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.

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.

Stable fuzzy controllers via LMI approach for non-linear systems described by type-2 T-S fuzzy model

Purpose-The purpose of this paper is to stabilize the type-2 Takagi-Sugeno(T-S)fuzzy systems with the sufficient and guaranteed stability conditions.The given conditions efficaciously handle parameter uncertainties by the upper and lower membership functions of the type-2 fuzzy sets(FSs).Design/methodology/approach-This paper reports on a relevant study of stable fuzzy controllers and type-2 T-S fuzzy systems and reported that the synthesis of controller for nonlinear systems described by the type-2 T-S fuzzy model is a key problem and it can be resolve to convex problems via linear matrix inequalities(LMIs).Findings-The multigain fuzzy controllers are established to improve the solvability of the stability conditions,and the authors design multigain fuzzy controllers which have extensive information of upper and lower membership grades.Consequently,the authors derive the traditional stability condition in terms of LMIs.One simulation examples illustrate the effectiveness and robustness of the derived stabilization conditions.Originality/value-The uncertain MIMO nonlinear system described by Type-2 Takagi-Sugeno(T-S)fuzzy model,and successively LMI approach used to determine the system stability conditions.The proposed control approach will give superior fault-tolerant control permanence under the actuator fault[partial loss of effectiveness(LOE)].Also the controller robust against the unmeasurable process disturbances.Additionally,the statistical z-test are carried out to validate the proposed control approach against the control approach proposed by Himanshukumar and Vipul(2019a).

A novel design of optimal intelligent fuzzy TID controller employing GA for nonlinear level control problem subject to actuator and system component fault

Purpose–The purpose of this article is about the design of controllers for conical two-tank noninteracting level(CTTNL)system in simulation.Local linearization around the equilibrium point has been done for the nonlinear CTTNL system to obtain a linearized model transfer function.Design/methodology/approach–This article deals with the design of novel optimal fractional-order tiltintegral-derivative(TID)controller using type-1 fuzzy set for the CTTNL prototype system.In this study,type-1 fuzzy TID controller parameters have been optimized through genetic algorithm(GA)and those set of values have been employed for the design of proportional-integral-derivative(PID)controller.Findings–A performance comparison between FTID and PID controller is then investigated.The analysis shows the superiority of FTID controller over PID controller in terms of integral absolute error(IAE),integral square error(ISE),integral of time multiplied absolute error(ITAE)and integral of time multiplied squared error(ITSE)integral errors.The transient and steady state performance of the FTID controller are superior as compared to conventional PID controller.In future,the FTID controller fault-tolerance capability tested on CTTNL system subject to actuator and system component(leak)faults.The detailed study of robustness in presence of model uncertainties will be incorporated as a scope of further research.Originality/value–A performance comparison between FTID and PID controller is then investigated.The analysis shows the superiority of FTID controller over PID controller in terms of IAE,ISE,ITAE and ITSE integral errors.Additionally,fault-tolerant performance of the proposed controller evaluated with fault-recovery time(F_(rt))parameter.The transient and steady state performance of the FTID controller are superior as compared to conventional PID controller.