Mode Control For Systems Research Articles

Enhancing Grid-Connected Photovoltaic Systems' Power Quality through a Dynamic Voltage Restorer Equipped with an Innovative Sliding Mode and PR Control System.

This study focuses on enhancing power quality in on-grid photovoltaic (PV) schemes through an innovative dynamic voltage restorer (DVR) that integrates two control strategies with a multi-level inverter. The DVR, a power electronic compensator, corrects voltage disturbances such as sag and swell by adjusting the voltage at the point of common coupling (PCC). It utilizes sliding mode control (SMC) for normal operations and proportional resonance (PR) during voltage disruptions, ensuring accurate voltage correction. The system's multi-level inverter offers a distinct advantage over traditional high-frequency inverters, which typically suffer from significant switching losses in high-power applications. The multi-level inverter effectively detects and mitigates voltage issues while minimizing harmonic distortion. The study evaluates the DVR's performance under various conditions, including voltage swell, disruption, mild sag, and severe sag. Simulation results using the Simulink tool demonstrate that the proposed DVR significantly reduces voltage disturbances and enhances power quality in the PV panel's output, the PCC, and the injected voltage. The findings suggest that this dual-control DVR designe, with its efficient use of a multi-level inverter, is a promising solution for improving power quality and stability in on-grid PV arrangements.

H ∞ prescribed tracking performance-based fractional-order sliding mode control for disturbed discrete-time systems: an LMI approach

This paper presents a novel approach to the design of a discrete-time Fractional-Order Sliding Mode Control (FSMC) system for Single Input Single Output (SISO) applications, utilising the Autoregressive with exogenous input (ARX) method for system modelling. The proposed methodology emphasises the Prescribed Performance Control (PPC) to ensure minimal tracking errors through a transformation of tracking errors based on a specified performance function. A Fractional-Order Quasi-Sliding Mode Control (FQSMC) is subsequently developed to maintain the tracking error within predetermined bounds, effectively addressing the chattering phenomenon commonly associated with the traditional sliding mode control. The integration of fractional calculus enhances the smoothness of the output while ensuring accurate tracking, making it ideal for real-world applications. Additionally, a novel Linear Matrix Inequality (LMI) observer is introduced to bolster the system's resilience against uncertainties and disturbances without complicating the computational process. The effectiveness of the proposed Prescribed Performance Fractional-Order Quasi-Sliding Mode Control (PP-FQSMC) is validated through extensive MATLAB simulations and experimental studies conducted on a Tank system. Results demonstrate that the PP-FQSMC significantly outperforms traditional methods, with maximum tracking errors of 1.6 × 10−4 compared to 0.2 for the PP-QSMC and a Root Mean Square Tracking Error (RMSTE) of 1.3 × 10−3 compared to 1.2 × 10−4 for the PP-QSMC, ensuring strong tracking performance and stability. The findings indicate that the proposed controller effectively mitigates chattering in control signals while maintaining a smooth output. It showcases its potential for practical applications in environments characterised by model inaccuracies, time delays, and external disturbances.

Novel Controller Methodology for the Cessna Citation X Under Turbulence During Cruise

The design of a new control approach for the longitudinal motion of the Cessna Citation X during cruise is performed using a combination of sliding mode control (SMC) system, type 1 fuzzy logic system, and adaptive control system. This methodology is presented for 1) controlling the aircraft pitch rate and 2) stabilizing the aircraft speed during turbulence. The nonlinear model of the aircraft was generated using a simulation platform, which was designed based on flight data obtained from the highest Federal Aviation Administration–certified Level-D Research Aircraft Flight Simulator. The type 1 adaptive fuzzy logic system was implemented to approximate unknown functions for constructing the equivalent part of the SMC system that handled the effects of uncertainties and turbulence. The adaptation laws, derived from the Lyapunov theorem, were used to update the approximated functions in the control law at each flight condition and simulation iteration. Using the control systems combination, the pitch rate could follow the given reference signal, while the aircraft speed remained at a reference value with and without turbulence across the whole flight envelope. Results have shown that the proposed controllers satisfied tracking performance while generating smooth elevator deflection, both of which are important for real-aircraft applications.

Realizing a kilowatt-level fiber amplifier with a 42 μm core diameter fiber for improved multi-mode performance towards single mode operation output through adaptive spatial mode control utilizing a 3×1 photonic lantern

The photonic lantern, a coherent beam combiner capable of controlling the phase, amplitude, and polarization of input light, has been utilized to enhance the brightness of fiber lasers by managing the output beam’s mode. In this work, a 3×1 photonic lantern-based adaptive spatial mode control system is employed to realize kilowatt-level operation in a 42 μm core fiber laser amplifier. Both simulation and experimental outcomes affirm the ability of this approach to manage modes within large-mode-area fiber laser systems through the use of 3 input arms. The experiment not only streamlines the overall system design but also has the potential to reduce production costs and complexities. Additionally, the spectrum width has been optimized to 10 GHz, striking a balance between the SBS threshold and the coherence of the photonic lantern’s input arms. By implementing this system, we have successfully achieved a stable, improved multi-mode performance towards single mode operation output of 1.08 kW, with a beam quality factor M2 of 2.20. This research furthers our understanding of how photonic lanterns can stabilize and enhance beam quality in high-power fiber lasers, paving the way for potential improvements in their performance and applications.

New Type-2-Fuzzy-Logic-Based Control System for the Cessna Citation X

This paper presents a new control law based on type-2 fuzzy logic system (T2FLS) for the Cessna Citation X aircraft during cruise. This methodology combines three control systems: a T2FLS, a sliding mode control (SMC) system, and an adaptive control system. Differing from conventional controllers, this control system can deal with uncertainties and aircraft dynamics variations using the T2FLS approximator. The approximated functions were updated during the simulation iterations using adaptation laws derived from the Lyapunov theorem. The adaptability characteristic of this controller allows updating the approximated functions while the other design parameters remain unchanged. This fact simplifies the controller design process and eliminates the need to use a group of conventional controllers with different gains to control the aircraft in various flight conditions. In addition, the sliding mode control system helps to guarantee the aircraft’s stability and robustness, along with two other methodologies in the presence and absence of turbulence. The performance of this control methodology was validated with a nonlinear simulation platform developed for the Cessna Citation X business aircraft using accurate flight data derived from a Level D flight simulator at the Research Laboratory in Active Controls, Avionics and AeroServoElasticity (LARCASE).

Improved Sliding Mode Model Reference Adaptive System Observer

In order to improve the accuracy and stability of sensorless control system of permanent magnet synchronous motor, considering the influence of external load torque on system performance, the symbol function of sliding mode control system of vehicle-mounted permanent magnet synchronous motor is prone to chattering and the robustness of traditional PI control is insufficient. In this paper, a method of combining Non-singular Fast Terminal Sliding Mode (NFTSM) and Model Reference Adaptive System (MRAS) is proposed. A Non-singular Fast Terminal Sliding Mode Controller (NFTSMC) is designed. A control strategy combining NFTSMC and Model Reference Adaptive System Observer (MRASO) (NFTSMC-MRASO) converts the observed torque value into torque current feedforward compensation to the current loop input. The large sliding mode gain is avoided, and the chattering problem of the system is overcome when the external disturbance is suddenly added. At the same time, the robustness of the system is improved under the premise of suppressing the chattering.

Derating factor determination of the three‐phase induction motor under unbalanced voltage using pumping system

AbstractA novel method is presented for determining the derating factors of a three‐phase induction motor under the condition of the unbalanced supply voltages. In this method, a mechanical system is used which consist of the a centrifugal pump, two valves, a DC motor, which are connected to the shaft of the three‐phase induction motor. A sliding mode control system is used for position control of the DC motor for adjusting the valve angle for derating the induction motor. The authors present the results of an experiment in which a three‐phase induction motor was subjected to various unbalanced voltage conditions. The results of simulations were used to look into what happened when there were different levels of imbalanced voltage. This was done to determine how these situations changed an induction motor's speed, torque, and efficiency. For this system, the stator current would be greater than the rated current if there was an imbalance in the supply voltage. Therefore, to reduce the amount of power that the three‐phase induction motor can produce, the control system uses a DC motor to reduce the angle of one of the two valves. This decreasing angle continues until the root mean square value of the stator current returns to the rated current. At this point, the derating factor may be calculated by dividing the output power of the three‐phase induction motor in the unbalanced condition by the output power when there are ideal sinusoidal. The MATLAB SIMULINK environment is utilised to perform simulations of the proposed system.

Enhanced Fuzzy-Based Super-Twisting Sliding-Mode Control System for the Cessna Citation X Lateral Motion

A novel combination of three control systems is presented in this paper: an adaptive control system, a type-two fuzzy logic system, and a super-twisting sliding mode control (STSMC) system. This combination was developed at the Laboratory of Applied Research in Active Controls, Avionics and AeroServoElasticity (LARCASE). This controller incorporates two methods to calculate the gains of the switching term in the STSMC utilizing the particle swarm optimization algorithm: (1) adaptive gains and (2) optimized gains. This methodology was applied to a nonlinear model of the Cessna Citation X business jet aircraft generated by the simulation platform developed at the LARCASE in Simulink/MATLAB (R2022b) for aircraft lateral motion. The platform was validated with flight data obtained from a Level-D research aircraft flight simulator manufactured by the CAE (Montreal, Canada). Level D denotes the highest qualification that the FAA issues for research flight simulators. The performances of controllers were evaluated using the turbulence generated by the Dryden model. The simulation results show that this controller can address both turbulence and existing uncertainties. Finally, the controller was validated for 925 flight conditions over the whole flight envelope for a single configuration using both adaptive and optimized gains in switching terms of the STSMC.

Trajectory tracking of a mobile robot manipulator using fractional backstepping sliding mode and neural network control methods

ABSTRACT In this paper, a fractional adaptive backstepping sliding mode control system based on the Caputo-Fabrizio derivative for a 2-DoF mobile robot manipulator is designed and described. The fractional dynamics of the system are obtained using the Atangana-Baleanu derivative and the Euler-LaGrange formalism, which include external disturbances, parametric uncertainties, and nonholonomic constraints. A fractional sliding mode control strategy is designed for trajectory tracking tasks. In order to compensate for the chattering phenomenon, the proposed controller is combined with a fractional backstepping strategy. Additionally, the Caputo-Fabrizio derivative is introduced to further reduce the chattering effects and improve the driver performance. A fractional adaptive control law is used to cope with the parametric uncertainties, while adding robustness to external disturbances. To further improve system performance, a tracking control strategy based on a fractional neural network is added. For a comparative analysis, the conventional adaptive neural network backstepping sliding mode control is implemented. Numerical simulations are described and discussed to validate the effectiveness of our control system for trajectory tracking tasks under different operating conditions such as trajectory changes and external disturbances. Our proposed control system and its traditional counterpart were tuned using the Cuckoo optimization approach.

CONTROL OF BIOMASS BOILER WATER TEMPERATUR USING SLIDING MODE CONTROL SYSTEM

Medium scale biomass temperature control is aspecific field of control issues where one of the most important features is cost effectiveness. It means that anykind of control system improvement should be done withthe lowest possible additional costs. Generally, the basiccontrol of such kind of boiler regulates temperature ofoutlet heating water. This control can be also performed bya conventional or advanced control. Although the main problem of this study is the constructionof the model of biomass boiler for control purposes, our taskdeals with technology of boilers and principles of its innerprocesses as well. Creation of the model comes out not onlyfrom these important findings, but also from experimentaldata collected during measurements in real operation. Heatand mass balance calculations were made according to thesedata and they serve to precise dynamic properties ofexperimental unit for biomass combustion.Based on the derived mathematical model of the biomassboiler, here is possibility to enhance the control byadditional algorithms that are responsible for extendedoptimization functions. In this paper, an advanced processcontrol such as sliding mode control system (SMC) is usedto control the temperature of the boiler water. The resultsshow that SMC has strong immunity for the disturbanceand the varying of process parameters.

A Cascaded Controller Design for Switched Reluctance Motor Based on Dung Beetle Optimizer

Due to the strong nonlinearity and large torque ripple of switched reluctance motor, a cascaded fractional order PID sliding mode control system is designed. Considering the difficulty of parameter adjustment caused by the complexity of the system, the optimization technology using dung beetle optimizer is introduced to optimize the designed cascaded controller and control the speed and torque ripple. To prove the effectiveness of the proposed cascaded controller, a control model is built in MATLAB/Simulink, and compared with whale optimization algorithm, particle swarm optimization, sparrow search algorithm to verify the response effect of the cascaded controller. A cascaded double PID controller is also built for comparison to verify the effectiveness of fractional order PID sliding mode controller. The results show that the cascaded fractional order PID sliding mode controller optimized by dung beetle optimizer is better than another cascaded double PID controller, produces the minimum torque ripple, and has better speed response and stability. The torque ripple of motor is suppressed. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Self-Organizing Type-2 Fuzzy Double Loop Recurrent Neural Network for Uncertain Nonlinear System Control.

Nonlinear systems, such as robotic systems, play an increasingly important role in our modern daily life and have become more dominant in many industries; however, robotic control still faces various challenges due to diverse and unstructured work environments. This article proposes a double-loop recurrent neural network (DLRNN) with the support of a Type-2 fuzzy system and a self-organizing mechanism for improved performance in nonlinear dynamic robot control. The proposed network has a double-loop recurrent structure, which enables better dynamic mapping. In addition, the network combines a Type-2 fuzzy system with a double-loop recurrent structure to improve the ability to deal with uncertain environments. To achieve an efficient system response, a self-organizing mechanism is proposed to adaptively adjust the number of layers in a DLRNN. This work integrates the proposed network into a conventional sliding mode control (SMC) system to theoretically and empirically prove its stability. The proposed system is applied to a three-joint robot manipulator, leading to a comparative study that considers several existing control approaches. The experimental results confirm the superiority of the proposed system and its effectiveness and robustness in response to various external system disturbances.

Design of ABS sliding mode control system for in-wheel motor vehicle based on road identification

Aiming at the problem that the current Anti-lock Braking System (ABS) control algorithm can not make full use of the ground friction to complete the braking when emergency braking on complex roads, an ABS sliding mode control method based on road surface identification is proposed. Combined with the in-wheel motor of in-wheel motor electric vehicle, a coordinated control method of motor regenerative braking and mechanical friction braking is designed. Based on the neural network control method, the road friction coefficient is estimated to realize the identification of typical roads and dynamically obtain the optimal slip ratio of different roads. The ABS sliding mode controler is designed with the optimal slip ratio and the actual slip ratio as input, and the saturation function is used to replace the symbol function in the traditional sliding mode control to weaken the chattering problem, and then the ABS controller is designed. The research results show that compared with the traditional ABS sliding mode controller, the designed ABS neural network sliding mode controller has the following advantages: 1. Through the identification of tire-road friction coefficient by neural network, the real-time performance and road adaptability of ABS controller are improved; 2. When the braking simulation is carried out at a given speed, the braking time is reduced by about 1.03 % and the braking distance is shortened by about 1.01%; 3. The identification of tire-road friction coefficient is realized, which weakens the chattering problem of traditional sliding mode control and improves the stability and robustness of ABS controller.

Disturbance Compensation in Discrete-Time Sliding Mode Control – A Comparative Study

This work is intended to compare three methods for disturbances estimation and compensation in discrete-time variable structure systems with sliding modes. All methods detect disturbance, which appear in control channel, with time delay of one sampling period. The first method is based on nominal discrete-time plant model and can be used in any type of discrete-time control systems. The second and the third methods detect disturbance by measurement of sliding function, and it is applicable in discrete-time sliding mode control systems only. The main task of this work is to check efficiency of the given methods in the presence of unmodeled inertial dynamics in actuators and position and velocity sensors of a positional servo system. It is shown that all three methods give near identical results in the nominal case, while the second and the third methods are superior in the presence of unmodelled dynamics. The third method introduces zig-zag motion in the nominal case. Results of research are illustrated by computer simulation of an example of positional servo system.

Operation Fault Detection of Electrical and Mechanical Equipment Based on Kalman Filter

In order to realize the remote collaborative diagnosis of electromechanical equipment fault in integrated energy system, a design method of remote collaborative diagnosis system of electromechanical equipment fault in integrated energy system based on Kalman filter is proposed. The hardware of the diagnosis system designed in this paper includes main control module, fault information parameter identification module, dynamic sensor acquisition module, fault signal filtering and detection module, adaptive control module, output interface module and so on. The collected fault information of electromechanical equipment in the system is fused by multi-source sensors, the fault information feature extraction is completed by Kalman filter, the information clustering processing is completed, and the algorithm design of electromechanical equipment operation fault diagnosis is realized. The fault diagnosis algorithm based on Kalman filter is loaded into the main control module of the motor equipment fault diagnosis system to realize the identification of motor equipment fault parameters and complete the development and design of the diagnosis system. The test results show that the text diagnosis system has good adaptability, high reliability and accuracy.

Feedback Linearization Sliding Mode Control Strategy for Three-Phase Voltage PWM Rectifier Based on New Variable Speed Reaching Law

Three-phase voltage PWM rectifier is a multivariable, strong coupling, nonlinear multi-input and multi-output system. In the design of rectifier control systems, with PI control it is difficult to achieve the ideal control effect, the dynamic performance is poor, and the parameter computation is complex. Moreover, the traditional sliding mode control voltage outer loop suffers from the problem of chattering, which is difficult to solve. Responding to the above issues, a new type of variable speed reaching law is proposed, which is applied to the voltage outer loop sliding mode control, while the feedback linearization principle is introduced to the current inner loop, and a new type of double closed-loop sliding mode control system is obtained by applying the two theories to the design of the sliding mode controller. A simulation model is established in MATLAB/Simulink to compare the PI control, the SMC control and the V-SMC control strategy proposed in this paper (voltage outer loop V-SMC current inner loop FLC-SMC control), and the simulation results show that the rectifier under the new dual-closed-loop sliding mode control strategy has the advantages of good dynamic performance, strong robustness and strong anti-interference ability. At the same time, compared with the traditional sliding mode control strategy, the vibration suppression effect under the proposed control strategy is obvious. Finally, a 10 kW rectifier control system is built on a semi-physical hardware-in-the-loop experimental platform to further verify the correctness and superiority of the proposed control strategy.

Design of Photoelectric Positioning System and Realization of Its Positioning Mathematical Equation

The research of photoelectric positioning system based on wireless data transmission is a multidisciplinary research direction. In the design of photoelectric positioning system, the LED used for light sensing is selected as the light source, and the AC/DC isolated LED driving circuit based on AP3706 is designed. When designing photoelectric conversion circuit, considering the influence of noise interference on detection accuracy, a capacitor is added and connected in parallel with the feedback capacitor. In order to improve the detection accuracy, reduce the relative error of the four-channel signal processing process and maintain the consistency of the four channels, a noninverting amplifier circuit composed of four operational amplifiers LM324 amplifier chips is adopted in this study. NewMsg-RF2401 module is used for wireless data transmission. The system control module adopts ADμC841 single chip microcomputer as the control core. According to the characteristics of this single chip microcomputer, the corresponding ADC module input drive circuit and control-data transmission interface circuit are designed. While designing the hardware of the system, it is necessary to calculate the positioning position. In this study, a positioning mathematical equation is proposed, which can obtain the position of the moving target in the geographical area under the wireless transmission network. In the experiment, firstly, the implementation process of the positioning mathematical equation is described, and then the performance of the proposed positioning mathematical equation is compared with that of the random positioning equation and the binary positioning equation. The results show that more messages can be transmitted by using the positioning mathematical equation proposed in this study. Based on this, it is used in the positioning system designed in this study, which is unfolded under the condition of constant background light, adjusts the position of the movable light source and determines the position coordinates. According to the horizontal and vertical displacement of the light source detected by the system, the positioning error is less than 0.1%, which is in line with the design expectation.

Industrial collaborative environments integrating AI, Big Data and Robotics for smart manufacturing

In recent years, global events have posed significant challenges to manufacturing firms’ business models, necessitating adaptable production systems that integrate human and automated resources seamlessly. Fortunately, technological advancements over the past decade have facilitated flexible production solutions. This paper introduces the approach of the CONVERGING EU project for collaborative smart manufacturing systems aiming at increasing flexibility, efficiency, and operators’ satisfaction. The proposed approach is structured into three technical pillars: perception, adaptation, collaboration, enhanced by modules for fostering user experience. Perception involves identifying and recognizing features of parts, resources, and surroundings to infer and analyse their status, and formulate action plans. Automated adaptations through hardware and control system modifications allow for executing formulated plans while complying with user characteristics and needs. Collaboration focuses on the software and hardware interfaces to ensure safe and seamless interaction with collaborative robotic solutions. Training, ergonomics tracking, and adaptable interfaces are also proposed to pave the way toward social industrial environments. This approach is applied to four industrial scenarios from different manufacturing sectors: automotive, white goods, aeronautics and additive manufacturing. The design of systems incorporating AI and robotics is presented together with the expected impact including safer, more intuitive, and trustful human-robot interaction, but also more inclusive industrial environments.

An integrative control theory perspective on consciousness.

An integrative account of consciousness should have a number of properties. It should build upon a framework of nonconscious behavior in order to explain how and why consciousness contributes to, and addresses the limitations of, nonconscious processes. It should also encompass the primary (phenomenal), secondary (access), and tertiary (self-awareness) aspects of consciousness. A number of accounts have proposed a role for consciousness in the prediction of sensory input, yet these proposals do not address how organisms deal with multiple, unpredictable, disturbances to maintain control. According to perceptual control theory (PCT), purposiveness is the control of hierarchically organized perceptual variables via changes in output that counteract disturbances which would otherwise increase error between the current value and the reference value (goal state) of each perceptual variable. In PCT, reorganization is the process required for the adaptive modification of control systems in order to reduce the error in intrinsic systems that control essential, largely physiological, variables. The current article proposes that primary consciousness emerges from this system, and is sustained as secondary consciousness through a number of processes including the control of the integration rate of novel information via exploratory behavior, attention, imagination, and altering the mutation rate of reorganization. Tertiary consciousness arises when internally sustained perceptual information is associated with specific symbols that form a parallel, propositional system for the use of language, logic, and other symbolic systems. The hypotheses and initial research designs to test this account are provided. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Improving robust indicators of sliding modes based on decomposition

The sliding mode control system based on the decomposition principle is divided into two parts: a sliding mode generation subsystem and a robust subsystem with large gain factor. Increasing the gain factor without loss of stability makes it possible to suppress the total uncertainty of the general form to an arbitrarily small value. This feature allows the system to move along a given trajectory without self-tuning of the sliding mode. Qualitative analysis on Simulink showed the effectiveness of the proposed approach. Keywords sliding mode, decomposition, uncertainty, navigator, robust control, Simulink