Integral Derivative Controller Research Articles

A novel fault classification‐based fault‐tolerant control for two degree of freedom helicopter systems

SummaryFault detection and diagnosis (FDD) plays an essential role in identifying and isolating various faults in a system. In general, fault detection is attained by monitoring the extent of matching between the actual operating condition and an analytical model prediction. This process aids in achieving enhanced performance, and for operating the system within the acceptable bounds. In this article, a neural network‐based classification method and fuzzy‐based control strategy are adapted to perform FDD on a two degree of freedom (2DoF) helicopter system. The operating voltage, pitch, and yaw outputs of the 2DoF helicopter system were considered for developing the algorithm. The signal processing properties of the discrete wavelet transform and pattern recognition properties of a multilayer perceptron neural network are adapted to design the classification algorithm. The developed algorithm improves training and testing efficiency. In order to reinstate the normal operation of the system, the classifier output is integrated with a hybrid fuzzy‐proportional integral derivative controller. This control technique enhances the 2DoF helicopter response as the time taken by the pitch and yaw angle to settle trajectory is reduced. The results depicted validate the efficiency of the projected approach.

Optimization of PID Controller Parameters for First Order plus Time Delay Process

Pressure control could be a key process variable in industrial sector because pressure provides an important condition for air-conditioning, chemical reaction, boiling, extrusion, vacuuming, and distillation. Worse pressure control will cause critical quality, productivity and safety issues at the same time excessive pressure within a closed container will result in dangerous explosion. Hence, it is highly important to maintain the pressure at desirable range even in the presence of disturbance and the change in set point. Usually the pressure is controlled by Proportional Integral Derivative (PID) controller in industries because of its higher performance and simple structure over other controllers. The PID controller was designed using Z-N tuning method. Further the PID values were optimized for higher performance by using Pattern Search and Genetic Algorithm. Finally, the response of optimized PID controller was compared with standard Z-N PID controller. The error performance criteria like ISE, IAE, and IATE were used for comparison

Robust Simultaneous Stabilization Using Derivative State Feedback

Abstract In simultaneous stabilization of continuous time switched linear system models of inertially coupled dynamic systems with bounded persistent external disturbance and internal parameter variations, the generalized proportional integral derivative (PID) controller suffers from a serious drawback. It loses the ability to guarantee exponential stability of the closed-loop error response, which is the difference between the actual and the desired closed-loop responses. The high value of the hardware gain has no control over the situation. On the contrary, the derivative state feedback (DSF) controller effectively employs the hardware gain in diminishing the effects of external and internal disturbances. These facts are proved and illustrated by suitable examples. The proposed method of simultaneous stabilization is shown to be an easier alternative to solve Diophantine equations encountered. The method for single input single output (SISO) systems is also shown to extend seamlessly to the control of multiple input multiple output (MIMO) square models with equal number of inputs and outputs. The shortcoming of the method is pointed out when the models are not square. The advantages of the proposed methodology over the existing methods are outlined. Finally, an efficient time domain simulation scheme is presented for the numerical study of such models in time and transfer function domain with nonzero initial conditions.

An Air Pressure Control Method for Fast and Precise Inspection on Triple Action Pressure Sensors

In this study, we proposed a multi-section gradient control method for fast and precise inspection on triple action pressure sensors, which is used to check the abnormal low, mid, and high pressures of the compressor. The multi-section gradient control is divided into time sections that change either rapidly or slowly as the pressure rises or falls, respectively. In the low-speed sections, the pressures are slowly changed so as to allow for precise measurements, while in the high-speed sections, the pressures are quickly changed in order to shorten the inspection time. This involves calculating the target (set-point) values of steps in each section in real time and adjusting the present value using the Proportional Integral Derivative (PID) control method. In order to verify the proposed method, we constructed an automatic inspection system and ran experiments to evaluate the performance. These performance results exhibited an error rate of 0.286% while the semi-automatic inspection took an error rate of 0.857%. The inspection time was greatly shortened to the point that the automatic inspection took less than 12 seconds per product while the semi-automatic inspection took about 30 seconds. The experimental results showed high reliability and shortened inspection time.

Precision positioning control of a long-stroke stage employing multiple switching control

This paper proposes a multiple switching control method for a long-stroke precision stage to improve its performance. The stage consists of a motor stage with a travel of 10 cm and a piezoelectric transducer (PZT) stage with a resolution of 1 nm, which allows a simultaneously large travel length and precision positioning. The developed switching algorithms can select the optimal control sequence that minimizes the system cost by predicting of the future responses. We obtain the stage models through experiments. For the PZT stage, we design two robust loop-shaping controllers: the fast controller provides rapid transient responses and the smooth controller give smooth responses. We then derive corresponding robust proportional–integral-derivative controllers and develop a control switching mechanism that can simultaneously accomplish fast and smooth responses. The switching mechanism predicts future system responses by all possible control sequences and selects the optimal one to minimize specified costs. For the motor stage, we apply gain scheduling control, where the gain adjustment is larger than previously because the PZT stage can quickly compensate for the position errors of the combined stage. The designed control structures are then implemented for simulation and experimental verification. The results indicate that the proposed control is effective in improving system responses.

Control of bearingless electric machines dedicated for aviation

Purpose The paper presents the results of work on control systems of bearingless electric motors. Authors proposed the applications of bearingless electric machines for aircraft actuation system. Suggested solution characterizes novel concept of on-board equipment design such as More Electric Aircraft. Magnetic suspension technology allows elimination of friction force and the negative performance features of classic bearing system. However, to achieve all these purposes appropriately, dedicated control system must be also applied. Design/methodology/approach The development of a control system of bearingless electric machine is presented in detail. Mathematical model and construction of induction bearingless motor are widely discussed. Then, proportional–integral-derivative controller algorithm designing for BEM control system was presented using the well pole placement method. Simulation model of BEM control system with use of Matlab-Simulink software was shown. Finally, experimental studies on laboratory stand were introduced. The paper presents design methodology of conventional and advanced control system of bearingless motor. Findings The presented concept of the bearingless electric machines could be applied in the on-board actuation system. During research, full control system of bearingless electric motor was designed and tested. This system consisted of two subsystems. The first responded for rotary speed stabilization and second one was designed for position control of the rotor in the air gap. Practical implications The presented concept of the bearingless electric machines could be applied in the on-board actuation system. During research, full control system of bearingless electric motor was designed and tested. This system consisted of two subsystems. The first responded for rotary speed stabilization and second one was designed for position control of the rotor in the air gap. Originality/value The idea of active magnetic suspension system will be implemented for aviation on technology readiness level V. The paper presents unique laboratory stand with bearingless electric motor and experimental studies. The stable time responses of designed control system were presented and discussed. In addition, preliminary considerations of advanced control system with robust controller were introduced as well.

A phase locking scheme of two-mode squeezed microwave preparation

As the core of quantum entanglement, two-mode squeezing is manifested in cross-correlations of incompatible observables between two subsystems, which makes the two-mode squeezed microwave an ideal resource for applications in quantum communication, quantum illumination, and quantum microwave navigation. Currently the preparation scheme of two-mode squeezed microwave, based on the Josephson parametric amplifier (JPA) and a superconducting 180° hybrid ring coupler, proves to be the most efficient and excellent in quantum properties. Nevertheless, the difficult phase locking processing restricts the further improvement of entanglement. There is no effective solution but the dual-path receiver with phase stabilization measures, and the phase error reaches as high as 0.3°, which still does not meet the requirements for phase locking precision and entanglement stability. To overcome the academic obstacle, we propose a phase locking scheme to achieve a stable two-mode squeezed microwave. There are two JPAs used to separately generate single-mode squeezed microwaves, between which the difference lies in the fact that the input of one JPA is phase-modulated but the other is not. A superconducting 180° hybrid ring coupler is used to distribute the two single-mode squeezed microwaves into two output paths, which are two-mode squeezing if the squeezing directions of the two single-mode squeezed microwave are orthogonal. That is to say, the relative phase satisfies the condition <inline-formula><tex-math id="M65">\begin{document}$\theta = {\text{π}}/2$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="3-20191348_M65.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="3-20191348_M65.png"/></alternatives></inline-formula>. By mixing the unmodulated single-mode squeezed microwave and one output of the superconducting 180° hybrid ring coupler, a relative phase is obtained in subsequent process. Proportional integral derivative (PID) controller is used as the input of phase error, and the output is used to adjust the pump phase of JPA, which is the key to phase locking and stable two-mode squeezing. The present research not only provides an effective strategy to achieve stable two-mode squeezed microwave, but also may attract more attention to the precisive measurement of two-mode squeezed microwave.

Fuzzy rule-based auto-tuned internal model controller for real-time experimentation on temperature and level processes

Recently, internal model control (IMC) technique has been widely employed for various industrial close-loop control applications. Rewarding feature of IMC controller is that we need to tune only one parameter λ (close-loop time constant) for achieving the desired close-loop response. But, finding an appropriate value of λ is not an easy task. From the basic behaviour of IMC-based close-loop responses, it is found that when the process variable is moving very fast towards the desired value, relatively larger value of λ (smooth control) is required to reduce the possible oscillations. In contrary, smaller value of λ (tight control) is preferred when the process response is quickly moving away from the set point to restrict its further deviation. Hence, to mitigate the limitation of conventional IMC tuning with a fixed λ, a fuzzy rule-based auto-tuning scheme is proposed here for IMC-proportional integral derivative (IMC-PID) controller and its performance is validated through real-time experimentation on temperature and level control loops.

Transverse dynamic analysis of semi-active quarter car model controlled with an optimal conventional controller

In the present work, a monotube magneto-rheological damper is fabricated and its dynamic characteristics are evaluated at different input currents. The non-parametric approach is used to model the damper from experimental results. A quarter car semi-active vehicle is considered and the passive damper is replaced with a magneto-rheological damper using nonparametric model. Controlling of system is achieved by adopting the proportional integral derivative (PID) controller. The parameters of the PID controller are identified by coupling the PID with an optimisation algorithm by considering three optimal criteria. After obtaining the desirable optimal parameters of the PID controller, the dynamic response of the vehicle subjected to random road excitation is estimated and compared with the vehicle with passive damper. The results show that there is a reduction in the acceleration and vertical displacement of sprung mass in all classes of the road under optimal parameters conditions and thus leads to improved performance.

Design of TID controller based on firefly algorithm for controlling the speed of a D.C. Motor

Implementation of tilt integral derivative (TID) controller for controlling the speed of a D.C. Motor using meta heuristic nature inspired algorithm named by firefly algorithm (FA) is proposed in this paper. By using FA based optimization technique, we have tuned TID controller parameters. Further, comparative analysis has been done with FA based conventional PID and fractional order PID (FOPID) controllers. The performance of TID is investigated in terms of various performance indices like integral of square error (ISE), integral of time-weighted absolute error (ITAE), integral of absolute error (IAE) and integral of time-weighted square error (ITSE). Investigation carried out reveals the advantage of TID over conventional PID and FOPID in terms of reduced settling time and performance indices.

A comparative evaluation of PID-based optimisation controller algorithms for DC motor

DC motors are generally used in industrial activities due to its simple structure and higher reliability. However, a DC motor is unable to control the operational speed as per required by the system. Proportional integral derivative (PID) controller is used in common for motor application due to its ease of control and operation. Nevertheless, the setting of PID parameters in DC motor control is difficult when the system is highly nonlinear and complex. Hence, the development of an improved auto-adjusted PID controller is an urgent necessity. This paper develops a robust PID controller-based optimisation algorithms for DC motor for finding the optimum parameters setting of PID controller. A comprehensive comparative analysis between PID-based backtracking search algorithms (BSA) and PID-based particle swarm optimisation (PSO) is provided. The conventional PID, PSO PID, and BSA PID models are evaluated based on overshoot reduction and settling time under ramp step and unit step speed variations. The results demonstrate that the PID controller with BSA achieves an optimum output with better dynamic and static performance.

Load Frequency Control Design for Two Area Interconnected Power System with DFIG Based Wind Turbine

Abstract In this paper, a modern two stage frequency control approach for two area interconnected power system with doubly fed induction generator (DFIG) based wind turbine is proposed. For first stage, a proportional integral derivative (PID) controller is designed for every conventional thermal area to control frequency and tie line power. In the second stage, a PID controller is implemented in DFIG to regulate its speed and accordingly control system frequency particle swarm optimization is used to tune the controllers of conventional thermal units and DFIG. The effectiveness and robustness of the proposed control scheme are investigated under different operating conditions using MATLAB/Simulink.

Model Predictive Control for Steering System of Water-Jet Propulsion

Water-jet propulsion is a widely applied ship propulsion technology. Its steering control system has an important impact on manoeuvre performance. In this paper, transfer function model is firstly established on the basis of mechanism analysis of water-jet steering system. Then, by considering the variability of model parameters and input constraints in practical operation, a model predictive controller is designed for steering system control. Subsequently, model based disturbance observer is employed in an attempt to reject environmental disturbances. The performance of the proposed model predictive control (MPC) scheme for a particular steering system is compared with that of conventional proportional integral derivative (PID) control strategy. Simulation results demonstrate that the proposed model predictive controller outperforms conventional PID controller, particularly in robustness, response delay and tracking accuracy.

Depth Control of Autonomous Underwater Vehicle Using Discrete Time Sliding Mode Controller

This study presents a Discrete Time Sliding Mode Controller (DSMC) application on depth plane of Autonomous Underwater Vehicle (AUV). The main contribution on this work is an implementation of DSMC on NSP AUV II. Sliding Mode Control (SMC) is a robust type of controller and certainly suitable for controlling AUV in the presence of environmental disturbances and uncertainties. DSMC preserves the properties of standard SMC. Linearized dynamic model of NSP AUV II is used in the numerical simulations. Discrete Proportional Integral Derivative (PID) controllers are used for performance comparative analysis. The design of discrete PID and DSMC for NSP AUV II depth is described. Comparative study between the control laws is presented. The simulated results illustrate strong robustness, improve performance and satisfactory stability of DSMC as compared to discrete-time PID controller.

Data‐driven control for combustion process of circulating fluidised bed boiler

Owing to the advantages of burning low-quality coal (coal slime and coal gangue), furnace desulfurisation, low N O x emission and deep load adjustment, the circulating fluidised bed (CFB) combustion technology becomes one of the few fossil fuel utilisation technologies funded continuously by the Chinese government. However, compared with the pulverised coal boiler, the combustion process of CFB boiler is more complicated because of the larger time delay, significant uncertainty and more coupled variables. In this study, a data-driven proportional–integral-derivative (DD-PID) control strategy is presented for the combustion control of CFB boiler to improve the operating performance under full operating conditions. By analysing the running mechanism of combustion process, an inverse decoupler is introduced to transfer the combustion object to the generalised controlled object, which has relatively independent input–output relationship. After that, a normative procedure of DD-PID, including PID-parameter database establishment, information-vector neighbourhood selection, active PID-parameter determination, database update, and redundant vector deletion, is given. Finally, a series of case study, including numerical tests applied to the proposed combustion model and application test employed on 330 MW CFB simulation platform proves the feasibility of DD-PID control strategy.

Voltage control of solid oxide fuel cell power plant based on intelligent proportional integral-adaptive sliding mode control with anti-windup compensator

Solid oxide fuel cell (SOFC) plant is considered a most important type in the field of fuel cells, which gives control difficulties such as fuel flow constraints, load disturbance, system nonlinearities, and parameter uncertainties. However, due to these difficulties, the voltage control of SOFC plant is extremely difficult. In this paper, a new intelligent proportional integral-adaptive sliding mode control (iPI-ASMC) with anti-windup compensator is proposed to control the output voltage of SOFC plant to keep up with the rated voltage. The referred iPI-ASMC is made of three sub-components: (i) an extended state observer (ESO)-based-intelligent proportional-integral to estimate the unknown dynamic, (ii) an adaptive sliding mode control is added to compensate the estimation error of unknown dynamic, and (iii) an anti-windup compensator based on back-calculation is used to deal with saturation problem which is caused by input constraints. Moreover, the effectiveness and efficiency of the proposed iPI-ASMC strategy is demonstrated by comparing with some other approaches such as conventional proportional integral-derivative (PID) controller, intelligent proportional-integral (iPI) and fuzzy PID controller. Corresponding simulation results show that the proposed iPI-ASMC approach provides better dynamic responses and outperforms to compared methods in term of settling time, peak overshoots, integral absolute error (IAE), integral square error (ISE), and integral time absolute error (ITAE).

Chicken Egg Incubator Temperature Control Using DC Lights With PID Control

Abstract - Hatching of chicken eggs or incubators is a tool to petrify the hatching process by using incandescent lamps as a substitute for the hatching process of hens, In the industry Chicken poultry hatchery cultivation is very important in terms of temperature stability especially using artificial incubators. The incubator circulating on the market today only uses the reley system, which works on and off on a very long time to reach the steady state. The purpose of this research is to make chicken egg incubatot using dc lamp and lm35 sensor with Proportional Integral Derivative (PID) control. In this experiment we can find out the values of Proportional gain (Kp), Integral Time (Ti), and Derivative Time (Td). Keyword : PID, lm35 sensor, DC light, Chicken Egg Incubator

Optimal AGC Design for a Hybrid Power System Using Hybrid Bacteria Foraging Optimization Algorithm

This paper proposes a hybrid optimization algorithm developed through the novel combination of particle swarm optimization (PSO) oriented bacteria foraging optimization algorithm (BFOA) for finest tuning of proportional integral derivative (PID) controllers for load frequency control problem of hybrid power system comprising of photovoltaic (PV) system and thermal generators. In order to prevent the solution from sub-optimal condition and to accelerate the convergence time of the problem the PSO is merged with BFOA to solve the LFC problem of the hybrid system. To check the power of the proposed strategy initially the hybrid system is evaluated for step load change and the results are compared with some powerful optimization algorithms such as BFOA, PSO, and flower pollination algorithm (FPA) based PID in terms of computed gains and achieved value of error. The results obtained show the cost and control efficacy of the proposed design. The study is extended to investigate the performance of proposed design with dead-band of governor and generation rate constraint non-linearity. Finally, the robustness of the proposed design is evaluated for random load change, sinusoidal load change and for extensive parametric variations from the typical plant values and the application results are presented.

Simulation Tool for Tuning and Performance Analysis of Robust, Tracking, Disturbance Rejection and Aggressiveness Controller

The RTD-A (robust, tracking, disturbance rejection and aggressiveness) controller is a novel control scheme that substitutes the classical proportional integral derivative (PID) controller. This novel controller’s performance depends on the four controller tuning parameters (θR, θT, θD and θA). The tuning of RTD-A controller is more transparent than classic PID controllers. The RTD-A tuning parameters values lies between ZERO and ONE. Availability of a tool to design optimal parameters for this controller and evaluating the performance on a given system is necessary for the researchers. In this paper, the new simulation tool is presented to deal with the RTD-A control scheme. There are four graphical user interface tools included in the proposed tool and working of each tool is explained in detail. To demonstrate the proposed tool, two examples, which involve a liquid level control application and an air pressure control application, are presented in this work. The performance of the RTD-A controller is compared with PID controller. RTD-A controllers are tuned using optimization algorithms and their performances are observed and analyzed in both cases under deterministic and uncertain conditions.

Application of fractional-order voltage controller in building-integrated photovoltaic and wind turbine system

The share of electricity generation based on clean, inexhaustible and continuous energy sources, such as solar and wind, in total energy production, is rising day by day due to its significant advantages such as having the less negative impact on global climate and environmental pollution and not requiring fuel for energy production. It is reported that commercial and residential buildings correspond to about 20.1% of the world energy consumption, so it is necessary to provide energy needs of buildings with hybrid renewable energy systems. When using non-continuous energy sources such as solar panel and wind turbines, it is important to ensure ensuring a stable and quality power flow to the building while the power demands of building show very sharp variability. This work presents a voltage control system using fractional-order operators in the smart residential building-integrated hybrid renewable power plant (solar + wind). In this research article, fractional-order proportional–integral/proportional–integral–derivative controllers are proposed on a synchronous frame for a pulse-width modulation based three-phase voltage source inverter in residential building-integrated solar panel and wind turbines system (building-integrated photovoltaic/wind turbine system) in order to improve the quality of injected voltage to building. When comparing the effect of closed-loop voltage control system with integer order controllers (proportional–integral and proportional–integral–derivative) on the power quality at the building distribution by analyzing the simulation results for proposed case study, use of fractional-order voltage controllers for nonlinear system such as building integrated with hybrid renewable sources is more suitable than using integer order voltage controllers.