Sliding Mode-Based Control of a UAV Quadrotor for Suppressing the Cable-Suspended Payload VibrationRead the full article
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.
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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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.
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.
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.
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.
Integrated Sensor Fault Diagnosis and Fault-Tolerant Control for Manipulator
In this paper, an integrated scheme including fault diagnosis and fault-tolerant controller design is proposed for the manipulator system with the sensor fault. Any constant fault or time-varying fault can be estimated by the fault diagnosis scheme based on the adaptive observer rapidly and accurately, and the designed parameters can be solved by the linear matrix inequality. Using the fault estimation information, a fault-tolerant controller combining the characteristics of the proportional differentiation control and the sliding model control is designed to trace the expected trajectory via the back-stepping method. Finally, the effectiveness of the above scheme is verified by the simulation results.
Design and Advanced Control of Intelligent Large-Scale Hydraulic Synchronization Lifting Systems
Lifting systems are in great demand since more and more massive buildings or bridges tend to be shifted or lifted integrally. Hydraulic cylinders in traditional lifting systems are usually supplied by a common pump with an oil tank, which brings long distance hydraulic pipes and signal lines. This paper designs a new architecture of an intelligent lifting system, with self-contained hydraulic power supply system, wireless communication modules, and distributed controller. Based on the designed architecture of the intelligent lifting system, an advanced iterative learning control strategy is proposed to enhance its synchronization performance. With the proposed advanced control strategy, synchronization is achieved in a finite time interval even under the effect of communication time delays and saturations. The distributed controller of a lifting subsystem only uses the delayed information received from subsystems around. This is distinguished from traditional lifting systems, in which all of the lifting subsystems are normally controlled in a centralized way.