Intrusion Detection Algorithm Based on Model Checking Interval Temporal Logic

Model checking based on linear temporal logic reduces the false negative rate of misuse detection.However,linear temporal logic formulae cannot be used to describe concurrent attacks and piecewise attacks.So there is still a high rate of false negatives in detecting these complex attack patterns.To solve this problem,we use interval temporal logic formulae to describe concurrent attacks and piecewise attacks.On this basis,we formalize a novel algorithm for intrusion detection based on model checking interval temporal logic.Compared with the method based on model checking linear temporal logic,the new algorithm can find unknown succinct attacks.The simulation results show that the new method can effectively reduce the false negative rate of concurrent attacks and piecewise attacks.

Nonsingular Terminal Sliding Mode Control With Ultra-Local Model and Single Input Interval Type-2 Fuzzy Logic Control for Pitch Control of Wind Turbines

As wind energy is becoming one of the fastestgrowing renewable energy resources,controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties.The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification.For this purpose,a novel model-independent nonsingular terminal slidingmode control(MINTSMC)using the basic principles of the ultralocal model(ULM)and combined with the single input interval type-2 fuzzy logic control(SIT2-FLC)is developed for non-linear wind turbine pitch angle control.In the suggested control framework,the MINTSMC scheme is designed to regulate the wind turbine speed rotor,and a sliding-mode(SM)observer is adopted to estimate the unknown phenomena of the ULM.The auxiliary SIT2-FLC is added in the model-independent control structure to improve the rotor speed regulation and compensate for the SM observation estimation error.Extensive examinations and comparative analyses were made using a real-time softwarein-the-loop(RT-SiL)based on the dSPACE 1202 board to appraise the efficiency and applicability of the suggested modelindependent scheme in a real-time testbed.

Timed automata for metric interval temporal logic formulae in prototype verification system

Based on analysis of the syntax structure and semantics model of the metric interval temporal logic （MITL） formulas, it is shown how to transform a formula written in the real-time temporal logic MITL formula into a fair timed automaton （TA） that recognizes its satisfying models with prototype verification system （PVS） in this paper. Both the tabular construction＇s principles and the PVS implementation details are given for the different type of MITL formula according to the corresponding semantics interpretations. After this transformation procedure, specifications expressed with MITL formula can be verified formally in the timed automata framework developed previously.

Fuzzy Interval Value Logic and Fuzzy Distributed Value Logic

In this paper, two kinds of fuzzy logic named “fuzzy intervalvalue logic” and “uzzy distributedvalue logic”with truth values in fuzzy intervals and probabilistic distribution functions are presented, respectively, and the syllogism (modus ponens) is given for each logic. It has been pointed out that they will have various applications in knowledgebased systems and other artificial intelligence fields.

Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm

The estimation of the fuzzy membership function parameters for interval type 2 fuzzy logic system(IT2-FLS)is a challenging task in the presence of uncertainty and imprecision.Grasshopper optimization algorithm(GOA)is a fresh population based meta-heuristic algorithm that mimics the swarming behavior of grasshoppers in nature,which has good convergence ability towards optima.The main objective of this paper is to apply GOA to estimate the optimal parameters of the Gaussian membership function in an IT2-FLS.The antecedent part parameters(Gaussian membership function parameters)are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm.Tuning of the consequent part parameters are accomplished using extreme learning machine.The optimized IT2-FLS(GOAIT2FELM)obtained the optimal premise parameters based on tuned consequent part parameters and is then applied on the Australian national electricity market data for the forecasting of electricity loads and prices.The forecasting performance of the proposed model is compared with other population-based optimized IT2-FLS including genetic algorithm and artificial bee colony optimization algorithm.Analysis of the performance,on the same data-sets,reveals that the proposed GOAIT2FELM could be a better approach for improving the accuracy of the IT2-FLS as compared to other variants of the optimized IT2-FLS.

Using a 3D Interval Type-2 Fuzzy Interpolation System to Improve Modeless Robots Measurement and Calibration Accuracy

This paper is an extended research for a novel technique used in the pose error compensations of the robot and manipulator calibration process based on an IT2FEI （interval type-2 fuzzy error interpolation） method. Robot calibrations can be classified into model-based and modeless methods. A model-based calibration method normally requires that the practitioners understand the kinematics of the robot therefore may pose a challenger for field engineers. An alternative yet effective means for robot calibration is to use a modeless method; however with such a method there is a conflict between the calibration accuracy of the robot and the number of grid points used in the calibration task. In this paper, an interval type-2 fuzzy interpolation system is applied to improve the compensation accuracy of the robot in its 3D workspace. An on-line type-2 fuzzy inference system is implemented to meet the needs of on-line robot trajectory planning and control. The simulated results given in this paper show that not only robot compensation accuracy can be greatly improved, but also the calibration process can be significantly simplified, and it is more suitable for practical applications.

Interval type-2 fuzzy logic based radar task priority assignment method for detecting hypersonic-glide vehicles

A radar task priority assignment method based on interval type-2 fuzzy logic system(IT2 FLS)was designed to solve the problem of resource management for phased-array radar to detect hypersonic-glide vehicles(HGVs).The mathematical model of the radar task and the motion and detection models of HGVs are described in detail.The target threat of an HGV is divided into maneuver,speed,azimuth,and distance threats.In the radar task priority assignment method based on IT2 FLS,the maneuver factor,speed,azimuth difference,distance,and initial priority are input variables.The radar task priority is the output variable.To reduce the number of fuzzy rules and avoid rule explosion,an IT2 FLS with a hierarchical structure was designed.Finally,the feasibility of the task priority assignment method was verified by simulations.Simulation results showed that the method based on IT2 FLS has a higher precise tracking rate,mean initial priority,and target threat degree,and a shorter offset time.

Detection and classification of multiple power signal patterns with Volterra series and interval type-2 fuzzy logic system

The paper deals with the application of Volterra bound Interval type−2 fuzzy logic techniques in power quality assessment.This work proposes a new layout for detection,localization and classification of various types of power quality events.The proposed method exploits Volterra series for the extraction of relevant features,which are used to recognize different PQ events by Interval type-2 fuzzy logic based classifier.Numerous single as well as multiple powers signal disturbances have been simulated to testify the efficiency of the proposed technique.This time–frequency analysis results in the clear visual detection,localization,and classification of the different power quality events.The simulation results signify that the proposed scheme has a higher recognition rate while classifying single and multiple power quality events unlike other methods.Finally,the proposed method is compared with SVM,feed forward neural network and type−1 Fuzzy logic system based classifier to show the efficacy of the proposed technique in classifying the Power quality events.

An interval type-2 fuzzy logic controller for TCSC to improve the damping of power system oscillations

In this paper an interval type-2 fuzzy logic controller （IT2FLC） was proposed for thyristor controlled series capacitor （TCSC） to improve power system damping. For controller design, memberships of system variables were represented using interval type-2 fuzzy sets. The three-dimensional membership function of type-2 fuzzy sets provided additional degree of freedom that made it possible to directly model and handle uncertainties. Simulations conducted on a single machine infinite bus （SMIB） power system showed that the proposed controller was more effective than particle swarm optimization （PSO） tuned and type-1 fuzzy logic （T1FL） based damping controllers. Robust performance of the proposed controller was also validated at different operating conditions, various disturbances and parameter variation of the transmission line parameters.

Type-2 fuzzy logic applications designed for active parameter adaptation in metaheuristic algorithm for fuzzy fault-tolerant controller

Purpose-In recent times,fuzzy logic is gaining more and more attention,and this is because of the capability of understanding the functioning of the system as per human knowledge-based system.The main contribution of the work is dynamically adapting the important parameters throughout the execution of the flower pollination algorithm(FPA)using concepts of fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.Design/methodology/approach-The fuzzy logic-based parameter adaptation in the FPA is proposed.In addition,type2 fuzzy logic is used to design fuzzy inference system for dynamic parameter adaptation in metaheuristics,which can help in eliminating uncertainty and hence offers an attractive improvement in dynamic parameter adaption in metaheuristic method,and,in reality,the effectiveness of the interval type2 fuzzy inference system(IT2 FIS)has shown to provide improved results as matched to type-1 fuzzy inference system(T1 FIS)in some latest work.Findings-One case study is considered for testing the proposed approach in a fault tolerant control problem without faults and with partial loss of effectiveness of main actuator fault with abrupt and incipient nature.For comparison between the type-1 fuzzy FPA and interval type-2 fuzzy FPA is presented using statitical analysis which validates the advantages of the interval type2 fuzzy FPA.The statistical Z-test is presented for comparison of efficiency between two fuzzy variants of the FPA optimization method.Originality/value-The main contribution of the work is a dynamical adaptation of the important parameters throughout the execution of the flower pollination optimization algorithm using concepts of type2 fuzzy logic.By adapting the main parameters of the metaheuristics,the performance and accuracy of the metaheuristic have been improving in a varied range of applications.

A survey on temporal logics for specifying and verifying real-time systems

Over the last two decades, there has been an extensive study of logical formalisms on specifying and verifying real-time systems. Temporal logics have been an important research subject within this direction. Although numerous logics have been introduced for formal specification of real-time and complex systems, an up to date survey of these logics does not exist in the literature. In this paper we analyse various temporal formalisms introduced for specification, including propositional/first-order linear temporal logics, branching temporal logics, interval temporal logics, real-time temporal logics and probabilistic temporal logics. We give decidability, axiomatizability, expressiveness, model checking results for each logic analysed. We also provide a comparison of features of the temporal logics discussed.

Application of metaheuristic algorithms in interval type-2 fractional order fuzzy TID controller for nonlinear level control process under actuator and system component faults

Purpose–The two-tank level control system is one of the real-world’s second-order system(SOS)widely used as the process control in industries.It is normally operated under the Proportional integral and derivative(PID)feedback control loop.The conventional PID controller performance degrades significantly in the existence of modeling uncertainty,faults and process disturbances.To overcome these limitations,the paper suggests an interval type-2 fuzzy logic based Tilt-Integral-Derivative Controller(IT2TID)which is modified structure of PID controller.Design/methodology/approach–In this paper,an optimization IT2TID controller design for the conical,noninteracting level control system is presented.Regarding to modern optimization context,the flower pollination algorithm(FPA),among the most coherent population-based metaheuristic optimization techniques is applied to search for the appropriate IT2FTID’s and IT2FPID’s parameters.The proposed FPA-based IT2FTID/IT2FPID design framework is considered as the constrained optimization problem.System responses obtained by the IT2FTID controller designed by the FPA will be differentiated with those acquired by the IT2FPID controller also designed by the FPA.Findings–As the results,it was found that the IT2FTID can provide the very satisfactory tracking and regulating responses of the conical two-tank noninteracting level control system superior as compared to IT2FPID significantly under the actuator and system component faults.Additionally,statistical Z-test carried out for both the controllers and an effectiveness of the proposed IT2FTID controller is proven as compared to IT2FPID and existing passive fault tolerant controller in recent literature.Originality/value–Application of new metaheuristic algorithm to optimize interval type-2 fractional order TID controller for nonlinear level control system with two type of faults.Also,proposed method will compare with other method and statistical analysis will be presented.

Balanced scorecard-based analysis of customer expectations for cosmetology services:a hybrid decision modeling approach

The goal of this study is to analyze and characterize customer expectations in the cosmetics sector.Within this framework,first,the extant literature is reviewed,and 12 most prominent performance measurement criteria are identified.Then,these criteria are organized along the four different balanced scorecard dimensions.By employing an Interval Type-2 Fuzzy DEMATEL methodology,the weighted importance of these dimensions and criteria are identified.Additionally,with the Interval Type-2 Fuzzy TOPSIS approach,13 leading cosmetic service providers in Ukraine are ranked based on their relative scores.The findings of the study indicate that consumer is the most significant dimension while learning and growth seem to have the least importance.Similarly,it is also concluded that all consumerfocused criteria(i.e.diversification of services,feedback on the product and services,and customer loyalty)have the highest priorities in the complete criterion set.

Completeness of the Accumulation Calculus

The accumulation calculus (AC for short) is an interval based temporal logic to specify and reason about hybrid real-time systems. This paper presents a formal proof system for AC, and proves that the system is complete relative to that of Interval Temporal Logic (ITL for short) on real domain.