PID Structure Research Articles

Improved Gorilla Troops Optimizer-Based Fuzzy PD-(1+PI) Controller for Frequency Regulation of Smart Grid under Symmetry and Cyber Attacks

In a smart grid (SG) system with load uncertainties and the integration of variable solar and wind energies, an effective frequency control strategy is necessary for generation and load balancing. Cyberattacks are emerging threats, and SG systems are typical cyber-attack targets. This work suggests an improved gorilla troops optimizer (iGTO)-based fuzzy PD-(1+PI) (FPD-(1+PI)) structure for the frequency control of an SG system. The SG contains a diesel engine generator (DEG), renewable sources like wind turbine generators(WTGs), solar photovoltaic (PV), and storage elements such as flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) in conjunction with electric vehicles (EVs). Initially, the dominance of the projected iGTO over the gorilla troops optimizer (GTO) and some recently suggested optimization algorithms are demonstrated by considering benchmark test functions. In the next step, a traditional PID controller is used, and the efficacy of the GTO method is compared with that of the GTO, particle swarm optimization (PSO), and genetic algorithm (GA) methods. In the next stage, the superiority of the proposed FPD-(1+PI) structure over fuzzy PID (FPID) and PID structures is demonstrated under various symmetry operating conditions as well as under different cyberattacks, leading to a denial of service (DoS) and delay in signal transmission.

Design, modeling, manufacturing, and control of dual axis stabilized system

Recently, Inertial Stabilized Systems (ISS) are widely spread either in military or civilian applications. It’s used to stabilize and point the onboard sensors. Therefore, the accurate modeling and control is a crucial factor to design a suitable control system. In this work, two axes gimbal system is designed, modeled, manufactured, and controlled. Firstly, the stabilized system is built using solid work software. Secondly, the system mathematical model is derived for the physical system with its actuators and encoders. Thirdly, the designed model is manufactured and integrated with the suitable motors; the overall open loop system model is implemented in MATLAB (Simulink). Finally, a modified PI-D structure is designed to stabilize the ISS in an efficient manner, the simulation results show the superiority of the designed controller’s performance and robustness compared to the classical PID in transient and steady state responses.

Frequency control of power system with electric vehicles using hybrid african vultures optimization algorithm and pattern search tuned fuzzy PID controller

This work suggests a hybrid African Vultures Optimization Algorithm (AVOA) and Pattern search (hAVOA-PS) based Fuzzy PID (FPID) structure for frequency control of a nonlinear power system with Electric Vehicles (EVs). To illustrate the dominance of the projected hAVOA-PS algorithm, initially PI controllers are considered and results are compared with AVOA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. To further enhance the dynamic performance, PID and FPID controllers are considered. The dominance of FPID over PID and PI controllers is shown. In the next step, EVs are incorporated in the test system and a comparative analysis of hAVOA-PS based PI/PID/FPID and FPID+EV is presented. To exhibit the superiority of projected frequency control scheme in maintaining the stability of system under different disturbance conditions like load increase in area-1 only, load decrease/increase in all areas, and large load increase in all areas are considered. It is noticed that the suggested hAVOA-PS based FPID controller n presence of EV is able to maintain system stability for all the considered cases where as other compared approaches fail to maintain stability in some cases.

Smith-Predictor-Based Design of Analytical PI-PD Control for Series Cascade Processes with Time Delay

For series cascade processes with a time delay, such as the first-order with time-delay (FOTD) process, the integral with time-delay (ITD) process, second-order integral with time-delay (SOITD) process, and unstable first-order with time-delay (UFOTD) process, this paper proposes a Smith-predictor-based design of analytical PI-PD control for these series cascade processes with a time delay. Firstly, targeting the common FOTD model in the secondary loop, a controller with a PID structure is designed using the direct synthesis method. Additionally, a Smith-predictor-based PI-PD control structure is adopted for the prevalent process model in the primary loop. Then, expressions representing the relationship between the corresponding controller parameters and the maximum sensitivity (Ms) index are established to facilitate the analytical design of the controllers. Finally, based on simulation experiments, the effectiveness and superiority are validated by using the proposed method.

Tuning of PID/PIDD2 controllers for integrating processes with robustness specification

Tuning of PID/PIDD2 controllers are proposed in the paper for integrating processes with time delay via the state space pole placement method. The tuning formulas give the controller parameters in terms of a given maximum sensitivity. An observer-based PID structure is proposed to implement the ideal PID or PIDD2 controllers. The structure utilizes a model-independent observer to estimate the various order of the derivatives of the plant output, thus the sensitivity of the derivatives on the measurement noise can be reduced. Simulation results show that the tuning formulas can achieve good compromise among robustness, disturbance rejection, and noise attenuation for the integrating processes.

Comparative analysis of different inverters and controllers to investigate performance of electrosurgical generators under variable tissue impedance

Electrosurgical generators (ESGs) are currently the most widely used surgical technology for clinical operations. The main disadvantage of ESGs is their output power is irregular due to the variable tissue impedance. The heat dissipation caused by the high amount of thermal energy generated leads to medical complications for both patient and surgeon. In this research, various inverter topologies and power controllers are investigated to specify the best structure that ensures best performance. The type of inverter topologies investigated are three level and five level, while the PID structures investigated are integer order (IO-PID) and fractional order (FO-PID). The simulation results indicate that FO-PID with five level inverters is better than IO-PID with three level inverters in terms of minimum heat dissipation rate and THD of the output voltage and current.

Single-layer neural-network based control of agricultural mobile robot

In this study, we propose a novel controller architecture and design for the automatic control of agricultural mobile robots to be used in farms and greenhouses. There are two novelties of this study. The first novelty is a completely new type of controller architecture proposed in which reference inputs and measured outputs are fed separately independent from each other to the controller. The controller architecture currently used in the literature uses only the difference between reference and measurement which is the error signal. The proposed architecture in this study is completely novel in the sense that not only the error information is used in the controller but also the information in reference inputs and information in measured outputs are used separately. This means a completely new type of look to control system by utilizing the information maximally in order to achieve superior performance. This performance boost is shown in the paper where the proposed architecture achieves up to 2000% better performance compared with state-of-the-art controllers. Second, controller architecture is grown to a complex structure from an initially simple PID structure. Using the maximal information comes with the cost of computational complexity to design the controller. The second novelty of growing the controller from initially simple PID equivalent controller tackles this difficulty by making the problem tractable and efficient to compute. This way the proposed novel controller can be designed within minutes in a commercially available laptop computer. The proposed controller is tested on a simulated agricultural mobile robot and results are compared with a previous state-of-the-art optimal controller. It is believed that the proposed architecture will be dominant in future automatic controllers and make current state-of-the-art controllers obsolete. This is because of the full utilization of information in controller design which results in robust disturbance rejection performance.

Controller design on a new 2DOF PID structure for different processes having integrating nature for both the step and ramp type of signals

Chemical reactors, heat exchangers, level-loops, and distillation columns are commonly encountered in the chemical process industry, and these are having a significant role in the functioning of any chemical process. For the smooth and efficient functioning of any such process, a robust control law design is an important work to be considered. In this paper, a modified 2DOF robust PID control law has been developed to ensure satisfactory performance in both the step and ramp type references and disturbances. Controller parameters are derived with Maximum sensitivity, Gain, and Phase margin specifications. Case studies with different chemical processes like CSTR, distillation column, heat exchangers, and boiler drum level-loop are included for both the nominal and perturbed cases. Lastly, a performance comparison of ISE (Integral of square error), ITAE (Integral time absolute error), IAE (Integral absolute error), and Total variation (TV) of the control signal is also included.

Adaptive-PID Experimental STM32F4 Controller for Rotary Inverted Pendulum

Rotary inverted pendulum (RIP) is a classical model of control engineering. Paper deals with a PID-adaptive structure which is based on structure of neuron to train Kp, Ki, Kd through operation. In simulation, our adaptive controller is proven to work in larger range than classical PID controller. Through experimental model using STM32F4, we prove vibration of system under adaptive-PID is smaller than under classical PID structure. Then, combination of neuron network (NN) and PID control can be used as simple structure for single-input multi output (SIMO) systems which are similar to RIP.

Research on robust fuzzy logic sliding mode control of Two-DOF intelligent underwater manipulators.

This study investigates the independent motion control of a two-degree-of-freedom (Two-DOF) intelligent underwater manipulator. The dynamics model of two-DOF manipulators in an underwater environment is proposed by combining Lagrange's equation and Morison's empirical formulation. Disturbing factors such as water resistance moments, additional mass force moments and buoyancy forces on the intelligent underwater manipulator are calculated exactly. The influence of these factors on the trajectory tracking of the intelligent underwater manipulator is studied through simulation analysis. Based on the design of the sliding mode surface of the PID structure, a new Fuzzy-logic Sliding Mode Control (FSMC) algorithm is presented for the control error and control input chattering defects of traditional sliding mode control algorithm. The experimental simulation results show that the FSMC algorithm proposed in this study has a good effect in the elimination of tracking error and convergence speed, and has a great improvement in control accuracy and input stability.

The Synchronization of a Class of Time-Delayed Chaotic Systems Using Sliding Mode Control Based on a Fractional-Order Nonlinear PID Sliding Surface and Its Application in Secure Communication

A novel approach for the synchronization of a class of chaotic systems with uncertainty, unknown time delays, and external disturbances is presented. The control method given here is expressed by combining sliding mode control approaches with adaptive rules. A sliding surface of fractional order has been developed to construct the control strategy of the abovementioned sliding mode by employing the structure of nonlinear fractional PID (NLPID) controllers. The suggested control mechanism using Lyapunov’s theorem developed robust adaptive rules in such a way that the estimation error of the system’s unknown parameters and time delays tends to be zero. Furthermore, the proposed robust control approach’s stability has been demonstrated using Lyapunov stability criteria and Lipschitz conditions. Then, in order to assess the performance of the proposed mechanism, the presented control approach was used to simulate the synchronization of two chaotic jerk systems with uncertainty, unknown time delays, and external distortion. The results of the simulation confirm the robust and desirable synchronization performance. Finally, a secure communications mechanism based on the proposed technique is shown as a practical implementation of the introduced control strategy, in which the message signal is disguised in the transmitter with high security and well recovered in the receiver with high quality, according to the mean squared error (MES) criteria.

Modified Golden Jackal Optimization Assisted Adaptive Fuzzy PIDF Controller for Virtual Inertia Control of Micro Grid with Renewable Energy

Frequency regulation of low inertia symmetric micro grids with the incorporation of asymmetric renewable sources such as solar and wind is a challenging task. Virtual Inertia Control (VIC) is the idea of increasing micro grids’ inertia by energy storage systems. In the current study, an adaptive fuzzy PID structure with a derivative filter (AFPIDF) controller is suggested for VIC of a micro grid with renewable sources. To optimize the proposed controllers, a modified Golden Jackal Optimization (mGJO) has been proposed, where variable Sine Cosine adopted Scaling Factor (SCaSF) is employed to adjust the Jackal’s location in the course of search process to improve the exploration and exploitation capability of the original Golden Jackal Optimization (GJO) algorithm. The performance of the mGJO algorithm is verified by equating it with original GJO, as well as Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching Learning Based Optimization (TLBO) and Ant Lion Optimizer (ALO), considering various standard benchmark test functions. In the next stage, conventional PID and proposed FPIDF controller parameters are optimized using the proposed mGJO technique and the superiority of mGJO over other symmetric optimization algorithms is demonstrated. The robustness of the controller is also investigated under intermittent load disturbances, as well as different levels of asymmetric RESs integration.

LPV Control and Virtual-Sensor-Based Fault Tolerant Strategies for a Three-Axis Gimbal System.

This paper deals with the LPV control of a three-axis gimbal including fault-tolerant capabilities. First, the derivation of an analytical model for the considered system based on the robotics Serial-Link (SL) theory is derived. Then, a series of simplifications that allow obtaining a quasi-LPV model for the considered gimbal is proposed. Gain scheduling LPV controllers with PID structure are designed using pole placement by means of linear matrix inequalities (LMIs). Moreover, exploiting the sensor redundancy available in the gimbal, a virtual-sensor-based fault tolerant control (FTC) strategy is proposed. This virtual sensor uses a Recursive Least Square (RLS) estimation algorithm and an LPV observer for fault detection and estimation. Finally, the proposed LPV control scheme including the virtual sensor strategy is tested in simulation in several scenarios.

Design and implementation of high-order PID for second-order processes with time delay

In this study, a state-space pole placement approach is first proposed to design high-order PID controllers for high-order processes. The method makes use of a single parameter to determine the locations of closed-loop poles; thus, a high-order PID controller can be tuned with this parameter. To implement the high-order PID controller in practice, an observer-based PID structure is proposed. The structure utilizes a model-free observer to estimate the plant output and its derivatives, thus retaining the high-order PID structure but can filter the measurement noise and make the high-order derivatives of the plant output available for control. The proposed method is applied to design high-order PID controllers for second-order processes with time delay. Simulation results show that high-order PID can indeed improve the performance of conventional PID controllers for second-order processes with time delay in disturbance rejection and robustness.

A Robust LQR-Based Fuzzy-Immune PID Applied for a Greenhouse Temperature Networked Control

Bioinspired control system strategies have received considerable attention in recent years, demonstrating their effectiveness to control various classes of systems. This paper presents a new robust LQR-based fuzzy-immune PID controller synthesis method, the particularity of this structure is the combination of the features granted by the linear quadratic regulator LQR and the fuzzy-immune PID controller as: robustness, optimization and self-adapting. The proposed approach is applied to the temperature control of a greenhouse system over Ethernet network. Such control loop is bound to be affected by several uncertainties such as communication delays, packet dropout... etc., it is therefore necessary to adopt a robust control strategy that can handle these problems. MATLAB/Simulink is used to simulate the proposed controller structure under several perturbations/uncertainties scenarios. The results show better time domain performance and greater robustness against uncertainties, in comparison with other PID structures (classic and fuzzy immune PID).

A New Analytical Approach for Set-point Weighted 2DOF-PID Controller Design for Integrating Plus Time-Delay Processes: An Experimental Study

In many industrial processes, e.g. temperature and level control, chemical reactors can be classified as a variant of integrating plus time-delay system. Controlling these processes is a difficult task due to open-loop instability, which consists of time-delay and unbounded output for bounded input. 1DOF PID control always leads to a large overshoot in set-point tracking for IPTD processes. In a 2DOF PID structure, tuning the set-point weights and the controller parameters is important to achieve good tracking and disturbance rejection properties. But tuning the set-point weights and the parameters of the cascade-feedback controller together is a difficult task. Usually, predetermined values for set-points are chosen, and a controller design is followed. In the present work, an alternative simple approach to obtain controller parameters along with set-point weights is presented which are tuned to yield good tracking and load–disturbance rejection. Explicit controller parameters for different classes of integrating processes are obtained using gain-margin, phase-margin, and inverse plant model which can also be used for controller auto-tuning. To validate the effectiveness of the proposed controller, simulation comparisons with some recently developed methods are included. Moreover, the experimental validation of the proposed controller on a temperature control plant is also presented.

State-Space PID: A Missing Link Between Classical and Modern Control

PID control is widely applied in industry. However, it is classified as a classical control technique, in that transfer function method is used to represent the ideal and/or practical PID controller. Modern control concepts, such as state feedback, observer, are seldom found in PID research. This paper proposes a state-space PID structure to fill the gap. The classical ideal PID is first shown to be a state-feedback control structure with the plant output and its derivative and integral as the states, and then a model-independent observer is proposed to estimate the states, thus approximate the ideal PID as a observer-based state feedback control structure (state-space PID). Then it is shown that the proposed state-space PID structure is the dual of the linear active disturbance rejection control structure, and it is a general-purposed control structure in that any strictly-proper linear controller with integration can be implemented via the proposed structure. The design of the state-space PID can be done via the well-known pole placement algorithm in modern control. Simulation and experiment results show that state-space PID structure is a practical implementation of ideal PID, which naturally integrates the noise reduction that is separated from PID tuning, and it is a natural generalization of the classical PID to high-order cases.

CONTROL OF REMOTELY OPERATED UNDERWATER VEHICLE USING MODEL PREDICTIVE CONTROL

This paper focuses on application of model predictive control on attitude control of remotely operated underwater vehicle. These vehicles are used in scientific, defence and oceanography applications. Remotely Operated Vehicle (ROV) considered in this paper is nonlinear model and complex. MPC is applied on ROV model to track in desired set point trajectories in the presence of uncertainties. Simulation has been carried out in MATLAB environment. Model Predictive Control has given significantly good results compared to PID, Adaptive and Variable structure control.

An Improved DC Motor Position Control Using Differential Evolution Based Structure Specified H∞ Robust Controller

Traditional synthesis of an H∞ controller usually results in a very high order of controller that is not practical for a low-cost embedded system such as a microcontroller. This paper presents a synthesis method of a low-order H∞ robust controller to control the position of a dc motor. The synthesis employed Differential Evolution optimization to find a controller that guarantees robust stability performance and robust stability against system perturbation. A second-order PID structure was chosen for the synthesized controller because this structure is simple and very famous. The proposed controller performance under uncertainties was compared to some other controllers. The first was compared with a conventional PID controller that had been finely tuned using the trial and error method in the nominal transfer function of the plant. Secondly, the proposed controller was compared with a full-order H∞ robust controller generated from a traditional synthesis method. Thirdly, the proposed controller was compared with another structure specified H∞ robust controller generated differently from the proposed method. All of the controllers result in a stable response. However, the proposed controller gives a better response in terms of overshoot and response time.

Optimization of DC motor speed control based on fuzzy logic-PID controller

In this paper the PID controller and the Fuzzy Logic Controller (FLC) are used to control the speed of separately excited DC motors. The proportional, integral and derivate (KP, KI, KD) gains of the PID controller are adjusted according to Fuzzy Logic rules. The FLC cotroller is designed according to fuzzy rules so that the system is fundamentally robust. Twenty-five fuzzy rules for self-tuning of each parameter of the PID controller are considered. The FLC has two inputs; the first one is the motor speed error (the difference between the reference and actual speed) and the second one is a change in the speed error (speed error derivative). The output of the FLC, i.e. the parameters of the PID controller, are used to control the speed of the separately excited DC Motor. This study shows that the precisiom feature of the PID controllers and the flexibllity feature of the fuzzy controller are presented in the fuzzy self-tuning PID controller. The fuzzy self – tuning approach implemented on the conventional PID structure improved the dynamic and static response of the system. The salient features of both conventional and fuzzy self-tuning controller outputs are explored by simulation using MATLAB. The simulation results demonstrate that the proposed self-tuned PID controller i.plementd a good dynamic behavior of the DC motor i.e. perfect speed tracking with a settling time, minimum overshoot and minimum steady state errorws.