Journal of Control Science and Engineering
 Journal metrics
Acceptance rate17%
Submission to final decision57 days
Acceptance to publication29 days
CiteScore0.720
Impact Factor-
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Intelligent Tuning of PID Using Metaheuristic Optimization for Temperature and Relative Humidity Control of Comfortable Rooms

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 Journal profile

Journal of Control Science and Engineering publishes research investigating the design, simulation and modelling, implementation, and analysis of methods and technologies for control systems and applications.

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Journal of Control Science and Engineering maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

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We currently have a number of Special Issues open for submission. Special Issues highlight emerging areas of research within a field, or provide a venue for a deeper investigation into an existing research area.

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Research Article

Hybrid Robust Fault-Tolerant Control with Random Delay NCS

In this paper, a hybrid fault-tolerant control method with off-line design and online scheduling is proposed for NCS with actuator faults, random delay, and external finite energy disturbance. The problem of less conservatism of robust generalized hybrid fault-tolerant control is studied. Firstly, a closed-loop fault model of the system with random delay parameters was established according to the Bernoulli 0-1 distribution; all possible prior faults are divided into a few intervals according to certain rules, and then an interval fault-tolerant controller is designed off-line according to the prior faults of each interval. Secondly, when the fault is estimated online, the corresponding interval fault-tolerant controller is called through the scheduling mechanism to achieve rapid fault tolerance of prior faults within the interval and mitigate the impact of other faults within the interval, which provides a guarantee for subsequent safe reconstruction control. Finally, the effectiveness of the proposed method is verified by Matlab simulation.

Research Article

Sliding Mode-Based Control of a UAV Quadrotor for Suppressing the Cable-Suspended Payload Vibration

This paper addresses the problem of damping vibrations of a cable-suspended payload during positioning of the quadrotor. A nonlinear model is derived for the coupled quadrotor-pendulum system in the X-Z plane using Euler–Lagrange formulation. Sliding mode control (SMC) is used for horizontal positioning and payload vibration damping, while a feedback linearizing controller is used for both altitude and attitude control. The SMC surface parameters are determined by placing the eigenvalues of the linearized system at a desired position. The simulation results show the effectiveness of the proposed control method in minimizing payload vibration by comparing it with a partial feedback linearizing controller and a ZVDD input shaper.

Research Article

State Estimation Based on Sigma Point Kalman Filter for Suspension System in Presence of Road Excitation Influenced by Velocity of the Car

The states of the suspension system including the road excitation depend on the road quality, the velocity of the car, and the sprung mass. Those states play a very important role in the control problem of stability, ride comfort, ride safety, and dynamic wheel load of the suspension systems. The velocities and deflections of the sprung mass and unsprung mass would not be measured fully in the practice. Therefore, it must be estimated by other measured quantities from the system such as acceleration and deflection of sprung mass and unsprung mass. To control the active suspension system, its states need to be estimated accurately and guaranteed the response time. This paper presents the method using the sigma point Kalman filter to estimate the suspension system’s states including the road excitation, the deflections, and the velocities of the sprung mass and unsprung mass. The mathematical model of the suspension system is rewritten for the state estimation problem, and the stochastic load profile is supposed the main noise input. The stochastic characteristic of the road excitation depending on the car’s velocity is taken into account in the model used for suspension system state estimation. The results calculated based on the practical experiment data for specific road profile with some particular velocities of the car show that the suspension system states are estimated quite accurately in comparison with the practice states.

Research Article

Reproducibility Experimentation among Computer-Aided Inspection Software from a Single Point Cloud

The ISO GPS and ASME Y14.5 standards have defined dimensional and geometrical tolerance as a way to express the limits of surface part variations with respect to nominal model surfaces. A quality-control process using a measuring device verifies the conformity of the parts to these tolerances. To convert the control measurement points as captured by a device such as a coordinate measurement machine (CMM) or noncontact scan, it is necessary to select the appropriate algorithm (e.g., least square size and maximum inscribed size) and to include the working hypotheses (e.g., treatment of outliers, noise filtering, and missing data). This means that the operator conducting the analysis must decide on which algorithm to use. Through a literature review of current software programs and algorithms, many inaccuracies were found. A benchmark was therefore developed to compare the algorithm performance of three computer-aided inspection (CAI) software programs. From the same point cloud and on the same specifications (requirements and tolerances), three CAI options have been tested with several dimensional and geometrical features.

Research Article

Faults Detection Using Sliding Mode Observer and Its Application on Elevating Servo Systems

The elevating servo system (ESS) of vehicle-mounted howitzer (VMH) is a typical closed-loop electrohydraulic position servo system, and the faults of its actuator and sensor seriously affect the safety and reliability of the system. In practice, model uncertainty, nonlinearities, unknown disturbance, and output noise present enormous challenges to conduct fault detection of the system. In the current paper, an online fault detection scheme using the sliding mode technology is proposed. Not only the derivation method of state equation and some common fault expressions but also a new design of sliding mode observer with the ability to eliminate the influences of the above factors on detection results is given. The observer’s parameter matrices are obtained by the linear matrix inequality. To promote the fault detection capability, a statistical-based dynamic threshold is developed to detect actuator faults and sensor faults simultaneously. Finally, experimental studies are implemented on a test rig for validating the system model, and the results of four experiments show the effectiveness of proposed methods.

Research Article

Multiaxis Servo Synergic Control Based on Sliding Mode Controller

This paper investigates a relative coupling control strategy based on the sliding mode controller to solve the problem of poor synergy performance of the axes of the dynamic seat during operation and to realize the multiaxis servo synergic control with variable proportions during the operation of the system. Firstly, the proposed method is theoretically proven to be accurate in eliminating tracking errors and synchronization errors between servos in the process of system operation. Secondly, the system simulation model is built in the Simulink simulation environment of MATLAB. On one hand, the final simulation result verifies the accuracy of the theoretical proof. On the other hand, the control strategy is characterized by fast convergence, high synchronization accuracy, and strong robustness; thus, the system has excellent synergy performance. Finally, the motion control platform of the dynamic seat was built for physical verification. The experimental result shows the effectiveness and feasibility of the control strategy.

Journal of Control Science and Engineering
 Journal metrics
Acceptance rate17%
Submission to final decision57 days
Acceptance to publication29 days
CiteScore0.720
Impact Factor-
 Submit