Dynamic Matrix Control Research Articles

Two-layer structure strategy for large-scale systems integrating online adaptive constraints adjustment method and cooperative distributed DMC algorithm

In this paper, a distributed two-layer structure strategy for large-scale systems is described. In the upper level of the structure, usually known as the Steady State Target Optimizer (SSTO) layer, we fully consider the possible constraints in the industrial process as well as their priority order and put forward an online adaptive constraints adjustment (OACA) scheme to ensure the stable operation of the production device. Based on Pareto optimal, a new cooperative distributed dynamic matrix control (CDDMC) algorithm is proposed for the lower MPC layer. The algorithm makes use of the finite step response model and Dynamic Matrix Control (DMC) method which are commonly applied in the process industry, decomposes the large-scale system into multiple interconnected subsystems for a significantly reduced computational burden, and works over a cooperative way based on Jacobi-type iteration to achieve the global optimal solution. Then the convergence of the CDDMC algorithm is investigated and the offset-free control of the strategy is discussed. Finally, the two-layer structure distributed strategy is applied to two examples to analyze its applicability and effectiveness in comparison with the centralized one.

Optimization and Simulation of DMC Algorithm with Terminal Weight Based on LQR Controller

Based on the multivariable dynamic matrix control algorithm, there are many similarities between the dynamic matrix control algorithm and LQR in the form of state equation, state variable and objective function. We can use the objective function of LQR to improve the objective function of DMC and improve the control effect of the system. Using the given mathematical model, the terminal weighting matrix of LQR is applied to DMC algorithm, and the optimized multivariable dynamic matrix control algorithm is simulated. The results show that the algorithm can effectively reduce the response time of the system, make the system sink faster and reach the given value faster.

Dynamic Control of a Fiber Manufacturing Process Using Deep Reinforcement Learning

This article presents a model-free deep reinforcement learning (DRL) approach for controlling a fiber drawing system. The custom DRL-based control system predictively regulates fiber diameter and produces a fiber with a desired, constant or nonconstant, diameter trajectory, i.e., diameter variation along the fiber length. Physical models of the system are not used. The system was trained and tested on a compact fiber drawing system, which has nonlinear delayed dynamics and stochastic behaviors. For a reference trajectory with random step changes, after 1 h of training, the DRL controller showed the same root-mean-squared error (RMSE) as an optimized PI controller; after 3 h of training, it achieved the performance of a quadratic dynamic matrix controller (QDMC). While the PI feedback controller showed 3.5 s of time lag in a step response, the DRL controller showed less than a second of time lag. Controller performance tests on trajectories not used in the training process are conducted; for a sine sweep reference trajectory, the DRL controller maintained an RMSE under 40 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu \text{m}$</tex-math></inline-formula> up to a frequency of 45 mHz, compared to 25 mHz for QDMC.

Active Launch Vibration Control of Power-Split Hybrid Electric Vehicle Considering Nonlinear Backlash

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;The backlash between engaging components in a driveline is unavoidable, especially when the gear runs freely and collides with the backlash, the impact torque generated increases the vibration amplitude. The power-split hybrid electric vehicle generates output torque only from the traction motor during the launching process. The nonlinear backlash can greatly influence the driveability of the driveline due to the rapid response of the traction motor and the lack of the traditional clutches and torsional shock absorbers in the powertrain. This paper focuses on the launch vibration of the power-split hybrid electric vehicle, establishes a nonlinear driveline model considering gear backlash, including an engine, two motors, a Ravigneaux planetary gear set, a reducer, a differential, a backlash assembly, half shafts, and wheels. For easier control, some components of the power-spilt system are simplified, after verifying the reliability of the simplified model, a linear observer(LSO) and a nonlinear observer(ESO) are designed to estimate the system state variables respectively. Based on the estimated information a dynamic matrix controller(DMC) is designed to correct the motor output torque. Through the feedback torque of the motor, the active control system can reduce the shock and vibration of the nonlinear driveline caused by the transient change of the motor torque during launch conditions.&lt;/div&gt;&lt;/div&gt;

Transient numerical modeling and model predictive control of an industrial-scale steam methane reforming reactor

A steam methane reforming reactor is a key equipment in hydrogen production, and numerical analysis and process control can provide a critical insight into its reforming mechanisms and flexible operation in real engineering applications. The present paper firstly studies the transport phenomena in an industrial-scale steam methane reforming reactor by transient numerical simulations. Wall effect and local non thermal equilibrium is considered in the simulations. A temperature profile of the tube outer wall is given by user defined functions integrated into the ANSYS FLUENT software. Dynamic simulations show that the species distribution is closely related to the temperature distribution which makes the temperature of the reactor tube wall an important factor for the hydrogen production of the reformer and the thermal conductivity of the catalyst network is crucial in the heat transfer in the reactor. Besides, there exists a delay of the reformer's hydrogen production when the temperature profile of the tube wall changes. Among inlet temperature, inlet mass flow rate and inlet steam-to-carbon (S/C) ratio, the mass flow rate is the most influencing factor for the hydrogen production. The dynamic matrix control (DMC) scheme is subsequently designed to manipulate the mole fraction of hydrogen of the outlet to the target value by setting the temperature profile trajectory of the reforming tube with time. The proportional-integral control strategy is also studied for comparison. The closed-loop simulation results show that the proposed DMC control strategy can reduce the overshoot and have a small change of the input variable. In addition, the disturbances of feed disturbance can also be well rejected to assure the tracking performance, indicating the superiority of the DMC controller. All the results give insight to the theoretical analysis and controller design of a steam methane reformer and demonstrate the potential of the CFD modeling in study the transport mechanism and the idea of combining CFD modeling with controller design for the real application.

Dynamic multi-objective matrix control for a class of switched systems

This article focuses on the tracking and stabilizing issues of a class of discrete switched systems. These systems are characterized by unknown switching sequences, a non-minimum phase, and time-varying or dead modes. In particular, for those governed by an indeterminate switching signal, it is very complicated to synthesize a control law able to systematically approach general reference-tracking difficulties. Taking into account the difficulty to express the dynamic of this class of systems, the present paper presents a new Dynamic matrix control method based on the multi-objective optimization and the truncated impulse response model. The formulation of the optimization problem aims to approach the general step-tracking issues under persistent and indeterminate mode changes and to overcome the stability problem along with retaining as many desirable features of the standard dynamic matrix control (DMC) method as possible. In addition, the formulated optimization problem integrates estimator variables able to manipulate the optimization procedure in favor of the active mode with an appropriate adjustment. It also provides a progressive and smooth multi-objective control law even in the presence of problems whether in subsystems or switching sequences. Finally, simulation examples and comparison tests are conducted to illustrate the potentiality and effectiveness of the developed method.

Simultaneous stable control of temperature field distribution uniformity and consistency for multi-temperature zone systems

As a key factor characterizing the control accuracy of multi-temperature zone systems (MTZSs), the stable control of temperature field distribution uniformity and consistency is of critical importance for MTZSs, and it largely determines the product quality and production efficiency. Due to the complicated multiple input and output properties, as well as the various external variations in practice, however, it is extremely difficult to monitor the temperature field distribution in production process. To address the uniform and consistent temperature field distribution problem in MTZSs, a multi-variable dynamic matrix control (DMC)-based predictive control mechanism is proposed in this paper. Specifically, we first establish a finite element-based heat transfer model to analyse heat transfer within the multi-temperature zone, and then propose a multi-variable DMC-based decoupling design method to decompose the entire system into multiple subsystems with single-input single-output for temperature uniformity distribution control in MTZS. By utilizing the ANSYS tools to analyse the transient field temperatures, we obtain both time and space distribution characteristics of the transient temperature field with the proposed control method, and also compare such results with those obtained using the PID control method. Finally, we apply the proposed multi-variable DMC control mechanism onto a multi-temperature sintering furnace of a practical industrial product line for verification. Results show that, with the proposed control mechanism adopted, the difference between the highest and lowest temperature of any workpiece could be maintained within 5°C in the heat rising up period, which convincingly verifies the effectiveness of the proposed predictive control algorithm in different cases.

Networked control system time-delay compensation based on PI-based dynamic matrix control

Abstract The network-induced time-delay caused by the introduction of the communication network in a networked control system has a great negative impact on the stability and performance of the system. In order to compensate for the performance degradation of the networked control system caused by time-delay, a time-delay compensation method based on PI-based dynamic matrix control for networked control system is proposed. In this study, autoregressive integrated moving average model is used to predict the future time-delay. The predictive time-delay replaces the actual time-delay as a parameter of the controller. In order to improve the compensation effect of dynamic matrix control, the feedback structure of the PI control and the predictive ability of dynamic matrix control are combined. The new objective function of dynamic matrix control is combined with PI structure to obtain the optimal control increment value. The PI controller can correct the output of dynamic matrix control and reduce the deviation between the actual output and the predicted output. The effect of the model mismatch and interference on the system is reduced. The robustness and anti-interference performance of the system is improved. The controller can select the appropriate control value to transmit to the actuator to compensate for the effect of the random time-delay in the networked control system. The stability of the compensation method is proved. Through the simulation results, the effectiveness of the proposed time-delay compensation method is verified.

Speed Control of Pipeline Inner Detector Based on Interval Dynamic Matrix Control With Additional Margin

Inpipe inspection technology is an important method for pipelines detection, and the smooth running speed of the inner detector is a prerequisite for ensuring the quality of inspection. Since the inner detector runs as a black box in the pipeline, it is difficult to observe the current speed state, and the energy source it carries is limited. To overcome the above problems, this article proposes an interval dynamic matrix control algorithm with additional margin (AM-IDMC). First, as an optimized control strategy, interval control can suppress disturbances and reduce energy consumption with smaller actions, which is a novel way to solve the speed control problem of the inner detector. Second, the dynamic matrix control can effectively predict the speed of the inner detector. At the same time, the additional margin method can avoid the actual speed from violating the expected interval to the greatest extent, allowing the controller to intervene in the control as soon as possible. Third, an adaptive penalty coefficient and interval reference trajectory are designed to ensure the rapidity and stability of the speed adjustment process. This article also systematically and completely builds the speed control model of the inner detector from pressurizing station and discharge device. The results have demonstrated that the AM-IDMC algorithm has good performance and has a good effect on the speed control of the inner detector.

Fast constrained nonlinear model predictive control for implementation on microcontrollers

Abstract Model predictive control (MPC) is based on the systematic resolution of an online optimization problem at each time step. In practice, the computation cost is often very high, especially for the non-linear case under constraints, thus complicating the application of MPC to real-time systems. This paper proposes to improve the non-linear quadratic dynamic matrix control (NLQDMC) algorithm for MPC by solving constrained optimization problems only when necessary, and defaulting to the unconstrained solution whenever possible. The new algorithm is called fast NLQDMC (FNLQDMC) and is applied to the control of a nonlinear system comprised of converter and a DC machine, and implemented in a microcontroller board. The results obtained show that, depending to the setpoint profiles, this algorithm saves more than 64% computation of the constrained problem compared to the conventional NLQDMC, while keeping identical performance in terms of setpoint tracking and constraint satisfactions.

Assessment of dynamic matrix control controller parameters via estimating Markov parameters of disturbance

AbstractFor an industrial control system, controller parameters are important factors that affect the control system performance. This article introduces a controller parameter performance assessment method based on disturbance characteristic variation for a dynamic matrix control system. Assuming that the process model is accurate and the setpoint is constant, disturbance characteristic variation without adjusting controller parameters leads to the degradation of system performance. Hence, the Markov parameters of a disturbance model, which inflect the variation of disturbance characteristics, are used to assess the controller parameter performance. These Markov parameters can be obtained from closed‐loop data using the subspace identification method. The differences between the Markov parameters in an actual running state and those in a well‐regulated state are used to design the assessing index of controller parameters. The simulation results in the Wood–Berry model and TE process show the validity of the proposed index.

Dynamic Matrix Based Thermal Power Tracking Control of Nuclear Power Reactor

power control of nuclear power plant is an important technology to ensure the safe and efficient operation of nuclear power unit. Because the power system of nuclear power reactor belongs to nonlinear system, there are many factors affecting the distribution of thermal power, which leads to the uncertainty of the tracking target of thermal power of nuclear power reactor. Therefore, this paper proposes a dynamic matrix-based thermal power tracking control method for nuclear power reactors. The dynamic matrix algorithm is used to establish the prediction model of the controlled object, to determine the tracking target value, to design the dynamic matrix controller, and to formulate the switching strategy combined with the minimum value of the cumulative prediction error, and to realize the thermal power tracking control of the power reactor. Simulation results show that the proposed method has different target values under different working conditions in accordance with the actual control value, it has better engineering value and practical significance for reducing the working intensity of operators and improving the performance of load tracking.

Inverse Heat Transfer Study of a Power Transmission Line Tower Foundation

Abstract In some northern regions, power transmission lines are built with metal tower footings buried in the permafrost. With a high thermal conductivity, the tower footing has a significant thermal effect on the foundation and the nearby permafrost. Heat transfer models were previously developed to predict the thermal effect with line heat source assumptions, without knowing the exact spatial distribution and temporal variation of the heat source strength. This limited the accuracy of these heat transfer models. In this work, an inverse heat transfer method (IHTM) based on dynamic matrix control (DMC) theory is developed to better estimate the heat source strength representing the tower footing. The methodology is validated with numerical simulations and experimental data. It is found that the distribution of heat source varies spatially and temporally in a more complicated way than what was assumed in previous studies. The inversed heat source is then used to reconstruct the temperature fields in a tower foundation, which provides more accurate heat transfer analysis for design and maintenance of the foundation.

DMC controller design for an integrated Allam cycle and air separation plant

Advanced process control is developed for a novel oxy-fuel Allam cycle power plant integrated with an Air Separation Unit (ASU) with no greenhouse gas and NOx emissions. The Dynamic Matrix Control (DMC) controller was developed with AspenTech's DMC Technology Version 11 engineering software. The DMC controller improves nitrogen purity, carbon dioxide purity and flowrate, and power output by an average of 4%. Also, the DMC controller is able to handle disturbances in the range of 12.5% for feed flow changes and 10% for feed composition changes. Substantial enhancement was observed in upgrading carbon dioxide purity from 97% Enhanced Oil Recovery (EOR) grade to 99.9% food/medical grade. Therefore, this advanced control strategy is superior to regulatory PID controllers and the developed DMC controller can be used as a seed model in the actual plant control by combining with the actual plant test data in the calibrate mode.

Perturbation Analysis and Control of Mach Number 2.4-Meter Transonic Wind Tunnel

Because of the large domestic civil aircraft projects started in China a decade ago, there is a greater need to control the accuracy of the Mach number in aerodynamic tests, especially near the designed cruise point of large commercial aircraft. Nowadays the control accuracy of China Aerodynamics Research and Development Center 2.4-meter transonic wind tunnel Mach number is in the range of to when , which is far from the measurement accuracy of drag coefficient required for testing advanced aircraft. This value should result in a better-than-one drag count. As a consequence, it is imperative to improve the control accuracy of Mach number urgently. The nonlinearity, large time delays, and strong coupling of wind tunnel flowfield control, along with the variation of the model angle of attack, could cause the Mach number to deviate from the expected value. To solve these problems, a model predictive control method based on dynamic matrix control algorithm is proposed. This method builds a prediction model based on step response test. The accuracy of Mach number predictive control can be efficiently improved by performance optimization in the form of vector norms, rolling optimization, and feed-forward compensation. This control strategy has been successfully tested in the wind tunnel, and the control accuracy of Mach number has been remarkably enhanced, to the point where it can be controlled to within . This value satisfies the requirements of aerodynamic aircraft testing.

Predictive Control Of Transient Air-Fuel Ratio for Gasoline Engine Based on Wavelet Network Inversion

To achieve accurate control of the transient air-fuel ratio for gasoline engines, a composite predictive control method based on wavelet network is proposed. The inverse system of transient air-fuel ratio system was to identify with wavelet network, which is able to dynamically compensate intake flow with feedforward control, and a pseudo-linear system is formed by cascading the inverse system with the original system. Then the dynamic matrix control(DMC) was used as a compensation for both internal and external disturbance in real time, and the effective control for transient air-fuel ratio system of nonlinear, time-delay and time-variation is realized. Finally simulated with experiment data at transient conditions, the results show that the inverse model based on wavelet network can accurately approximate the air fuel ratio transient process, and this method has stronger robustness and anti-interference. Therefore, the composite predictive control strategy has good control performances and can improve the control precision of air-fuel ratio in transient conditions.

Practical PLC-Based Implementation of Adaptive Dynamic Matrix Controller for Energy-Efficient Control of Heat Sources

For the efficient control of industrial heat sources, adaptation to significant changes in operating conditions and in heat demand variations are the critical issues. This article presents the concept of the adaptive dynamic matrix controller dedicated to control of heat sources operated as a part of heat distribution systems. The adaptation is based on interpolation of the process nonlinearities. The implementation in programmable logic controller in the form of a general purpose function block is presented and practical issues of the minimization of the memory load and computational complexity are addressed. The suggested concept is experimentally validated by both virtual and real commissioning in the industrial conditions. The aspect of energy efficiency of the heat source control systems is also discussed and for assessment of the energy supply performance, the energy error index is proposed. In terms of this index, the results show superiority of the suggested controller over the conventional approaches.

Dynamic matrix control for thermal power of multi-modular high temperature gas-cooled reactor plants

To suppress the fluctuation from both load side and intermittent renewable energy (IRE), nuclear power plants (NPPS) should be operated in load-following mode to improve economic competitiveness. The modular high temperature gas-cooled reactor (MHTGR) belongs to the category of small nuclear reactor (SMRs) and is suitable for load-following by the virtue of online refueling ability and inherent safety. To realize economies of scale for MHTGR, multi-modular scheme that multiple nuclear steam supply system (NSSS) modules are connected in parallel providing superheated steam for common turbine is recommended to achieve desired power ratings. However, because of the large heat capacity in the pebble-bed of MHTGR and thermal coupling of different NSSSs through common secondary loop fluid network, the current control strategy which suppresses the nuclear power, coolant temperatures measurement from their set-points without considering thermal dynamic of NSSS itself, may not favorable for heat transfer in the NSSS. To improve the load-following ability, a multivariable dynamic matrix control (DMC) is constituted to dynamic compensate the thermal energy variation of NSSS. The implementation of the DMC has a typical cascade structure, where DMC revises the set-points of NSSS module in outer loop and the existing PID control law is adopt for stabilization in inner loop. Numerical results show that this cascade DMC can improve the transient of thermal power under power maneuvering, and can also attenuate the nuclear power, helium flowrate set-points and feed-water temperature step disturbance.

MODEL PREDICTIVE CONTROL OF A HYDRAULIC ACTUATOR IN TORQUE APPLYING SYSTEM OF A MECHANICALLY CLOSED-LOOP TEST RIG FOR THE HELICOPTER GEARBOX

Transmission health is an important factor in safety and maintenance costs in industries, so construction of test rigs for testing high-powered gearboxes under different operating conditions of helicopters is required. The studied test rig, which is developed at Sharif University of Technology branch of ACECR (Academic Centre of Education, Culture and Research) is mainly used for testing high-powered gearboxes through a mechanically closed-loop procedure. For providing a variety of speeds and torques in test rigs, torque applying system is required. According to generation of higher forces, reduced size of equipment and accurate positioning, electro hydraulic actuators (EHAs) are used for applying torques for planetary gearboxes of this test rig. Due to the importance of applying accurate torques in evaluation of the gearbox performance, first an accurate model of EHA is derived, which captures the system dynamics using system identification method with low consumed time and simple relations. After that, a type of model predictive controller called dynamic matrix controller is proposed for controlling EHA under determined requirements. Then, the performance of proposed controller under normal conditions as well as in presence of disturbance is investigated. The results show a good tracking of controller for various reference inputs in different conditions. Moreover, the performance of the proposed controller is compared with the performance of classical proportional-integral-derivative (PID) controller and superior characteristics of the proposed controller is concluded.

Tuning Guidelines for Model-Predictive Control

This paper reviews available tuning guidelines for model-predictive control (MPC) from theoretical and practical perspectives. Its primary focus is on the guidelines introduced since the publication of our previous review of MPC tuning guidelines in this same journal in 2010. Since then, new guidelines based on approaches such as pole placement and multiobjective optimization have been proposed, and more autotuning methods have been introduced. This review covers different implementations of MPC such as dynamic matrix control, generalized predictive control, and state-space-model predictive control that requires Kalman filter tuning. The closed-loop performances of a distillation column and the Shell fractionator under model-predictive controllers tuned using four different tuning guidelines are compared through numerical simulations.