Reduction of Large Scale Linear Dynamic MIMO Systems Using Adaptive Network Based Fuzzy Inference System

This paper investigates the integration of Fuzzy Logic with PID (Proportional, Integral, Derivative) controllers to enhance the performance of temperature control systems. Traditional PID controllers, widely used in various applications, often encounter difficulties with nonlinear, time-varying, and uncertain systems, resulting in performance issues like oscillations and overshoots. To mitigate these challenges, the adoption of Fuzzy PID control, which improves adaptability, robustness, and responsiveness by incorporating fuzzy logic into the control mechanism. The study involves simulations using Simulink to compare three distinct control models: conventional PID, standalone Fuzzy Control, and the hybrid Fuzzy PID Control across standardized control scenarios. Our results show that Fuzzy PID controllers significantly outperform traditional methods, especially in complex environments lacking precise mathematical modeling. The enhanced system response times and stability demonstrated by Fuzzy PID controllers suggest substantial potential for broader application across diverse industries, promising considerable improvements in operational efficiency and reliability.

A fractional-order fuzzy proportional integral derivative (PID) controller is a controller that combines the benefits of fractional calculus and fuzzy logic with the conventional PID controller. In this paper, a four-stage optimization algorithm is proposed for the design of a Type-2 Fuzzy fractional-order PID controller based on the Fourier Series Method (FSM). Three distinct control structures are introduced: Type-2 fuzzy fractional PD + fractional PI controller, Type-2 fuzzy fractional PID, and Type-2 fuzzy fractional PD + Type-2 fuzzy fractional PI controller. In addition to a modified multi-performance criterion cost function, four integral performance criteria are employed as cost functions for each stage. The suggested algorithm avoids the utilization of the approximation equivalent for the fractional-order system and instead employs FSM. Furthermore, the approach optimizes the nonlinearity within the upper membership function (UMF) and the uncertainty range through the lower membership function, as opposed to arbitrary selection. By considering variations in the membership functions, the outcomes exhibit a superior response compared to previous investigations. The results of the three control structures are compared with the traditional PID controller, and simulation results demonstrate the feasibility of this technique. The findings suggest that by optimizing different integral performance criteria using this design technique, controllers for both integer and fractional-order plants can yield favorable step responses. The proposed algorithm is validated by comparing its step response performance with that of previous research, followed by a discussion on sensitivity analysis and computational requirements.

Mobile robots experience a lot of challenges with path tracking because of the significant problem with DC motor speed control. The particle swarm optimization (PSO) tuned proportional integral derivative (PID) controller is commonly used to control DC motor speed. However, it fails to reach the optimal solution quickly. Therefore, this paper demonstrates the application of the artificial bee colony (ABC) algorithm to tune a PID controller for speed regulation of a DC motor. The proposed approach was used to obtain the optimal PID controller gains (proportional, integral, and derivative) by minimizing the integral of time absolute error (ITAE) as the objective function. The analysis of statistical tests, transients, and frequency responses was conducted to test the rapid convergence of the proposed approach. Also, the performance of the proposed ABC-tuned PID controller has been compared with three variants of the PSO-tuned PID controller. The conducted simulation results and comparison with the proposed ABC controller and variant PSO controllers have shown that the proposed ABC-PID controller is more effective and robust than the variant PSO-PID controllers for the speed control of a DC motor.

Desalination plants have an important concern regarding controlling the permeate flow rate and pH during operability. This paper proposes the proportional integral derivative (PID) control design using modified Particle Swarm Optimization (PSO) techniques called autonomous groups PSO (AGPSO) in the two-input two-output (TITO) RO desalination plant to control the permeate flow rate and pH. Here, three different versions (AGPSO1, AGPSO2, and AGPSO3) of the AGPSO algorithm are utilized to design PID control for the same TITO plant. In addition, an integral time absolute error (<inline-formula> <tex-math notation="LaTeX">$J_{\mathrm {ITAE}}$ </tex-math></inline-formula>) based objective function is utilized to design a PID controller. The simulation results suggest that the proposed controller designs are flexible, self-tuning, and have stable characteristics, while the AGPSO3-PID control design attained a robust design for optimum tuning compared to existing improved grey wolf optimization PID (IGWO-PID) and other versions of AGPSO based PIDs (AGPSO1-PID, AGPSO2-PID). The design of AGPSO-PID achieved a minimum objective function than existing IGWO-PID and other versions of AGPSO based PIDs &#x007B;AGPSO1-PID, AGPSO2-PID&#x007D;. Finally, the proposed controller designs outperform the existing IGWO-PID design in literature in terms of control performance, demonstrating a precise control for and the improvement of plant performance.

Aircraft are the most common kind of transportation utilized by the government, commercial, military, and so on. Controlling the motion of an aircraft is a highly nonlinear operation. However, regulating direction and motion is critical in the aviation industry to prevent accidents, injury, and other problems. It is vital to pay attention to factors like stability in an aircraft. For stabilization, 3 orientationswere used to determine the movements: yaw, pitch, and roll. The main purpose of this research is to create a controller that could be used to regulate the pitch of an aircraft. This part of control will assist the plane in dropping or rising. Pitch can be varied by altering the elevator, which is located on the plane's rear portion. The longitudinal mechanics of aircraft were used to create the aircraft pitch system mathematically. The advanced controller, neuro-fuzzy, is used to regulate the pitch automatically. The performance of the neuro-fuzzy controller is equated to the traditional Proportional Integral Derivative (PID) controller. Two parameters are used for comparison: time characteristics and assessment metrics. Integral square error (ISE), Integral Absolute Error (IAE), and Integral Time Absolute Error (ITAE) is the assessment measures used in this study. The simulation outcomedemonstrates that the neuro-fuzzy controller outperforms the PID controller.

Electric load simulator (ELS) plays a vital role in the ground test and simulation of the electromechanical actuator (EMA) of an unmanned aerial vehicle (UAV), which is preferred by researchers for its dynamic response and high precision. However, clearance is an inevitable problem of the ELS system which can introduce backlash influencing the stability of the system. The backlash nonlinear can induce mechanical impact and impose limitations on the quality of loading torque control. In order to increase the accuracy of loading torque, a switching control method is presented to compensate for the backlash nonlinear. A time-optimal sliding mode control (TOSMC) method is used when the ELS system entering backlash, and a nonlinear proportional integral derivative (PID) controller is presented for the different system dynamic. A switching controller is also introduced to acquire suitable moment switching from TOSMC to nonlinear PID controller, ensuring the stability of the system. Experimental tests show that compared with the traditional PID control, this method can effectively reduce the torque overshoot when ELS crossing backlash and guarantee torque tracking speed and precision of ELS.

This paper demonstrates the design and analysis of automatic generation control using intelligent genetic algorithm tuned fuzzy based controller. A two area thermal power system simulated for four different scenarios considers a reheat steam turbine in each area with Generator rate constraints. The Integral Time Squared Error (ITSE) employed to get an objective function for the optimization of controller gains. The simulation results compared with the conventional Proportional Integral Derivative (PID) controller, Genetic Algorithm (GA) tuned PID controller and GA tuned Fuzzy PID controller. The proposed GA tuned Fuzzy based PID Controller can generate the best performance for peak overshoot, undershoot and settling time with step load disturbances. Robustness of the performance of the proposed controller provided with system parametric uncertainties.

Superheat steam temperature control is critical to the normal and optimal operation of a power plant. Usually, cascade proportional integral derivative (PID) control system is introduced to regulate the superheat temperature with the PID parameters fixed constant. However, Due to the gains and time constants of the controlled plant change significantly with disturbances, the control effects of the conventional PID are not ideal. In this paper, a new adaptive control strategy is proposed to improve conventional superheat steam temperature control. Based on cascade PID control system, recursive least squares (RLS) method is used to identify the plant parameters and then genetic algorithm (GA) is applied to adjust the parameters of the PID controllers. MATLAB simulation investigation indicates that, compared to the parameter fixed PID system, GA-self-tuned adaptive control system is able to reject endogenous and exogenous disturbances more effectively and rapidly, thus has better self-adaptation capability and robustness.

In this paper, an optimal PID (proportional-integral-derivative) controller is designed for controlling the non-minimum phase system with time delay and performed greater than the conventional control approaches. When there is an increment in time delay then complications related to NMP system determines the undershoot response due to presence of zeros in the right half plane. Furthermore, Ziegler-Nichols, Internal Model Control (IMC) and Chien-Hrones & Reswick tuning approaches are developed for the conventional PID controller. The time-domain characteristics obtained are unable to persuade the requirements of the system. In order to improve the performance criteria, Smith’s predictor is used for controlling the NMP system. Smith’s predictor is better than the conventional PID controller techniques for tuning the parameters but has the incapability to achieve all the design requirements. For improving the performance requirements, the optimal PID controller is designed with the employment of Linear Quadratic Regulator (LQR). The tuning parameters of PID controller are optimal values using popular technique that is Linear Quadratic Regulator (LQR). In order to minimize integral time absolute error (ITAE) and integral time square error (ITSE), the tuning parameters are optimal and give precise values of rising time, peak time, % overshoot and settling time. The simulation results are obtained and according to that LQR gives better results than Smith Predictor and other conventional PID controller techniques.KeywordsNon-minimum phase systemPID controllerSmith predictorConventional tuning methodsLinear quadratic regulator

The present generation of wireless communications systems, to a greater extent, do not optimally utilize the scarce radio spectrum and also not flexible in the allocation of the time-frequency resource. This may also be the case with the next generation systems if a viable solution is not found. Many researchers worked on resolving these two problems but suffered some limitations in their results, tools approaches and techniques used. The main problem was that they failed to collectively utilize the advantages of both the high spectral efficiency of Filter Bank Multicarrier Modulation Offset Quadrature Amplitude Modulation (FBMC-OQAM) and the efficient capacity property of large Multiple Input Multiple Output (MIMO) systems. In this paper, we shall propose to use the advantages of both systems in order to transmit FBMC-OQAM data symbols over a large MIMO system by employing a specific Space Time Transmission Scheme (STTS) of FBMC-OQAM for large MIMO. The transmission, however, will be prior to error correction using Hadamard scheme to double the spectral efficiency by restoring complex orthogonality in the imaginary field. The STTS will eliminate imaginary intrinsic interference, thereby enabling the efficient transmission of the FBMC-OQAM data over the large MIMO system. By employing the Hadamard scheme and STTS, we propose to develop a spectrally efficient large MIMO/FBMC-OQAM system with an improved capacity gain over a conventional MIMO/FBMC-OAQM.

Multiple Input Multiple Output (MIMO) low complexity receiver which utilizes the compressive sensing detection for Spatial Modulation in large scale MIMO system in order to reduce the system complexity. In conventional MIMO system; huge amount of antennas is used at both ends to exploit the multipath propagation. This system maximizes the throughput performance and data rates are increased but only at the cost of high hardware complexity and increased power-consumption. Spatial Modulation Matching Pursuit (SMMP) is the proposed enhanced CS technique used for the improvement of detection performance. Hence, this paper reviews recent research findings concerning normalized Compressive Sensing (CS) detection algorithm, used for Spatial Modulation (SM) in massive MIMO, to lowers the signal processing complexity, which in result improves the energy efficiency of system against that of conventional MIMO system.This strategy is achieved by involving additional structures and sparsity in which a single transmitter antenna or a subset of it is turned on at each case to transmit a certain data. The subset of antenna which is turned on for transmission depends on approaching data bits. Therefore, the total increase in the spectral efficiency of the system is given as base-two logarithm of whole antennas at the transmitter. It reduces the signal processing load at base station and doesn’t depend upon any synchronization between transmitters. The Spatial Modulation Matching Pursuit used prevents the Inter Channel Interference (ICI) of the system which in result improves the Bit Error Rate (BER) performance than the typical MIMO system.

One of the key drivers in gaining the cost-effective, reliable and low-downtime Operation system for major Oil Fields is implementation of Water Injection System (WIS) with capability of online-automated regulation and control. This Paper outlines an application of Proportional, Integral, Derivative (PID) control loop algorithm for Decentralized WIS (with direct injection from Water Source wells to Injection wells by means of high capacity ESP's) used in West Qurna-2 oilfield located in Iraq, operated by LUKOIL. PID control loop algorithm has being used in the industry for the years, but not commonly applied as integral component of Water Injection System allowing to maintain optimal equipment modes. Such limited PID deployment is explained by complexity of operational parameters synchronizing for every Water Injection System component. The decentralized Water Injection System at the West Qurna 2 project is common and united pipeline system for every WellPad that provides water transfer from Water source wells (3-5 wells per WellPad) to injection wells (3-6 wells per WellPad) with line pressure of 70-130 Barg by means of high-capacity ESP equipped with VSD. Water injection process is regulated by controlling both the conventional ESP parameters (frequency, flow rate, motor current and load, Intake and discharge pressures), line pressure, required injection rate by means of flow control valves, and implemented PID control loop algorithm. This paper discusses the techniques of PID control loop algorithm application as the tool for: –Pipeline protection against high pressure without full shutdown of water injection process and–ESP automated regulation to ensure operation inside Recommended Operated Range (ROR) and smoothening of ESP mode when any changes in the system happen (i.e. shutdown of other water source well ESP's at the same WellPad or shutdown of injection well) with immediate feedback to Operator Control Room. Implemented approach allows to decrease number of ESP shutdowns and avoid high jumping of ESP loads that consequently leads to maximizing of ESP run life. Comparative examples and case studies of submersible equipment operation results before and after the application of PID regulation are specified. Mainly by implementing PID regulation and control stable and smooth operation of equipment and ESP's used for WIS (direct injection from Water Source Well to Injection Well) has been achieved. New approach for PID application as a tool for pipeline overpressure protection has been formed, which allowed to reduce Capital Expenses for the WIS construction works. Specified case can be used as example for further development and projects in the oil and gas industry.

In guided missiles, the major function of a seeker is to track a target continuously. In target tracking process most seekers employ a gimbal system, usually a two-axis, on which a tracking device and a rate gyroscope are mounted. For such guided missiles, the stabilization of gimbal is essential for maintaining the tracking device directing towards the target. Various control methods have been developed for the gimbal stabilization to make the gimbal to respond faster for a rate command input so that the gimbal follows the rate input in the presence of disturbances. Here, a fuzzy self-tuning proportional, integral, derivative (PID) type controller based on parameters adaptive method is proposed for two-axis gimbal stabilization which can be applicable for most guided missiles. The controller gains in the proposed control technique are made of input and output scaling factors used in fuzzification and defuzzification processes. The scaling factors are tuned online based on the missile rotation rate and the gimbal rate response. The response of the gimbal in the stabilization loop with the proposed controller has been analyzed in MATLAB for various missile rotation rates and the simulation results are compared with a traditional PID controller. The results prove the efficiency of the proposed control method which gives a better and faster response with zero steady-state error than the traditional control method.

A near maximum likelihood performance modified firefly algorithm for large MIMO detection

The competition of connected sources to access to the resources within a network leads to a congestion that causes a global delay in the network. For this reason, it's challenging to design an optimized controller that stabilizes the system and reduces the present delay. This paper proposed a developed PID (Proportional Integral Derivative) controller based on an extension of Hermite-Biehler theorem applicable to quasipolynomials, that is to say to systems with delay. Then the stability region of the PID controller parameters was obtained. An improved Multi-objective Genetic Algorithm (GA) is employed to seek the optimal PID controller gains such that performance indices of integrated-absolute error (IAE), integrated-squared error (ISE), integrated-time-absolute error (ITAE) and integrated-time-squared error (ITSE) are minimized, and thereby a stability of TCP (Transmission Control Protocol)network is guaranteed. The performance of the proposed control scheme is evaluated via a series of numerical simulations that show its efficiency.