PID Controller Design Research Articles

Design of Robust PID Controller Using PSO-Based Automated QFT for Nonminimum Phase Boost Converter

This brief reports a novel method of synthesizing a robust PID controller for regulating boost DC-DC converter that exhibits non-minimum phase (NMP) dynamics and complex-conjugate poles in its linear model. The NMP dynamics restrict the achievable closed-loop bandwidth and make tuning of PID parameters a difficult task. To solve this problem, the proposed design method uses the Quantitative Feedback Theory (QFT) in conjunction with particle swarm optimization (PSO) to carry out automatic loop-shaping. Due to the global optimization capability of PSO, the proposed multi-objective function approach with PID simplifies the loop-shaping to compensate the converter having complex-conjugate zeros. An attractive feature of this design method is that it accounts for the worst-case scenario due to parametric variations in the converter model. The real-time simulation results and the experiments reveal the efficacy of the proposed method.

Genetic algorithm-based design of a nonlinear PID controller for the temperature control of load-following coolant systems

Genetic algorithm-based design of a nonlinear PID controller for the temperature control of load-following coolant systems

Efficient PID Control Design for Frequency Regulation in an Independent Microgrid Based on the Hybrid PSO-GSA Algorithm

Microgrids are a part of the power system that consists of one or more units of distributed generation and are expected to remain in operation after being disconnected from the system. Since they rely on overlying networks, frequency control is very important for network-independent operation. Some of the most common problems in independently operating microgrids are frequency sustainability and its fluctuations. The main purpose of this study is to control the frequency of a microgrid in island mode in different scenarios. The objective function is defined based on time and changes in the system frequency. Thus, the variable parameters of the PID controller are transformed into an optimization problem and are solved through the hybrid PSO-GSA algorithm. The study considers four scenarios: (a) a microgrid dynamic model and optimal PID controller coefficients; (b) variable velocity disturbance applied to the studied system in order to observe power changes and the microgrid frequency; (c) stepped load changes applied to the studied system; and (d) the proposed methods on the standard test function. Simulations under different operating conditions are performed, indicating improvements in the stability of microgrid frequency fluctuations by means of the proposed control method.

A Fast Calibration Method for Sensors of Atmospheric Detection System

To meet the needs of a large number of high-altitude meteorological detections, we need to perform fast, high-precision, and high-reliability calibrations of the sensors in the atmospheric detection system (ADS). However, using the traditional method to calibrate the sensor with high precision often takes a lot of time and increases the cost of workforce and material resources. Therefore, a method for realizing fast sensor calibration under the current system hardware conditions is required. A physical field model of Tube–Air–ADS is proposed for the first time, and the transfer function is obtained by combining the system identification, which provides the possibility for dynamic analysis of the calibration system. A Multi-Criteria Adaptive (MCA) PID controller design method is proposed, which provides a new idea for the parameter design of the controller. It controls the amplitude and switching frequency of the controller’s output signal, ensuring the safe and stable operation of the calibration system. Combined with the hardware parameters of the system, we propose the Variable Precision Steady-State Discrimination (VPSSD) method, which can further shorten the calibration time. Comparing and analyzing the current simulation results under Matlab/Simulink, the proposed MCA method, compared with other PID controller design methods, ensures the stable operation of the calibration system. At the same time, compared with the original system, the calibration time is shortened to 47.7%. Combined with the VPSSD method, the calibration time further shortens to 38.7 s.

Designing PID Controller Using improved Differential-Pole-clustering Approach of Model Order Reduction Techniques

The method of mathematical modelling that takes into account various physical systems, such as various tele-communications, High voltage transmission, and various chemical reactors, ultimately produced a variety of solutions for bigger order complex mathematical models with higher order. Order reduction is essential for such higher order systems (HOS) for reducing mathematical complexity for designing controllers. In order to improve upon several existing model order reduction approaches, the goal of this paper is to solve difficult higher order models using Differential Pole Cluster Mixed (DPM) Techniques. The accuracy of the proposed reduced model has been made via comparing step responses of original and reduced order models. In order to improve upon several existing model order reduction approaches. The higher order system PID Controller has been made using the proposed reduced-order approach.

Optimal PID Controller Design Based on Proportional Gain for Quarter Vehicle Model

In this study, an effective and new design method was used to determine the parameters of the PID controller used in order to improve the performance of a vehicle's active suspension system and to suppress vibrations in the vehicle. In this method, the PID controller is designed based on the optimal proportional gain kp setting, taking into account the settling time and maximum overshoot of the quarter vehicle system. This method is based on obtaining the other parameters of the controller by adjusting the kp to minimize the settling time and maximum overshoot error in a stable cycle. The obtained simulation results were evaluated by comparing the uncontrolled suspension system and the suspension system in which the PID controller whose parameters were adjusted with the proposed effective design method. It suppressed the system responses of the PID controller more effectively than the passive suspension system.

Design and Testing of a Pid Controller on a Parrot Minidrone

This paper focuses on quadcopter control design and uses the Simulink Support Package for Parrot Minidrones to test various control approaches. This project's goal is to bridge the knowledge gap between control design and implementation, making it simpler to comprehend the fundamental ideas of control theory. Obtaining a dynamic model of the quadcopter, linearizing the system around an equilibrium point, designing PID controller on the linearized system, and then verifying the controllers on the non-linear model using simulations and test flights with the actual drone are the key components of this research. The tuned controllers are validated by trajectory tracking, setpoint regulation, and disturbance rejection.

Design and Testing of a Pid Controller on a Parrot Minidrone

This paper focuses on quadcopter control design and uses the Simulink Support Package for Parrot Minidrones to test various control approaches. This project's goal is to bridge the knowledge gap between control design and implementation, making it simpler to comprehend the fundamental ideas of control theory. Obtaining a dynamic model of the quadcopter, linearizing the system around an equilibrium point, designing PID controller on the linearized system, and then verifying the controllers on the non-linear model using simulations and test flights with the actual drone are the key components of this research. The tuned controllers are validated by trajectory tracking, setpoint regulation, and disturbance rejection.

Optimal PID plus second-order derivative controller design for AVR system using a modified Runge Kutta optimizer and Bode’s ideal reference model

Optimal PID plus second-order derivative controller design for AVR system using a modified Runge Kutta optimizer and Bode’s ideal reference model

Design and Application of Optimally-Tuned Variable Parameters PID Controller for Nonlinear Engineering Systems

Abstract The goal of this article is to investigate the implementation of the Cuckoo Search Algorithm (CSA) as an optimization technique to determine the parameters of variable parameters PID (VP-PID) controller. The VP-PID has three parameters that have to be optimally evaluated. A case of three physical imbedded nonlinearities in a single area electric power system has been selected to test the suitability of the proposed technique. The integral-square error (ISE) criterion has been considered as a part of the objective function together with the percentage overshoot and settling time. Matlab/Simulink software has been used in the simulation process. The simulation results show that the proposed VP-PID controller furnishes a better performance than the conventional PID controller.

Fractional Order PID Controller Design for Maximum Power Point Tracking of Dynamic Loaded PV System

Fractional Order PID Controller Design for Maximum Power Point Tracking of Dynamic Loaded PV System

Enhanced design of PID controller and noise filter for second order stable and unstable processes with time delay

Abstract In this work, a PID controller along with a noise filter is designed using direct synthesis method for second order stable and unstable processes with time delay. Proposed method involves a single design parameter λ whose value need to be adjusted such that a desired balance between performance and robustness of the system is achieved. Guidelines to select suitable values of λ based on the maximum sensitivity values are provided. Various computer simulations are performed in presence of measurement noise on stable, unstable, integrating and double integrating dynamic systems to illustrate the advantages of suggested control method over some contemporary techniques. Performance measures (integral absolute error and integral squared error) and robustness measures such as maximum sensitivity (M s), complimentary sensitivity (M t) are calculated for the quantitative performance evaluation of the proposed tuning strategy. The suggested tuning algorithm is simple and it yields improved closed loop response compared to some reported methods, satisfactory robustness and smooth control action in presence of noise.

Design of discrete PID controllers for maximizing stability margins

AbstractThe objective of this paper is to provide a discrete PID controller design procedure for maximizing stability margins. First, a new and complete characterization of the entire set of stabilizing discrete PID controllers for a given plant is presented. Then, based on this characterization, an efficient algorithm is developed for testing if, for a given plant, there exists a digital PID controller gain parameter space corresponding to closed‐loop poles being inside the circle of radius centered at the origin. The developed algorithm is finally applied along with a bisection strategy to determine, for a specified small positive number , a minimum value and the corresponding discrete PID controller set for achieving at least of stability margin. To illustrate the features of our new characterization of stabilizing digital PID controller sets and the effectiveness of the presented algorithms to the maximum stability‐margin discrete PID controller design, two numerical examples are provided.

Ball Balancing PID System using Image Processing

Abstract: Control theory and its applications are crucial when operating within the area of dynamic systems. Compensating for disturbances and external actions imposed on a given system being inherently unstable or semi-stable. This project consists in the realization of a Ball-Plate system with 2 degree of freedom which will control the position of the ball by tilting the plate. Two servomotors will allow the table to be oriented with a certain angle of inclination to counterbalance the movements of the ball. A Pi camera placed above the device will transmit live images of the plate to a Raspberry Pi which will be responsible for analyzing them to draw conclusions such as the position of the all, its speed and acceleration. A Python program will then be responsible for processing these data, feed it to designed PID controller and transmitting the result by USB to the Arduino which will control the rotation of both servos independently. All the data will be sent to the Python program running in another computer using MQTT protocol. And set point, error and PID v/s time graphs would be plotted. The experiment is done by dropping a ball on the plate and waiting for the system response to balance the ball in the center of the plate and to follow the set trajectories. The plate is made of wood to ensure smooth slipping of the ball without friction. Balancing experiments were done, following the set trajectories, and positioning the ball at the center of the plate. Through the use of multithreading, image processing at the rate of 90 FPS was achieved. And results were plotted. In conclusion it should be emphasized that in control systems acceptable real time performance can be achieved by decentralizing the processing unit into several PUs. It is notable to mention that with small additional piece of software and control checkpoints PU redundancy feature can be added to the plant, so in the event of physical damage and PU failure the other PU can be notified and take over the system.

A Novel Adaptive PID Controller Design for a PEM Fuel Cell Using Stochastic Gradient Descent with Momentum Enhanced by Whale Optimizer

This paper presents an adaptive PID using stochastic gradient descent with momentum (SGDM) for a proton exchange membrane fuel cell (PEMFC) power system. PEMFC is a nonlinear system that encounters external disturbances such as inlet gas pressures and temperature variations, for which an adaptive control law should be designed. The SGDM algorithm is employed to minimize the cost function and adapt the PID parameters according to the perturbation changes. The whale optimization algorithm (WOA) was chosen to enhance the adaptive rates in the offline mode. The proposed controller is compared with PID stochastic gradient descent (PIDSGD) and PID Ziegler Nichols tuning (PID-ZN). The control strategies’ robustnesses are tested under a variety of temperatures and loads. Unlike the PIDSGD and PID-ZN controllers, the PIDSGDM controller can attain the required control performance, such as fast convergence and high robustness. Simulation results using Matlab/Simulink have been studied and illustrate the effectiveness of the proposed controller.

Reinforcement learning based adaptive PID controller design for control of linear/nonlinear unstable processes

Control of unstable process is challenging owing to its dynamic nature, output multiplicities and stability issues. This research work focuses to develop a generic data driven modified Proximal Policy Optimization (m-PPO) reinforcement learning based adaptive PID controller (RL-PID) for the control of open loop unstable processes. The RL agent acting as the supervisor explores and identifies optimal gains for the PID controller to ensure desired servo and regulatory performance. Adaptive modifications in terms of inclusion of action repeat, modified reward function and early stopping criterion are incorporated to the m-PPO algorithm to handle the unbounded output nature of unstable processes. Effect of m-PPO algorithm is proven in terms of reward earned by the RL agent. Servo and regulatory performance of the proposed RL-PID controller is compared with that of classical PID controller, Deep Discriminant Policy Gradient based PID controller and Advantage Actor Critic based PID controller on various linear, non linear, multivariable unstable systems including unstable jacketed CSTR process and Unmanned Aerial Vehicle in simulation environment. Validation of the proposed controller is also done in real time level control process station, a laboratory level experimental test rig. It is observed that the proposed RL-PID performs satisfactorily better than the other controllers in both qualitative and quantitative metrics. The striking feature of this control scheme is that it eliminates the need of process modeling and pre-requisite knowledge on process dynamics and controller tuning. The proposed controller is a data driven generic approach that can be directly applied to any industrial process.

Research on Sliding Mode Control Method of Medium and Low Speed Maglev Train Based on Linear Extended State Observer

As a new mode of transportation, maglev train has a broad prospect. As one of the key technologies of maglev train, suspension control technology has been a hot research field. Maglev train has the characteristics of complex system modeling, strong nonlinear model, unstable open-loop system, and complex and changeable working conditions. To date, the widely used method is still the design of PID controller based on linearized maglev model. However, with the passage of time, its shortcomings become increasingly clear. To achieve better control effect, an adaptive sliding mode control method based on linear extended state observer (LESO) is proposed in this paper, which not only improves the response speed of the system, but also improves the robustness and anti-interference ability of the system, and greatly reduces the impact of external disturbances on the suspension stability. First, the dynamic model of the system is established, the control characteristics of the system are analyzed, and the design method of current loop is proposed to reduce the order of the system model. Then, the traditional sliding mode control based on reaching law is designed for the reduced order system, and the performance and shortcomings of the controller are analyzed. Aiming at the defects of traditional sliding mode control, a sliding mode controller based on linear extended state observer is designed. The total disturbance and unmodeled part of the system are estimated in real time by LESO and eliminated in sliding mode control. It can be proved that the designed controller can ensure the stability of the closed-loop system, the system state can converge asymptotically in the neighborhood near the expected value, and has a very fast convergence speed. At the same time, the system has strong robustness to noise and external disturbances. Finally, the effectiveness of the proposed controller is verified by simulation and experiment.

Design and Evaluation of Self-Tuning Fuzzy PID Controller with Reference Model for Ball and Beam Mechanism

—Fuzzy Logic controller is one of the popular techniques in control system. However, the accuracy depends on numbers and the design of membership functions. Further, the output does not always fulfill specific design requirements. In this study, Fuzzy PID controller with first-order reference model had been designed and evaluated. The proposed new structure is able to guide fuzzy mechanism to produce desired output response as specified by the first-order model such as the time constant, rise time and settling time. The study was implemented on a ball and beam system to control the position of the ball while rolling on a beam. The control of a ball and beam system is challenging because it is an open-loop unstable system as the ball will continuously moves on the beam without control. The study also compares the results acquired from Fuzzy PID and Fuzzy PI plus PD against the proposed Fuzzy PID with first-order reference model controller. The evaluation covers for a pole starting from 0 until 1.0 for the first-order model. As a results, the proposed controller is able to produce an output response as specified where the fastest response was acquired when pole is set to 0.9. Whereas the Fuzzy PID and Fuzzy PI plus PD always produce the same transient response during step input test.

Resonant PID Controller Design for a Three-Phase Four-Wire Voltage Inverter with Split DC Buses

Resonant PID Controller Design for a Three-Phase Four-Wire Voltage Inverter with Split DC Buses

Linear System Order Reduction Model Using Stability Equation Method and Factor Division Algorithm for MIMO Systems

Abstract: A New mixed method is proposed which combines the advantages of Stability Equation method and factor division algorithm in deriving the reduced order models for higher-order linear dynamic systems. The denominator of the reduced order model is obtained by the stability equation method and the numerator values are calculated using factor division algorithm. The reduced order models retain the steady-state value and guarantees stability of the original system. The proposed algorithm has also been extended for the design of PID controller for MIMO systems. The numerical examples are solved in literature to show the flexibility and effectiveness over other existing methods