DESIGNING HEDGE ALGEBRAIC CONTROLLER AND OPTIMIZING BY GENETIC ALGORITHM FOR SERIAL ROBOTS ADHERING TRAJECTORIES

In recent years, the application of hedge algebras in the field of control has been studied. The results show that this approach has many advantages. In additions, industrial robots are being well-developed and extensively used, especially in the industrial revolution 4.0. Accurate control of industrial robots is a class of problems that many scientists are interested in. In this paper, we design a controller based on hedge algebra for serial robots. The control rule is given by linguistic rule base system. The goal is to accurately control the moving robot arm which adheres given trajectories. Optimization of fuzzy parameters for the controller is done by genetic algorithms. The system has been simulated on the Matlab-Simulink software. The simulation results show that the orbital deviation is very small. Moreover, the controller worked well with correct control quality. This result once presents the simplicity and efficiency of the hedge algebras approach to control

Active control of a three-story building using hedge-algebras-based fuzzy controller

In this paper, conventional and hedge-algebras-based fuzzy controllers, respectively denoted by FC and HAFC, are designed to suppress vibrations of a three-story building against earthquake. The structural system is simulated against the ground accelerations of the El Centro earthquake in USA on May 18th, 1940; the Northridge earthquake in USA on January 17th, 1994 and the Kobe earthquake in Japan on January 16th, 1995. The control effects of FC and HAFC are compared via the time history of the story displacements of the structure

HEDGE-ALGEBRAS-BASED FUZZY CONTROLLER: APPLICATION TO ACTIVE CONTROL OF A FIFTEEN-STORY BUILDING AGAINST EARTHQUAKE

Active control problem of seism-excited civil structures has attracted considerable attention in recent years. In this paper, conventional, hedge-algebras-based and optimal hedge-algebras-based fuzzy controllers, respectively denoted by FC, HAFC and OHAFC, are designed to suppress vibrations of a structure with active tuned mass damper (ATMD) against earthquake. The interested structure is a high-rise building modeled as a fifteen-degree-of-freedom structure system with two type of actuators installed on the first storey and fifteenth storey which has ATMD. The structural system is simulated against the ground accelerations, acting on the base, of the El Centro earthquake in USA on May 18th. The control effects of FC, HAFC and OHAFC are compared via the time history of the storey displacements of the structure

Actuator saturation control of a benchmark structure using hedge-algebras-based fuzzy controller

In this paper, the problem of actuator saturation control of a benchmark structure using hedge-algebras-based fuzzy controller (HAC) is presented. In HAC, linguistic values of linguistic terms are obtained through semantically quantifying mappings (SQMs) based on few fuzziness parameters of each linguistic variable without using any fuzzy set and inherent order relationships between linguistic values of each linguistic variable are always ensured. Hence, the design of a HAC leads to determining parameters of SQMs, which are fuzziness measures of primary terms and linguistic hedges occurring in a fuzzy model. As a case study, a HAC is designed to actuator saturation control of a benchmark structure with active bracing system (ABS) subjected to earthquake excitation. Control performance of the controller is also discussed in order to show advantages of the proposed method

HEDGE ALGEBRAS, THE SEMANTICS OF VAGUE LINGUISTIC INFORMATION AND APPLICATION PROSPECTIVE

The report aims to show that hedge algebras model actually the proper qualitative semantics of words of linguistic variables based on the argument that the inherent qualitative semantics of words should be expressed through the order relationships, induced by the word semantics, between the words in their respective variable domains, as required by decision making of human daily lives. This makes the hedge algebra based approach to the word semantics quite different from the existing approaches and become the only approach that can immediately deal with the natural qualitative semantics of words. We explain clearly and systematically distinguished features and properties of this approach to show that these seem to make the approach to be sound and ensure its effectiveness in applications. This approach seems to be promising for development of hedge algebra-based method to solve problems in various application fields. For illustration, we will give a short overview of effective results some of the initial applications of hedge algebras in the fields of knowledge based systems and in fuzzy control

CONTROL OF A PENDULUM USING HEDGE ALGEBRAS CONTAINING ACTUATOR SATURATION

In this study, the control problem of a pendulum using hedge-algebras-based fuzzy controller (HAC) containing actuator saturation is presented. In HAC, linguistic values of linguistic terms are obtained through semantically quantifying mappings (SQMs) based on several fuzzy parameters of each linguistic variable without using any fuzzy set and inherent order relationships between linguistic values are always ensured. Hence, the design of a HAC leads to determining parameters of SQMs. Numerical results of HAC are compared with those of an analogical conventional fuzzy controller (FC) in order to show advantages of the proposed method.In this study, the control problem of a pendulum using hedge-algebras-based fuzzy controller (HAC) containing actuator saturation is presented. In HAC, linguistic values of linguistic terms are obtained through semantically quantifying mappings (SQMs) based on several fuzzy parameters of each linguistic variable without using any fuzzy set and inherent order relationships between linguistic values are always ensured. Hence, the design of a HAC leads to determining parameters of SQMs. Numerical results of HAC are compared with those of an analogical conventional fuzzy controller (FC) in order to show advantages of the proposed method

A HEDGE ALGEBRAS BASED CLASSIFICATION REASONING METHOD WITH MULTI-GRANULARITY FUZZY PARTITIONING

During last years, lots of the fuzzy rule based classifier (FRBC) design methods have been proposed to improve the classification accuracy and the interpretability of the proposed classification models. Most of them are based on the fuzzy set theory approach in such a way that the fuzzy classification rules are generated from the grid partitions combined with the pre-designed fuzzy partitions using fuzzy sets. Some mechanisms are studied to automatically generate fuzzy partitions from data such as discretization, granular computing, etc. Even those, linguistic terms are intuitively assigned to fuzzy sets because there is no formalisms to link inherent semantics of linguistic terms to fuzzy sets. In view of that trend, genetic design methods of linguistic terms along with their (triangular and trapezoidal) fuzzy sets based semantics for FRBCs, using hedge algebras as the mathematical formalism, have been proposed. Those hedge algebras-based design methods utilize semantically quantifying mapping values of linguistic terms to generate their fuzzy sets based semantics so as to make use of fuzzy sets based-classification reasoning methods proposed in design methods based on fuzzy set theoretic approach for data classification. If there exists a classification reasoning method which bases merely on semantic parameters of hedge algebras, fuzzy sets-based semantics of the linguistic terms in fuzzy classification rule bases can be replaced by semantics - based hedge algebras. This paper presents a FRBC design method based on hedge algebras approach by introducing a hedge algebra- based classification reasoning method with multi-granularity fuzzy partitioning for data classification so that the semantic of linguistic terms in rule bases can be hedge algebras-based semantics. Experimental results over 17 real world datasets are compared to existing methods based on hedge algebras and the state-of-the-art fuzzy sets theoretic-based approaches, showing that the proposed FRBC in this paper is an effective classifier and produces good results

Optimal fuzzy control using hedge algebras of a damped elastic jointed inverted pendulum

In this paper, three controllers including OFCHA (optimal fuzzy control using hedge algebras-HAs), FCHA (fuzzy control using HAs) and CFC (conventional fuzzy control) are designed. Our attention is paid to the stability in the vertical position of a damped-elastic-jointed inverted pendulum subjected to a time-periodic follower force. Different values of the pendulum length are considered. Simulation results are exposed to illustrate the effect of OFCHA in comparison with FCHA and CFC

Cogitator : a parallel, fuzzy, database-driven expert system

The quest to build anthropomorphic machines has led researchers to focus on knowledge and the manipulation thereof. Recently, the expert system was proposed as a solution, working well in small, well understood domains. However these initial attempts highlighted the tedious process associated with building systems to display intelligence, the most notable being the Knowledge Acquisition Bottleneck. Attempts to circumvent this problem have led researchers to propose the use of machine learning databases as a source of knowledge. Attempts to utilise databases as sources of knowledge has led to the development Database-Driven Expert Systems. Furthermore, it has been ascertained that a requisite for intelligent systems is powerful computation. In response to these problems and proposals, a new type of database-driven expert system, Cogitator is proposed. It is shown to circumvent the Knowledge Acquisition Bottleneck and posess many other advantages over both traditional expert systems and connectionist systems, whilst having non-serious disadvantages.KMBT_22