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In this paper, a new control mechanism has been proposed for grid-connected three-phase inverter that provides regenerative energy recuperation in direct current (DC) rail transit. In DC rail transit, line voltage can change dynamically depending on the regenerative energy generated by the trains during braking. In order to respond rapidly to dynamic changes in line voltage, a proportional-integral-derivative (PID) controller designed based on the dominant pole assignment method has been used in the control structure of the inverter. With the proposed control mechanism, the PID controller design has been performed considering the current loop. Thus, the design accuracy has been increased. The derivative effect of the PID provides fast response to these changes in line voltage by increasing the speed of the system response and the slow dynamic response of PI-based control structure has been improved. In addition, a new operating strategy that considers two different voltage values, unlike the systems that operate at constant voltage value in the literature, is proposed. This operating strategy provides more regenerative energy recovery by increasing the inverter operation region and contributes to energy efficiency. Finally, a detailed model of a real system has been developed in Matlab/Simulink environment. The simulation results comparing the performance of the PID-based control structure with the PI-based control has been presented to illustrate the feasibility and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Nowadays, electronic safety functions such anti-lock brake system (ABS), electronic stability control (ESC) and traction control system (TCS) are integrated to the air brake system of heavy-duty vehicles. The fact that the number of heavy-duty electric vehicles will increase in the future makes inevitable the transition of the brake system architecture from air actuation to electromechanic actuation. The main purpose of this study is to contribute to the development of heavy-duty vehicle electromechanical disc brake controller. A scaled experimental rig was constructed to investigate the dynamics of the electromechanical braking system. In addition, a measurement system has been developed to collect the electromechanical brake system parameters (motor current, motor angular position and clamping force). The system dynamics model of the experimental rig was constructed in Matlab Simulink environment in consideration of linear and nonlinear friction models. Experimental measurements were collected for the determination of the system variables. The simulations were conducted by using linear and nonlinear system dynamics models. The system dynamics model was verified by the comparison of simulation results with the experimental measurements. PI/PID and PI/PID cascade force controllers and PID position controller were developed in Matlab Simulink environment in consideration of the braking performance requirements of heavy-duty vehicle. The controller parameters determined in the virtual environment were defined to the physical control hardware and the experimental measurements were conducted. The performance of the force and position controllers was evaluated by considering the numerical and experimental measurement results. The switching scenario of force - position controller was implemented and functional tests were carried out on the physical system. [ABSTRACT FROM AUTHOR]

To ensure a balance between the power generated and the consumed power in power systems, a control process namely automatic generation control (AGC) must be carried out. This process becomes more challenging due to increasing use of renewable energy sources (RES) such as wind turbines (WT) and photovoltaic (PV) panels. Therefore, AGC needs to be performed more sensitively. In this study, it has been aimed to determine the parameters of the PID controller by using the whale optimization algorithm (WOA) for the AGC in a hybrid power system consisting of photovoltaic (PV) system and thermal generator. The performance of WOA tuned PID controller is tested under load change in area-1 and area-2. Additionally, comparisons have been made with the performances of other optimization techniques such as firefly algorithm (FA), genetic algorithm (GA) and population extremal algorithm (PEO). The results obtained indicated that the WOA tuned PID controller proposed in the study gave better results than the other methods in terms of overshoot values and settling time of system frequency. [ABSTRACT FROM AUTHOR]

In this study, it is aimed to design discrete time PI, PID and PIR controllers with the dominant pole region assignment method in order to have time domain characteristics of the closed loop system in the desired interval. First of all, determination of the boundary functions for the regions where the dominant and non-dominant poles of the closedloop system are desired to be located are explained. Here, for the boundary functions, the region where the dominant poles are desired to be located are two circles of constant radius and a constant damping ratio curve in the discrete time domain, and the region where the remaining poles are desired to be located is a circle of constant radius. Then, solution method of dominant pole region assignment problem is given for discrete PI controller. The proposed method is extended for discrete PID and PIR controllers by fixing a parameter of the controller (Kp = kp*). In addition, the design starts with selecting the delay parameter ℎ as a positive integer in the PIR controller. The proposed method is demonstrated for discrete PI, PID and PIR controllers via two systems. [ABSTRACT FROM AUTHOR]

In this article, PID-F controller is proposed for aircraft pitch control (APC) system in order to obtain a better dynamic system response. PID-F controller represents P proportional action with gain (kp), I integral action with gain (ki), D derivative action with gain (kd) and F derivative filter with gain (kf). Battle royale optimization (BRO) algorithm is used to find the optimal values of the independent parameters kp, ki, kd and kf. The performance of the BRO based PID-F controller has been verified by comparing with the BRO based PID controller. In addition, in order to make a more comprehensive performance evaluation, the BRO based PID-F controller is compared to the PID controllers existing in the literature for the same aircraft pitch control system, designed using harris hawks optimization (HHO) and atom search optimization (ASO). Transient response, frequency response and pole-zero analyses are used for comparative analysis. The results obtained from the simulations show that the proposed BRO/PID-F controller is superior to other controllers in terms of improving the transient and frequency responses of the APC system. [ABSTRACT FROM AUTHOR]

In this study, real-time application of load cell-based two-wheel balancing robot (TWBR) has been realized. The control of the system is provided by the PID controller with four load cells placed on the two-wheel balancing robot. The analog signals of the weight information coming from the load cell are converted into digital signals with the 24-bit resolution HX711 module. The data converted into digital signals are interpreted through the microprocessor over the synchronous serial communication protocol. The output of the dynamic model of the system can be updated instantly, according to the measured weight information. This process updates the maximum pitch attitude. Thus, the control of the two-wheel balancing robot is facilitated and the risk of the user falling off the vehicle is reduced. The control of the system is carried out using an ARM architecture based STM32F103C8T6 microprocessor. Current values and motor rotation speed information of the Brushless Direct Current Motor (BLDC) are obtained during the real time application of the vehicle. In addition, 12 different data are recorded on the SD card with using the SD card module. As a result of the data recorded on the card, the correlation value of each load cell is obtained as 0.99 in the repetition test of the load cells. As a result, the measurement error rate of the weight on the two-wheel balancing robot is obtained as 1%. [ABSTRACT FROM AUTHOR]

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With the developments in power electronics and microprocessor technology, it is considered that the application areas of Electronic Power Transformers (EPTs), which are expected to replace classical power transformers in the near future, will increase. One of the most important capabilities of EPTs is the ability to perform reactive power compensation without the need for additional filter elements. In addition, EPTs can be highly robust to disturbances in grid with appropriate design and control algorithms. In this study, a threephase EGT structure consisting of input, isolation and output stages is developed in the laboratory. With EPT structure, the disturbances in the grid can be compensated in the input stage of EPT. For this reason, three phase Pulse Width Modulation (PWM) based rectifier structure is preferred in the input stage of EPT. Type- 2 Neuro-Fuzzy Controller (T2NFC) is proposed instead of the classical PI or PID controller to control this rectifier structure. The proposed controller structure is used to control both the DC link voltage and the dqaxis currents of the PWM based rectifier. Furthermore, it is aimed to improve the performance of EPT against disturbances by the proposed controller structure. The control algorithms developed for the input and output stages of EPT are provided with the dSPACE DS1104 controller card. In order to evaluate the voltage sag and swell, harmonic and reactive power compensation performances of EPT, real-time operating conditions are prepared and experimental results are obtained. [ABSTRACT FROM AUTHOR]

This article presents a modified version of atom search optimization (ASO) algorithm that uses the opposition-based learning (OBL) to improve the search space exploration. OBL is a commonly used machine learning strategy for increasing the performance of meta-heuristic algorithms. As a new design method, the opposition-based ASO (OBASO) algorithm was proposed for the first time in determining the optimum values of the proportional-integralderivative plus second order derivative (PIDD2) controller parameters in an automatic voltage regulator (AVR) system. In the design problem, a new objective function, including the integral of time-weighted squared error (ITSE) and overshoot all together, was optimized with the proposed OBASO algorithm to find the best values of the PIDD2 controller parameters. The performance of the proposed OBASO tuned PIDD2 (OBASO-PIDD2) controller is compared to that of the classic ASO tuned PIDD2 (ASO-PIDD2) controller as well as the PID, fractional order PID (FOPID) and PIDD2 controllers tuned with modern meta-heuristic algorithms. Comparative transient and frequency response analyzes were conducted to assess the stability of the proposed approach. In addition, considering the possible changes in AVR parameters, the robustness of the proposed approach was tested. The extensive simulation results and comparisons with other existing controllers show that the proposed OBASO-PIDD2 controller with a new objective function has a superior control performance and can highly improve the system robustness with respect to model uncertainties. [ABSTRACT FROM AUTHOR]

Polymeric nanocomposites prepared with clay are of great importance in nanocomposites. Belonging to the family of smectite clays, particularly bentonite and montmorillonite, with a regular layered structure is widely used in preparing polymeric nanocomposites. In this experimental study, two different production method and two different operating conditions were used to obtain polymeric nanocomposites. Production methods used in this study is the in situ polymerization method and melt intercalation method. Experiments were performed at constant 1000C and 1050C temperatures. System temperature was kept constant with selftuning PID (STPID) controller. STPID control model and tuning parameters were determined by the genetic algorithm. After obtaining nanocomposites, firstly % monomer conversion and viscosity average molecular weights were calculated and then characterization studies were performed. Thermogravimetric Analysis (TGA) was used to determine thermal properties; Transmission Electron Microscopy (TEM) was used to determine surface characterization. Fourier transform Infrared Spectroscopy (FTIR) was used for structural analysis. Shore D hardness measurement method was used in the evaluation of mechanical properties. According to the characterization of the study it was determined to be generally better than the properties of nanocomposites obtained by melt intercalation method. [ABSTRACT FROM AUTHOR]

In this study, fault tolerant control is made using improved PID controller approach with different motor fault scenarios in a quadrotor. A realistic simulation was set up by obtaining dynamics equations of aircraft and modeling motor dynamics. By linearizing nonlinear model suitable controller is formed and this controller scheme is used in nonlinear models. Finally, designed control structure over different motor fault scenarios is tested whether a robust control structure is built. When the simulation results are analyzed, the performance of the designed control system shows a robust behavior under various conditions. [ABSTRACT FROM AUTHOR]

In this study, an internet based remote access experiment setup was developed for induction direct current motor speed control with PID controller which can be used as a support material in engineering education. The experiment setup is wireless and communicates with the remote server using transfer control protocol/internet protocol through a wireless ADSL modem. Users can perform the experiments as real time accessing the web pages in the remote server by using any computer which has internet connection. By means of interactively-designed web pages, users can monitor the speed change executing alterations of the PID controller parameter and motor reference speed. Also users can save the measured values on their own computers. In addition to this, with the support of a webcam, the running of the experimental set can be monitored on the web page. Additionally, for the experimental set, preparing the peripheral units card, the interaction was expanded between the user and the experimental set. Relatively to this, the user can monitor the ambient temperature of the experimental set’s current place on the web page and can make his/her own message write on LCD of the experimental set and can enlighten it if he/she wants. [ABSTRACT FROM AUTHOR]

The purpose of this study is to design and verify a fuzzy logic controller for a Quadrotor,which is a nonlinear system due to its mathematical model, in real time experimental setup. In this sense performances of the fuzzy controllers were compared with the performances of PID controllers that were designed for the same Quadrotor. Controllers were verified and their performances were augmented in an experimental setup that facilitates to set parameters in real time. When nonlinear dynamics of system due to mathematical model are increasing, designed fuzzy controller trajectory pursuit and robustness performance is getting better than PID controller's performance. When the improvement in microprocessor technology is considered, fuzzy logic controller, which do not require dense mathematical operations in design process, design and verification for the control of nonlinear dynamic systems is very simple and fast. [ABSTRACT FROM AUTHOR]

In this study, a neural network assisted real-time controller has been designed for highly nonlinear quadrotor orientation control. As controlled dynamic system, a highly nonlinear quadrotor model were used in this study. The controller has been designed with neural networks for Quadrotor attitude and trajectory control, and this controller's performance was compared against the classical PID controller's performance. These controllers for dynamic systems performance evaluations were made with the help of real-time experimental setup. Attitude and trajectory controls have done for designed controllers performance evaluation. Neural network performance was compared against the classical PID controller which was designed in the same experimental setup. Designed controllers robustness was tested with pulse inputs. We observed that neural network assisted controller was more succesful than PID controller in more complicated nonlinear dynamic systems, both in attitude and trajectory control performance. We comment that with today's microcontroller technology, neural networks are faster and more simple for designing controllers for highly nonlinear dynamic systems. [ABSTRACT FROM AUTHOR]

Because of increasing need for reliability, safety, maintainability and survivability in technological systems, fault tolerant control system has become extremely important. Fault tolerant control systems have been developed to overcome some weaknesses of the conventional feedback control design, such as instability and unsatisfactory performance in the faulty cases. In complex systems such as aircrafts, nuclear power plants, chemical plants etc., the results of a minor fault in the system can be destructive. Therefore, it is necessary to design control systems that are able to tolerate potential faults in these systems. A control system with this kind of fault tolerance capability is defined as fault tolerant control system. A fault tolerant control system is a closed-loop control system which can tolerate malfunctions while maintaining desirable performance and stability properties. A typical active fault tolerant control system includes three subsystems: reconfigurable controller, fault detection and diagnosis unit and decision supervisor unit. The reconfigurable controller is placed in control loop, instead of regular controller in traditional closed-loop control system. Since the real time toleration of faults can only be achieved if the control system has an automatic reconfiguration mechanism. This reconfiguration is generally activated after a fault has been detected and isolated. A fault detection and diagnosis system is a unit that obtains the occurrence of faults and determines their features in terms of type, location, size and/or time. The decision supervisor activates reconfiguration action in response, which can be pre-determined for each fault or obtained from real time analysis and optimisation. In active fault tolerant control systems, reconfiguration mechanism can be classified as on-line controller selection and on-line controller calculation techniques. In the on-line controller selection approach, the controllers associated with presumed faulty conditions are computed in an off-line manner in the design stage and they are selected in an on-line manner based on the real time information from fault detection and diagnosis algorithm. In the on-line controller calculation approach, the controller parameters are calculated in an on-line manner after the occurrence of fault. In this study, an active fault tolerant control technique, support vector machines based direct fault tolerant control system, is presented. In general, reconfiguration mechanism of a fault tolerant control system utilizes the information from fault detection and diagnosis unit at the decision stage. In the presented method, reconfiguration mechanism and diagnosis unit work independently. Both of them use only real time system outputs. A powerful and fast learning algorithm is needed for this purpose. Support vector machines is one of the most popular intelligent machine learning tools. They have become a very good alternative of neural networks with their superior generalization capacity, classification, regression and modeling performance. In this paper, support vector regression machines have been used in fault detection and diagnosis process and also in reconfigurable controller unit. PID type controllers have been used in reconfiguration sub-system. The PID coefficients of faulty and un-faulty cases to be used in training stage are obtained by genetic algorithm approach in an off-line manner. In reconfiguration mechanism, for each PID coefficient one support vector regression machine is set up. Faulty and un-faulty system outputs are collected for different input signals. In training stage, faulty system outputs and corresponding PID parameters are used as support vector regression machines' inputs and outputs, respectively. Thus the training phase of support vector machines is completed in an off-line manner. After completing the training phase, system is run for the reference input signal. The outputs of system are sent to decision unit periodically. Three of support vector regression machines are simultaneously evaluated the data sent by the system, and produce coefficients of the PID controller. The controller of which its coefficients are reconfigured, starts to work to maintain system performance in an on-line manner. In order to determine the type of fault, a similar process is exploited using one support vector regression machine. In training phase, inputs of this support vector regression machine are faulty and un-faulty system outputs but outputs are the features of the faults. This fault diagnosis unit runs parallel with intelligent fault tolerant controller. The performance of this knowledge based fault diagnosis and active fault tolerant control methods is illustrated on simulation example involving a two-tank water level control system under faulty conditions. [ABSTRACT FROM AUTHOR]

In this study, the gains of PI controller which is used for load-frequency control in a two area reheat thermal power system are tuned with the Particle Swarm Optimization (PSO). Tuning of the controller gains is taken up an optimization problem, and the new cost function is derived to reach to goal. The results which are obtained are compared with the literature, and it is observed that the dynamic response of the system is got better with proposed self-tuning PSO-PI controller. [ABSTRACT FROM AUTHOR]

A control system is an interconnection of components to perform certain tasks and to generate desired output signal, when it is driven by the input signal. In contrast to an open-loop system, a closedloop control system uses sensors to measure the actual output to adjust the input in order to achieve desired output. Most industrial control systems are no longer single-input and single-output (SISO) but multi-input and multi-output (MIMO) systems with a high coupling between the channels. In the design of all dynamical systems stability is the most important property. When a dynamic system is described by its input-output relationship such as a transfer function, the system is stable if it generates bounded outputs for any bounded inputs; bounded-input boundedoutput (BIBO) stability. For a linear, time-invariant system modeled by a transfer function matrix, the BIBO stability is guaranteed if and only if all the poles of the transfer function matrix are in the openleft- half complex plane. A reasonable approach to controller design is to find the set of all stabilizing compensators and then using a member of this set to satisfy further design criteria. A complete parameterization of all stabilizing controllers for a given system was suggested by Youla. An important disadvantage of this parameterization is that the order of the controller cannot be fixed. As a result, the order of the controller tends to be quite high most of the time. Therefore, in the last few years computation of all stabilizing controllers of a given order is examined by several researchers. It is a common fact that it is more difficult to design controllers for MIMO systems because there are usually interactions between different control loops. To overcome this difficulty decentralized controllers are considered which have fewer tuning parameters compared to general multivariable controllers. For example, decentralized PID (P: proportional, I: integral, D: derivative) controllers are widely used in process control due their simplicity and facility in working in case of actuator and/or sensor failure because it is relatively easy to tune manually as only one loop is directly affected by the failure. If a MIMO system described by a n×n transfer-function matrix G(s) is diagonal dominant over the bandwidth of interest, or there exists an input compensator matrix C(s) to achieve diagonal dominance, then the stability and time domain behavior of the system can be inferred from the diagonal elements of G(s)C(s). The relative gain array the (inverse-) Nyquist array approach, the block Nyquist array method, the Perron-Frobenius scaling procedure and the characteristic locus method are among the analysis and design methods to reduce the interaction in a multivariable system.… [ABSTRACT FROM AUTHOR]

Automatic control strategies force physical systems to behave in prescribed ways using the error value that is the difference between the system output and the desired reference input. This idea gives rise to feedback control systems. Since the only signal processor is the feedback controller, this classical control structure is also known as a one degree of freedom (1-DOF) control structure. In recent times, there has been considerable interest in more general control structures. In the two degree of freedom (2-DOF) case, the reference input is processed by the filter F(s), and the classical error is processed by the primary controller C(s). The prefilter F(s) is used as the second DOF to weight the set-point change in a desirable manner. In literature, there are many applications that use 2-DOF control structure which is sometimes called as model following control. Since PID controllers assure satisfactory results for a large range of processes and due to the simplicity of their structures, they still often represent the best solution from a cost/benefit ratio point of view. Therefore, the controller C(s) used in 2-DOF control structure is mostly a PID controller. Therefore, through this study, PI and PID controllers are used to design the proposed new structure. Internal Model Control (IMC) based PID is preferred for the feedback controller which is designed for a fast disturbance rejection performance. The processes are modeled as first order plus dead time (FOPDT) systems. Therefore the static gain (K), the time constant (T), and the time delay (L) of the model are obtained using well-known area method. The parameters of the PID controller depend on the process model parameters and in addition on IMC filter time constant (λ). λ is the only tuning parameter to be selected by the designer to achieve an appropriate compromise between the performance and the robustness issues in control system design. A smaller λ provides a faster closed loop response, but causes the manipulated control variable to become more vigorous, while a larger λ provides a slower but smoother response and a mild control effort. In this paper, a new 2-DOF control structure is proposed in which the advantages of 1-DOF and 2-DOF control structures are both exploited. In this new structure, the filtered output of the reference and the pure reference signals are blended so that the overall performance of the system is ameliorated with respect to load disturbance rejection and setpoint following. This new structure proposed in this study is named as a set-point regulator with blending mechanism (HAM-RA, SPR-BM). When the blending dynamics is set to be equal to zero then the proposed structure turns out to be a 2-DOF control structure; when the same dynamics is taken as unity, the proposed structure becomes 1-DOF control structure. The blending dynamics is determined with the aim of producing a system output that exactly matches to the filtered reference signal. The prefilter of the SPR-BM defines the desired behavior of the system and in order not to have an oscillatory behavior it is designed as FOPDT filter. When the feedback controller type is chosen to be a PI, the resulting blending mechanism becomes a pure gain. This blending constant is a function of system time delay (L), prefilter time constant and IMC filter time constant (λ). On the other hand, when the feedback controller is chosen to be a PID type, the blending mechanism then becomes a first order filter. The time constant of the obtained blending filter is half of the system time delay (L).… [ABSTRACT FROM AUTHOR]