IMC Controller Research Articles

Modified fractional order IMC design based drug scheduling for cancer treatment

This paper aims to improve chemotherapy drug(s) scheduling of the drug dose injected into a patient. The existing practice has been established on experiments performed during the drug development process. In general, chemotherapeutic drugs are highly toxic in nature and directly affect the probability of a patient's survival. Therefore, a modified fractional order internal model control (MFOIMC) scheme with a minimal number of design parameters is proposed for effective drug scheduling. The proposed control scheme is a combination of fractional calculus and IMC. The fractional order IMC (FOIMC) is modified by incorporating an extra control loop with a proportional transfer function. Further, IPD and IMC control techniques are also designed for comparative analysis. The dragon fly algorithm (DA) is employed to optimize the parameters of the controller. Results show that the proposed control scheme provides a continuous and precise chemotherapeutic drug dose to the patient on a daily basis. It is also shown that MFOIMC improves IAE by 34% and 32% in comparison to IMC and FOIMC, respectively, which proves its superiority over other controllers.

An optimised 2-DOF IMC-PID-based control scheme for real-time magnetic levitation system

This paper addresses an optimised 2-DOF internal model-based PID controller for unstable magnetic levitation system. Here, the proposed controller is realised using IMC control theory and its parameter are calculated using Maclaurin series expansion. Particle swarm optimisation (PSO) algorithm is used for obtaining an optimised 2-DOF IMC-PID controller. The proposed method is simpler to use due to its explicit tuning method as compared to other frequency response methods. The real-time experimental results are given, illustrating the effectiveness of proposed controller. The suggested controller not only improves the transient and tracking response but also maintains the robustness of maglev system under various disturbance environments. The performance of the proposed controller is compared with conventional PID controller.

Automatic Control on Batch and Continuous Distillation Columns

Distillation is fundamental in Chemical Engineering. It is a highly complex and non-linear process. Therefore, developing intelligent control systems for distillation columns is challenging. These control techniques are based on previous knowledge and intuitive rules. In this work, several control strategies, such as IMC, Gain Scheduling, Expert, Fuzzy (Mamdani and Sugeno) and Neural-Network Control are applied to control a simulated distillation column for batch and continuous processes, and their performance is compared with a traditional PI controller. The controlled variable was the distillate molar fraction using as manipulated variable the reflux ratio. All control strategies were tested with respect set-point changes in two scenarios: without and with disturbances. The best control strategy was the Neural-Network, using a NARMA-L2 controller. This control has a good disturbance rejection and a fast set-point tracking with a smooth control action.

Comparison for Level Control of a Coupled-Tank using PI, PI-plus-Feedforward, and IMC Controllers

Comparison for Level Control of a Coupled-Tank using PI, PI-plus-Feedforward, and IMC Controllers

IMC Multi-Controller Strategies applied on a Manipulator Robot

The paper focuses on the use of multi-controller approach to control a robot wrist (STÄUBLI robot RX 90). The descriptions of a nonlinear mathematical model of the process have been presented with the local parametric models around operating points. Controller design of a conventional PID, IMC control, LQG control and Hv (loop shaping) has been described around each selected operating points for each local parametric models. Finally , in order to show the efficiency of the proposed method, some simulation results in CAO 3D solid-works and MATLAB environments are given.

Design And Analysis of Intelligent Controller For Temperature Control In CSTR System

Continuous Stirred Tank Reactor (CSTR) is one of the most important unit operations in chemical industries which exhibits highly non-linear behaviour and usually has wide operating ranges. Chemical reactions in the reactor are exothermic and require that energy can either be removed or added to the reactor to maintain a constant temperature. In this work, different controllers such as PID, Cascade, IMC controller, Differential Evolution, and Fuzzy Logic Controller have been evaluated. The objective is to control the temperature of CSTR in presence of the set point and analyzed which controller provides the most linear response. Model design and simulation are done in the MATLAB/SIMULINK software. The response of the CSTR, which is observed with applying step input and improved by designing conventional and intelligent controllers.

Analytical design 2 DOF IMC control based on inverted decoupling for non‐square systems with time delay

AbstractNon‐square systems which have more inputs than outputs are difficult to control because of their special structure. In this article, inverted decoupling is extended to non‐square systems and an effective dynamic decoupling effect is achieved. The method to obtain realizable and stable decoupler matrices is provided. Based on the decoupled processes, the 2 DOF (degrees of freedom) controllers consisting of feedback filters and reference controllers are designed and then the performances for the reference response and the disturbance response are improved simultaneously. The feedback filters are designed based on the trade‐off between robustness and performance for input disturbance rejection. The reference controllers are designed in line with the IMC principle. To restrain overshoot, a requirement on the system maximum singular is proposed and the parameters of the reference controllers are determined based on the requirement. Simulation studies are provided to demonstrate the effectiveness of this method.

Tuning of IMC based PID controllers for integrating systems with time delay

Design of Proportional Integral and Derivative (PID) controllers based on IMC principles for various types of integrating systems with time delay is proposed. PID parameters are given in terms of process model parameters and a tuning parameter. The tuning parameter is IMC filter time constant. In the present work, the IMC filter (Q) is chosen in such a manner that the order of the denominator of IMC controller is one less than the order of the numerator. The IMC filter time constant (λ) is tuned in such a way that a good compromise is made between performance and robustness for both servo and regulatory problems. To improve servo response of the controller a set point filter is designed such that the closed loop response is similar to that of first order plus time delay system. The proposed controller design method is applied to various transfer function models and to the non-linear model equations of jacketed CSTR to demonstrate its applicability and effectiveness. The performance of the proposed controller is compared with the recently reported methods in terms of IAE and ITAE. The smooth functioning of the controller is determined in terms of total variation and compared with recently reported methods. Simulation studies are carried out on various integrating systems with time delay to show the effectiveness and superiority of the proposed controllers.

Analyses of robust stablity of imc control systems

Analyses of robust stablity of imc control systems

Improved 3D trajectory tracking by Nonlinear Internal Model-Feedback linearization control strategy for autonomous systems

This paper presents a nonlinear controller for 3D trajectory tracking of an autonomous helicopter. The main idea consists of combining feedback linearization controller together with a novel nonlinear IMC control. This approach allows more robustness, fast and good trajectory tracking. It is applied to a small, eight-rotor, Square-Shaped Octo-Rotor and has shown satisfactory results using adequate control architecture. The controller effectiveness is shown through numerical simulations and confirmed using a software simulator and real tests.

English

Level control in a hemispherical tank is a challenging task in process industries due to nonlinear variation of level with height. The need for an accurate and appropriate online or off line model to control such nonlinear process is on huge demand to avoid process complications in practical applications such as oil refineries, dye industries etc. In this work, a hemispherical tank of 40 liter capacity was subjected to dynamic analysis and level measurement was done using an on-line Honeywell capacitance sensor. Modeling was performed using first principle of mathematics, open loop analysis and Skogestad technique. The various models were validated using standard performance indices and it was observed that Skogestad model performed better with minimum model error. Real time level control was implemented using various robust, adaptive and intelligent controllers such as Smith, IMC and NMPC. The performance of the controllers was evaluated using time domain specifications. Error analysis was also performed and it was observed that NMPC and IMC controller outperformed the other controllers.

Output constrained IMC controllers in control systems of electromechanical actuators

Electromechanical actuators are widely used in many industrial applications. There are usually some constraints existing in a designed system. This paper proposes a simple method to design constrained controllers for electromechanical actuators. The controllers merge the ideas exploited in internal model control and model predictive control. They are designed using the standard control system structure with unity negative feedback. The structure of the controllers is relatively simple as well as the design process. The output constraint handling mechanism is based on prediction of the control plant behavior many time steps ahead. The mechanism increases control performance and safety of the control plant. The benefits offered by the proposed controllers have been demonstrated in real-life experiments carried out in control systems of two electromechanical actuators: a DC motor and an electrohydraulic actuator.

Design of RTDA controller for industrial process using SOPDT model with minimum or non-minimum zero

This research paper focuses on the design and development of simplified RTDA control law computation formulae for SOPDT process with minimum or non-minimum zero. The design of RTDA control scheme consists of three main components namely process output prediction, model prediction update and control action computation. The systematic approach for computation of the above three components for SOPDT process with minimum or non-minimum zero is developed in this paper. The design, implementation and performance evaluation of the developed controller is demonstrated via simulation examples. The closed loop equation, block diagram representation and theoretical stability derivation for RTDA controller are developed. The performance of proposed controller is compared with IMC, SPC, MPC and PID controller and it is demonstrated on Industrial non-linear CSTR process.

Design and analysis of a multivariable fractional order controller for a non-minimum phase system

Two control strategies for multivariable processes are proposed that are based on a decentralised and a steady state decoupling approach. The designed controllers are fractional order PIs. The efficiency and robustness of the proposed strategies is tested and validated using a non-minimum phase process. Previous research for the same non-minimum phase process has proven that simple decentralised or decoupling techniques do not yield satisfactorily results and a multivariable IMC controller has been proposed as an alternative solution. The simulation results presented in this paper, as well as the experimental results, show that the proposed fractional order multivariable control strategies ensure an improved closed loop performance and disturbance rejection, as well as increased robustness to modelling uncertainties, as compared to traditional multivariable IMC controllers.

A Novel Tuning Algorithm for Fractional Order IMC Controllers for Time Delay Processes

A Novel Tuning Algorithm for Fractional Order IMC Controllers for Time Delay Processes

Design of Multimodel based MPC and IMC control schemes applied to injection molding machine

Good control of plastic melt temperature for injection molding is very important in reducing operator setup time, ensuring product quality, and preventing thermal degradation of the melt. The controllability and set points of barrel temperature also depend on the precise monitoring and control of plastic melt temperature. Motivated by the practical temperature control of injection molding, this paper proposes MPC and IMC based control scheme. A robust system identification and control methodology is developed which uses canonical varieties analysis for identification and model predictive control for regulation. The injection molding process consists of three zones and the mathematical model for each of the zone is different. The control output for each zone controller is assigned a weight based on the computed probability of each model and the resulting action is the weighted average of the control moves of the individual zone controllers. Keywords: Injection-Molding Machine (IMM), IMC Control, Temperature Control.

Application of IMC Control for Rotor Side Converter of DFIG WPGS

The principle of internal model control was analyzed, which was designed as the controller for the rotor side converter of double fed induction generator based wind power generation system, the stator flux-oriented vector control structure of DFIG with internal model control was designed, with the mathematical models of the DFIG under d-q coordinated system, combined with the principle of IMC control strategy, the inner current loop and outer speed control loop was designed, the simulation shows the control characteristic.

An Improved Control Method to Solve Thin System Problem

Recently, research of non-square systems mainly focuses on fat system, and control approach to thin systems is less. This paper proposes a new method using improved selection control to square the systems and then design IMC controller for thin systems in which the number of output variables exceeds the number of input variables. This proposed method is applied to the control problem in which there is an output variable that is barely impact on the system. Then we use PSO method to seek the parameters. Then we can come to a conclusion that this method has better performance to reducing loop method through simulation. Moreover, this new method is simple and easy to implement.

Nonlinear Model Predictive Control Based on Wave Model of High-Purity Internal Thermally Coupled Distillation Columns

Although the internal thermally coupled distillation column (ITCDIC) is much more energy-efficient than the conventional distillation column, the complex dynamics stemming from thermal coupling between the rectifying column and the stripping column have restrained the achievement of control strategies and application in chemical industry. To reduce the difficulties, a novel nonlinear wave model of ITCDIC process is proposed based on the wave theory in the separation processes to simplify the mechanism model of ITCDIC. A nonlinear model predictive control based on the proposed wave model (NWMPC) of the ITCDIC process is further established to handle the multivariable interactions and improve the control performance. A dynamic optimization scheme characterized by an improved control parametrization method is introduced to solve the problem generated by the NWMPC model. An IMC controller is also explored as a comparison research. In the example of a benzene–toluene system, NWMPC presents great advantage over...

The Control of Non Isothermal CSTR Using Different Controller Strategies

In all process industries, the process variables like flow, pressure, level, concentrationand temperature are the main parameters that need to be controlled in both set pointand load changes.A control system of propylene glycol production in a non isothermal (CSTR) wasdeveloped in this work where the dynamic and control system based on basic massand energy balance were carried out.Inlet concentration and temperature are the two disturbances, while the inletvolumetric flow rate and the coolant temperature are the two manipulations. Theobjective is to maintain constant temperature and concentration within the CSTR.A dynamic model for non isothermal CSTR is described by a first order plus deadtime (FOPDT).The conventional PI and PID control were studied and the tuning of controlparameters was found by Ziegler-Nichols reaction curve tuning method to find thebest values of proportional gain (Kc), integral time ( I) and derivative time ( D).The conventional controller tuning is compared with IMC techniques in this work andit was found that the Ziegler –Nichols controller provides the best control for thedisturbance and the worst for the set-point change, while the IMC controller resultsshow satisfactory set-point responses but sluggish disturbance responses because theapproximate FOPTD model has relatively small time delay.Feedforward and feedforward combined with feedback control systems were used asanother strategy to compare with above strategies. Feedforward control provides abetter response to disturbance rejection than feedback control with a steady statedeviation (offset). Thus, a combined feedforward-feedback control system is preferredin practice where feedforward control is used to reduce the effects of measurabledisturbances, while feedback trim compensates for inaccuracies in the process model,measurement error, and unmeasured disturbances. Also the deviation (offset) infeedforward control was eliminated.