Internal Model Control Method Research Articles

A robust internal model control design for low-quality waste heat power generation systems

Recovering low-quality waste heat using industrial waste heat is challenging, and the reuse technology needs to erupt. Moreover, the gas source of low-quality waste heat is relatively volatile, which makes it challenging to keep the actual working condition of the plant stable. Therefore, it is inspiring to research the robustness of root-waste heat power generation processed measurement and control system to improve the stability of the plant operation. Hence, in this paper, we have applied uncertainty theory to analyze it and formulate the uncertainty model based on the Bode diagram. We also proposed a control method based on the uncertainty model, which combines robust control and internal model control to make the roots waste heat power generation system operate stably under the effect of external disturbances and changes of internal structure or parameters in actual operation. Experimental results show that the robust internal model control method has a speed deviation of no more than 7.9 r/min compared with the PID control method. The adjustment time to track the set value does not exceed 73.1 seconds within the allowed fluctuation range. The fluctuation variance is 30.95% of that of the PID controller. The dynamic performance is better, with strong anti-interference capability and significantly improved tracking performance. It ensures the stability of the roots-type waste heat utilization system, which is essential for future intelligent grid-connected power generation.

An adaptive internal model control approach for unmanned surface vehicle based on bidirectional long short-term memory neural network: Implementation and field testing

This paper investigates a practical adaptive internal model control (IMC) for an unmanned surface vehicle (USV) with unknown time-varying nonlinear model parameters and environmental disturbances. Firstly, an internal model of the USV is presented using the Bidirectional Long Short-Term Memory (BiLSTM) neural network. Then, an adaptive neural IMC controller is designed for the trajectory tracking of USV by using the IMC method. The internal model and the controller are updated by an error threshold algorithm. The proposed control scheme comprises of a trajectory guidance module via the Line-of-Sight (LOS) guidance method and a tracking control module designed by IMC theory. Under the proposed control scheme, the development processes of the vehicle platform and the control algorithms are described, and accurate tracking control can be achieved. Finally, the results of simulation and field experiments are presented and discussed to validate the effectiveness of the proposed control scheme.

Suspension Flux Internal Model Control of Single-Winding Bearingless Flux-Switching Permanent Magnet Motor

A suspension flux internal model control method is proposed to address the problem of the strong coupling of a single-winding bearingless flux-switching permanent magnet motor leading to a significant ripple of the rotor radial displacement. Firstly, based on air-gap magnetic field modulation theory, the stator flux equation considering rotor dynamic eccentricity is established to reveal the relationship between the eccentric rotor and the magnetic field. Secondly, according to the dynamic characteristics of the motor and the variation law of the air-gap magnetic field, the suspension-plane flux is substituted into the rotor dynamic model, and the suspension flux-dynamics internal model and corresponding output are constructed, respectively. Finally, a complete control strategy is established, and the rotor is stably suspended by PWM control. The simulation and experimental results show that the proposed method has better steady-state and dynamic performance than traditional PID control, and the maximum radial displacement ripples of the rotor are reduced by 53% and 50% in steady-state and dynamic operation.

Modified modeling and internal model control method of thrust ripples in PMLSMs for ultraprecision air-bearing linear feed systems

With the aim of attenuating thrust ripples in ultraprecision air-bearing linear feed systems, a simple and effective internal model control (IMC) system is herein presented based on a modified modeling and identification method of permanent magnet linear synchronous motors (PMLSMs). First, flux linkage equations were used to describe the volt–ampere characteristics of PMLSMs and provide a thrust expression in a differential form based on the principle of virtual work. Then, an analytical formula was obtained through derivation based on the condition of field-oriented control. On this basis, an IMC compensator was designed using an inverse model to attenuate nonlinear thrust effects, and an extended Kalman filter (EKF) was adopted to estimate the actual current in an analog linear amplifier. The boundedness of the nonlinear system was analyzed based on the convergence condition; furthermore, the stability of the proposed IMC compensator with EKF could be guaranteed. Then, an accurate model and thrust parameters were obtained using an identification experiment on an air-bearing linear platform driven by a linear analog amplifier. To demonstrate the coupling effect of current on thrust and confirm the effectiveness of the proposed method, both simulations and experiments were performed at a uniform velocity under extra loads of different weights; then, an extended state observer (ESO) was introduced as a comparative method. Finally, the results of the following error indicated that the proposed method demonstrated improved performance in terms of overcoming the influence of nonlinearity and that it results in smooth velocities in steady states.

The Implementation of Internal Mode Control Method to SEPIC Converter for Battery Charging Systems

In this paper, internal model control (IMC) method, which is a model-based approach that offers more robust and better reference tracking capability than conventional controllers for the unstable process, is applied to the SEPIC converter used in battery charging system for military applications. When a system is not based on a plant model, it is possible to encounter some problems such as dead time and non-linearity in controlling of the system. The purpose of the SEPIC topology is to eliminate the disadvantage of other topologies such as Buck-Boost and Cúk converters that are used for similar applications in reversing the output voltage. In addition, a great amount of voltage and current stress on a component causes the power board to overheat in such converters and requires additional cooling equipment. These problems are not encountered in SEPIC topology. Also, this topology provides high efficiency, step-up/step-down voltage conversion, and excellent transient state response over a wide range. The performance of IMC method applied on SEPIC converter is detailed analyzed in terms of simulation studies that are obtained by using MATLAB/Simulink and experimental studies.

ANALYSIS OF NON-INTERACTING LEVEL PROCESS USING VARIOUS PI CONTROL SETTINGS: A COMPARATIVE STUDY

This study presents a comparative analysis of different proportional-integral (PI) controller tuning methods for the control of a non-interacting liquid level process. Four different PI controller tuning methods, Ziegler-Nichols, Cohen-Coon, Tyreus-Luyben, and Internal Model Control, are evaluated based on their ability to track setpoint changes and reject disturbances. The simulation results show that all four tuning methods can provide satisfactory performance, but the Internal Model Control method outperforms the others in terms of all performance metrics evaluated. The Ziegler-Nichols method produces the worst performance, while the Cohen-Coon and Tyreus-Luyben methods perform better but still have limitations. This study highlights the importance of choosing the appropriate tuning method for liquid level control systems.

Research on clutch position control based on backstepping method for small-sized tractors.

Tractors installed automated manual transmission can avoid discomfort for the drivers because of excessive limbs intervention as well as improve shift quality. Automatic clutch control is critical for the performance of the automated manual transmissions. For a good operation, precise and fast control of clutch position is mandatory. In order to meet these requirements, an enhanced strategy focused on the clutch is presented adopting a simple tracking control method based on the detailed models in this study. Clutch models including DC motor model and mechanical actuator model are established and transformed to a controllable model. On the basis of the control model, a clutch position tracking control scheme is proposed composed of motor control circuit and motor angle tracking controller designed according to the backstepping method. Simulations are carried out in comparation with the internal model control method, and the results demonstrate the effectiveness of the presented control scheme by superior rapidity and accuracy of the controller response for the clutch position tracking system.

Controller Design and StabilityAnalysis of Intensification Process using Analytical Exact Gain-Phase Margin approach.

The controllable intensified process has received immense attention from researchers in order to deliver the benefit of process intensification to be operated in a desired way to provide a more sustainable process toward reduction of environmental impact and improvement of intrinsic safety and process efficiency. Despite numerous studies on gain and phase margin approach on conventional process systems, it is yet to be tested on intensified systems as evidenced by the lack of available literature, to improve the controller performance and robustness. Thus, this paper proposed the exact gain and phase margin (EGPM) through analytical method to develop suitable controller design for intensified system using Proportional-Integral-Derivative (PID) controller formulation, and it was compared to conventional Direct Synthesis methods (DS), Internal Model Control (IMC), and Industrial IMC method in terms of the performance and stability analysis. Simulation results showed that EGPM method provides good setpoint tracking and disturbance rejection as compared to DS, IMC, and Industrial IMC while retaining overall performance stability as time delay increases. The Bode Stability Criterion was used to determine the stability of the open-loop transfer function of each method and the result demonstrated decrease in stability as time delay increases for controllers designed using DS, IMC, and Industrial IMC, and hence control performance degrades. However, the proposed EGPM controller maintains the overall robustness and control performance throughout the increase of time delay and outperform other controller design methods at higher time delay with [Formula: see text] uncertainty test. Additionally, the proposed EGPM controller design method provides overall superior control performance with lower overshoot and shorter rise time compared to other controllers when process time constant is smaller in magnitude ([Formula: see text]) than the instrumentation element, which is one of the major concerns during the design of intensified controllers, resulting overall system with a higher order. The desired selection of gain margin and phase margin were suggested at 2.5 to 4 and 60 °-70[Formula: see text],respectively, for a wide range of control conditions for intensified processes where higher instrumentation dynamic would be possible to achieve robust control as well. The proposed EGPM method controller is thought to be a more reliable design strategy for maintaining the overall robustness and performance of higher order and complex systems that are highly affected by time delay and high dynamic response of intensified processes.

Fractional-order model identification and indirect internal model controller design for higher-order processes

Several studies have shown that fractional-order models with dead-time can be used to capture the dynamics of a wide range of processes. Also, there is more scope to improve the existing identification and control strategies. Hence, this work revisits the identification of fractional-order models (IDFOM) approach to augment the same with a robust indirect fractional-order internal model control (IFOIMC) method to formulate a new identification and control strategy. In this strategy, the fractional-order model obtained using the IDFOM approach is shifted in the frequency domain by a frequency-shifting parameter. With the help of IMC principles, the frequency-shifted model is used to design the IFOIMC controller with the frequency-shifting parameter as the only tuneable parameter. Thus, the frequency-shifting parameter/robustness parameter replaces the only tuning parameter of conventional IMC design. This frequency-shifting parameter is tuned based on maximum sensitivity considerations to ensure the robustness of the design. The resulting IFOIMC controller is further realized as a fractional-order proportional-integral controller in series with a fractional-order filter (FOPIFOF). The effectiveness of the proposed identification and control strategy is illustrated by comparing the closed-loop performance achieved by IFOIMC controllers designed using two widely used identification strategies.

An internal model control method for wave rotor refrigeration process based on Harris hawks optimization

A novel internal model control (IMC) method for wave rotor refrigeration process (WRRP) based on Harris hawks optimization (HHO) is presented in this paper. Firstly, an identification model is established by the test data of the WRRP. In order to reduce the complexity of the model, the Routh order reduction method was used to reduce the order of the identification model. This procedure yields an approximate second order model with time delay for the WRRP. Secondly, an IMC method based on HHO is proposed after analyzing the time delay characteristics of the WRRP model. This method improves the traditional IMC structure, and introduces a three degree of freedom IMC structure. The parameters of the controller are optimized by HHO to make the comprehensive performance index of the system reach the best. Simulation results demonstrate that the proposed method can achieve a good performance of tracking and disturbance rejection.

A 2-DOF-IMC method for suppressing transmission chain vibration of wind power generation system with a clearance

To address the vibration problem caused by gear clearance in the wind drivetrain, a two-degree-of-freedom internal model control (2-DOF-IMC) method was proposed to suppress the clearance’s nonlinear vibration. The two-mass wind drivetrain with clearance is the object of this paper’s research. First, we discuss the nonlinear characteristics of gear clearance and the mechanism by which vibration occurs. The nonlinear clearance unit is then decomposed into a linear unit and a nonlinear bounded disturbance unit. A suppression disturbance method based on 2-DOF-IMC was proposed to address nonlinear bounded disturbances. The 2-DOF-IMC overcomes the shortcoming of the PID control and the common internal model control (1-DOF-IMC) by allowing for independent adjustment of the anti-disturbance performance, effectively suppressing the nonlinear disturbance caused by gear clearance. A 2-DOF-IMC scheme and an IMC controller are designed, and the method’s effectiveness is validated through simulation.

Robust tracking control for operator‐based uncertain micro‐hand actuator with Prandtl–Ishlinskii hysteresis

AbstractSince the hysteresis property inherently exists in the rubber material, it is necessary to deal with the control issues for the micro‐hand by considering the hysteresis property. Therefore, in this paper, the robust tracking control for the micro‐hand systems is discussed from the aspect of the Prandtl–Ishlinskii hysteresis property which is more applicable for the real applications. Firstly, a new model is obtained by combining the dynamic model of the micro‐hand with Prandtl–Ishlinskii hysteresis property. Secondly, a new stability condition based on bounded input and bounded output stability is proposed for the Prandtl–Ishlinskii hysteresis modeled micro‐hand system from two different cases. Thirdly, by designing the robust controllers based on the internal model control method, the tracking performance can be improved by eliminating the effect from the disturbance. Finally, simulation is used to further demonstrate the effectiveness of the proposed design scheme.

A PID Control Method Based on Internal Model Control to Suppress Vibration of the Transmission Chain of Wind Power Generation System

Vibrations occur in the wind turbine drivetrain due to the drivetrain’s elasticity and gear clearance. Typically, the PID control method is used to suppress elastic vibration, while the method with the disturbance suppression function is used to suppress nonlinear gear clearance vibration. The purpose of this paper is to propose an equivalent PID control method based on the internal model control (IMC) for suppressing vibration caused by the wind turbine drivetrain’s elasticity and gear clearance. The equivalent PID controller can suppresses elastic vibration; the IMC controller can suppresses gear clearance vibration. First, the vibration principle of the two-mass wind turbine drivetrain with clearance is discussed. After analyzing the nonlinear characteristics of the gear clearance, the nonlinear clearance system is decomposed into a linear unit and a nonlinear bounded disturbance unit. To suppress nonlinear bounded disturbances, a disturbance suppression method based on IMC is proposed; simultaneously, an equivalent PID controller based on IMC is designed to resolve the vibration issue caused by the wind turbine drivetrain’s elasticity. The simulation experimental results show that the clearance vibration is suppressed by the original IMC method. The PID controller obtained by the IMC equivalent transformation can suppress the elastic vibration.

Decoupled Fractional Order Filter with PID Controller Design for Multivariable Distillation Column System

The main objective of this research work is the design of decentralized PID controller with fractional order filter for strongly connected multivariable distillation column system. Wherein, the major contribution of this paper is the proposition of compensators for the decoupling process, in addition to extending the application of the proposed approach from Single-Input Single-Output (SISO) systems into Multi-Input Multi-Output (MIMO) systems. More precisely, the proposed idea is based on eliminating the strongly interactive terms between the inputs and outputs of the multivariable distillation column systems so that, the separated multi-loop parts can be treated as a set of SISO subsystems, which have an equivalent dynamic of the whole original system. Thereafter, a PID controller with a fractional filter has been introduced to the decoupled subsystems in decentralized scheme in order to improve the control system robustness. Two multivariable systems have been carefully considered in this paper; the first is a theoretical Two-Input Two-Output (TITO) system while the second is the Wood and Berry distillation column. The obtained results have confirmed the superiority of the proposed approach over the two degrees of freedom technique, which is based on Internal Model Control method. Indeed, the proposed approach has reduced the dynamic error, the settling time, and the rise time. Furthermore, the designed decentralized PID controller with fractional filter has demonstrated rejection to structured perturbation from one loop to another.

Music Psychological Meta-Analysis and Real-Time Measurement Algorithm Based on Nonlinear Dynamic Incremental Internal Model Algorithm

As an important part of aesthetic education, music is the artistic expression of human emotions. It has a crucial impact on the cultivation of individual music perception ability, music aesthetic ability, music creation ability, etc. The degree of influence of emotions and values in music runs through the individual. This study introduces a method to independently design a predictive controller using the theoretical framework of the state-space method. Since the same results as DMC can be derived, it can be regarded as an understanding of DMC in the time domain. We take the asymptotically stable object of SISO as the model and use the step response coefficient to directly model, but this method makes the control uncontrollable, so we use the method of adding the correction parameter to make the observable process more effective. The advantages of one-time online optimization can reduce the amount of calculation and greatly enhance the robustness in the control process. In order to study the dynamic characteristics of the system, an internal model control system is introduced. By studying the closed-loop stability of the internal model system, the internal model structure of the dynamic matrix control system is studied, and its dynamic characteristics are further studied. When analyzing the dynamic characteristics, we can know that the dynamic characteristics of the system only depend on the object characteristics and control strategies, and have nothing to do with the model length. This study introduces the basic structure, main properties, and design method of the internal model controller. On the basis of conventional internal model control, an enhanced internal model control method is introduced. Through the analysis of the sensitivity function and the complementary sensitivity function, the robust performance and robust stability of the enhanced internal model control system are studied. Music learning psychology is related to the effect of music teaching. Since individual psychological development is dynamic and controllable, by grasping students’ music learning motivation and music psychological ability, we can well practice the concept of contemporary new curriculum standards and implement high-quality music courses. This study mainly discusses the music learning psychology itself, the analysis of real-time measurement results, and the analysis of teaching countermeasures, and does some research on music theory and teaching practice. Through real-time measurement research, it can be concluded that the real-time measurement results are relatively optimistic, which shows that teachers can maintain students’ learning well as long as they use teaching methods that conform to students’ learning psychology. The nonlinear dynamic incremental internal model algorithm can improve students’ various music psychological abilities and achieve the expected music teaching goals.

Adaptive Internal Model Control of SCR Denitration System Based on Multi-Objective Optimization

Many thermal power plants use selective catalytic reduction (SCR) systems to complete flue gas denitration. The system has the characteristics of large inertia, large delay and nonlinearity. At the same time, it is difficult to use the controller under a single working condition to meet the control task of the system under the full working conditions. In order to solve the above control difficulties, This paper proposes a two-degree-of-freedom internal model control (2-DOF-IMC) method based on controller parameter adaptation and multi-model adaptation to realize the control of the full working conditions of the SCR system. First, the intelligent identification method based on Differential evolution quantum particle swarm optimization (DEQPSO) is used to obtain the sub-model of ammonia injection-SCR outlet Nitrogen Oxide (NOx) concentration in typical working conditions. A 2-DOF-IMC controller under each sub-model is established. Then, aiming at system set point tracking performance, anti-disturbance performance, and control energy consumption, the Pareto optimal solution of each controller is obtained by using the Non-dominated Sorting Genetic Algorithms-II (NSGA-II) algorithm based on chaotic mutation. Finally, the controller parameter adaptive strategy is designed based on the Takagi-Sugeno (T-S) fuzzy model, and the multi-model adaptive strategy is designed based on the recursive bayesian probability weighting. Through the dynamic performance test and the anti-disturbance performance test, it is verified that the 2-DOF-IMC based on controller parameter adaptation and multi-model adaptation has good control performance and adaptability to all working conditions. The method proposed in this paper combines the advantages of multi-parameter and multi-model strategies, further improves the control quality, and provides a new solution for the control of thermal power plant SCR system.

A Novel Discrete Internal Model Control Method for Underactuated System

A Novel Discrete Internal Model Control Method for Underactuated System

Internal model control based proportional-integral controller with class topper optimization for power control of molten salt breeder reactor core

Internal model control (IMC) method is based on mathematical process model to design the controller. In IMC method, the approximated object model is parallelized with the actual model. The inverse of invertible part of the approximated dynamic model and a low pass filter is considered in the proposed controller design. As an IMC approach has an intuitive design with simple structure and it does not need an accurate model of the object, to explore its application in power control, molten salt breeder reactor (MSBR) core is chosen. A proportional-integral (PI) controller based on IMC technology is designed to control core power of MSBR. The filter constant of IMC technology is optimized with Class topper optimization (CTO) algorithm which improves robustness of the control scheme. Power control of MSBR core is studied for load tracking with step disturbance. This study shows that core power is controlled by CTO based IMC-PI controller.

Design of an IMCPID Optimized Neural Network for Stepless Flow Control of Reciprocating Mechinery

It is usually difficult to design a controller for a nonlinear multiple-input and multiple-output (MIMO) system. The methodological approach taken in this study is a mixed methodology based on a PID-type internal model control (IMC) method and neural network (NN) optimization algorithm. The NN controller is designed for adjusting the sole parameter in IMCPID and compensating the characteristic changes and non-linearity in stepless flow control. In this study, a simulation of a nonlinear MIMO system with strong coupling is carried out. The simulation results indicate that the proposed control method has a better performance in settle time, overshoot, robustness and set-point tracking accuracy compared with other considered methods.

Improved internal model control method for carbon content of argon–oxygen refining ferrochromium alloys

We propose an improved internal model control method for the carbon content in the production process of argon–oxygen refining ferrochromium alloys. In the actual process, the control output is restricted and cannot fully demonstrate the control effect. Therefore, by decomposing the traditional internal model controller, we achieved saturation compensation, overcoming this limitation. In addition, by referring to the current production process, the smelting stages with different carbon-content ranges were determined. Combined with the actual equipment conditions, an anti-saturation internal model controller structure and a controller saturation numerical expert system were constructed, forming a fully improved internal model control system. The proposed method fully utilizes the steady-state error-free characteristic of the internal model control, achieving the preset control goal and significantly shortening the smelting time and improving the smelting efficiency.