Implementation of Fuzzy Sugeno Method for Power Efficiency

Energy is one of the basic needs for human being. One of the most vital energy sources is electricity. Electricity is a type of energy that sustains survival of human being, more particularly in industrial sector. Efficiency in industrial sector refers to a state where electricity is used to as little as possible to produce the same amount of product. The case study was conducted in marine commodity sector, anchovy and jellyfish supplier. The supplier was classified as SME that installed 33,000 VA electric powers (B2). The data were in the form of energy consumption intensity (ECI) and specific energy consumption (SEC) to determine the energy efficiency level. The objective of the study was to classify the efficiency level of electricity consumption using Sugeno Fuzzy method. The findings of the study were 1) the average ECI between January, 2016 and April, 2017 was 1,949 kWh/m2; it was classified as efficient; 2) the average SEC at the same period was 126,108 kWh/ton; it was classified as excessive. Sugeno Fuzzy logic was implemented to determine efficiency level of electricity in this company. Based on the average ECI and SEC, the electricity consumption of the company was categorized as excessive with FIS Sugeno output of 0.803

Design of a Memristor-based Chattering Free Sliding Mode Controller and Speed Control of the BLDC Motor

In this study, a memristor-based sliding mode controller (Mem-SMC) was designed for speed control of BLDC motor and the performance of the controller was tested in simulation. The sliding mode controller, known for its robustness against disturbances and parameter variations, was designed with a memristor known as a missing circuit element. Simulation results show that the proposed controller is successful in the speed reference tracking and is also able to respond quickly to sudden changes in the reference

Designing the Model Predictive Control for Interval Type-2 Fuzzy T-S Systems Involving Unknown Time-Varying Delay in Both States and Input Vector

In this paper, the model predictive control is designed for an interval type-2 Takagi-Sugeno (T-S) system with unknown time-varying delay in state and input vectors. The time-varying delay is a weird phenomenon that is appeared in almost all systems. It can make many problems and instability while the system is working. In this paper, the time-varying delay is considered in both states and input vectors and is the sensible difference between the proposed method here and previous algorithms, besides, it is unknown but bounded. To solve the problem, the Razumikhin approach is applied to the proposed method since it includes a Lyapunov function with the original nonaugmented state space of system models compared to Krasovskii formula. On the other hand, the Razumikhin method act better and avoids the inherent complexity of the Krasovskii specifically when large delays and disturbances are appeared. To stabilize output results, the model predictive control (MPC) is designed for the system and the considered system in this paper is interval type-2 (IT2) fuzzy T-S that has better estimation of the dynamic model of the system. Here, online optimization problems are solved by the linear matrix inequalities (LMIs) which reduce the burdens of the computation and online computational costs compared to the offline and non-LMI approach. At the end, an example is illustrated for the proposed approach

Consensus of multi-agent systems with faults and mismatches under switched topologies using a delta operator method

© 2018 Elsevier B.V. This paper studies the consensus of multi-agent systems with faults and mismatches under switched topologies using a delta operator method. Since faults and mismatches can result in failure of the consensus even for a fixed topology with a spanning tree, how to reach a consensus is a complicated and challenging problem under such circumstances especially when part topologies have no spanning tree. Although some works studied the influence of faults and mismatches on the consensus, there is little work on reaching a consensus for the multi-agent systems with faults and mismatches. In this paper, we introduce the delta operator to unify the consensus analysis for continuous, discrete, or sampled systems under one framework. We develop the theories on the delta operator systems first and then apply theories of the delta operator systems to the consensus problems. By converting the consensus problems into stability problems, we investigate and prove consensus and the associated conditions for systems 1) without any fault, 2) with a known fault, and 3) with unknown faults, under switching topologies with matching or mismatching coefficients. Numerical examples are provided and validate the effectiveness of the theoretical results

Adaptive sliding mode control for Takagi-Sugeno fuzzy systems

This paper is devoted to robust adaptive sliding mode control for a class of nonlinear systems in the Takagi-Sugeno forms with mismatched parametric uncertainties. Sufficient conditions for the existence of linear sliding surfaces are given in terms of linear matrix inequalities, by which the corresponding adaptive reaching motion controller is also designed. Simulation studies show the effectiveness of the control scheme.Jinhui Zhang, Peng Shi, Yuanqing Xia and Mengyin F

Adaptive Sliding Mode Control for Takagi-Sugeno Fuzzy Systems and Its Applications

This paper investigates the problem of adaptive integral sliding mode control for general Takagi-Sugeno fuzzy systems with matched uncertainties and its applications. Different control input matrices are allowed in fuzzy systems. The matched uncertainty is modeled in a unified form, which can be handled by the adaptive methodology. A fuzzy integral-type sliding surface is utilized and the parameter matrices can be determined according to user\u27s requirement. Based on the designed sliding surface, a new sliding mode controller is proposed, and the structure of the controller depends on the difference between the disturbance input matrices and the control input matrices. It is shown that under the proposed sliding mode controller, the resulting closed-loop system can achieve the uniformly ultimate boundedness. Furthermore, simulation examples are presented to show the merit and applicability of the proposed fuzzy sliding mode control method