Multi-loop PID Controller Research Articles

A New H∞ Weighted Sensitive Function-Based Robust Multi-Loop PID Controller for a Multi-Variable System

A New <i>H_∞ </i> Weighted Sensitive Function-Based Robust Multi-Loop PID Controller for a Multi-Variable System

A Novel Multi-Loop PID Controller for Photovoltaic-Grid Interface DC Energy Utilization Farm

This paper proposes a novel control system for control of a hybrid photovoltaic PV farm utilization with alternative power source for DC type loads. A controller consisting of two different controllers is mainly used to regulate the DC-DC converter and also to control power flow from alternative power source to reduce a weighted total sum of all loop errors, to mainly track a given speed reference trajectory depicting the demand for discharge or flow and also to ensure power quality, reliability and stability. The proposed control function is digitally simulated using the MATLAB/Simulink/SimPower System software environment. The dynamic performance of the hybrid system is examined for the control system validation under normal and abnormal operating conditions.

An Effective Optimization Method and Implementation of Permanent Magnet Electrodynamic Wheel for Maglev Car

The levitation-propulsion integration ability of radial permanent magnet electrodynamic wheel (PM EDW) renders its competitive edge over other magnetic levitation systems. A low-cost and effective second induction method is proposed to target the synchronous improvement of the saturation speed, levitation and propulsion forces. Its effectiveness is determined from the small-scale EDW to the full-scale EDW via theoretical model, simulation analysis and experiments test. First, according to magnetic charge theory, an updated EDW is proposed and developed. Simulated and tested results of the small-scale EDW demonstrate that the levitation force, propulsion force and saturation speed are increased by 14%, 7% and 30%. This improvement benefits the increased induction current and the mitigated skin effect. Afterwards, further analysis of the full-scale EDW with rings of various conductivity and thickness is conducted. The levitation force, propulsion force and saturation speed are enhanced by more than 50%, 10% and 200% synchronously. Based on analysis of power loss under the same levitation and propulsion forces, the updated EDW is more efficient than the original EDW. Ultimately, a proof-of-principle prototype with the updated EDW and 4-m long guideway are developed. The multi-loop PID control strategy along with dynamic mode implementation methodology are introduced. The scaled prototype is levitated over guideway at 12 mm and the levitation-propulsion ability is implemented with the maximum acceleration of 1.25 m/s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . This proof-of-principle prototype with updated EDW and control strategy paves the way to engineering applications of Maglev car.

Bayesian Optimization for automatic tuning of digital multi-loop PID controllers

In recent years, the use of Bayesian optimization (BO) for efficient automatic tuning of general controller structures through iterative closed-loop experiments, has been attracting increasing interest. However, its potential for tuning interactive multi-loop PID controllers in Multi Input Multi Output (MIMO) processes remains largely unexplored. Even though the optimization domain greatly affects closed-loop performance and safety, it is usually defined manually, through expert knowledge or experimentation. This paper presents a novel systematic methodology for defining the optimization domain for automatic multi-loop PID tuning using BO. Sequential loop closing, system identification and tuning relations are used to constrain the bounds on controller parameters to meaningful ranges, including gains and sampling times. This provides an effective way to improve the convergence of BO and secure process safety during closed-loop experiments, without requiring a MIMO process model or extensive prior knowledge. The methodology can be applied ”as is” to single-loop PID controllers.

Multi-loop PID controllers design with reduced loop interactions based on a frequency-domain direct synthesis method

A novel direct synthesis (DS) method for simultaneous and non-iterative design of multi-loop PID controllers for stable multivariable processes is presented in this article. We deal with the specifications of the desired closed-loop dynamics, which is a critical design decision in the DS method, for designing multi-loop controllers. Control loop interactions in multi-loop control systems are usually undesirable but unavoidable due to inter-channel interactions of multivariable processes. The main feature of the method is that the multi-loop control design aims at reducing the interactions among loops. The proposed DS method specifies the design target in terms of the frequency response of the desired closed-loop transfer function (CLTF) and synthesizes the controllers in the frequency domain. We develop an approach to effectively specify the desired closed-loop frequency response to achieve improved control performance by minimizing the sum of the magnitude of the interactive parts in the desired CLTF matrix. With the desired closed-loop frequency response and a process model, the frequency response of an ideal multi-loop controller is synthesized and then approximated to a PID controller. We provide simulation studies of three industrial benchmark processes and a nonlinear quadruple tank system to illustrate the design result and performance of the proposed method and make comparisons with several existing methods. Our results prove the effectiveness of the frequency-domain DS method. The proposed multi-loop PID controllers achieve reduced loop interactions and provide satisfactory overall performance.

MIMO modeling and multi-loop control based on neural network for municipal solid waste incineration

The Municipal solid wastes incineration (MSWI) process with complex mechanism and strong nonlinearity is an important part of resource cycle. It is a challenge to design its multivariable controlled object model and control strategy. To solve this problem, a multi-input multi-output (MIMO) data-driven model and a multi-loop PID controller are proposed in this paper. Firstly, a feature selection method based on Pearson correlation coefficient (PCC) and expert knowledge is used to analyze the relationship between the manipulated variable and the controlled variable of MSWI process. Secondly, a MIMO Takagi–Sugeno fuzzy neural network (TSFNN) based on multi-task learning (MTL) is designed to construct the multivariable controlled object model. Thirdly, a multi-loop PID controller based on quasi-diagonal recurrent neural network (QDRNN) is constructed, which has self-feedback channel and interconnection channel, and can adjust the control parameters automatically. Next, the stability of control strategy is proved by Lyapunov second method. Finally, the modeling effect and control performance are confirmed on the simulation experiments based on the real MSWI process data.

Development of control strategies for an air separation unit with a divided wall column using a pressure-driven digital twin

Digital twins of process plants provide various opportunities to improve plant operation by in silico studies. A major advantage of a simulation-based digital twin is its availability prior to the physical plant. Thus, it can be used for design purposes. In this work, dynamic simulation studies of a novel air separation unit topology are conducted to develop a reliable control strategy. This novel air separation design includes an integrated argon removal column. That is, a column with the intent to remove an argon-rich fraction is included into the low-pressure column by means of a divided wall section. The liquid reflux for the integrated argon removal column is generated by an additional condenser/reboiler in the low-pressure column above the divided wall section. The intent of the argon removal is to increase the energy efficiency of large scale air separation units for oxygen production. Using the digital twin, three multi-loop PID control strategies are compared regarding reliable operability.

Data-based Sequential Design of 2 × 2 Multi-loop PID Controllers

This paper introduces a sequential design method for multi-loop PID controllers under the Virtual Reference Feedback Tuning (VRFT) methodology. Simulation studies are presented to illustrate the effect of different reference models on the proposed design for two-input two-output (TITO) systems. Lastly, the proposed design is compared with benchmark designs for well-known multivariable processes.

Event-driven enabled regression aided multi-loop control for SEC minimisation in SWRO desalination considering salinity variation

This paper addresses the energy minimised operation of seawater reverse osmosis (SWRO) desalination process by simultaneous manipulation of feed pressure and reject valve opening. The specific energy consumption (SEC) analysis of SWRO desalination process for maintaining constant permeate flow during feed salinity variation is performed. The analysis is carried out to identify the suitable manipulating variables that can reduce the energy requirement for regulating permeate flow during feed salinity variation. Based on the analysis, a multi-loop control strategy using event-driven programming paradigm aided by regression based predictive model is proposed. The proposed methodology is more desirable than traditional event-driven multi-loop PID control due to smoother control transition and energy reduction. The investigation of SEC and analysis of proposed control strategy were performed using a previously validated dynamic model for SWRO desalination process. The simulation results show that the proposed methodology is superior to conventional PID control by enabling energy-minimised operation of RO process with significant reduction of feed pressure. The analysis shows that the proposed control approach reduces the feed pressure requirement by approximately 300 kPa during feed salinity variation.

Design and Experimental Validation of the Temperature Control of a PEMFC Stack by Applying Multiobjective Optimization

The current environmental challenges require the implementation of environmentally friendly energy production systems. In this context, proton exchange membrane fuel cell stacks (PEMFC) represent, due to their high electrical efficiency and their low level of $CO_{2}$ emissions, a promising alternative technology. However, there are still many technical aspects that need to be improved before they become a commercial reality. One of them is the temperature control of the stack, since its electrical efficiency and its lifetime depend on the performance of this control. In this work, we design a multiloop PID control of the temperature of a PEMFC stack and validate it experimentally. The stack is the prime mover of a micro combined heat and power system (micro-CHP). For this task, we use a previously developed nonlinear model and apply a multiobjective optimization methodology. To assess its performance, the PID control is compared to a second PID control designed with a linearized model. The results show, on the one hand, the importance of having a nonlinear model valid in a wide operation range for the correct design of the temperature control of a PEMFC stack and, on the other hand, the advantages of applying a multiobjective optimization methodology to this problem.

Design of a Decentralized PID Controller for Poultry House System using Genetic Algorithm

Climate control for livestock building is of considerable significance but it is additionally a difficult and convoluted task. The chickens are mainly affected by the variation of temperature and relative humidity. The arrangement of these parameters is accomplished by selecting proper control techniques. In this paper, an optimized controller for the stabilization of the poultry house system has been designed in order to reduce the heat stress of broilers and to achieve the preservation of chickens’ health and comfort. A hygro-thermal model describing the behavior of the poultry house is decomposed into two single loops based on the theory of the effective open-loop transfer function. Adopting a model reduction technique, the equivalent transfer function of each loop is then designed by developing an independent multi-loop PID controller. The initial stability of the reduced model is assured via the Hermite-Biehler theorem. Then, the Genetic Algorithm is adopted to search the optimal gain values that contribute to the desired indoor climate monitoring. An extensive numerical simulation is tested with original experiments measures to show the effectiveness of the design control and the results are compared to those of the ant colony optimization and Ziegler-Nichols methods.

Síntesis secuencial de controladores PID basada en el método LQR

The linear quadratic regulator (LQR) method is generalized to allow synthesis of PID controllers in MIMO processes. The proposed method is sequentially applied to produce proportional, integral and derivative actions. Three major usages are conceived for the proposed methodology: (i) &lt;&lt;de novo&gt;&gt; design of PID controllers, (ii) addition of derivative action to existing PI controllers and (iii) diagonalization of PID gain matrices. The two last procedures can be applied to controllers designed with different methodologies. The developed method was applied to the &lt;&lt;de novo&gt;&gt; design of a centralized PID controller for a three input-three output distillation column as well as the addition of derivative action to existing both centralized and multiloop PI controllers for a nonlinear CSTR. Proposed LQR method allowed the synthesis of centralized and multiloop PID controllers with better characteristics for set-point tracking, disturbance rejection, limited use of control signal and insensitivity to plant model uncertainty than those reported by other authors.

Design of a Data-Driven Multi-loop Self-Tuning PID Controller

PID controllers have been widely employed in real processes. Since PID gains strongly affect the control performance, lots of schemes for tuning PID gains have been proposed. Recently, data-driven PID tuning schemes which determine PID gains directly from the closed-loop operating data attract attentions. Lots of controlled objects are multi-input and multi-output systems, though almost data-driven PID tuning schemes target single-input and single-output systems. In this paper, a data-driven multi-loop self-tuning PID controller design is proposed. The proposed scheme first employs a post-compensator to remove mutual interference. Multi-loop self-tuning PID controller is designed for the decoupled system. The effectiveness of the control scheme is evaluated by a simulation example.

Adaptive multi-loop IMC-based PID controller tuning using bat optimisation algorithm for two interacting conical tank process

In this paper, multi-loop adaptive internal model controller (IMC)-based PID is designed for the two interacting conical tank level process (TICTLP). The nonlinear TICTLP is decomposed into linear transfer function matrix around the operating points and the effective open loop transfer function (EOTF) is developed using simplified decoupler. The IMC-based PID controller parameters are obtained for EOTF model using bat optimisation algorithm (BOA). A weighted sum of integral time absolute error is used as control design objective function for multi-loop IMC-PID design which yields faster settling time with minimum over shoot. The fuzzy-based adaptive gain scheduling is used to provide complete control to TICTLP and fuzzy-based adaptive decoupler is implemented to eliminate the dynamic interaction between control loops. The simulation results of proposed controller are compared with conventional ZN-PID, IMC controllers to show the superiority of proposed controller. The simulation response of proposed controller indicates the performance improvement control schemes interns of time domain performance indices, servo tracking, regulatory response and faster settling time.

Real Time implementation of Multivariable Centralized FOPID controller for TITO process

The development and real time implementation of multivariable centralised FOPID (MC-FOPID) controllers for two interacting frustum conical tank level process (TICFTLP) is presented. The modelling and control of TICFTLP is difficult due to its dynamic coupling between inputs and outputs. The black box model is developed from the open loop experimental data using process reaction curve (PRC) method. The multivariable centralised FOPID (MC-FOPID) controller with five tuning parameters is designed based on the steady state gain matrix of the process and then the controller parameters are tuned using bat optimisation algorithm. The comparison of proposed MC-FOPID controller with multiloop PID controller is demonstrated in the simulation study. The simulation results of the controllers are compared in terms of settling time and integral error criteria. It is found that the MC-FOPID controller has better servo and regulatory response than multiloop PID control. The real time implementation of MC-FOPID is done in MATLAB/SIMULINK using USB-based DAQ module.

Developing Control of Cryo-Pump Test Cold-Box System: Some Investigations

Tokamak, a leading contender of practical fusion reactor, is a popular system using powerful superconducting magnets to confine plasma in a toroidal space to conduct controlled thermo-nuclear reactions required for fusion power research. Tokamak uses state-of-the-art superconducting magnet system requiring specialized cryogenic cooling, which is achieved and maintained by a forced-flow of helium at supercritical state. Supercritical helium mass flow rate as high as 2.21 kg/s at the cryogenic temperature of ~ 4.6 K is necessary not only to obtain cryogenic conditions required for these toroidal superconducting magnet system, but also to regulate cryo-conditions against severe thermal shocks and disturbances due to exothermic plasma reactions and other operational variations. In prior work, the largest cryogenic centrifugal pump was developed to meet and obtain such special cryogenic conditions with various normal and off-normal operating modes. However, such special cryo-pump needs to be tested first rigorously in a special, custom-designed cryogenic test set-up before using them in actual Tokamak systems. A dedicated test-system, called Test Cold-Box, is proposed and developed to test such large cryogenic centrifugal pump. The test-system consists of a liquid helium sub-cooler bath, heat-exchangers, control valves, heaters, etc. In our work, a suitable multi-loop control scheme for the Test Cold-Box is also proposed. Classic multi-loop PID control scheme with classic Ziegler-Nichols and modern IMC tuning have been evaluated using ASPEN HYSYS® simulation environment. The paper describes this Test Cold-Box system including cryo-pump along with suitable controls, and its operational analysis in ASPEN HYSYS® simulation environment.

Multi-loop PID Control Method of Brushless DC Motors via Convex Combination Method

This paper proposes the explicit tuning rule of multi-loop PID controller for brushless direct current motors to predict the system behaviors in time and frequency domains, using properties of the convex combination method. The convex set of the proposed controllers formulates the envelope to satisfy the performances in time and frequency domains. The final control parameters are determined by solving the convex optimization problem subject to the constraints which are represented as convex set of time domain performances. The effectiveness of the proposed control method is shown in the numerical simulation, in which controller tuning algorithm and dynamics of brushless DC motor are well taken into account.

Fuzzy Multivariable Control Strategy Applied to a Refrigeration System

Abstract The refrigeration process involves complex systems exhibiting nonlinearities and coupled behavior, so this paper aims to evaluate the comparative performance of a multivariable fuzzy logic-based control system and a classic multi loop PID. The process variables were the temperature of the secondary fluid (propylene glycol) outlet and the evaporating temperature. The manipulated variables were the compressor frequency speed and the pump frequency speed. Aspen Plus and Aspen Dynamics simulators were used to simulate the experimental prototype. The model was previously validated and linked with MATLAB software, where the controllers were implemented. Tuning of the fuzzy controller was performed through the membership functions and gains adjustments. The tuning of the multi loop PID controller was performed using the Ziegler-Nichols method and then a fine tuning was carried out. In order to fairly compare energy consumption and control effort, the tune of PID-based strategy was finished when similar values of Integral of Squared Error were achieved. Thus, very similar behavior for the process variables in both controllers. On the other hand, a great improvement in the control effort and energy saving was observed when the multivariable fuzzy controller was used in comparison to classic PID. The energy consumption was reduced by 25 % and the control effort by 96 % when the proposed strategy was used.

Heuristic-based multi-scale control procedure of simultaneous multi-loop PID tuning for multivariable processes

A multi-loop PID control system is widely used in process industry where finding good values for the controller parameters is very challenging without systematic procedures. In this paper, based on the multi-scale control scheme a simultaneous multi-loop tuning method for an arbitrary n×n MIMO processes is proposed. The salient feature of the method is that it reduces the multi-loop PID tuning parameters from 4n to only 4 common multi-scale control parameters. Both heuristic- and optimization-based procedures are proposed in order to apply the simultaneous tuning method, which should substantially simplify difficult multi-loop tuning involving numerous controller parameters. To ensure adequate robustness of the multi-loop control system, the balanced sensitivity function is used with the tuning method. Numerical studies based on 2×2, 3×3, 4×4 and 5×5 MIMO processes demonstrate the effectiveness of the tuning method.

Multiobjective Optimization of Multiloop Fractional Order PID Controller Tuned Using Bat Algorithm for Two Interacting Conical Tank Process

Multiloop fractional order PID controller is tuned using Bat algorithm for two interacting conical tank process. Two interacting conical tank process is modelled using mass balance equations. Two Interacting Conical Tank process is a complex system involving tedious interaction. Straight forward multiloop PID controller design involves various steps to design the controller. Due to easy implementation and quick convergence, Bat algorithm is used in recent past for solving continuous non-linear optimization problems to achieve global optimal solution. Bat algorithm, a swarm intelligence technique will be attempted to tune the multiloop fractional order PID controller for two interacting conical tank process. The multi objective optimized multiloop fractional PID controller is tested for tracking, disturbance rejection for minimum Integral time absolute error.