Electric vehicles are beneficial to the environment owing to its nonproduction of emissions and excessive noise; however, they have their own limitations with respect to charging difficulties and ...mileage anxiety. In order to address these problems, dynamic wireless power transfer (DWPT) technology has been developed. In this article, we replace a conventional open-loop method without dc-dc converter with the proposed dc-dc converter in the energy receiver in order to improve output power. Moreover, to make sure that the DWPT system is reliable when the coupling coefficient changes rapidly over a wide range of values, we propose model predictive control (MPC) to ensure optimal dynamic-tracking performance. Considering the fact that sampling delay will cause an error in the controller output, the system is modeled accurately in order to improve the MPC performance. In addition, the MPC and double closed-loop proportional-integral-differential control are compared with simulations and experiments, the results of which demonstrate the effectiveness of MPC-based DWPT.
This paper studies the problem of high-precision positioning of laser beams using an intelligent proportional-integral-derivative (i-PID) controller. The control problem addressed in laser beams aims ...at maintaining the position of the laser beam on a position sensing device under the effects of noise and active disturbances. The design of an i-PID control is based on the so-called ultralocal model. The i-PID controller has been implemented and validated on a real test bench. For the sake of enhancing the performance of the closed loop, it has been combined with a nonasymptotic and robust modulating function-based estimation method, which is used to estimate the unmodeled dynamics and disturbances. The proposed i-PID controller has shown good performance in handling the active disturbances and uncertainties present in the platform. A comparison to the classical PID and robust PID is also provided based on the experimental setup. Robustness tests are performed experimentally to show the effectiveness of the i-PID control.
Iterative learning control (ILC) has been well recognized for its output tracking ability in systems that perform repetitive tasks, such as robot manipulators. In practice, however, the application ...of ILC remains challenging as it generally requires the repetition of the initial settings and such industrial manipulators do not provide measurements of actual joint positions. This article presents a practical and fully automated implementation of ILC for industrial robot manipulators while assuming complete model uncertainty and the unavailability of joint velocity measurements. We propose the employment of a dedicated controller tasked only with bringing the arm back to its initial position while reducing the joint position reinitialization error after every iteration. We show that the convergence of the position tracking error is bounded by the initial mismatch. Finally, we provide experimental justification of the proposed approach on a 4-DOF commercial robot manipulator while only using the measurements of relative joint positions and show that our fully automated process outperforms two ILC algorithms with thorough manual homing.
This article is concerned with the <inline-formula><tex-math notation="LaTeX">H_{\infty }</tex-math></inline-formula> proportional-integral-derivative (PID) control problem for class of discrete-time ...Takagi-Sugeno fuzzy systems subject to infinite-distributed time delays and round-robin (RR) protocol scheduling effects. The information exchange between the sensors and the controller is conducted through a shared communication network. For the purpose of alleviating possible data collision, the well-known RR communication protocol is deployed to schedule the data transmissions. To stabilize the target system with guaranteed <inline-formula><tex-math notation="LaTeX">H_{\infty }</tex-math></inline-formula> performance index, a novel yet easy-to-implement fuzzy PID controller is developed whose integral term is calculated based on the past measurements defined in a limited time window with hope to improve computational efficiency and reduce accumulation error. Based on the Lyapunov stability theory and the convex optimization technique, sufficient conditions are derived to ensure the exponential stability as well as the <inline-formula><tex-math notation="LaTeX">H_{\infty }</tex-math></inline-formula> disturbance attenuation/rejection capacity of the underlying system. Furthermore, by utilizing the cone complementarity linearization algorithm, the nonconvex controller design problem is transformed into an iterative optimization one that facilitates the controller implementation. Finally, simulation examples are given to show the effectiveness and correctness of the developed control method.
•A new car-following model is proposed to describe the dynamic behavior of autonomous vehicle.•The bifurcation characteristic of traffic flow composed of autonomous vehicle is analyzed.•A controller ...that considers multi-step memory and multi-step prediction effect is designed.•A hybrid control strategy is proposed, which combines multi-step prediction and memory mechanism with PID.
This paper is committed to capturing the dynamic behaviors of homogenous flow of autonomous vehicles (AVs), and exploring the control strategies to improve traffic conditions, which can alleviate traffic congestion and improve traffic efficiency. Firstly, a car-following model of AVs considering real-time driving state is established. Secondly, based on bifurcation theory and stability theory, bifurcation analysis is carried out and the relationship between bifurcation and stability is revealed. In order to suppress the bifurcation and improve the stability, a controller considering multi-step prediction and memory mechanism (MPM) is designed, and the root trajectories for eigenvalues and stable time length of the model controlled by MPM controller are calculated. In response to the limitations of the MPM controller, a hybrid controller including the MPM controller and PID controller is further proposed, and it is found that the model controlled by hybrid controller has greater range of stable bifurcation parameter and stable time length, which means better ability of bifurcation suppression. Finally, the capabilities of the controller proposed in this paper are effectively demonstrated by numerical experiments in MATLAB and simulation experiments in the ROS-Gazebo environment.
•Implemented five simultaneously independent proportional integral derivative controllers to maintain thermal stability in CFD using a similar methodology as employed in the plant.•Developed a ...comprehensive model of an industrial scale LDPE autoclave reactor consisting of rotating mesh elements, reaction kinetics, and complex geometry.•Validated numerical methods of time step size, grid resolution, and turbulence model sensitivity.•Replicated proposed mixing patterns in CFD.
CFD was employed to develop a rigorous model of an LDPE autoclave reactor. Different numerical settings within the solver are evaluated to eliminate false diffusion and to reflect the sensitive heat generation taking place during free radical polymerization. An accurate model can allow geometry and process adaptations to be evaluated for much lower costs than physical experiments. Improving the reactor design allows for longer run times and a higher degree of catalyst conversion. The rigorous CFD model employed reaction kinetics, PID-automated thermal management, and a rotating stirrer shaft. Validation was carried out to determine the sensitivity to time-step size, turbulence model, and grid resolution. Data were compared to an industrial scale plant autoclave to guide the development of CFD. In a comparison of turbulence models, the shear stress transport (SST) model was found to predict higher concentrations of turbulent kinetic energy (TKE) resulting in a lower temperature distribution throughout the reactor than the differential Reynolds stress model (DRSM). The less diffusive DRSM was recommended for future studies. A mesh refinement study revealed slight variation in the results between the base mesh of 6 million computational elements and the refined mesh consisting of 40 million. Ultimately, the variation between different grid resolutions was not significant enough to justify slowing down the solver speed by 14X by using the refined mesh. Increased rigor improved the model’s ability to match plant data, and CFD thermocouples were within 2.5% of temperatures from plant data.
The dilemma of PID tuning Somefun, Oluwasegun Ayokunle; Akingbade, Kayode; Dahunsi, Folasade
Annual reviews in control,
2021, 2021-00-00, Volume:
52
Journal Article
Peer reviewed
A lot of automatic feedback control and learning tasks carried out on many dynamical systems still fundamentally rely on a form of proportional–integral–derivative (PID) control law. The PID law is ...often viewed as a simplistic computational control algorithm. However just like all non-convex optimization problems, tuning the PID algorithm for accurate and stable closed-loop control becomes a NP-Hard Problem. This leads to a dilemma, for both users and designers, most especially in practise. It is then no wonder that tuning software is a big business in the industrial automation sector. In this review, we present and classify PID tuning methods till date into three general areas. Finally, we then present a proposal to minimize the dilemma of complexity and cost that has become associated with tuning the three main parameters of the PID control law. Hopefully, continuous attempts at the minimization of this dilemma can lead to both a money-savings investment and a significant improvement in the field of PID control design.
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