Search

A systematical decision-making approach is constructed for quality function deployment (QFD) in uncertain linguistic situations. The mathematical expression and operation of linguistic terms play important roles in the proposed approach in terms of customer requirements (CRs) and design requirements (DRs) in QFD. First, hesitant fuzzy linguistic term sets are designed to conveniently express uncertain linguistic terms and compute with words after the data derived from customers are pretreated and integrated in the decision-making process. Second, the tolerance deviation is defined to restrict innovatively the deviation range of fuzzy linguistic terms in the assessment stage of relative importance for CRs. Third, information entropy is originally designed to determine the final importance of DRs. Moreover, an empirical study on the research project called vortex recoil hydraulic retarder is conducted to demonstrate the performance of the systematical decision-making approach. The proposed approach can be applied to a wide variety of new product development problems in uncertainty settings. [ABSTRACT FROM AUTHOR]

A display window or store window is the shop's window that is designed to display items for sale to attract the customers to the stores. Window dressing that depends on visual merchandising is done to make a better impression and implies something dishonest. Knowing the customer from inside and outside through demographic data like ages, psychographics, lifestyles, and behaviors is the main factor that must be kept in display window designer's mind. The designer takes display colors, light, and signage in consideration. In the presented paper, factors of designing display windows that affect increasing customer attraction and buying rate are studied. An analysis of this variable is established to select which of them have good effects. Optimizing customers' attraction and buying rate values is carried out by controlling the selected affected variables through a designed and implemented fuzzy logic control system as an artificial intelligence tool. The fuzzy system, used for optimizing the number of viewers for stores' display windows by controlling the affected factors, is a new approach used in the display window design field. [ABSTRACT FROM AUTHOR]

The accurate abdominal vessel segmentation of CT angiography (CTA) data is essential for diagnosis and surgical planning. However, accurate abdominal vessel segmentation is a difficult problem since the following challenges: (1) complex abdominal vessel structure containing a wide range size of vessel branches, (2) low contrast of small vessels, and (3) uneven distribution of vessel grayscale. With full consideration of the challenges, we propose an automatic vessel segmentation algorithm. For challenge 1, the algorithm's framework is divided into large and small vessel segmentation and has the following steps. Firstly, a vessel model embedded fuzzy c-means (VMEFCM) method with full consideration of challenge 2 is presented to obtain the initial vessel voxels. Then, considering challenge 3, a large vessel segmentation method based on the initial vessel voxels, similarity, and morphologic is proposed. Finally, a small vessel segmentation method based on spine is described. Extensive analysis is carried out on simulation datasets and 78 CTA datasets. The experimental results indicate that each step of the algorithm achieves the prospective results, and the proposed algorithm is effective and accurate with low computational cost. The dice, sensitivity, Jaccard coefficient, and precision rate were 93.7±2.8%, 93.7±2.8%, 88.2±4.8%, and 94.2±7.5% respectively. [ABSTRACT FROM AUTHOR]

Cybersecurity is rapidly gaining significance due to growing use of computers in daily life and business sectors. Likewise, industrial sector has also become more vulnerable to cyber threats exclusively with the onset of Industry 4.0, which is a digital transformation evolved with industrial control systems (ICS). Nowadays industrial organizations aim to build capacity towards protection of ICS to be cybersafe. To assess the effects of vulnerabilities in ICS, organizations utilize Common Vulnerability Scoring System (CVSS), which calculates severity categories/scores. In this study, we implemented a prediction model for CVSS vulnerability categorization of ICS. Although there exist many applicable methods to use in data analysis paradigm such as statistical regression, cluster and classification analysis, the categorical form of CVSS data based on verbal statements and the failure to satisfy basic statistical assumptions for classical models motivated us to focus on implementation of fuzzy logistic regression (FLR) model, which is one possible alternative method. We chose the FLR method to explore that it is applicable to ICS vulnerability data. Furthermore, the model was improved by employing metaheuristic algorithms to optimize the spread of fuzzy numbers representing input variables. This study is expected to contribute to practical application of vulnerability categorization of ICS. [ABSTRACT FROM AUTHOR]

It is necessary to upgrade and transform the sorting equipment in the industrial production line. In order to improve production efficiency and reduce labor intensity, a high-speed lightweight parallel mechanism control system for the high-speed sorting and packaging of light items was studied. A fuzzy PID controller based on genetic algorithm (GA) optimization is proposed according to the nonlinear and strong coupling characteristics of the parallel mechanism (PM) control system. The inverse kinematic analysis was conducted to map the workspace trajectory tracking problem to the joint space. It was transformed into the trajectory planning and solving problems in the joint space. The motion trajectory was obtained utilizing quintic polynomial interpolation. Finally, the servo control system model was established, and the PID control parameters were optimized and self-tuned by the GA. They were applied to the fuzzy PID controller for simulation experiments. The simulation results showed that the GA-optimized fuzzy PID control system compared with the fuzzy PID control system had a 23.39% shorter rise time, 22.32% less regulation time, and 7.18% less steady-state error. The control system had a good dynamic and steady-state performance. [ABSTRACT FROM AUTHOR]

In this article, an adaptive tracking control approach is developed for a class of strict-feedback nonlinear systems with time-varying full state constraints. As a breakthrough in this system, the special function constraints (whose constraint boundary is relevant to both state variables and time) are considered, which are rarely studied by research work. And there is no doubt that this method increases the complexity of designing this scheme. Furthermore, the time-varying integral barrier Lyapunov functions combining with backstepping technique is introduced to break the limitation of traditional methods as well as achieve the full state constraints. Meanwhile, fuzzy logic systems are selected to approximate unknown nonlinear functions. It is verified that all closed-loop signals are bounded and all states are forced in the time-varying boundness. In addition, the proposed control strategy has a good performance. The effectiveness of the theoretical analysis results is proved via a simulation example. [ABSTRACT FROM AUTHOR]

This article addresses fuzzy tracking control question when switched systems are subjected to unknown input backlash, nonconstant control gain, and asymmetric full-state constraints. A new mode-dependent integral barrier Lyapunov function (MIBLF) can handle conservative feasibility conditions that only assure asymmetric full-state constraints and all subsystems share a common controller. To handle unknown input backlash nonlinearities in the presence of unknown nonconstant control gain function, fuzzy logic systems are utilized and a new parameterized smooth backlash inverse (PSBI) is presented. It is hard to construct the barrier Lyapunov function-based controller in the presence of unknown backlash, switching framework, and full-state constraints. By employing the fuzzy logic systems and the PSBI, a novel MIBLF-based adaptive fuzzy controller is presented to overcome this challenge. Furthermore, the presented controller not only prevents violation of all constrained states, but also ensures the boundedness of the closed-loop system. Eventually, feasibility of achieved theoretical results can be proven by two examples. [ABSTRACT FROM AUTHOR]

Drawing on the main characteristics of police professional education, this paper proposes an evaluation index system consisting of four subsystems and their index sets, in which society, police units, colleges, and students themselves jointly participate. The objective of this paper is to extract both subjective and objective evaluation information to develop an effective evaluation index system for professional education in police colleges. This paper uses a method based on improved information entropy to determine the weight of each index in the evaluation system, employs this weight calculation function to determine the subjective and objective weights of each index comprehensively, evaluates the professional education of police colleges using the improved fuzzy matter-element model, and verifies the training situation faced by graduates of the police university. The results show that combined with the evaluation system thus constructed, the entropy weight and fuzzy element model exhibit strong integrity and systematicity with respect to the evaluation of professional education in police colleges and that the evaluations produced by this approach are consistent with expert analysis. The evaluation thus becomes more comprehensive and objective and receives more social recognition. [ABSTRACT FROM AUTHOR]

In this paper, we explain the design and implementation of an intelligent irrigation control system based on fuzzy logic for the automatic control of water pumps used in farms and greenhouses. This system enables its user to save water and electricity and prevent over-watering and under-watering of the crop by taking into account the climatic parameters and soil moisture. The irrigation system works without human intervention. The climate sensors are packaged using electronic circuits, and the whole is interfaced with an Arduino and a Simulink model. These sensors provide information that is used by the Simulink model to control the water pump speed; the speed of the water pump is controlled to increase or decrease the amount of water that needs to be pushed by the pump. The Simulink model contains the fuzzy control logic that manages the data read by the Arduino through sensors and sends the command to change the pump speed to the Arduino by considering all the sensor data. The need for human intervention is eliminated by using this system and a more successful crop is produced by supplying the right amount of water to the crop when it is needed. The water supply is stopped when a sufficient amount of moisture is present in the soil and it is started as soon as the soil moisture levels drops below certain levels, depending upon the environmental factors. [ABSTRACT FROM AUTHOR]

Due to the large flutter boundary variation and the difficulty of conducting flutter tests on the ground of hyper-sonic vehicles, the thermal flutter test technology of wing surface structure on the ground is studied. Firstly, the aerodynamic heating of the structure is analyzed based on the engineering method, and then the thermal flutter characteristics of the structure are evaluated. Considering the influence of structure temperature rise on the actual flight, an aerodynamic force comprehensive optimization order reduction algorithm based on multi-condition points is established to ensure the accuracy of aerodynamic force simulation during the whole temperature rise process. By establishing a multi-point coordinated control system based on the fuzzy logic proportional integral derivative (PID) control, the excitation force controller of the time-varying system in the process of temperature rise is designed. Finally, the ground flutter test system is built, and the thermal flutter characteristics of the structure are tested according to the typical flight conditions. The relative error between the test results and the simulation results is about 10%. [ABSTRACT FROM AUTHOR]

When the low-magnification stope is filled, the problem of insufficient slurry in the vertical section of the filling pipeline will appear, which will accelerate the wear of the vertical pipeline, and even cause the phase change of the slurry to cause the pipeline to block. Through on-site investigation and theoretical analysis and calculations self-flow conveying model is established. Under the condition of ensuring the filling amount, a fuzzy control algorithm is established to adjust the filling concentration and the effective diameter of the pipeline, and improve the slurry conveying resistance and full tube degree. The algorithm stabilizes and adjusts the time 17 s, the overshoot is 6%, and the control effect is better than the PID control algorithm, which can improve the state of deep well filling with low line filling and unfilled pipes. [ABSTRACT FROM AUTHOR]

This study presents an extended dissipative analysis of fractional order fuzzy networked control system with uncertain parameters. First, we designed the network-based fuzzy controller for the considered model. Second, a novel Lyapunov-Krasovskii functional (LKF) approach, inequality techniques, and some sufficient conditions are established, which make the proposed system quadratically stable under the extended dissipative criteria. Subsequently, the resultant conditions are expressed with respect to linear matrix inequalities (LMIs). Meanwhile, the corresponding controller gains are designed under the larger sampling interval. Finally, two numerical examples are presented to illustrate the viability of the obtained criteria. [ABSTRACT FROM AUTHOR]

Controlling time-delayed processes is one of the challenges in today's process industries. If the multi-input/multi-output system is dynamically coupled, the delay problem becomes more critical. In this paper, a new method based on Smith's predictive method, with the help of a type-2 fuzzy system to control the system with the mentioned features, is presented. The variability in the time delay, the existence of disturbances and the existence of structural and parametric uncertainty lead to the poor performance of the traditional Smith predictor. Even if the control system is set up correctly at the beginning of the setup, it will eventually wear out, and the above problems will appear. Therefore, computational intelligence is used here, and by updating the parameters of the control system at the same time as the system changes, the control system adapts itself to achieve the best performance. To evaluate the proposed control system, a complex process system is simulated, the results of which show the good performance of Smith's prediction method based on a type-2 fuzzy system. [ABSTRACT FROM AUTHOR]

This paper further develops a relaxed method to reduce conservatism in H ∞ feedback control for continuous-time T-S fuzzy systems via a generalized non-quadratic Lyapunov function. Different from the results of some exisiting works, the generalized H ∞ state feedback controller is designed. The relaxed stabilization conditions are obtained by applying Finsler's lemma with the homogenous polynomial multipliers, and the H ∞ performance is acquired by solving an optimization problem. In addition, the proposed method could be expanded to handle other control problems for fuzzy systems. Two examples are given to show the validity of the proposed results. [ABSTRACT FROM AUTHOR]

Reputation is a crucial factor that governs the importance of a software agent in the agent-mediated e-market. In the e-market, various buyers and service providers are involved in buying and selling the products. A buyer agent (BA) acts on behalf of a buyer to buy the products from a service provider agent (SPA) preferably having a good reputation score (Rep-Score). The conventional customer rating mechanism for online transactions lacks adequate analysis and investigation of customer reviews and hence does not reflect the accurate reputation of the service providers. This research investigates the reputation of a software agent using customer feedback based on product attributes such as product quality, design, price, delivery time, and defects. A knowledge rule-set is formed to establish a link between customer feedback and the repute of a software agent. Further, a simulation-based approach using the Rosetta toolkit and the Fuzzy Control System is applied to quantify and fine-tune the reputation of a software agent. There could be a chance of an unfair relationship between the same buyer-seller pair due to recurrent transactions. The proposed work eliminates any chance of a conspiracy between a service provider and a buyer agent. In case, the buyer agent makes repeated transactions with a particular service provider agent, the value of the weight assigned to the reputation of the service provider agent is significantly diminished for each new transaction, hence decreasing the final value of the Rep-Score. As a result, this method guarantees the correctness of the reputation evaluation of a software agent. A performance analysis is performed to validate the proposed approach using mean squared error and standard deviation. [ABSTRACT FROM AUTHOR]

This article investigates the nonfragile guaranteed cost (GC) control problem of discrete-time impulsive switched Takagi–Sugeno (T–S) fuzzy systems with input quantization and asynchronous switching. The model-dependent dynamic quantizers are applied to obtain the quantized input signal. To deeply study the GC performance analysis and GC control problems in the presence of quantization, asynchronous switching, and impulses, a novel piecewise cost function containing the quantized input instead of normal input is applied in this article. By using the mode-dependent average dwell time approach and introducing a class of Lyapunov-like functions allowing to increase during the asynchronous period, new sufficient conditions are established to guarantee the asymptotical stability with the GC performance index for the impulsive switched T–S fuzzy systems with quantized control input and asynchronous switching. Then, new design conditions about the nonfragile GC controllers and dynamic quantizers of impulsive switched T–S fuzzy systems are obtained in the form of linear matrix inequalities. Finally, a numerical example and a practical example are provided. [ABSTRACT FROM AUTHOR]

Tracking control of redundant and hyperredundant manipulators is a fundamental and critical problem in practical applications. In order to effectively decrease the end-effector position errors, a novel dual fuzzy-enhanced neurodynamic (DFEN) scheme is put forward for solving the position error accumulation problem followed by achieving accurate tracking control results. The proposed scheme is established based on a zeroing neurodynamic approach in conjunction with two fuzzy adjustment units that are capable of tuning the control parameters by monitoring the tracking error. Moreover, the DFEN scheme can effectively solve the tracking problem without requiring knowing a priori knowledge of the kinematic model of the robot. The convergence and the stability of the proposed approach are demonstrated by theoretical analysis. The effectiveness, accuracy, and robustness of the proposed DFEN scheme are verified on the simulative redundant manipulator, continuum robot, and hybrid robot (integrating the redundant manipulator and the continuum robot). A practical experiment is provided to validate the proposed scheme as well. [ABSTRACT FROM AUTHOR]

This article presents a hybrid metaheuristic optimization algorithm that combines particle filter (PF) and particle swarm optimization (PSO) algorithms. The new PF–PSO algorithm consists of two steps: the first generates randomly the particle population;and the second zooms the search domain. An application of this algorithm to the optimal tuning of proportional-integral-fuzzy controllers for the position control of a family of integral-type servo systems is then presented as a second contribution. The reduction in PF–PSO algorithm's cost function allows for reduced energy consumption of the fuzzy control system. A comparison with other metaheuristic algorithms on canonical test functions and experimental results are presented at the end of this article. [ABSTRACT FROM AUTHOR]

This article focuses on developing a static output feedback (SOF) control scheme for Takagi–Sugeno fuzzy systems. The proposed SOF controller does not share the same premise membership functions with the model, which permits enhancing the flexibility in controller design and implementation. By contrast with the state feedback case, the SOF control generally results in nonconvex design conditions. To circumvent this problem, we develop a successive convex optimization algorithm, which is based on solving a sequence of more tractable convex optimization problems obtained by approximating the nonconvex constraints with some convex ones. As a heuristic algorithm, the validity of the developed successive convex optimization algorithm is highly affected by initial conditions, and, recognizing this, we put forward an iterative procedure for determining the feasible initial condition. Finally, two illustrative examples are presented to validate the efficiency of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Solid-state welding is a derivative of the friction stir spot welding (FSSW) technique, which has been developed as a new method for joining aluminum alloys. FSSW is a variant of linear friction stir welding intended to deal with lightweight alloy resistance spot welding (RSW) and riveting. Tensile strength refers to a material's ability to withstand excessive stress when being stretched or pulled before necking; it is expressed in terms of force per unit area. The tensile strength in stir spot welding is affected by dynamic and static parameters. The control of dynamic parameters and static parameters is studied in this paper to optimize the friction stir spot welding strength. A fuzzy logic control system is used to optimize the process as a new approach that can be used in this field. The obtained results prove that the fuzzy logic control system is an easy and inexpensive technology that can be used in prediction and optimization for the strength of FSSW. Furthermore, the results show the efficacy and adequacy of the proposed fuzzy logic control system. [ABSTRACT FROM AUTHOR]

Stand-alone hydropower plant is a major energy source in grid isolated zone because they do not require dams to be built. In a stand-alone hydropower plant Voltage and frequency, instability is caused by the load variation. This can cause the alternator to spin very quickly or very slowly, causing the induced voltage and output frequency to rise or fall. Furthermore, if the rate of alternator growth is too high or too low, the load appliances connected to the generator can undergo huge damage. For optimal overall performance of a small hydropower plant, generated voltage and frequency must be within the required range. To overcome these issues, a system is discussed in this paper. The proposed system not only stabilizes stand-alone hydropower plant output through an electronic load control system but is also easy and price-effective. Electronic load controller managed small hydro energy generation that takes into vital parameters, i.e, stabilization of both voltage and frequency despite variable consumer load. The presented technique consists of PID and fuzzy logic control system and also a couple of DC motors interconnected with an Hbridge to control the water valve known as a gate. The proposed control system also consists of several dummy loads to dump the extra generated power to keep the output power constant and to overcome frequency variations. For increased efficiency and life span of the generator, dummy loads used are switched only at zero crossings of a sinusoidal signal. The proposed system is implemented on both Simulink/MATLAB and Proteus. The simulation results prove that the presented technique overcomes the challenges of stand-alone hydropower plants. [ABSTRACT FROM AUTHOR]

The precise motion control of a hydraulic motor system has some problems due to uncertain disturbance, complex nonlinear dynamics. Traditional methods are difficult to obtain the desired control performance. In this paper, a new fuzzy neural network (FNN) combined with terminal sling mode control (TSMC) and time delay estimation (TDE) is proposed. FNN is used to adjust the parameter of TSMC to reduce the time for the system to reach the equilibrium point and chatting. To increase the accuracy of the system, TDE is used to compensate the error caused by uncertain disturbance. This controller was simulated in Amesim and Simulink, and the results showed that the control scheme proposed in this paper has the smallest angular displacement error, angular velocity error and variance than other control schemes, such as PID and sliding mode control (SMC). Furthermore, the designed controller was implemented on a drill pipe automatic handling manipulator, and its control performance was verified. [ABSTRACT FROM AUTHOR]

• This study is based on field data from shelters' environmental conditions in Spain. • An archaeological site has been detailed examined. • A fuzzy inference system to estimate technical suitability of shelters is presented. • Digital models contribute to the description of future maintenance policies. Exposed sites are highly vulnerable to decay, and shelters have been proposed as preventive conservation measures systematically. However, they need to be evaluated periodically as they may introduce new decay factors into the sites or provide an insufficient level of protection. Nonetheless, there is a lack of tools to help site managers make the complex decision of sheltering. Artificial intelligence systems can model information with a degree of uncertainty and are associated with material degradation processes and risky external hazards subjected to seasonality. This method has allowed a systematic assessment of the shelters at the Complutum archaeological site (Spain). The system has been applied twice a day during the summer, autumn, winter and spring seasons, taking into consideration atmospheric and environmental input variables and vulnerabilities in the shelter design and management. By providing the model predictions, specific preventive conservation measures could be taken in advance to avoid further damage or failures. [ABSTRACT FROM AUTHOR]

In this paper, the design and simulation of a Fuzzy Control for a 3 Degrees Of Freedom (3-DOF) Delta Parallel Robot with Prismatic actuators are presented. The position of the moving platform and prismatic joints are solved the direct and inverse kinematic analysis. The forces of the actuated prismatic joints are computed with the dynamic analysis using the Lagrangian approach and compared with the obtained forces in simulation; trajectory planning is "point-to-point", with polynomial functions. The proposed controller is a Fuzzy Control System, and the effectiveness has performance comparing the desired trajectory against the obtained via simulation. [ABSTRACT FROM AUTHOR]

For the stability analysis problem of a T-S fuzzy system, a membership functions integration-based method is proposed to relax the existing conservatism. Firstly, indefinite integral functions are derived for the membership functions. Then with a piecewise linear approximation approach, the membership functions and their integration functions are involved in a fuzzy-like Lyapunov function-based stability analysis process. Finally, comparisons with existing methods are presented in the simulation section to show the advantages of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Southeast University (English Edition) is the property of Journal of Southeast University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To overcome the problem of poor uniformity of solid-fertilizer-dissolving devices due to lag of fertilizer dissolution, a closed-loop control system based on fuzzy proportional-integral-derivative (PID) was designed and tested. A fertilizer concentration regulation model was then established according to the results. In this system, the control core was an STM32 used to feed back the fertilization concentration by detecting the electrical conductivity. For real-time adjustment of the fertilizer flow rate and water flow rate, a fuzzy PID control algorithm was utilized to compare the detected concentrations with the set concentrations. The linear relationships between quantities such as the fertilizer rate and PWM frequency, water flow rate and PWM duty ratio of the direct-current pump, and fertilizer concentration and electrical conductivity were all established to calibrate the system. The influence of the fertilizer flow rate and water flow rate on fertilizer concentration was determined by the control variable test method. The results showed a positive linear relationship between fertilizer concentration and fertilizer flow rate, while a reverse linear relationship was established between fertilizer concentration and water flow rate. After the introduction of the control system into the self-developed solid-fertilizer-dissolving device, the fertilizer concentration fluctuated near the set concentration in a range of no more than 1 g/L. After the disturbance of the fertilization device, the control system fine-tuned the device with a steady-state error of about 0.55 g/L after the system reached stability. The control system designed in this study was shown to run normally with good stability, speed, and accuracy, and with improved fertilization uniformity of the solid-fertilizer-dissolving device. This study lays the foundation for further study of fertilization control systems. It also provides a reference for the development of precise and intelligent fertigation. [ABSTRACT FROM AUTHOR]

In recent years, with the steady and rapid growth of the national economy, various industries have developed rapidly and the resulting fire accidents have also been on the rise. This study mainly discusses the control system of a fire rescue robot for a high-rise building design. Robot fire detection method involves obtaining the video image of the fire detection area through a high-definition camera, performing image preprocessing on the current frame image of the video in the robot operating system to obtain the image; and performing the flame area segmentation based on the Ohta color space and the Otsu threshold segmentation algorithm on the image, to obtain the segmented image; through the interframe difference method, the preprocessed image of the previous frame is subtracted from the current frame image and the moving area of the image is segmented to obtain the segmented image; the obtained segmented image is combined with the segmented image in the robot operating system and images are intersected to obtain a segmented image with the characteristics of flame motion; based on other characteristics of the flame, flame recognition is performed on the area in the segmented image. Fires in high-rise buildings are increasing gradually, which seriously endangers the safety of human life and property. The firefighting robot and its control system play an important role in the fire protection of high-rise buildings. The purpose of this study is to analyze the disaster relief effect of a firefighting robot and control system in high-rise buildings. In this study, we use MATLAB software to model and simulate the rescue situation of a firefighting robot in high-rise buildings. The fuzzy control system established in the fuzzy logic toolbox of MATLAB can easily replace human field work and can change the control rules and membership function in the FIS editor. The results show that the rise time and adjustment time of the system are basically the same under the condition of variable load stiffness. The maximum overshoot is 0.59%, and the steady-state error is 0.19%. The maximum overshoot is 1.0148%, and the stability error is 0.46%. It is concluded that the expert PID algorithm is efficient and practical. It can be concluded that the robot position control system adopts PID control algorithm, and the attitude control system adopts expert PID control algorithm. This research provides some value for the development and design of firefighting robots in high-rise buildings in the future and also brings important significance. [ABSTRACT FROM AUTHOR]

The basic technological process of sludge conditioning and pressing is introduced in this paper. The purpose is to set up an adaptive fuzzy control algorithm to treat the problems of conditioning, mixing, feeding, and pressing control, so that the equipment used to process the sludge can run on demand. The algorithm is verified by MATLAB simulation. The results show that the control accuracy of the fuzzy adaptive control system is significantly improved compared with the original PID (proportion integration differentiation) control algorithm. The upper computer program is compiled with VB (visual basic) and applied to industry control to save the energy consumption. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the concept of a WPH-space without linear structure and proceed to establish a new upper semicontinuous selection theorem for fuzzy mappings in the framework of noncompact WPH-spaces as well as a special form of this selection theorem in crisp settings. As applications, fuzzy collective coincidence point theorems, fuzzy collectively fixed point theorems, and existence theorems of equilibria for the generalized fuzzy games with three constraint set-valued mappings and generalized fuzzy qualitative games in WPH-spaces are obtained. As their special cases in crisp settings, we derive existence theorems of equilibria for generalized games and generalized qualitative games. Finally, we construct a multiobjective game model for water resource allocation and prove the existence of Pareto equilibria for this multiobjective game based on the existence theorem of equilibria for qualitative games. [ABSTRACT FROM AUTHOR]

To reduce the influence of controller uncertainties and lower the computational burden of the system, a novel nonfragile sampled-data control scheme is proposed in this article for the Tagaki–Sugeno fuzzy system with time delay. First, an improved Lyapunov–Krasovskii functional is established with adjusted looped functional, which contains not only the current states, but the delayed states. Then, utilizing the Wirtinger inequality and improved single integral inequality, the new stability criteria are proposed with less conservativeness. By calculating the solution of linear matrix inequalities, the nonfragile controller parameters can be acquired. Furthermore, the sampled-data fuzzy controller leads to a good stable performance for the system, even under the possible gain fluctuations. Finally, three examples are given to verify the effectiveness and superiority of the proposed control scheme. [ABSTRACT FROM AUTHOR]

A novel adaptive-neuro fuzzy interfaced system (ANFIS) control algorithm-based smart grid to solve power quality issues is investigated in this paper. To improve the steady-state and transient response of the solar-wind and grid integrated system proposed ANFIS controller works very well. Fuzzy maximum power point tracking (MPPT) algorithm-based DC-DC converters are utilized to extract maximum power from solar. A permanent magnet synchronous generator (PMSG) is employed to get maximum power from wind. To maximize both power generations, back-to-back voltage source converters (VSC) are operated with an intelligent ANFIS controller. Optimal power converters are adopted this proposed methodology and improved the overall performance of the system to an acceptable limit. The simulation results are obtained for a different mode of smart grid and non-linear fault conditions and the proven proposed control algorithm works well. [ABSTRACT FROM AUTHOR]

The steering system, suspension system, and braking system of the vehicle are interrelated, so the ride comfort and handling stability of the vehicle are also closely related. But the vertical and lateral dynamics equations and controls system of the vehicle are always independent of each other, and the multiobjective control is generally achieved through the coordination of control algorithms. In this paper, taking the dynamic load of the tire as a link, the vertical dynamic model and the lateral dynamic model of heavy-duty vehicle are coupled. When the heavy-duty vehicle is turning, the proposed coupling model not only reflects the influence of the front wheel angle on the vertical motion and the vertical tire load, but also reflects the unevenness of the road surface on vehicle lateral motion. In order to improve the handling stability and transient safety of the vehicle, a synchronous control system combining six-wheel steering and front wheel active steering is proposed. It solves the problem that it is difficult to effectively track the desired yaw rate for the three-axle all-wheel steering vehicle with the middle rear wheel angle as the control input. Under the framework of the vehicle vertical/lateral unified coupling dynamics model, the semiactive suspension system controlled by fuzzy PID and the six-wheel active steering system combined with fuzzy control and fuzzy PID control are integrated. It is verified that the synchronous control method effectively optimizes the vertical and lateral motion characteristics of heavy-duty vehicles during steering and, at the same time, improves the ride comfort and steering stability. [ABSTRACT FROM AUTHOR]

This work focuses on the dissipative analysis and quantized sampled-data control design issues for T-S fuzzy networked control system (TSFNCS) under stochastic cyber-attacks (SCAs), which have strong application backgrounds and significant theoretical research value in the field of network security. For this work, a novel time-delay-product relaxed condition (TDPRC) is introduced, which can obtain the slack constraints based on the delay information. Then, by fully considering the delay and sampling time point information, an improved boundary looped-functional (BLF) is developed to acquire more information on the Lyapunov-Krasovskii functional (LKF). In addition, based on the relationship between the sampling moments $(t_{k+1}-t)\eta ^{T}_{3}(t)$ and $(t-t_{k})\eta ^{T}_{4}(t)$ in $V_{c}(x_{t})$ , the obtained constraints may be further relaxed. Next, a new criterion and the corresponding algorithm are established using reciprocally convex matrix inequality (RCMI), proper integral inequalities, and the linear convex combination method (LCCM). In addition, a new quantitative sample data (QSD) controller under SCA is designed to ensure that TSFNCS is asymptotically stable (AS) and dissipative. Finally, the experiment of the truck-trailer system (TTS) dynamics equations proves the correctness of the theory proposed in this paper. [ABSTRACT FROM AUTHOR]

Accurate energy production forecasting is critical when planning energy for the economic development of a country. A deep learning approach based on Long Short-Term Memory (LSTM) to predict one-day-ahead energy production from the run-of-river hydroelectric power plants in Turkey was introduced in the present study. Furthermore, to compare the prediction accuracy, the methods of Adaptive Neuro-Fuzzy Inference System (ANFIS) with Fuzzy C-Means (FCM), ANFIS with Subtractive Clustering (SC), and ANFIS with Grid Partition (GP) were utilized. The predicted values obtained by the application of these four methods were evaluated with detected values. The correlation coefficient (R), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Square Error (RMSE) were used as quality metrics for prediction. The comparison showed that the LSTM neural network provided higher accuracy results in short-term energy production prediction than other ANFIS models used in the study. [ABSTRACT FROM AUTHOR]

In view of the difficulties in the navigation of facility agricultural equipment in a greenhouse environment, which are greatly affected by environmental factors, being difficult to navigate, and low accuracy, a magnetic navigation controller suitable for greenhouse environments is designed based on fuzzy PID (proportion integration differentiation) control and combined with the principle of magnetic navigation control in this paper. The magnetic navigation in a greenhouse environment is realised, and the installation test is carried out on the existing agricultural machinery platform. The results show that when driving in a straight line, the straightness error is controlled at ±2.5 cm m -1 , and when driving on a bend, the driving deviation is controlled at ±4.5 cm m -1. Therefore, it can be considered that the magnetic navigation control method based on fuzzy PID control designed in the greenhouse environment can effectively improve the accuracy of navigation and promote the application of facility agricultural equipment to a certain extent. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: A solar panel is a device that converts solar rays into electricity. It is a step to reduce emissions from fossil energy, which is to replace it with renewable energy. It requires a control system to ensure that the position of the solar panel is always perpendicular to the sun's rays. This study aims to modify the fuzzy set based on fuzzy entropy in the control system that has been developed. The modifications made are expected to increase the efficiency of solar panels in harvesting energy. METHODS: Type II fuzzy sliding mode control is used, along with a modified fuzzy set based on the entropy value. Before modification, the system containing the fuzzy set generates a histogram of entropy and voltage performance, which is the initial value and the comparison value. The algorithm alters the footprint of the uncertainty limit. This change results in a new fuzzy set, which results in a new histogram and voltage. The final step is to compare the initial and final parameters based on the results of the modifications. FINDINGS: The solar panels require only 7.3x10-5 degrees of movement per second. This is a very slow movement for a dc motor with a maximum voltage of 12 volts. The simulation produced a stable speed of 7.297x10-5 on the unmodified system and 7.295x10-5 on the modified system. The modified system experiences a slight delay towards the stable point because the fuzzy entropy method reduces the dominance of set point positions in the system. CONCLUSION: The modified fuzzy set is good at controlling the solar panel driving motor based on the output voltage value. On both controllers under consideration, the voltages follow the same pattern. However, it experienced a control mismatch at the point towards the set point. Finally, by changing the foot of uncertainty and adjusting it proportionally according to control needs, the control system based on fuzzy sets with fuzzy entropy can be further developed. [ABSTRACT FROM AUTHOR]

In this paper, cluster synchronization in finite/fixed time for semi-Markovian switching complex dynamical networks (CDNs) with discontinuous dynamic nodes is studied. Firstly, the global fixed-time convergence principle of nonlinear systems with semi-Markovian switching is developed. Secondly, the novel state-feedback controllers, which include discontinuous factors and integral terms, are designed to achieve the global stochastic finite/fixed-time cluster synchronization. In the framework of Filippov stochastic differential inclusion, the Lyapunov-Krasovskii functional approach, Takagi-Sugeno(T-S) fuzzy theory, stochastic analysis theory, and inequality analysis techniques are applied, and the global stochastic finite/fixed time synchronization conditions are proposed in the form of linear matrix inequalities (LMIs). Moreover, the upper bound of the stochastic settling time is explicitly proposed. In addition, the correlations among the obtained results are interpreted analytically. Finally, two numerical examples are given to illustrate the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

This work deals with minimizing fluctuations of propulsion force and improving the motion quality in a linear switched reluctance motor. In order to minimize the jerks in the moving part of the motor, a new profile is used to generate an appropriate reference speed profile. Then, a simple fuzzy logic system which is able to overcome the uncertainties problem in nonlinear systems is designed and applied to the motor. The fuzzy control system can regulate the motor performance so that it tracks the reference speed with minimum error and fluctuation. The system is designed and its efficiency is shown through simulation and experimental tests in different performance situations. The obtained results confirm that the proposed strategy outperforms other conventional methods. [ABSTRACT FROM AUTHOR]

This article presents a new sampled-data-based event-triggered pointwise security controller by pointwise measurements for partial differential equation (PDE) systems under stochastic cyberattacks. First, according to the Takagi–Sugeno fuzzy model, the considered nonlinear system is reconstructed and an event-triggered pointwise fuzzy controller is proposed with pointwise measurements. Moreover, networked control systems are introduced to improve the transmission convenience; however, two deception cyberattacks with different characteristics are brought into PDE systems for the first time. In addition, based on novel Lyapunov–Krasovskii functionals, some relaxed conditions to assure system’s exponential stability are established. Finally, the effectiveness and practicability of the designed controller are demonstrated by numerical and application examples. [ABSTRACT FROM AUTHOR]