Virtual Thermal Sensing and Control of Heat Distribution Using State Estimation

2012 ◽  
Author(s):  
Kaveh Fathian ◽  
Fatemeh Hassanipour ◽  
Nicholas R. Gans
Keyword(s):  
Steady State ◽  
Temperature Distribution ◽  
Heat Flow ◽  
Control Method ◽  
Industrial Applications ◽  
Electrical Circuit ◽  
Accurate Estimation ◽  
Plate Temperature ◽  
And Control ◽  
State Error

Many industrial applications require or can be improved by strict control of the temperature distribution on a surface. This initial investigation presents modeling and control of heat flow on an aluminum plate. Temperature distribution is modeled using a dense equivalent electrical circuit. An observer is designed based on the model to estimate the temperature distribution on the plate. The estimation is used in a controller to regulate the temperature of a desired point on the plate, given discrete heat input elements but no cooling elements. Experiments are conducted to compare the realism of the heat flow model and efficacy of the control method with experimental data. Results show that the steady state error between the actual and estimated temperatures at different points on the surface is always less than 0.5°C, which indicates accurate estimation of the temperature. The RMS error between desired and actual temperatures through all experiments is less than 2°C which indicates fast regulation and low steady state error.

scholarly journals Study and Application of Intelligent Sliding Mode Control for Voltage Source Inverters

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2544 ◽  
Author(s):  
En-Chih Chang
Keyword(s):  
Steady State ◽  
Sliding Mode Control ◽  
Digital Signal Processor ◽  
Sliding Mode ◽  
Transient Behavior ◽  
Voltage Source ◽  
Accurate Estimation ◽  
Inference System ◽  
Mode Control ◽  
State Error

In this paper, an intelligent sliding mode controlled voltage source inverter (VSI) is developed to achieve not only quick transient behavior, but satisfactory steady-state response. The presented approach combines the respective merits of a nonsingular fast terminal attractor (NFTA) as well as an adaptive neuro-fuzzy inference system (ANFIS). The NFTA allows no singularity and error states to be converged to the equilibrium within a finite time, while conventional sliding mode control (SMC) leads to long-term (infinite) convergent behavior. However, there is the likelihood of chattering or steady-state error occurring in NFTA due to the overestimation or underestimation of system uncertainty bound. The ANFIS with accurate estimation and the ease of implementation is employed in NFTA for suppressing the chatter or steady-state error so as to improve the system’s robustness against uncertain disturbances. Simulation results display that this described approach yields low distorted output wave shapes and quick transience in the presence of capacitor input rectifier loading as well as abrupt connection of linear loads. Experimental results conducted on a 1 kW VSI prototype with control algorithm implementation in Texas Instruments DSP (digital signal processor) support the theoretic analysis and reaffirm the robust performance of the developed VSI. Because the proposed VSI yields remarkable benefits over conventional terminal attractor VSIs on the basis of computational quickness and unsophisticated realization, the presented approach is a noteworthy referral to the designers of correlated VSI applications in future, such as DC (direct current) microgrids and AC (alternating current) microgrids, or even hybrid AC/DC microgrids.

Composite Fuzzy Control Method for Temperature in Intelligent Moisture Analyzer

2013 ◽  
Vol 401-403 ◽  
pp. 1010-1013
Author(s):  
Jing Ling ◽  
Jin Che ◽  
Da Ming Liu
Keyword(s):  
Steady State ◽  
Fuzzy Control ◽  
Control Method ◽  
Fuzzy Controller ◽  
Time Lag ◽  
Threshold Value ◽  
National Standards ◽  
Infrared Heating ◽  
Temperature Control System ◽  
State Error

Temperature control system of infrared heating oven in moisture analyzer is characteristic of nonlinear, time-varying and time-lag. A composite fuzzy control (CFC) method is proposed, which combines improved Bang-Bang control with two-stage intelligent fuzzy control. The control algorithm is implemented by MSP430F5438. When the temperature error e between the desired temperature and actual temperature in heating oven is larger than threshold value, the improved Bang-Bang controller is employed in rapidly reducing the error; to decrease the system overshoot, the basic fuzzy controller is used; to reduce the steady-state error of basic fuzzy controller, the auxiliary fuzzy controller is applied. The steady-state error of improved fuzzy controller for oven temperature is less than 0.5°C, which is better than the Chinese National Standards for moisture content measurement.

scholarly journals Modeling, Prediction, and Control of Heating Temperature for Tube Billet

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Yachun Mao ◽  
Dong Xiao ◽  
Dapeng Niu
Keyword(s):  
Control Method ◽  
Heating Temperature ◽  
Nonlinear Models ◽  
Time Lag ◽  
Industrial Applications ◽  
Billet Temperature ◽  
Tube Billet ◽  
Prediction And Control ◽  
Coupling Characteristics ◽  
And Control

Annular furnaces have multivariate, nonlinear, large time lag, and cross coupling characteristics. The prediction and control of the exit temperature of a tube billet are important but difficult. We establish a prediction model for the final temperature of a tube billet through OS-ELM-DRPLS method. We address the complex production characteristics, integrate the advantages of PLS and ELM algorithms in establishing linear and nonlinear models, and consider model update and data lag. Based on the proposed model, we design a prediction control algorithm for tube billet temperature. The algorithm is validated using the practical production data of Baosteel Co., Ltd. Results show that the model achieves the precision required in industrial applications. The temperature of the tube billet can be controlled within the required temperature range through compensation control method.

scholarly journals Intelligent Control of a Novel Hydraulic Forging Manipulator

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
J. Wang ◽  
F. Gao ◽  
Y. Zhang
Keyword(s):  
Intelligent Control ◽  
Position Control ◽  
Control Method ◽  
Industrial Applications ◽  
Heavy Duty ◽  
Force Perception ◽  
Large Size ◽  
Forging Manipulator ◽  
Combination Of Methods ◽  
And Control

The increased demand for large-size forgings has led to developments and innovations of heavy-duty forging manipulators. Besides the huge carrying capacity, some robot features such as force perception, delicacy and flexibility, forging manipulators should also possess. The aim of the work is to develop a heavy-duty forging manipulator with robot features by means of combination of methods in mechanical, hydraulic, and control field. In this paper, through kinematic analysis of a novel forging manipulator, control strategy of the manipulator is proposed considering the function and motion of forging manipulators. Hybrid pressure/position control of hydraulic actuators in forging manipulator is realized. The feasibility of the control method has been verified by the experiments on a real prototype of the novel hydraulic forging manipulator in our institute. The intelligent control of the forging manipulator is performed with programmable logic controller which is suitable for industrial applications.

scholarly journals Adaptive neural PD controllers for mobile manipulator trajectory tracking

2021 ◽  
Vol 7 ◽  
pp. e393
Author(s):  
Jesus Hernandez-Barragan ◽  
Jorge D. Rios ◽  
Javier Gomez-Avila ◽  
Nancy Arana-Daniel ◽  
Carlos Lopez-Franco ◽  
...  
Keyword(s):  
Steady State ◽  
Pid Controller ◽  
Poor Performance ◽  
Industrial Applications ◽  
Mobile Manipulator ◽  
Pid Controllers ◽  
Mobile Manipulators ◽  
Pd Controller ◽  
Adaptive Neuron ◽  
State Error

Artificial intelligence techniques have been used in the industry to control complex systems; among these proposals, adaptive Proportional, Integrative, Derivative (PID) controllers are intelligent versions of the most used controller in the industry. This work presents an adaptive neuron PD controller and a multilayer neural PD controller for position tracking of a mobile manipulator. Both controllers are trained by an extended Kalman filter (EKF) algorithm. Neural networks trained with the EKF algorithm show faster learning speeds and convergence times than the training based on backpropagation. The integrative term in PID controllers eliminates the steady-state error, but it provokes oscillations and overshoot. Moreover, the cumulative error in the integral action may produce windup effects such as high settling time, poor performance, and instability. The proposed neural PD controllers adjust their gains dynamically, which eliminates the steady-state error. Then, the integrative term is not required, and oscillations and overshot are highly reduced. Removing the integral part also eliminates the need for anti-windup methodologies to deal with the windup effects. Mobile manipulators are popular due to their mobile capability combined with a dexterous manipulation capability, which gives them the potential for many industrial applications. Applicability of the proposed adaptive neural controllers is presented by simulating experimental results on a KUKA Youbot mobile manipulator, presenting different tests and comparisons with the conventional PID controller and an existing adaptive neuron PID controller.

scholarly journals ENHANCEMENT OF STABILITY ON AUTONOMOUS WAYPOINT MISSION OF QUADROTOR USING LQR INTEGRATOR CONTROL

2022 ◽  
Vol 23 (1) ◽  
pp. 129-158
Author(s):  
Oktaf Agni Dhewa ◽  
Tri Kuntoro Priyambodo ◽  
Aris Nasuha ◽  
Yasir Mohd Mustofa
Keyword(s):  
Steady State ◽  
Trajectory Tracking ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
System Specification ◽  
Linear Quadratic ◽  
Environmental Disturbances ◽  
Essential Requirement ◽  
Lqr Control ◽  
State Error

The ability of the quadrotor in the waypoint trajectory tracking becomes an essential requirement in the completion of various missions nowadays. However, the magnitude of steady-state errors and multiple overshoots due to environmental disturbances leads to motion instability. These conditions make the quadrotor experience a shift and even change direction from the reference path. As a result, to minimize steady-state error and multiple overshoots, this study employs a Linear Quadratic Regulator control method with the addition of an Integrator. Comparisons between LQR without Integrator and LQR with Integrator were performed. They were implemented on a quadrotor controller to track square and zig-zag waypoint patterns. From experimental results, LQR without Integrator produce of 2 meters steady-state error and -1.04 meters undershoot average with an accuracy of 64.84 % for square pattern, along 3.19 meters steady-state error, and -1.12 meters undershoot average with an accuracy of 46.73 % for a zig-zag way. The LQR method with integrator produce of 1.06 meters steady-state error with accuracy 94.96 % without multiple-overshoot for square pattern, the 1.06 meters steady-state error, and -0.18 meters undershoot average with an accuracy of 86.49 % for the zig-zag way. The results show that the LQR control method with Integrator can minimize and improve steady-state error and multiple overshoots in quadrotor flight. The condition makes the quadrotor able to flying path waypoints with the correct system specification. ABSTRAK: Kemampuan quadrotor dalam pengesanan lintasan waypoint menjadi syarat penting dalam menyelesaikan pelbagai misi pada masa kini. Walau bagaimanapun, besarnya ralat keadaan mantap dan banyak kelebihan kerana gangguan persekitaran menyebabkan ketidakstabilan pergerakan. Keadaan ini menjadikan quadrotor mengalami pergeseran dan bahkan mengubah arah dari jalur rujukan. Oleh itu, kajian ini menggunakan kaedah kawalan Linear Quadratic Regulator dengan penambahan integrator dalam meminimumkan ralat keadaan mantap dan banyak kelebihan. Perbandingan antara LQR tanpa Integrator dan LQR dengan Integrator dilakukan. Mereka dilaksanakan pada pengawal quadrotor untuk mengesan corak titik jalan persegi dan zig-zag. Dari hasil eksperimen, LQR tanpa Integrator menghasilkan ralat keadaan mantap 2 meter dan -1.04 meter rata-rata undur tembak dengan ketepatan 64.84% untuk corak persegi, sepanjang ralat keadaan tetap 3.19 meter, dan -1.12 meter rata-rata undur bawah dengan ketepatan 46.73 % untuk cara zig-zag. Kaedah LQR dengan integrator menghasilkan ralat keadaan mantap 1.06 meter dengan ketepatan 94.96% tanpa tembakan berlebihan untuk corak segi empat sama, ralat keadaan mantap 1.06 meter, dan rata-rata undur tembak -0.18 meter dengan ketepatan 86.49% untuk zig-zag cara. Hasilnya menunjukkan bahawa kaedah kawalan LQR dengan Integrator dapat meminimumkan dan memperbaiki ralat keadaan mantap dan banyak overhoot dalam penerbangan quadrotor. Keadaan tersebut menjadikan quadrotor dapat terbang ke titik jalan dengan spesifikasi sistem yang betul.

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