconfiguration of the pole of repetitive control internal model, so that the dynamic response of the repetitive control is improved greatly.

By analyzing the mathematical model of repetitive control, the repetitive control delay can reduce by giving up the needless poles of the internal model, and the general mk + i repetitive control can be designed through the pole configuration method. The controller can track a set of specific order harmonics.

The experimental results are coincident with the theoretical analyses, which prove the effectiveness of the proposed method on harmonic suppression and great performance in dynamic response.

An APF prototype has been designed with the serial structure repetitive control proposed in this paper, and it can successfully eliminate the harmonics current of nonlinear load with faster dynamic response. Moreover, the proposed controller can be applied to any three-phase system for fast dynamic response and high tracking accuracy.

In this paper, the mathematical model of the repetitive control for specific set of harmonica is developed. A novel serial structure repetitive control is designed, so that the SAPF can eliminate the fundamental reactive current and specific order harmonics and speed up the dynamic response of the repetitive control.

Proposes a conceptual interpretative framework as a reading key to management differences in the two principal manufacturing contexts – intermittent manufacturing and repetitive manufacturing – within the three basic operations management subsystems: planning, inventory control and shopfloor control.

The purpose of this paper is to propose a double exponentially weighted moving average control chart using repetitive sampling (RS-DEWMA) for a normally distributed process variable to improve the efficiency of detecting small process mean shift.

The algorithm for the implementation of the proposed chart is developed and the formulae for the in-control and out-of-control average run lengths (ARLs) are derived. Tables of ARLs are presented for various process mean shift. The performance of the proposed chart is investigated in terms of the average run-length for small process mean shift and compared with the existing DEWMA control chart. Numerical examples are given as illustration of the design and implementation of the proposed chart.

The proposed control chart is more efficient than the existing DEWMA control chart in the detection of small process mean shifts as it consistently gives smaller ARL values and quickly detects the process shift. However, the performance of the proposed chart relatively deteriorates for large smoothing constants.

The application of repetitive sampling in the control chart literature is gaining wide acceptability. The design and implementation of the RS-DEWMA control chart offers a new approach in the detection of small process mean shift by process control personnel.

This paper fills a gap in the literature by examining the performance of the repetitive sampling DEWMA control chart. The use of repetitive sampling technique in the control chart is discussed in the literature, however, its use based on the DEWMA statistic has not been considered in this context.

Proposes a classification of different production categories and their respective productive systems and defines various classes of plants which carry out repetitive manufacturing. Also examines the applicative possibilities of repetitive production in regard to production volumes required and grades of flexibility necessary. Among the intermittent production systems described are those which present strong analogies with repetitive manufacturing systems; in particular that of the Zanussi‐Electrolux plant in Susegana, Italy. Finally, describes the fundamental elements which differentiate repetitive production from intermittent production.

This paper is concerned with the repetitive trajectory tracking control for space manipulators under model uncertainties and vibration disturbances.

The model uncertainties and link vibration of manipulators will degrade the tracking performance of space manipulators; in this paper, a new hybrid control scheme that consists of a composite hierarchical anti-disturbance controller and an iterative learning controller is developed to solve this problem.

The composite hierarchical controller can effectively attenuate model uncertainties and reject vibration disturbances, whereas the iterative learning controller is able to improve the tracking accuracy for repetitive reference trajectory.

The proposed scheme compensates for the shortcomings of iterative learning control which can only deal with repetitive disturbances, ensuring the accuracy and repeatability of space manipulators under model uncertainties and random disturbances.

Applying discrete linear optimal control to robot manipulators faces two challenging problems, namely nonlinearity and uncertainty. This paper aims to overcome nonlinearity and uncertainty to design the discrete optimal control for electrically driven robot manipulators.

Two novel discrete optimal control approaches are presented. In the first approach, a control-oriented model is applied for the discrete linear quadratic control while modeling error is estimated and compensated by a robust time-delay controller. Instead of the torque control strategy, the voltage control strategy is used for obtaining an optimal control that is free from the manipulator dynamics. In the second approach, a discrete optimal controller is designed by using a particle swarm optimization algorithm.

The first controller can overcome uncertainties, guarantee stability and provide a good tracking performance by using an online optimal algorithm whereas the second controller is an off-line optimal algorithm. The first control approach is verified by stability analysis. A comparison through simulations on a three-link electrically driven robot manipulator shows superiority of the first approach over the second approach. Another comparison shows that the first approach is superior to a bounded torque control approach in the presence of uncertainties.

The originality of this paper is to present two novel optimal control approaches for tracking control of electrically driven robot manipulators with considering the actuator dynamics. The novelty is that the proposed control approaches are free from the robot's model by using the voltage control strategy. The first approach is a novel discrete linear quadratic control design supported by a time-delay uncertainty compensator. The second approach is an off-line optimal design by using the particle swarm optimization.

Discrete control of robot manipulators with uncertain model is the purpose of this paper.

The proposed control design is model-free by employing an adaptive fuzzy estimator in the controller for the estimation of uncertainty as unknown function. An adaptive mechanism is proposed in order to overcome uncertainties. Parameters of the fuzzy estimator are adapted to minimize the estimation error using a gradient descent algorithm.

The proposed model-free discrete control is robust against all uncertainties associated with the model of robotic system including the robot manipulator and actuators, and external disturbances. Stability analysis verifies the proposed control approach. Simulation results show its efficiency in the tracking control.

A novel model-free discrete control approach for electrically driven robot manipulators is proposed. An adaptive fuzzy estimator is used in the controller to overcome uncertainties. The parameters of the estimator are regulated by a gradient descent algorithm. The most gradient descent algorithms have used a known cost function based on the tracking error for adaptation whereas the proposed gradient descent algorithm uses a cost function based on the uncertainty estimation error. Then, the uncertainty estimation error is calculated from the joint position error and its derivative using the closed-loop system.

This paper reviews research examining how the use of new office technologies can contribute to the risk of stress‐related health changes. Looking to the future of office work, the potential stressors associated with expert systems are discussed and the conditional nature of stress demonstrated.

Repetitive lifting tasks have detrimental effects upon balance control and may contribute toward fall injuries, yet despite this causal linkage, risk factors involved remain elusive. The purpose of this paper is to evaluate the effects of different weights and lifting postures on balance control using simulated repetitive lifting tasks.

In total, 20 healthy male participants underwent balance control assessments before and immediately after a fatiguing repetitive lifting tasks using three different weights in a stoop (ten participants) or a squat (ten participants) lifting posture. Balance control assessments required participants to stand still on a force plate with or without a foam (which simulated an unstable surface) while center of pressure (CoP) displacement parameters on the force plate was measured.

Results reveal that: increased weight (but not lifting posture) significantly increases CoP parameters; stoop and squat lifting postures performed until subjective fatigue induce a similar increase in CoP parameters; and fatigue adversely effected the participant’s balance control on an unstable surface vis-à-vis a stable surface. Findings suggest that repetitive lifting of heavier weights would significantly jeopardize individuals’ balance control on unstable supporting surfaces, which may heighten the risk of falls.

This research offers an entirely new and novel approach to measuring the impact that different lifting weights and postures may have upon worker stability and consequential fall incidents that may arise.

This paper aims at improving progress tracking and control of repetitive projects by developing a novel framework that automates the documentation of as-built information directly into the project schedule and also introduces enhanced linear scheduling formulation to support project control decisions.

The proposed framework uses e-mail technology to facilitate detailed tracking of daily as-built events of all parties through bidirectional communication between site and head office. It also provides a new formulation for more accurate critical path and linear scheduling computation to accurately update the project's time and cost during construction.

Using a case study of a road project, the paper proves that the proposed framework reduces as-built documentation effort and its schedule updates are more responsive to all as-built events than traditional scheduling techniques.

The proposed method applies to linear projects (e.g. highways) and can be extended to other repetitive projects such as high-rise buildings. It can also be extended to include voice features and procedures for forensic schedule analysis.

The developed methodology presents a low-cost approach to document timely progress information for decision makers of massive linear projects (often associated with infrastructure) to have better control over the execution of projects, save documentation time and cost, and avoid disputes and problems.

This research contributes in improving construction productivity by collecting timely as-built information using affordable communication technologies. It also presents novel advancements to the existing scheduling and control techniques to suit linear projects, which are most challenging.