Internal Model Control Approach Research Articles

Assessment of the performance and robustness of a new PID tuning technique for AVR systems

ABSTRACT In this work, a hybrid PID controller, combining Zeigler–Nichols (ZN) theory and the dominant pole placement, has been developed for the automatic voltage regulator (AVR) systems. Furthermore, the reduced order models (ROMs) of AVR systems, namely, AVR-1, AVR-2, and AVR-3, have been established using Particle Swarm Optimization (PSO), Big Bang Big Crunch (BBBC), and Pade’s approximation, respectively. Then, the proposed PID controller has been applied to both the original and developed lower order models of AVR to check the efficacy and robustness of the developed hybrid controller. It is shown that the proposed hybrid PID controller provides a very small value of the percentage peak overshoot (%M p ) and settling time (t s ). Also, the gain margin (GM) and phase margin (PM) are found to be in the desired range. Finally, the sensitivity analysis has also been performed to check the robustness of the proposed controller. The sensitivity function, complementary sensitivity function, and various performance indices have been evaluated for the proposed controller based on Bode’s Integral (BI), Tyreus–Lyuben (T–L), and Internal Model Control (IMC) approaches. The comparative studies of the results show that the proposed controller has smaller values of performance indices and sensitivity function.

Feedback control strategy of Fischer–Tropsch process in a micro-GtL plant

Gas-to-liquid technology monetizes flared natural gas to produce green fuel while reducing carbon emissions. In the first step, oxygen reforms methane to CO and H2 followed by Fischer–Tropsch synthesis (FTS), which is highly exothermic and requires a tight temperature control to avoid thermal runaway. Bench-scale units are insufficient to generate basic data to design dynamic control systems for pilot-plants, particularly for intensified processes, because of uncertainties related to heat losses and the spatial and temporal reaction rates. Here, we propose a simulation-based feedback controller design strategy to initially estimate the parameters of a proportional Integral (PI) controller. We applied a power law model to design the controller in Aspen V12 and tested its robustness with a fractional lumped model as an alternative. An Excel ‘solver module’ estimated heat exchange parameters considering the fluidized bed hydrodynamics at steady state. Then, through dynamic simulation, we identified the parameters of a ‘first-order plus dead time’ model via a step response of the reactor temperature to design the PI temperature controller. The controller parameters were characterized by the internal model control (IMC) approach, which is robust to upstream disturbances, kinetic model mismatch, and heat exchange uncertainties.

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.

An IMC decentralized PID controller retuning method based on frequency domain data

In this work, a method is proposed for retuning decentralized proportional-integral-derivative controllers. It consists in applying the internal model control approach in order to ft the closed-loop frequency response to that of a desired reference model. Then, an optimization problem is solved to adjust the increments on the controller parameters in order to meet the closed-loop requirements. To guarantee stability and robustness, linear margin constraints are applied to each loop, using the concept of effective loop transfer functions to take the coupling into account. The procedure is validated through simulations studies, by comparing it with other decentralized and centralized tuning methods.

Generalized optimal 3-degree of freedom parallel cascade control strategy for stable, unstable and integrating chemical processes

To control stable, unstable and integrating chemical processes, a new three-degree of freedom (3DOF) decoupled parallel cascade control architecture (PCCA) is proposed. The proposed PCCA assimilates two/three controllers (secondary disturbance rejection controller, stabilizing controller for only unstable/integrating plants and set-point tracking controller). Internal model control approach (IMCA) augmented with integral of squared error (ISE) minimization and robustness considerations are adopted to design both the secondary loop disturbance rejection controller and the outer-loop set-point tracking controller with the satisfactory performance-robustness tradeoff. Maximum sensitivity constraints and Routh-Hurwitz stability criteria are applied to design the proportional-derivative (PD) controller which stabilizes the unstable and integrating primary plant. It is worth mentioning that the suggested decoupled 3DOF PCCA requires tuning of only two/three controller parameters which are less when compared to recently reported strategies. Robust stability of the suggested 3DOF PCCA is studied in the presence of uncertainty. The simulation results epitomize that the suggested methodology imparts pre-eminent enhancement in closed-loop performance (faster setpoint following and disturbance elimination) for both nominal as well as perturbed plants.

Low‐gain internal model control PID controller design based on second‐order filter

AbstractA design method is proposed for low‐gain internal model control (IMC) proportional‐integral‐derivative (PID) controllers based on the second‐order filter. The PID parameters are obtained by approximating the feedback form of the IMC controller with a Maclaurin series, in which the second‐order filter is applied using the IMC approach to achieve a low‐gain PID controller that is suitable for model mismatch problems. Analytical PID tuning rules based on the second‐order filter are derived for several common‐use process models. The second‐order filter is designed from the desired time domain performances of maximum overshoot and settling time. Furthermore, the robustness of the IMC PID controller based on the second‐order filter is analyzed, and results show that its robustness performance is better than the first‐order filter under certain conditions. Finally, three categories of models divided by the ration of time constant and time delay are presented in the comparative numerical simulations to validate the effectiveness and generality of the proposed PID controller design method.

A Simple Closed-Loop Test Based Control of Boost Converter Using Internal Model Control and Direct Synthesis Approach

In this article, a simple controller design method for output voltage control of dc–dc boost converter (BC) has been proposed. A simple closed-loop step test with proportional gain <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k_{0}$ </tex-math></inline-formula> is performed. BC open-loop transfer function is obtained from the closed-loop step response test data, which does not require information of BC circuit parameters. Furthermore, the controller is designed from the open-loop model of the BC through the internal model control (IMC) scheme and direct synthesis (DS) approach. The robust stability analysis of both the control schemes has been carried out. The proposed modeling technique and controller design methods have been validated in the experimental setup. Both the controller design techniques work satisfactorily. Superior transient performance of the IMC scheme in comparison to the DS scheme has been observed.

Optimisation of Internal Model Control Performance Indices for Autonomous Vehicle Suspension

Autonomous vehicles (AVs) have grown in popularity and acceptability due to their unique capacity to reduce pollution, road accidents, human error, and traffic congestion. Vehicle suspension is an important component of a car chassis since it affects the performance of vehicle dynamics. As a result, enhancing suspension performance and stability is critical in order to achieve a more pleasant and safer car. Although there are several suspension control methods, they all suffer from fixed gain characteristics that are prone to nonlinearities, disturbances, and the inability to be tuned online. This research provides a comparison of Internal Model Control (IMC) performance metrics for vehicle suspension control. The IMC approach was tuned using the Genetic Algorithm and the Particle Swarm Optimisation algorithms. The performance of each of these schemes was analysed and compared in order to determine the approach with the best performance in terms of AV suspension control. The performance of the system response was compared to that of the traditional IMC. According to the comparison analysis, the optimized IMC systems had lower IAE, ITAE, ISE, rising time, and settling time values than the traditional IMC. Furthermore, there were no overshoots in any of the controllers.

Analytical Design of Fractional-Order PI Controller for Parallel Cascade Control Systems

The fractional-order proportional-integral (FOPI) controller tuning rules based on the fractional calculus for the parallel cascade control systems are systematically proposed in this paper. The modified parallel cascade control structure (PCCS) with the Smith predictor is addressed for stable, unstable, and integrating process models with time delays. Normally, the PCCS consists of three controllers, including a stabilized controller, for a class of unstable and integrating models, a disturbance rejection controller in the secondary loop, and a primary servomechanism controller. Accordingly, the ideal controller is obtained by using the internal model control (IMC) approach for the inner loop. The proportional-derivative (PD) controller is suggested for the stabilized controller and is designed based on a stability criterion. Based on the fractional calculus, the analytical tuning rules of the FOPI controller for the outer loop can be established in the frequency domain. The simulation study is considered for three mentioned cases of process models and the results demonstrate the flexibility and effectiveness of the proposed method for the PCCS in comparison with the other methods. The robustness of the proposed method is also justified by perturbed process models with ±20% of process parameters including gain, time constant, and delay time.

Robust PIDD2 Controller Design for Perturbed Load Frequency Control of an Interconnected Time-Delayed Power Systems

The extensive practice of open communication links in the power system network introduces unavoidable communication time delays (CTDs). These CTDs demean the performance of the load frequency control (LFC) system, and in the worst condition, the LFC system becomes unstable. Thus, this brief proposes a robust proportional integral derivative double derivative (PIDD2) controller design for the perturbed LFC of the interconnected time-delayed power system. In this brief, the worst case plant selection approach is applied to find the worst case plant model using Kharitonov’s stability theorem of the interval system. The proposed PIDD2 controller is designed for the selected worst case plant model of the original interval plant. Furthermore, the tuning of PIDD2 controller is carried out using an internal model control (IMC) approach. The notable feature of the presented IMC scheme is that the IMC filter coefficient ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> ) is determined in terms of maximum sensitivity ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M_{s}$ </tex-math></inline-formula> ) and CTD, which shows the tradeoff between robustness and performance. The proposed control scheme is validated on a two-area time-delayed power system model. The effectiveness and robustness of the proposed IMC-PIDD2 control approach are assessed under parametric uncertainties in system parameters as well as CTD, nonlinearities, and step load demand disturbances. Besides, delay margin (DM) is also computed in the sense of Walton and Marshall stability theorems for the proposed control system. The efficacy of the proposed IMC-PIDD2 control scheme is verified by comparing it with the recently reported control schemes.

Anaerobic Digestion Process Control Using a Data-Driven Internal Model Control Method

Anaerobic digestion processes offer the possibility for wastewater treatment while obtaining a benefit through the obtained biogas. This paper aims to continue the effort to adopt data-driven control methods in the case of anaerobic digestion processes. The paper proposes a data-based Internal Model Control approach applied to an anaerobic digestion process. The paper deals extensively with the issue of choosing the reference model and proposing an engineering approach to this issue. The paper also addresses the issue of verifying robust stability, a very important aspect considering the uncertainties that characterize bioprocesses in general. The approach proposed in the paper is validated through a numerical simulation using the Anaerobic Digestion Model No. 1. During the validation of the proposed control solution, the main operating conditions were analyzed, such as the setpoint tracking performance, the rejection of disturbance generated by variations in the influent concentration, and the effect of the measurement noise on the controlled variable.

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.

An explicit robust stability condition for uncertain time-varying first-order plus dead-time systems

First-order plus dead-time (FOPDT) models are broadly used in process control to represent damped dynamic processes with time delays. An explicit condition for parameter- and delay-dependent robust stability of FOPDT systems with varying uncertain parameters and delay is derived in this paper. An internal model control (IMC) approach is proposed to parameterize stabilizing controllers that satisfy the output tracking objective in time-varying FOPDT systems represented by an uncertain first-order dynamic model with a time-varying delay in the control input. The small-gain theorem is used to derive an explicit necessary and sufficient parameter-dependent robust stability condition as a function of the nominal system gain, nominal varying delay, nominal time constant, and the bounds of the parameter uncertainties. An equivalent proportional-integral-derivative (PID) controller is then extracted to facilitate the implementation of the proposed IMC-based robust control. The application of the proposed explicit robust stability condition is studied in the context of air-fuel ratio (AFR) control in lean-burn spark ignition (SI) engines with a large time-varying transport delay in the control loop due to the placement of the universal exhaust gas oxygen (UEGO) sensor downstream the catalytic converter.

A simple active carbody roll scheme for hydraulically actuated railway vehicles using internal model control

The paper presents the first classical internal model control (IMC) design in the context of railway carbody roll control. We propose a simple control approach for a recent hydraulically actuated vehicle body roll concept that offers limited carbody roll. The IMC approach addresses both preview- and nulling-type tilt setups, highlighting related benefits and limitations. The design provides a model simplification process that facilitates PI and PID-type control structures without the need for complex optimization. A simple, yet practical, tool for the industrial rail rolling stock engineer in vehicle control design is offered. Vehicle roll performance is rigorously studied on the deterministic (curving acceleration response) and stochastic (ride quality) trade off. Simulations are performed on an in-house multibody dynamics software package employing a realistic nonlinear railway vehicle model and allow to appropriately assess the performance of preview and nulling type tilt performance. The results obtained confirm that preview tilt control offers the better tilt performance as it utilizes a tilt command reference, and highlighted that nulling-type tilt performance remains at a relatively comparable level with the former.

Exhaust temperature control for safe and efficient thermal regeneration of diesel particulate filter

Abstract It is crucial for the diesel particulate filter (DPF) that the exhaust temperature at the DPF inlet is well managed and accurately controlled during the thermal regeneration process, in order to ensure the integrity of the filter and improve regeneration efficiency simultaneously. However, this is challenging because the DPF and the upstream diesel oxidation catalyst are complex systems with complicated chemical, thermal and fluid phenomena, especially in real-world driving where the operation and environment conditions are varying and unpredictable. In some cases when the engine speed is suddenly dropped to idle (DTI) from normal operation conditions, uncontrolled regeneration events may occur and result in excessive temperature spikes inside the DPF that may melt down the filter. The objective of this work is to improve safe, reliable and efficient filter operation during the DPF thermal regeneration process, thus reducing the risk of destructive melting of the DPF. Firstly, an experimental method based on the DTI regeneration tests is investigated under a wide range of operation conditions with different soot load levels and regeneration temperatures. Results indicate that the target regeneration temperature curve can be derived as an empirical function of the amount of soot loading in the DPF, which is essential to ensure regeneration safety of the filter in runtime. Then, a novel control strategy combining a model-based feedforward control law and a feedback control law based on the internal model control approach is proposed and developed. The presented control strategy is finally validated under transient conditions in the real driving cycles. Results show that the temperature overshoot is less than 5% during the initial regeneration control stage and the tracking error remains within ± 15 °C of the target regeneration temperature, which is beneficial to safe and efficient thermal regenerations of the filter.

Design of Fractional-Order PID for Stabilized Sight System via Internal Model Control Approach

This paper aims at the problem of accuracy reduction of stabilized sight system caused by uncertain factors and disturbances under complex working conditions. Here, a fractional-order PID (FOPID) controller design method based on internal model control (IMC) approach is proposed for stabilized sight system. First, the IMC-PID is constructed by IMC approach, and then the fractional order is added to its differential and integral terms to obtain the FOPID. The traditional FOPID requires five parameters for tuned, while the proposed FOPID has only three tuning parameters, which can be obtained through the CRONE control technology. The optimal rational approximation algorithm (ORAA) with a high degree of fit is used to approximate the fractional-order calculus operator. Matlab simulation experiments show that the proposed controller outperforms other controllers and can obtain good robustness, disturbance rejection and tracking performance.

Optimal Fractional Order IMC-Based Series Cascade Control Strategy with Dead-Time Compensator for Unstable Processes

In industrial unstable processes, disturbance rejection is more challenging task than setpoint tracking. So, cascade control structure is widely used in many chemical processes to reject disturbances. In this work, an advanced dead-time compensator-based series cascade control structure (SCCS) is suggested for unstable processes. The suggested SCCS has three controllers (named as primary, secondary and stabilizing controllers). Both primary and secondary controllers are designed using fractional order-based internal model control (IMC) approach. The stabilizing proportional–derivative controller is designed using maximum sensitivity considerations and Routh–Hurwitz stability criteria. Optimal values of the closed-loop time constants and fractional orders of IMC filters are obtained using constrained artificial bee colony (ABC) algorithm. This ABC algorithm uses a multi-objective function involving minimization of integral of absolute error, integral of time weighted absolute error and integral of squared error. Simulation studies are conducted using some benchmark plant models used in literature for illustrating the advantages of the proposed strategy compared to the state of the art. Moreover, robust stability of the proposed design is analysed and quantitative performance measures are also computed.

Experimental validation of fractional order internal model controller design on buck and boost converter

In this paper, fractional order internal model control technique is formulated for non-ideal dc–dc buck and boost converter. The fractional order internal model control approach integrates the concept of Commande Robuste d’Ordre Non Entier principle for tuning a fractional order filter with internal model control scheme. The final controller can be expressed as a series combination of proportional integral derivative controller and a fractional order low pass filter. To assess the robustness of the proposed fractional order internal model control scheme, both the servo response and regulatory response of the dc–dc converters are investigated in the presence of disturbances. The efficacy of fractional order internal model control technique is demonstrated via comparison with 2 degrees of freedom internal model control scheme. Furthermore, an experimental validation of fractional order internal model control is conducted on laboratory setup, and a dSPACE 1104 microcontroller is used for hardware implementation. The simulation results and the hardware validation are a testimony to the effectiveness of fractional order internal model control technique.

Experiments-Based Comparison of Different Power Controllers for a Solid Oxide Fuel Cell Against Model Imperfections and Delay Phenomena

Solid oxide fuel cell systems such as those presented in this paper are not only applicable for a pure supply with electric energy, they can typically also be used in decentralized power stations, i.e., as micro-cogeneration systems for houses, where both electric and thermal energy are required. For that application, obviously, the electric power need is not constant but rather changes over time. In such a way, it essentially depends on the user profiles of said houses which can refer to e.g., private households as well as offices. The power use is furthermore not predefined. For an optimal operation of the fuel cell, we want to adjust the power, to match the need with sufficiently small time constants without the implementation of mid- or long-term electrical storage systems such as battery buffers. To adapt the produced electric power a simple, however, sufficiently robust feedback controller regulating the hydrogen mass flow into the cells is necessary. To achieve this goal, four different controllers, namely, a PI output-feedback controller combined with a feedforward control, an internal model control (IMC) approach, a sliding-mode (SM) controller and a state-feedback controller, are developed and compared in this paper. As the challenge is to find a controller ensuring steady-state accuracy and good tracking behavior despite the nonlinearities and uncertainties of the plant, the comparison was done regarding these requirements. Simulations and experiments show that the IMC outperforms the alternatives with respect to steady-state accuracy and tracking behavior.

Stabilized IMC-PI controller designing for IPDT processes based on gain and phage margin criteria

Objective of this work is to design proportional integral (PI) controller based on internal model control (IMC) approach. Proportional (kc) and integral (kI) gains of the proposed IMC-PI controller for integrating plus dead time (IPDT) processes are calculated based on gain and phase margin specifications. Suitable choice of the sole tuning parameter for IMC-PI controller i.e. closed loop time constant (λ) plays crucial towards achieving the desired closed loop response. Comprehensible guideline is provided here towards appropriate choice of (λ). Efficacy of the proposed scheme is verified through simulation study on IPDT processes during servo as well as regulatory responses in comparison with other reported settings.