An auxiliary control aided modified sliding mode control for a PMSG based wind energy conversion system

Attempts are being made to enhance the drive performance by intelligent control using fuzzy logic (FL) and neural network techniques. One of the frequently discussed applications of artificial intelligence in control is the replacement of a standard proportional plus integral (PI) speed controller with an FL or artificial neural network (ANN) speed controller. Regardless of all the work, it appears that a thorough comparison of the drive behavior under PI, FL, and ANN speed control is necessary. This article attempts to compare PI, fuzzy, and ANN controllers that are implemented in an embedded system for closed-loop speed control of DC drive fed by a buck-type DC–DC power converter. The PI controller is designed based on the small signal modeling of the system. The PI-like fuzzy controller structure is considered for comparison. Two ANN controllers are designed. One controller uses training data obtained from the simulation of a fuzzy controller and the other uses training data from the simulation of a PI controller. The performance of the controllers is studied for a variety of operating conditions, such as step change in speed command and step change in load torque. The parameters selected for the comparison are the steady-state error and the rise time of the response. It is shown that ANN speed controllers provide a superior speed response in terms of rise time and the steady-state error compared to PI and FL controllers. This advantage arises from the fact that the neural network has the property of generalization and the control surface of the neural controller is smooth. The designed neural network controller is simple, with three neurons only, and so it is best suited for embedded system implementation. It is also found that the ANN controller trained with the training data from a PI controller has a better response compared to the ANN controller trained with data from a fuzzy controller.

To enhance the control and stability of the wind energy conversion system (WECS) based on direct drive permanent magnet synchronous generator (PMSG), this artefact presents a modified sliding mode control approach. A detailed time domain dynamic model of PMSG-based WECS integrated to infinite bus is also presented in terms of d-q reference frame. In order to compensate the general limitations with regard to various control strategies, a proportional integral (PI) type sliding surface-based fast sliding mode control is executed for the above. A current control strategy has been suggested for real and reactive power control keeping voltage under the desired limit. To justify the superior performance of the proposed controller in terms of robustness, reliability and accuracy compared to PI controller, the control strategy is validated through MATLAB simulation, when the system is subjected to diverse operating conditions like wind speed and system parameter variations.

This paper aims at the design and simulation of hybrid PI-fuzzy control system for the speed control of a brushless dc motor. The performance of the fuzzy logic controller (FLC) is better under transient conditions, while that of the proportional plus integral (PI) controller is superior near the steady-state condition. The combined advantages of these two controllers can be obtained with hybrid PI -fuzzy speed controller. Both the design of the fuzzy controller and its integration with the proportional-integral (PI) controller is to be done. The principle of the proposed control system is to use a PI controller, which performs satisfactorily in most cases, while keeping in the background, a fuzzy controller, which is ready to take over the PI controller when severe perturbations occur. By combining the two controllers, one can get the quick response of the PI controller while eliminating the overshoot possibly associated with it.

In modern times, the design and optimization of different actuator systems for controlling a high-precision position control system represent a popular interdisciplinary research area. Initially, only single-stage actuator systems were used to control most of the motion control applications. Currently, dual-stage actuation systems are widely applied to high-precision position control systems such as hard disk drive (HDD) servo systems. In the dual-stage system, a voice coil motor (VCM) actuator is used as the primary stage and a piezoelectric micro-actuator is applied as the secondary stage. However, a dual-stage control architecture does not show significant performance improvements to achieve the next-generation high-capacity HDD servo system. Research continues on how to fabricate a tertiary actuator for a triple-stage HDD servo system. A thermal positioning controller (TPC) actuator is considered promising as the tertiary stage. The triple-stage system aims to achieve greater bandwidth, track density, and disk speed, with minimum sensitivity and greater error minimization. In this work, these three actuation systems with different combinations of proportional plus integral (PI), proportional plus derivative (PD), and proportional plus integral plus derivative (PID) controller, lag-lead controller, lag filter, and inverse lead plus a PI controller were designed and analyzed through simulation to achieve high-precision positioning. The comparative analyses were done on the MATLAB/Simulink simulation platform.

This paper presents a conventional sliding mode control (SMC) and chattering free improved sliding mode control design strategy for nonlinear systems. In this paper, theoretical and mathematical concept of variable structure control (VSC) system and sliding mode control has been discussed. The modelling of conventional sliding mode controller as well as chattering free improved sliding mode controller for sample nonlinear equation and robotic vehicle located underwater, forming a single direction motion is the main motive of this paper. Chattering in conventional sliding mode controller can be easily removed by using continuous function in place of discontinuous sign function. The Lyapunov stability criterion is used for nonlinear system control giving a simple control algorithm. Simulation result depicts the feasibility and satisfactory performance of chattering free improved sliding mode control as compared to conventional sliding mode control.

This paper presents a Radial Basis Function neural network based higher-order Sliding Mode Control for robust control of a dynamical system. A conventional sliding mode controller is suffering from a chattering problem, and the Super Twisting Algorithm is a special kind of higher-order Sliding Mode Control that has the capability of minimizing the chattering problem. There are also unknown model parameters and external disturbances that exert a negative influence on the control performance. To address the issues of model uncertainties and chattering, a Radial Basis Function (RBF) neural network based Super Twisting Algorithm is designed. The RBF neural network evaluates the model parameters and uncertainties, while the Super Twisting approach mitigates chattering, hence improving the controller’s overall performance. Lyapunov stability based adaptive laws are derived for online updating of the parameters of the neural network. The proposed control algorithm was tested on a 2-degree-of-freedom serial flexible joint robotic arm to investigate its efficacy. The controller has a lower control chattering amplitude, lower control energy consumption, and a good tracking response, when compared to the RBF based conventional Sliding Mode controller and simple STA controller, as shown by the results.

Objective:This paper explores the power condition abilities of Shunt Hybrid Power Filter (SHPF) with fuzzy tuned PI based control method in a distribution system. Method:A fuzzy tuner is proposed in this paper for tuning the parameters of proportional plus integral (PI) controller so that to improve the performance of the SHPF.The compensation process is based on source current sensing only. Synchronous Reference Frame(SRF) theory is used for generating reference currents, whereas linear current controller has been used to track these reference currents. Space Vector Pulse Width Modulation (SVPWM) has been employed to obtain the switching signals required for Voltage Source Converter (VSC). Findings/Improvements:Simulation analysis has been carried out to assess the performance of proposed control scheme. The simulation analysis proved that shunt hybrid power filters to be a potent solution for compensating the harmonics andreactive power of the distribution system.From the Simulation results, total harmonic distortion (THD), steady state response and dynamic behavior of the fuzzy tuned PI controller based SHPF is found to be better than conventional PI controller.

In this paper, we describe our design for a new electrohydraulic (EH) pump-driven renal perfusion pressure (RPP)-regulatory system capable of implementing precise and rapid RPP regulation in experimental animals. Without this automated system, RPP is manually controlled via a blood pressure clamp, and the imprecision in this method leads to compromised RPP data. This motivated us to develop an EH pump-driven closed-loop blood pressure regulatory system based on flow-mediated occlusion using the vascular occlusive cuff technique. A closed-loop servo-controller system based on a proportional plus integral (PI) controller was designed using the dynamic feedback RPP signal from animals. In vivo performance was evaluated via flow-mediated RPP occlusion, maintenance, and release responses during baseline and ANG II-infused conditions. A step change of -30 mmHg, referenced to normal RPP, was applied to Sprague-Dawley rats with the proposed system to assess the performance of the PI controller. The PI's performance was compared against manual control of blood pressure clamp to regulate RPP. Rapid RPP occlusion (within 3 s) and a release time of approximately 0.3 s were obtained for the PI controller for both baseline and ANG II infusion conditions, in which the former condition was significantly better than manual control. We concluded that the proposed EH RPP-regulatory system could fulfill in vivo needs to study various pressure-flow relationships in diverse fields of physiology, in particular, studying the dynamics of the renal autoregulatory mechanisms.

This article presents an original motion control strategy for robot manipulators based on the coupling of the inverse dynamics method with the so-called second-order sliding mode control approach. Using this method, in principle, all the coupling non-linearities in the dynamical model of the manipulator are compensated, transforming the multi-input non-linear system into a linear and decoupled one. Actually, since the inverse dynamics relies on an identified model, some residual uncertain terms remain and perturb the linear and decoupled system. This motivates the use of a robust control design approach to complete the control scheme. In this article the sliding mode control methodology is adopted. Sliding mode control has many appreciable features, such as design simplicity and robustness versus a wide class of uncertainties and disturbances. Yet conventional sliding mode control seems inappropriate to be applied in robotics since it can generate the so-called chattering effect, which can be destructive for the controlled robot. In this article, this problem is suitably circumvented by designing a second-order sliding mode controller capable of generating a continuous control law making the proposed sliding mode controller actually applicable to industrial robots. To build the inverse dynamics part of the proposed controller, a suitable dynamical model of the system has been formulated, and its parameters have been accurately identified relying on a practical MIMO identification procedure recently devised. The proposed inverse dynamics-based second-order sliding mode controller has been experimentally tested on a COMAU SMART3-S2 industrial manipulator, demonstrating the tracking properties and the good performances of the controlled system.

Load Frequency Control (LFC) is critical for ensuring stable operation of power systems, especially under diverse operating conditions. Within the analyzed single-area power network, the area control error (ACE) has been effectively managed despite uncertainties in system dynamics and the presence of external disturbances. The most recent study on disturbance rejection mechanisms has revealed that Active Disturbance Rejection Control (ADRC) is an effective controller for controlling uncertainty in systems, whether the system is linear or nonlinear. The importance of the ADRC controller resides in its model-free nature, that requires little understanding of the system model. The extended state observer (ESO) facilitates continuous estimation and compensation for disturbances, whether originating within the system or from external environments. However, certain process disturbances, such as time-delay, makes ADRC controller design more difficult. A solution to this problem is to use a Disturbance Observer (DO) which improves system performance. This study presents a comparative analysis of six control strategies: General Active Disturbance Rejection Control (ADRC) Controller with neglected delay, Delayed Input ADRC Controller, Smith Predictor ADRC Controller (ADRC-SP), Disturbance Observer (DO), PID (Proportional plus Integral plus Derivative) Controller, and PI (Proportional plus Integral) Controller, for their effectiveness in LFC of a single-area power system. Controllers are evaluated based on key performance metrics such as settling time, rise time, overshoot, and Integral of Absolute Error (IAE) under three scenarios: step load change, variable wind speed penetration, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$12 ~\mathrm{m} / \mathrm{s}$</tex> constant wind speed penetration. The results highlight the superior performance of the Disturbance Observer in minimizing settling time, overshoot, and Integral Absolute Error (IAE), making it the most robust and efficient controller among the evaluated strategies.

Currently, the main control strategy of the modular multi‐level converter (MMC) is a combination of vector control (VC) and proportional‐integral (PI) control, which allows decoupling active and reactive power control and maintaining the power balance within the high voltage direct current (HVDC) system. Although the existing PI control or conventional sliding mode control (SMC) shows a satisfactory control performance under steady state, its robust performance is poor when parameter uncertainty occurs, which greatly affects the stable operation of MMC. Therefore, a novel interval sliding mode control (ISMC) for MMC‐based HVDC systems is proposed in this paper, along with the stability criterion and design procedure. The proposed method can attenuate the influence of the parameter uncertainty, make the system robust and stable, and achieve both satisfactory transient and steady‐state performance under parameter uncertainty. The comparative simulation experiments of PI control, conventional SMC, and ISMC for MMC were conducted in PSCAD/EMTDC, demonstrating that the proposed ISMC shows better robustness and tracking performance than either PI control or SMC under different disturbance working conditions.

Chattering-free higher order sliding mode controller with a high-gain observer for the load following of a pressurized water reactor

Variable structure control with sliding mode, which is commonly known as sliding mode control (SMC), is a nonlinear control strategy that is well known for its robust characteristics (Utkin, 1977). The main feature of SMC is that it can switch the control law very fast to drive the system states from any initial state onto a user-specified sliding surface, and to maintain the states on the surface for all subsequent time (Utkin, 1977), (Phuah et al., 2005 a). The conventional SMC has two disadvantages (Ertugrul & Kaynak, 2000), (Slotine & Sastry, 1983), which are the chattering phenomenon (Slotine & Sastry, 1983), (Young et al., 1999) and the difficulty in calculating the equivalent control law of SMC that requires a thorough knowledge of the parameters and dynamics of the nominal controlled plant (Ertugrul & Kaynak, 2000), (Slotine & Sastry, 1983), (Hussain & Ho, 2004). Many methods of SMC using neural networks (NN) have been proposed (Phuah et al., 2005 a), (Ertugrul & Kaynak, 2000), (Hussain & Ho, 2004), (Phuah et al., 2005 b), (Yasser et al., 2007), (Topalov et al., 2007). In this paper, sliding mode controls using NN are proposed to deal with the problem of eliminating the chattering effect and the difficulty in calculating the equivalent control law of SMC that requires a thorough knowledge of the parameters and dynamics of the nominal controlled plant. The first method of this method applies a method using a simplified form of the distance function proposed in (Phuah et al., 2005 a), (Phuah et al., 2005 b). Furthermore, the simplified distance function of our method uses a sliding surface in the space of the output error and its derivations, as proposed in (Yasser et al., 2006 a), (Yasser et al., 2006 c), instead of the space of the states error to construct a corrective control input. Thus, no observer is required in the proposed method. Moreover, we also propose the application of an NN to construct the equivalent control input of SMC. The weights of the NN are adjusted using a backpropagation algorithm as in (Yasser et al., 2006 b). Hence, a thorough knowledge of the parameters and dynamics of the nominal controlled plant is not required for calculating the equivalent control law. Finally, a stability analysis is carried out, and the effectiveness of this first control method is confirmed through computer simulations. This first method has been previously discussed in (Yasser et al., 2007). The second method of this paper applies an NN to produce the gain of the corrective control of SMC. Furthermore, the output of the switching function the corrective control of SMC is applied for the learning and training of the NN. There is no equivalent control of SMC is used in this second method. As in the first method, this second method applies a method using a sliding surface in the space of the output error and its derivations, as proposed in

Distributed generation (DG) systems achieve an important role in electrical power networks due to their technical and economic benefits. This paper presents a novel application of the Crow Search Algorithm (CSA) with purpose of enhancing the performance of an inverter-based DG system. The control strategy of the inverter is based on a vector cascaded control scheme, which relies on the Proportional plus Integral (PI) controller. The proposed CSA is utilized to fine tune the PI controller parameters. The response surface methodology (RSM) is used to create the objective and constraint function of the optimization problem. The validity of the proposed control strategy is extensively verified using the simulation results, which are performed using PSCAD/EMTDC environment. These simulation results are investigated under different operating conditions such as 1) transition of the system from grid connected to islanded mode of operation, and 2) subject the system to a single line to ground fault in the autonomous mode. The effectiveness of the proposed controller is verified by comparing its results with that obtained using the genetic algorithm-based PI controller.

Introduction. This paper describes the simulation and the robustness assessment of a DC-DC power converter designed to interface a dual-battery conversion system. The adopted converter is a Buck unidirectional and non-isolated converter, composed of three cells interconnected in parallel and operating in continuous conduction mode. Purpose. In order to address the growing challenges of high switching frequencies, a more stable, efficient, and fixed-frequency-operating power system is desired. Originality. Conventional sliding mode controller suffers from high-frequency oscillation caused by practical limitations of system components and switching frequency variation. So, we have explored a soft-switching technology to deal with interface problems and switching losses, and we developed a procedure to choose the high-pass filter parameters in a sliding mode-controlled multicell converter. Methods. We suggest that the sliding mode is controlled by hysteresis bands as the excesses of the band. This delay in state exchanges gives a signal to control the switching frequency of the converter, which, in turn, produces a controlled trajectory. We are seeking an adaptive current control solution to address this issue and adapt a variable-bandwidth of the hysteresis modulation to mitigate nonlinearity in conventional sliding mode control, which struggles to set the switching frequency. Chatter problems are therefore avoided. A boundary layer-based control scheme allows multicell converters to operate with a fixed-switching-frequency. Practical value. Simulation studies in the MATLAB / Simulink environment are performed to analyze system performance and assess its robustness and stability. Thus, our converter is more efficient and able to cope with parametric variation.