Tracking Error Accuracy Research Articles

Design and analysis of 3-UPU wave compensation platform based on improved sliding mode control

ABSTRACT In this paper, the 3-UPU parallel mechanism platform is designed through SolidWorks software, and the assembly model of the 3-UPU parallel mechanism is imported into the Simulink environment through Simscape/Multibody. Aiming at the heave motion of the ship at sea, an improved sliding mode controller is designed in this research, named as global fast terminal sliding mode controller, to track and compensate the ship heave motion data. In order to verify the effect of the designed controller, the traditional PID controller is selected for comparison. The results show that: when the traditional PID controller is used to track and compensate it, if the appropriate parameters are selected, the tracking effect is better, the tracking error is small but fluctuates up and down, and the tracking error accuracy is poor. After the introduction of the improved sliding mode controller proposed in this paper, when entering the stable stage, the tracking compensation effect of the improved controller is better than that of the traditional PID control, and the tracking error is smaller than that of the traditional PID control. The global fast terminal sliding mode control has good robustness and can be applied to the ship heave compensation system.

Adaptive fuzzy sliding mode control of the manipulator based on an improved super-twisting algorithm

The high-precision trajectory tracking and chatter-free performance of the manipulators are of great significance to the improvement of the automation level. Therefore, in view of the problems of chattering and tracking performance degradation of multi-joint manipulators caused by uncertain factors such as external disturbances and modeling errors, an adaptive fuzzy sliding mode control of the manipulator based on an improved super-twisting algorithm is proposed. First, fuzzy control is chosen to approximate the uncertainty of the manipulator model, which reduces the influence of unknown disturbances on the system, and then the adaptive law is utilized to automatically modify and improve the fuzzy rules to enhance the approximation capability; Second, an improved super-twisting algorithm is used on this basis to put the discontinuous term into the integral term to avoid chattering and eliminate the approximation error; Finally, a comparative simulation experiment is carried out with the 3-DOF manipulator as the research object. The experimental results show that the method in this paper improves the convergence speed by up to 69.74% and the tracking error accuracy by up to 85.11% over the fuzzy control based on adaptive reaching law with no chattering and little difference in control inputs, thus verifying the feasibility and superiority of the method.

Practical fixed-time bipartite consensus control for nonlinear multi-agent systems: A barrier Lyapunov function-based approach

This paper develops a practical fixed-time bipartite consensus control framework for the uncertain nonlinear multi-agent systems (MASs) via using a barrier Lyapunov function (BLF)-based approach. Distinguish from the most existing results, the unknown nonlinearities of MASs in this paper are tackled by utilizing the robustness of BLF instead of applying fuzzy logic systems/neural networks approximating. In order to avoid feasibility verification in the traditional BLF method, a piecewise and differentiable function named the shift function is skillfully inserted into the coordination transformation of the controller design process, allowing not only the initial value of MASs states to be chosen arbitrarily, but also the settling time of bipartite consensus errors can be pre-designated. According to the backstepping framework, an approximated-free control algorithm is developed by combining the shift function with BLF, which guarantees that for any initial state of MASs, the outputs of all the agents can achieve the practical fixed-time bipartite consensus tracking, and all the signals in closed-loop systems are bounded. Especially, the settling time and the tracking error accuracy can be appointed by the designer. Finally, simulation results are given to show the effectiveness of the proposed control method.

Optimal Augmented Linear and Nonlinear PD Control Design for Parallel Robot Based on PSO Tuner

This article presents the optimal control design for trajectory tracking of Delta\Par4-like parallel manipulator controlled by two augmented control schemes: Augmented PD Controller (APD) and Augmented Nonlinear PD (ANPD) Controller. Firstly, the Particle Swarm Optimization (PSO) technique is employed for optimal tuning of design parameters for each control structure in order to reach better dynamic performance. Then, two comparisons are made in order to evaluate the performance of parallel robot based on optimized ANPD and APD controllers. The first comparison is established in terms of tracking error accuracy due to the involved controllers, while the other one is based on the strength of robustness granted by each controller against variation of parallel robot parameters. The verification of performance comparisons is made via simulation within the environment of MATLAB/Simulink programming platform. The circular path is used for performance evaluation of controllers for trajectory tracking control. The simulated results have showed that ANPD controller outperforms the APD controller in terms of tracking accuracy and robustness.

Prescribed performance control of strict‐feedback systems under actuation saturation and output constraint via event‐triggered approach

SummaryIn this work, we study the performance‐guaranteed event‐triggered control for a class of uncertain nonlinear systems in strict‐feedback form subject to input saturation and output constraint. The prescribed performance (ie, convergence rate, tracking error accuracy) and output constraint are firstly taken into account for nonlinear systems with event‐triggered input. By blending a speed transformation into the barrier Lyapunov function and introducing an intermediate variable to the system, two different event‐triggered control schemes are proposed for systems with and without saturation, respectively. Each scheme has two rules to determine triggering time sequences, one for control signal updating and the other for control signal transmission with the latter being a subsequence of the first. Meanwhile, it is proved that the tracking error converges to a preset compact set around zero at the prescribed decay rate and the output is maintained within a given bound at all times. Simulation verification also confirms the effectiveness of the proposed approach.

Control of MIMO nonlinear systems: A data-driven model inversion approach

A data-driven control design approach for Multiple Input Multiple Output nonlinear systems is presented in this paper. The approach, called Nonlinear Inversion Control (NIC), is based on the identification of a polynomial prediction model of the system to control and the on-line inversion of this model. The main features of the NIC approach can be summarized as follows: it does not require a physical model of the plant to control which, in many real-world situations, may be difficult to derive; it can guarantee a priori properties such as closed-loop stability and tracking error accuracy; it is general, numerically efficient and relatively simple. Extensive simulations are carried out to test the numerical efficiency of the NIC approach. A simulated example of industrial interest is also presented, concerned with control of a robotic manipulator.

SU-E-T-512: Targeting Mobile Tumors Precisely with an Integrated Robotic Target Tracking and Dynamic Couch-Based Motion Compensation System for a Conventional Linear Accelerator

Purpose: To introduce a novel, integrated tumor tracking and dynamic robotic couch‐based target motion compensationsystem with a conventional linear accelerator and to evaluate system accuracy. Methods: We have developed an integrated real‐time tumor tracking and motion compensationsystem using the treatment couch. The system comprises an infra‐red (IR) camerasystem capable of tracking optical reflectors placed on or near a target at a rate of 60 Hz, a robotic couch that is controlled in real‐time and the embedded couch controller capable of feedback control. System accuracy was tested using, a 4D phantom, placed on the couch and programmed to simulate 20 time‐varying 3D tumor motion (derived from patient tumor trajectories) with peak‐peak displacements of up to 4 cm. The position of the optical reflector was maintained at the reference position by tracking it with the robotic couch. Camera lag, system latency and tracking errors were evaluated. Dosimetric accuracy was also studied between with and without motion compensation.Results: In the absence of the IR camera (phantom‐couch direct positive feedback control), the system latency is < 0.5 ms. The IR camera introduces a 17 ms delay in the control system. This lag induces an overall system latency of 67–150 ms. In the absences of the camera, the roboticsystem achieved with standard deviation for tracking errors accuracy of 0.01 mm, 0.03 mm and 0.04 mm in ML, AP and SI directions, respectively. The integrated system achieved standard deivation for tracking error accuracy of 0.5 mm in all three in ML, AP and SI directions, respectively. Dosimetric accuracy was improved by 11–36% Conclusions: We have developed a viable and integrated tumor tracking and real‐time robotic couch‐based target motion compensationsystem that may be integrated with a conventional linear accelerator, obviating the need for a specialized radiation delivery device. Supported by grant #CA122403 from the NCI