scholarly journals Quantum eigenlogic observables applied to the study of fuzzy behaviour of Braitenberg vehicle quantum robots

Kybernetes ◽  
2019 ◽  
Vol 48 (10) ◽  
pp. 2307-2324 ◽  
Author(s):  
Zeno Toffano ◽  
François Dubois
Keyword(s):  
Fuzzy Logic ◽  
Quantum Control ◽  
Measurement Theory ◽  
Mathematical Formulation ◽  
Quantum Probability ◽  
Fuzzy Membership Function ◽  
Projection Operators ◽  
Logical Connective ◽  
Content Type ◽  
Braitenberg Vehicle

Purpose The purpose of this paper is to apply the quantum “eigenlogic” formulation to behavioural analysis. Agents, represented by Braitenberg vehicles, are investigated in the context of the quantum robot paradigm. The agents are processed through quantum logical gates with fuzzy and multivalued inputs; this permits to enlarge the behavioural possibilities and the associated decisions for these simple vehicles. Design/methodology/approach In eigenlogic, the eigenvalues of the observables are the truth values and the associated eigenvectors are the logical interpretations of the propositional system. Logical observables belong to families of commuting observables for binary logic and many-valued logic. By extension, a fuzzy logic interpretation is proposed by using vectors outside the eigensystem of the logical connective observables. The fuzzy membership function is calculated by the quantum mean value (Born rule) of the logical projection operators and is associated to a quantum probability. The methodology of this paper is based on quantum measurement theory. Findings Fuzziness arises naturally when considering systems described by state vectors not in the considered logical eigensystem. These states correspond to incompatible and complementary systems outside the realm of classical logic. Considering these states allows the detection of new Braitenberg vehicle behaviours related to identified emotions; these are linked to quantum-like effects. Research limitations/implications The method does not deal at this stage with first-order logic and is limited to different families of commuting logical observables. An extension to families of logical non-commuting operators associated to predicate quantifiers could profit of the “quantum advantage” due to effects such as superposition, parallelism, non-commutativity and entanglement. This direction of research has a variety of applications, including robotics. Practical implications The goal of this research is to show the multiplicity of behaviours obtained by using fuzzy logic along with quantum logical gates in the control of simple Braitenberg vehicle agents. By changing and combining different quantum control gates, one can tune small changes in the vehicle’s behaviour and hence get specific features around the main basic robot’s emotions. Originality/value New mathematical formulation for propositional logic based on linear algebra. This methodology demonstrates the potentiality of this formalism for behavioural agent models (quantum robots).

scholarly journals Adapting Logic to Physics: The Quantum-Like Eigenlogic Program

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 139 ◽  
Author(s):  
Zeno Toffano ◽  
François Dubois
Keyword(s):  
Information Technologies ◽  
Logical Truth ◽  
Quantum Probability ◽  
Combinatory Logic ◽  
Fuzzy Membership Function ◽  
Projection Operators ◽  
Logical Operators ◽  
Binary Alphabet ◽  
Fast Development ◽  
Logical Semantics

Considering links between logic and physics is important because of the fast development of quantum information technologies in our everyday life. This paper discusses a new method in logic inspired from quantum theory using operators, named Eigenlogic. It expresses logical propositions using linear algebra. Logical functions are represented by operators and logical truth tables correspond to the eigenvalue structure. It extends the possibilities of classical logic by changing the semantics from the Boolean binary alphabet { 0 , 1 } using projection operators to the binary alphabet { + 1 , − 1 } employing reversible involution operators. Also, many-valued logical operators are synthesized, for whatever alphabet, using operator methods based on Lagrange interpolation and on the Cayley–Hamilton theorem. Considering a superposition of logical input states one gets a fuzzy logic representation where the fuzzy membership function is the quantum probability given by the Born rule. Historical parallels from Boole, Post, Poincaré and Combinatory Logic are presented in relation to probability theory, non-commutative quaternion algebra and Turing machines. An extension to first order logic is proposed inspired by Grover’s algorithm. Eigenlogic is essentially a logic of operators and its truth-table logical semantics is provided by the eigenvalue structure which is shown to be related to the universality of logical quantum gates, a fundamental role being played by non-commutativity and entanglement.

Measuring paper industry's ecological performance in an imprecise and vague scenario: a fuzzy DEA-based analytical framework

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sunil Kumar Jauhar ◽  
Natthan Singh ◽  
A. Rajeev ◽  
Millie Pant
Keyword(s):  
Fuzzy Logic ◽  
Paper Industry ◽  
Paper Mill ◽  
Analytical Framework ◽  
Efficiency Score ◽  
Comparative Performance ◽  
Content Type ◽  
Ecological Performance ◽  
Fuzzy Dea ◽  
Desirable And Undesirable Outputs

PurposeProductivity improvement is key to sustainability performance improvements of organizations. In a real-world scenario, the nature of inputs and outputs is likely to be imprecise and vague, leading to complexity in comparing firms' efficiency measurements. Implementation of fuzzy-logic based measurement systems is a method for dealing with such cases. This paper presents a fuzzy weight objective function to solve Data Envelopment Analysis (DEA) CCR model for measuring paper mills' performance in India for 15 years.Design/methodology/approachAn integrated methodology is proposed to solve DEA models having fuzzy weights. The fuzzy DEA methodology is an extended version of the DEA approach that researchers have used for performance measurement purposes in imprecise and vague scenarios. The ecological performance of the paper industry is evaluated, considering some desirable and undesirable outputs. The effect of non-discretionary input on the performance of a paper mill is also analyzed.FindingsAnalysis suggests that the productivity of the paper industry is improving consistently throughout the period. The comparative evaluation of methods suggests that a diverse cluster of DMUs and integration of DEA with the fuzzy logic increases the diversity in the efficiency score while DEA-DE imitates the results of CCR DEA.Originality/valueProposed a fuzzy DEA-based analytical framework for measuring the paper industry's ecological performance in an imprecise and vague scenario. The model is tested on data from the paper industry in a developing country context and comparative performance analysis using DEA, fuzzy DEA and DE algorithm is done.

Parameter identification for load frequency control using fuzzy FOPID in power system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ram Kumar ◽  
Afzal Sikander
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Parameter Identification ◽  
Fractional Order ◽  
Optimization Technique ◽  
Load Frequency Control ◽  
Control Law ◽  
Content Type ◽  
Load Frequency ◽  
Frequency Controller

Purpose This paper aims to suggest the parameter identification of load frequency controller in power system. Design/methodology/approach The suggested control approach is established using fuzzy logic to design a fractional order load frequency controller. A new suitable control law is developed using fuzzy logic, and based on this developed control law, the unknown parameters of the fractional order proportional integral derivative (FOPID) controller are derived using an optimization technique, which is being used by minimizing the integral square error. In addition, to confirm the effectiveness of the proposed control design approach, numerous simulation tests were carried out on an actual single-area power system. Findings The obtained results reveal the superiority of the suggested controller as compared to the recently developed controllers with regard to time response specifications and quantifiable indicators. Additionally, the potential of the suggested controller is also observed by improving the load disturbance rejections under plant parametric uncertainty. Originality/value To the best of the authors’ knowledge, the work is not published anywhere else.

scholarly journals Difficulty in implementing continuous improvement – Rasch measurement analysis

2019 ◽  
Vol 25 (6) ◽  
pp. 1228-1250 ◽  
Author(s):  
Lidia Sanchez-Ruiz ◽  
Beatriz Blanco ◽  
Emma Diaz
Keyword(s):  
Continuous Improvement ◽  
Measurement Theory ◽  
Reliability And Validity ◽  
Rasch Measurement ◽  
Point Of View ◽  
Future Research ◽  
Theoretical Point ◽  
Content Type ◽  
Level Of Difficulty ◽  
New Perspective

Purpose The purpose of this paper is to define a general and common construct in order to measure the level of difficulty companies experience when they implement continuous improvement (CI). Additionally, a rank of barriers is obtained together with a rank of companies. Design/methodology/approach In order to achieve the objective, first, a literature review is carried out to specify the domain of the construct; second, a sample of items is selected; third a survey is carried out in companies that have already implemented CI initiatives, the results being thus limited to this population; fourth, measures are purified by analysing the reliability and validity of the measurements, and finally results are obtained. The Rasch measurement theory will be used to provide a new perspective on a mature research topic. Findings It can be concluded that a new valid construct has been defined together with a rank of CI barriers, being lack of time the main barrier. A rank of companies is also obtained which is a first step in the development of future research studies. Practical implications Managers are provided with a better understanding of the barriers that can obstruct CI implementation. Thus, the rank of CI barriers guides managers through the most common and important obstacles so that they will be able to plan better CI strategies. In addition, the rank of companies allows each company to undertake a benchmarking exercise. Originality/value This work proposes a new way of analysing the difficulty in implementing CI as a continuum, rather than as independent barriers. From a theoretical point of view, it defines a new construct and offers a rank of CI barriers together with a rank of companies based on their level of difficulty when implementing CI initiatives. This is something new, as previous studies were mainly focussed on the items side. From a practical point of view, this study offers the surveyed companies the opportunity to see how they are positioned with respect to the other companies. Moreover, this rank of companies is the foundation on which to develop further studies with a practical orientation in the future.

Performance improvement of direct torque control for induction motor drive via fuzzy logic-feedback linearization

2019 ◽  
Vol 38 (2) ◽  
pp. 672-692 ◽  
Author(s):  
Abdelkarim Ammar
Keyword(s):  
Fuzzy Logic ◽  
Robust Control ◽  
Feedback Linearization ◽  
Control Algorithm ◽  
Direct Torque Control ◽  
Torque Control ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Content Type ◽  
Control Approach

Purpose This paper aims to propose an improved direct torque control (DTC) for the induction motor’s performance enhancement using dual nonlinear techniques. The exact feedback linearization is implemented to create a linear decoupled control. Besides, the fuzzy logic control approach has been inserted to generate the auxiliary control input for the feedback linearization controller. Design/methodology/approach To improve the DTC for induction motor drive, this work suggests the incorporation of two nonlinear approaches. As the classical feedback linearization suffers while the presence of uncertainties and modeling inaccuracy, it is recommended to be associated to another robust control approach to compensate the uncertainties of the model and make a robust control versus the variations of the machine parameters. Therefore, fuzzy logic controllers will be integrated as auxiliary inputs to the feedback linearization control law. Findings The simulation and the experimental validation of the proposed control algorithm show that the association of dual techniques can effectively achieve high dynamic behavior and improve the robustness against parameters variation and external disturbances. Moreover, the space vector modulation is used to preserve a fixed switching frequency, reduce ripples and low switching losses. Practical implications The theoretical, simulation and experimental studies prove that the proposed control algorithm can be used on different AC machines for variable speed drive applications such as oil drilling, traction systems and wind energy conversion systems. Originality/value The proposed DTC strategy has been developed theoretically and realized through simulation and experimental implementation. Different operation conditions have been conducted to check the ability and robustness of the control strategy, such as steady state, speed reversal maneuver, low-speed operation and parameters variation test with load application.

Obstacle avoidance and path planning of humanoid robot using fuzzy logic controller aided owl search algorithm in complicated workspaces

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abhishek Kumar Kashyap ◽  
Dayal R. Parhi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Search Algorithm ◽  
Optimal Path ◽  
Humanoid Robots ◽  
Steering Angle ◽  
Content Type ◽  
Hybrid Controller ◽  
Humanoid Nao

Purpose This paper aims to outline and implement a novel hybrid controller in humanoid robots to map an optimal path. The hybrid controller is designed using the Owl search algorithm (OSA) and Fuzzy logic. Design/methodology/approach The optimum steering angle (OS) is used to deal with the obstacle located in the workspace, which is the output of the hybrid OSA Fuzzy controller. It is obtained by feeding OSA's output, i.e. intermediate steering angle (IS), in fuzzy logic. It is obtained by supplying the distance of obstacles from all directions and target distance from the robot's present location. Findings The present research is based on the navigation of humanoid NAO in complicated workspaces. Therefore, various simulations are performed in a 3D simulator in different complicated workspaces. The validation of their outcomes is done using the various experiments in similar workspaces using the proposed controller. The comparison between their outcomes demonstrates an acceptable correlation. Ultimately, evaluating the proposed controller with another existing navigation approach indicates a significant improvement in performance. Originality/value A new framework is developed to guide humanoid NAO in complicated workspaces, which is hardly seen in the available literature. Inspection in simulation and experimental workspaces verifies the robustness of the designed navigational controller. Considering minimum error ranges and near collaboration, the findings from both frameworks are evaluated against each other in respect of specified navigational variables. Finally, concerning other present approaches, the designed controller is also examined, and major modifications in efficiency have been reported.

Fuzzy Logic-Based Inference Systems

2015 ◽  
pp. 209-239
Keyword(s):  
Fuzzy Logic ◽  
Knowledge Representation ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Mathematical Formulation ◽  
Cognitive Map ◽  
Fuzzy Cognitive Map ◽  
Adaptive Networks ◽  
Inference System ◽  
Inference Systems

This chapter presents the mathematical formulation of the fuzzy logic-based inference systems, used as means to infer about the response of ill-conditioned systems, based on the field knowledge representation in the fuzzy world. Particular approaches are explored, e.g., Fuzzy Inference System (FIS), Adaptive Networks-based FIS (ANFIS), Intuitionistic FIS (IFIS) and Fuzzy Cognitive Map (FCM), surfacing their potentialities in modeling applications, such as those in the field of learning, examined in the chapters of Part III that follow.

Path optimization for navigation of a humanoid robot using hybridized fuzzy-genetic algorithm

2019 ◽  
Vol 7 (3) ◽  
pp. 112-119 ◽  
Author(s):  
Asita Kumar Rath ◽  
Dayal R. Parhi ◽  
Harish Chandra Das ◽  
Priyadarshi Biplab Kumar ◽  
Manoj Kumar Muni ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Path Planning ◽  
Humanoid Robot ◽  
Fuzzy Logic Controller ◽  
Target Location ◽  
Target Position ◽  
Content Type ◽  
Hybrid Controller ◽  
Fuzzy Genetic

Purpose Humanoids have become the center of attraction for many researchers dealing with robotics investigations by their ability to replace human efforts in critical interventions. As a result, navigation and path planning has emerged as one of the most promising area of research for humanoid models. In this paper, a fuzzy logic controller hybridized with genetic algorithm (GA) has been proposed for path planning of a humanoid robot to avoid obstacles present in a cluttered environment and reach the target location successfully. The paper aims to discuss these issues. Design/methodology/approach Here, sensor outputs for nearest obstacle distances and bearing angle of the humanoid are first fed as inputs to the fuzzy logic controller, and first turning angle (TA) is obtained as an intermediate output. In the second step, the first TA derived from the fuzzy logic controller is again supplied to the GA controller along with other inputs and second TA is obtained as the final output. The developed hybrid controller has been tested in a V-REP simulation platform, and the simulation results are verified in an experimental setup. Findings By implementation of the proposed hybrid controller, the humanoid has reached its defined target position successfully by avoiding the obstacles present in the arena both in simulation and experimental platforms. The results obtained from simulation and experimental platforms are compared in terms of path length and time taken with each other, and close agreements have been observed with minimal percentage of errors. Originality/value Humanoids are considered more efficient than their wheeled robotic forms by their ability to mimic human behavior. The current research deals with the development of a novel hybrid controller considering fuzzy logic and GA for navigational analysis of a humanoid robot. The developed control scheme has been tested in both simulation and real-time environments and proper agreements have been found between the results obtained from them. The proposed approach can also be applied to other humanoid forms and the technique can serve as a pioneer art in humanoid navigation.

Minimum carbon dioxide emission based selection of traffic route with unsignalised junctions in tandem network

2019 ◽  
Vol 30 (3) ◽  
pp. 657-675 ◽  
Author(s):  
Anand Jaiswal ◽  
Cherian Samuel ◽  
Chirag Chandan Mishra
Keyword(s):  
Carbon Dioxide ◽  
Queuing Theory ◽  
Mathematical Formulation ◽  
Carbon Dioxide Emission ◽  
Arrival Rate ◽  
Selection Strategy ◽  
Service Rate ◽  
Content Type ◽  
Fuel Consumption Rate ◽  
Route Choices

Purpose The purpose of this paper is to provide a traffic route selection strategy based on minimum carbon dioxide (CO2) emission by vehicles over different route choices. Design/methodology/approach The study used queuing theory for Markovian M/M/1 model over the road junctions to assess total time spent over each of the junctions for a route with junctions in tandem. With parameters of distance, mean service rate at the junction, the number of junctions and fuel consumption rate, which is a function of variable average speed, the CO2 emission is estimated over each of the junction in tandem and collectively over each of the routes. Findings The outcome of the study is a mathematical formulation, using queuing theory to estimate CO2 emissions over different route choices. Research finding estimated total time spent and subsequent CO2 emission for mean arrival rates of vehicles at junctions in tandem. The model is validated with a pilot study, and the result shows the best vehicular route choice with minimum CO2 emissions. Research limitations/implications Proposed study is limited to M/M/1 model at each of the junction, with no defection of vehicles. The study is also limited to a constant mean arrival rate at each of the junction. Practical implications The work can be used to define strategies to route vehicles on different route choices to reduce minimum vehicular CO2 emissions. Originality/value Proposed work gives a solution for minimising carbon emission over routes with unsignalised junctions in the tandem network.

A practical review and taxonomy of fuzzy expert systems: methods and applications

2019 ◽  
Vol 27 (1) ◽  
pp. 81-136 ◽  
Author(s):  
Madjid Tavana ◽  
Vahid Hajipour
Keyword(s):  
Fuzzy Logic ◽  
Conference Proceedings ◽  
Expert Systems ◽  
Future Research ◽  
Specific Domain ◽  
Comprehensive Review ◽  
Content Type ◽  
Fuzzy Expert Systems ◽  
Journal Publications ◽  
Inference Systems

Purpose Expert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems. Design/methodology/approach The authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems. Findings The authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field. Originality/value Fuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.

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