DYNAMIC DE-EXCITATION PERFORMANCE OF BRUSHLESS SYNCHRONOUS MACHINES USING ADVANCED CONTROL STRATEGY

The brushless excitation system of aircraft AC generator is a strong coupled and nonlinearity dynamic system which is often being subjected to disturbances. Therefore, the conventional PID controller is unable to meet the brushless excitation system control requirements of More Electric Aircraft (MEA) or All Electric Aircraft (AEA). A new brushless excitation compound control controller (RBFPID) is proposed in this paper based on radical basis function (RBF) neural networks and the conventional PID control. Because the new brushless excitation compound controller (RBFPID) has a number of mutually coupled parameters that needs to be set, the improved adaptive particle swarm optimization (APSO) algorithm is used to optimize mutually coupled PID parameters Kp , Ki , Kd and RBF parameters ! , ! , m , n on line. In order to validate performances of the new brushless excitation compound controller based on multi-parameter op- timization by the improved APSO, the simulation model of the aircraft brushless excitation system is implemented in MATLAB/SIMULINK according to differential equations of each component of brushless excitation system. The simula- tion results show that the optimized adaptive compound excitation controller (APSORBFPID) exhibits quick response speed, short adjustment time and high steady state accuracy.

A new type of flexible excitation system (FES) is proposed by using fully‐controlled power electronic devices such as IGBTs to replace the half controlled devices in the conventional static excitation system, which has the merit of independent control of rotor angle and terminal voltage of the synchronous generator. This paper proposes nonlinear adaptive control (NAC) strategies for synchronous generator with FES in a single machine infinite bus system. External disturbances and the uncertainties of all parameters as well as modelling are defined as lumped perturbation terms and estimated by perturbation observers or state and perturbation observer. The estimated perturbation terms are used to compensate the real perturbations and achieve a model‐independent and robust NAC. Merits of the FES against the conventional static excitation system and effectiveness of the proposed NAC scheme against the accurate model based multi‐variable feedback linearisation control are verified via small‐signal stability analysis and simulation studies. The simulation results have shown that the proposed NAC can achieve superior control performance with less states feedback during a three‐phase short circuit and better robustness against parameter uncertainties, compared with linear control and multi‐variable feedback linearisation control.

The fast de-excitation capability of Synchronous Generators (SG) using Standard Brushless Excitation (SBE) system is one of the most challenging problems. Thus, supplementary de-excitation system may be necessary to improve the dynamic performance of the voltage regulation for SG. This paper aims to provide an advanced dynamic de-excitation system based on a de-excitation power structure connected to the rotor winding of the SG and associated with a dedicated de-excitation control strategy. This proposed system consists of an IGBT connected in parallel with a non linear discharge resistor and controlled continuously by a dedicated PID controller to provide a fast dynamic de-excitation during loads rejections or excitation shutdowns. An excitation H∞ voltage regulator is also designed by considering the de-excitation system as perturbations. Consequently, the stability of the system is ensured during the dynamic operation of the discharge system. A comparison between the SBE and the proposed de-excitation system is presented and analyzed. Realistic simulation results show significant improvement in the dynamic regulation of the generator terminal voltage in terms of voltage overshoot, response time and stability.

In terms of improving the dynamic response characteristics of brushless AC synchronous generators, the concept of integrated design of AC exciter and rotating rectifier and their electromagnetic characteristics are studied, and the conditions and judgment methods for determining their operating modes are obtained in theoretical design and simulation design, pointing out that when the brushless excitation system operates in or is close to mode III, i.e., the rectifier always has three or four diodes in each operating cycle. The linear current amplifier characteristics can be basically achieved when the brushless excitation system is operated in mode III or is close to mode III, i.e., the rectifier always has three or four diodes alternating in each operating cycle. The impact of the key parameters of the AC exciter at different rotational speeds and temperatures on the characteristics of the linear current amplifier was explored, and an engineering prototype was manufactured. The related test verified the correctness of the concept of integrated electromagnetic design and simulation calculation. This study provides an engineered design method for enhancing the dynamic response properties of the brushless AC synchronous generators.

This paper examines the deployment of a 25 MVA Static Synchronous Compensator (STATCOM) to improve voltage stability in a real 66 kV 525 MVA transmission network in the Middle Egypt Electricity Zone. A MATLAB/Simulink model is developed to assess the performance of the STATCOM in both normal and fault conditions, including single-phase and three-phase faults. The STATCOM regulates the voltage by adjusting it within ±10% of the nominal value and is connected to a shunt with the bus B11. Four control strategies are implemented: a proportional–integral (PI) controller, an adaptive neuro-fuzzy inference system (ANFIS), a fuzzy logic controller (FLC), and an FLC combined with a supercapacitor. FLCs outperform PI controllers in maintaining voltage stability; however, they exhibit limitations regarding their responsiveness to dynamic changes within the network. The findings demonstrate that the STATCOM enhances the voltage and current stability compared to the system without this component. The ANFIS controller demonstrates optimal performance characterized by minimal waveform fluctuations. Under standard conditions, a single STATCOM integrated with an ANFIS elevates the bus voltages to 100.382% (B10) and 101.953% (B11), surpassing the performance of the FLC (100.314% and 101.246%) and the FLC–supercapacitor combination (100.326% and 101.392%). The deployment of two STATCOM units alongside an ANFIS improves the voltage levels to 102.122% (B10) and 102.200% (B11). The findings demonstrate that the AN-FIS-controlled STATCOM enhances system performance under normal operating conditions, voltage source fluctuations, and fault scenarios. The deployment of two STATCOM units, each rated at 25 MVA and controlled by an ANFIS, significantly enhances voltage stability compared to a single unit.

This paper proposes a universal adaptive fuzzy logic controller design procedure. This procedure provides explicit adaptation mechanism to tune and update the global input and output ranges of the fuzzy logic controller (FLC) as well as implicitly influences the rule base and the membership functions of the FLC. The adaptation is based on new concepts in evaluating the FLC performance according to some performance monitors taken from the operational environment. The proposed algorithm is tested in the design of an excitation system for a synchronous power generator in which it proved superiority when compared to a conventional excitation system.

Islanding operation mode has been highly used in the distribution networks where the distance between generation regions and rural areas are longer. Therefore, many issues have been addressed in islanding Microgrids (MGs) especially during renewable energy resources (RESs) integration. For example, fluctuation in power transfer, changing in load voltage profile resulting to load demand response, and the reliability of MG during distributed generation insertion. Energy storage systems (ESSs) have an important role in improving the reliability of islanding MG system in presence of wind power generation (WPG). This paper presents the impact of superconducting magnetic energy storage (SMES) on the operation of MG-islanding mode. Fuzzy logic controller (FLC) used in controlling SMES active power transfer between SMES coil and MG at WPG insertion period. The obtained results indicate the effectiveness of SMES control in enhancing the reliability of islanding MG during WPG insertion and sudden load rejection on distribution systems.

Multiport DC-DC converters have been most commonly used in stand-alone renewable power systems to provide smooth and constant power to the loads. To supply the load without any interruption under various disturbances, the centralised controller in various typologies of multiport converter has been implemented only by using conventional proportional integral (PI) controller. This study presents the output voltage control of the three-port full-bridge converter interfacing photovoltaic (PV) system with three different controllers. The dynamic response of the proposed converter is analysed with the PI controller, fuzzy logic controller (FLC), and the sliding mode controller (SMC). The state space model of the three-port full-bridge converter is developed to analyse the performance using SMC. PI, FLC, and SMC-based control scheme is developed using the MATLAB/Simulink environment. The response of the PI, FLC, and SMC are analysed for line regulation, load voltage regulation, and for the converter parameter variation. The simulation results illustrate that the SMC gives a better steady state and dynamic response when compared with the PI and FLC. The results are presented to confirm the proposed control schemes.

The doubly fed differential linear active disturbance rejection control (DLADRC) in the speed loop control of permanent magnet synchronous motor (PMSM) produces observation time lag due to the bandwidth impact, which leads to the problem of slower dynamic response and poorer disturbance rejection performance of the system. To solve this problem, a speed controller of PMSM based on series lead correction DLADRC (SLC‐DLADRC) is investigated in this paper. Firstly, the speed loop of PMSM is modeled and the traditional LADRC is reconstructed to obtain DLADRC to improve the control performance of the system. Based on DLADRC, a phase lead correction unit is introduced, and a feedback differential extended state observer based on series lead correction (SLC‐DLESO) is investigated for observing the total disturbance of the system to further improve the system's anti‐disturbance performance. Then, the estimation error analysis of the studied SLC‐DLESO is performed and its stability performance is proved. The stability analysis of the SLC‐DLADRC control strategy is conducted using the Nyquist stability criterion. Finally, MATLAB/Simulink simulation and DSPACE semi‐physical platform are used to verify the effectiveness of the control strategy. Theoretical analyses and experimental results show that, without changing the bandwidth, SLC‐DLADRC not only improves the observation time lag problem but also extends the estimation range of the total disturbance. In the speed loop control of PMSM, the control strategy provides better dynamic response performance and anti‐disturbance under various operating conditions compared to the conventional LADRC and DLADRC.

An algorithm called Incremental Best Estimate Directed Search (IBEDS) was proposed for Takagi-Sugeno type fuzzy logic controller (FLC) automatic optimization. IBEDS starts with an initial training set that may be empty, an FLC with randomly initialized rule output parameters is trained by least mean square (LMS) learning algorithm in an iterative procedure. In each iteration, the trained FLC is evaluated with cell state space based global and local performance measures, the training set is then updated based on the evaluation under best kept policy, which only keeps the best control commands found so far. In this way, the training set is optimized in every iteration, and the FLC trained by the training set is also optimized progressively. The philosophy behind IBEDS is that the parameters of an FLC do not represent the performance of the controller directly although the goal of the optimization is to find an optimal controller parameter set so that the controller can have optimal global performance. However, the parameter set of an FLC with suboptimal performance may well represent a point in the parameter search space where the optimal one is nearby. Therefore the search algorithm should put more efforts in that area. LMS learning error is discarded in IBEDS as it does not represent the performance of the trained FLC either. This learning error can be reused when the training set is highly optimized and an exact approximation of the training set by an FLC is desired. To further speed up the optimization, in addition to suggesting the reuse of the LMS learning error, this paper also proposes to reuse the FLC parameter set during a search. A 4D inverted pendulum is studied, and the simulation results show that the search speed is improved.

The worldwide direction moving towards sustainable energy solutions requires more advanced control mechanisms within power systems, especially in DC microgrids that combine renewable energy sources like solar panels and wind turbines with conventional power setups. This paper addresses the necessary challenge of maintaining steady and efficient DC voltage control—important for the dependability and performance of power plants. Specifically, it looks at the efficiency of four different control strategies: classic PID (Proportional-Integral-Derivative) controllers, Fuzzy Logic Controllers (FLC), Fractional Order PID (FOPID) controllers, and a new mixed system that merges Fuzzy Logic with PID controllers in a Fuzzy-PI layout. Our approach utilizes a strict comparative analysis using MATLAB Simulink simulations, assessing each controller’s capacity to manage dynamic load shifts, adjust to the unpredictability of renewable energy inputs, and preserve strong voltage stability under various operational cases. The simulations are crafted to single out the most effective control strategy to boost efficiency and toughness in microgrid operations. This study adds substantially to the progress of control strategies in hybrid energy systems, offering important insights into the creation of more complex and reliable power management solutions. By evaluating the performance of these varied controllers, we aim to underline potential upgrades in control systems that could support better energy management in intricate grid setups, thereby encouraging the wider inclusion of renewable energy technologies into power grids.

Reports a discovery that has never been reported before on the global performance of Tskagi-Sugeno (TS) type fuzzy logic controller (FLC) with random rule output function parameters. We found that under certain cell resolutions, the chance that the performance of a random controller is comparable with that of a man made controller is very high. A cell state space based TS type FLC automatic parameter optimization algorithm named incremental best estimate directed search (IBEDS) is presented with a detailed analysis of its capability of designing a FLC totally without any expert knowledge. Initially, IBEDS was suggested to start with an initial training set sampled from the control surface of a FLC with poor performance. Then another random FLC is trained in an iterative procedure by a least mean square (LMS) algorithm. In each iteration, the global and local performance of the trained FLC is evaluated, the training set is then updated based on the evaluation. The initial value of the training set may need expert knowledge. However, with the discovery on random FLCs, IBEDS is found to be able to bootstrap with an empty training set, and still reach an optimal solution within a reasonable number of iterations. The mechanism behind this phenomenon is analyzed in detail with 2D and 4D inverted pendulums. It is shown that with IBEDS, a totally blind FLC design without any expert knowledge can be done efficiently.

To optimize controller design and improve static and dynamic performances of three-phase four-leg inverter systems, a compound control method that combines state feedback and quasi-sliding mode variable structure control is proposed. The linear coordinate change matrix and the state variable feedback equations are derived based on the mathematical model of three-phase four-leg inverters. Based on system relative degrees, sliding surfaces and quasi-sliding mode controllers are designed for converted linear systems. This control method exhibits the advantages of both state feedback and sliding mode control. The proposed controllers provide flexible dynamic control response and excellent stable control performance with chattering suppression. The feasibility of the proposed strategy is verified by conducting simulations and experiments.

The reliability of the wound field synchronous machines is improved by the brushless exciter (BLE) rather than using static exciter which requires brushes and slip rings. Conventional BLEs uses a rotating diode bridge rectifier for converting AC to DC voltage. However, these exciters cannot produce a negative voltage across the field winding because of which dynamic response of the field current is very low. The proposed topology in this paper introduces a new line commutated-thyristor bridge emulated power electronic converter that can produce both positive and negative voltage across the field winding of the generator. Also, this topology eliminates the need for a DC-link capacitor which improves the reliability of the BLE system. The proposed topology is simulated in MATLAB-SIMULINK platform and the simulation results for both rectification and inversion mode are presented. Also, a simpler control methodology has been proposed for the BLE with the proposed converter.

This study examines the application of Fuzzy Logic Controller (FLC) to optimize the performance of Direct Current (DC) motors. DC motors offer advantages such as high starting torque and ease of maintenance, making them suitable to replace oil-fueled engines that contribute to pollution and global warming. The transition to electric vehicles is supported by advances in battery technology, which provides reliable DC electricity. An important aspect of using DC motors in vehicles is speed control, which is essential for optimizing performance. FLC provides an alternative by using fuzzy rules for decision making, improving stability, accuracy, and dynamic response under various conditions. This study aims to determine the optimal control parameters for DC motors using FLC. The results showed that the rise time was around 1.05 seconds and the settling time was around 1.1 seconds. Simulations performed in Simulink Matlab showed that FLC allows the system to reach the desired point with minimal overshoot.