{"title":"On Fuzzy Mapping and Control","authors":"Sheldon S. L. Chang, L. Zadeh","doi":"10.1109/TSMC.1972.5408553","DOIUrl":"https://doi.org/10.1109/TSMC.1972.5408553","url":null,"abstract":"A fuzzy mapping from X to Y is a fuzzy set on X × Y. The concept is extended to fuzzy mappings of fuzzy sets on X to Y, fuzzy function and its inverse, fuzzy parametric functions, fuzzy observation, and control. Set theoretical relations are obtained for fuzzy mappings, fuzzy functions, and fuzzy parametric functions. It is shown that under certain conditions a precise control goal can be attained with fuzzy observation and control as long as the observations become sufficiently precise when the goal is approached.","PeriodicalId":79994,"journal":{"name":"IEEE transactions on systems, man, and cybernetics","volume":"12 1","pages":"30-34"},"PeriodicalIF":0.0,"publicationDate":"1996-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74756704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiobjective heuristic search in AND/OR graphs","authors":"Ching-Fang Liaw, B. Stewart, C. White","doi":"10.1109/21.467717","DOIUrl":"https://doi.org/10.1109/21.467717","url":null,"abstract":"Develops and analyzes a heuristic search algorithm that determines the nondominated set of solution graphs for a multiobjective AND/OR graph. This algorithm, MOAO*, is a multiobjective generalization of AO*. MOAO* uses sets of vector-valued heuristic estimates to give guidance to the search. The authors show that MOAO* satisfies termination, completeness, and admissibility conditions, generalizing results associated with AO*. Further, the authors prove that if the heuristic sets satisfy a monotonicity condition, then MOAO* possesses an efficiency property reminiscent of a well-known result associated with A*. >","PeriodicalId":79994,"journal":{"name":"IEEE transactions on systems, man, and cybernetics","volume":"23 1","pages":"1513-1521"},"PeriodicalIF":0.0,"publicationDate":"1995-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74790202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automated fault detection and accommodation: a learning systems approach","authors":"M. Polycarpou, A. Helmicki","doi":"10.1109/21.467710","DOIUrl":"https://doi.org/10.1109/21.467710","url":null,"abstract":"The detection, diagnosis, and accommodation of system failures or degradations are becoming increasingly more important in modern engineering problems. A system failure often causes changes in critical system parameters, or even, changes in the nonlinear dynamics of the system. This paper presents a general framework for constructing automated fault diagnosis and accommodation architectures using on-line approximators and adaptation/learning schemes. In this framework, neural network models constitute an important class of on-line approximators. Changes in the system dynamics are monitored by an on-line approximation model, which is used not only for detecting but also for accommodating failures. A systematic procedure for constructing nonlinear estimation algorithms is developed, and a stable learning scheme is derived using Lyapunov theory. Simulation studies are used to illustrate the results and to gain intuition into the selection of design parameters. >","PeriodicalId":79994,"journal":{"name":"IEEE transactions on systems, man, and cybernetics","volume":"18 1","pages":"1447-1458"},"PeriodicalIF":0.0,"publicationDate":"1995-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75424076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A framework for on-line learning of plant models and control policies for restructurable control","authors":"S. Reveliotis, M. Kokar","doi":"10.1109/21.467715","DOIUrl":"https://doi.org/10.1109/21.467715","url":null,"abstract":"In this paper a learning framework to deal with restructurable control of a single-output dynamic plant is proposed. The central concept used to represent the restructurable behavior of the plant, and subsequently for the design of the framework, is the behavioral graph. The nodes of this graph correspond to possible local behaviors of the system while its edges model the switching scheme of the plant among its local behaviors. In the definition of this concept, general dynamical system theory is used. The framework is able to learn the dynamics (models) of a reconfigurable system, select appropriate models, and ultimately control the plant according to given specifications. The framework design borrows concepts and techniques from the active fields of adaptive and learning control. The underlying ideas and the software prototype implementing the framework design are tested through a series of simulated experiments. The simulations demonstrate the feasibility of the approach for controlling plants with unexpectedly and structurally changing behaviors in moderately noisy environments. They also identify a number of constraints that have to be satisfied for successful operation of the framework. This paper also discusses further validation of the approach, real-time application issues, and potential enhancements of the framework's functionality. >","PeriodicalId":79994,"journal":{"name":"IEEE transactions on systems, man, and cybernetics","volume":"94 1","pages":"1502-1512"},"PeriodicalIF":0.0,"publicationDate":"1995-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81243830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Image restoration using recursive estimators","authors":"Yagnesh C. Trivedi, L. Kurz","doi":"10.1109/21.467712","DOIUrl":"https://doi.org/10.1109/21.467712","url":null,"abstract":"In this paper, edge preserving recursive estimators are proposed For restoring images corrupted by noise. Edge detection using a 5/spl times/5 Graeco-Latin squares (GLS) mask is carried out as the first step for preserving edges. The GLS mask preprocessor determines the orientation of edges in horizontal, vertical, 45/spl deg/ diagonal, or 135/spl deg/ diagonal directions. The actual removal of noise is done in the second step. If the noise is Gaussian, the center pixel in the 5/spl times/5 mask is estimated using a multiple linear regression model fitted to the noisy image on the same side of the edge. The parameters of the regression model are estimated using the least squares estimator. The least squares estimator is made recursive using the Robbins-Monro stochastic approximation (RMSA) algorithm. The RMSA guarantees convergence of the estimate in the mean square sense and with probability one. If the Gaussian noise is contaminated by a small percentage of heavy tailed (impulsive) noise (salt and pepper noise), the recursive least square estimator is robustized using a symmetrical version of Wilcoxon signed rank statistic. The GLS mask for edge detection uses an F-ratio test which is robust for small deviations from normality assumption of the noise. The mathematical properties and various forms of convergence of the robustized algorithm are shown in the appendix. The efficacy of the proposed restoration procedures are demonstrated on two types of images (\"girl\" and \"house\"). >","PeriodicalId":79994,"journal":{"name":"IEEE transactions on systems, man, and cybernetics","volume":"80 1","pages":"1470-1482"},"PeriodicalIF":0.0,"publicationDate":"1995-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82729419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simple direction-dependent rhythmic movements and partial somesthesis of a marionette","authors":"H. Hemami, J. A. Dinneen","doi":"10.1109/21.467714","DOIUrl":"https://doi.org/10.1109/21.467714","url":null,"abstract":"The simple rhythmic movements of a multi-link sagittal marionette with many muscle-like actuators are considered in this paper. The marionette is standing on the ground, and contact with surrounding objects is not permitted. Every actuator has two inputs: a firing rate, analogous to the collective action of the alpha motoneurons of a muscle, and a threshold signal, analogous to the effective action of the gamma motoneurons that excite the sensory organ of the natural muscle-the spindle. The system possesses intrinsic position and velocity feedback due to the structure of its actuators, and extrinsic feedback with transmission delays between the actuators and the control system. The extrinsic feedback is nonlinear and is fashioned after the spindle response in natural systems. Force and length sensors convey information from which the angular position of the marionette is estimated by simultaneous solution of a redundant set of equations. Thus, the marionette is endowed with partial somesthesis: awareness of the whereabouts of its limbs. A control strategy for simple rhythmic movements is developed. This is a preliminary effort to develop an analytical structure for a multiactuator system. The long range findings may shed some light on the elaborate control structure of the central nervous system in natural systems. >","PeriodicalId":79994,"journal":{"name":"IEEE transactions on systems, man, and cybernetics","volume":"9 1","pages":"1491-1501"},"PeriodicalIF":0.0,"publicationDate":"1995-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87842493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Convergence of teams and hierarchies of learning automata in connectionist systems","authors":"M. Thathachar, V. V. Phansalkar","doi":"10.1109/21.467711","DOIUrl":"https://doi.org/10.1109/21.467711","url":null,"abstract":"Learning algorithms for feedforward connectionist systems in a reinforcement learning environment are developed and analyzed in this paper. The connectionist system is made of units of groups of learning automata. The learning algorithm used is the L/sub R-I/ and the asymptotic behavior of this algorithm is approximated by an ordinary differential equation (ODE) for low values of the learning parameter. This is done using weak convergence techniques. The reinforcement learning model is used to pose the goal of the system as a constrained optimization problem. It is shown that the ODE, and hence the algorithm exhibits local convergence properties, converging to local solutions of the related optimization problem. The three layer pattern recognition network is used as an example to show that the system does behave as predicted and reasonable rates of convergence are obtained. Simulations also show that the algorithm is robust to noise. >","PeriodicalId":79994,"journal":{"name":"IEEE transactions on systems, man, and cybernetics","volume":"44 1","pages":"1459-1469"},"PeriodicalIF":0.0,"publicationDate":"1995-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74954212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Explaining control strategies in second generation expert systems","authors":"XueJon Tong, J. Ang","doi":"10.1109/21.467713","DOIUrl":"https://doi.org/10.1109/21.467713","url":null,"abstract":"Explaining control strategies is an important aspect in second generation expert system explanation. With explicit representation of control, it is possible to construct explanations at different levels of abstraction so as to satisfy different needs. This paper presents the authors, work on explaining control strategies within the context of the system tool, CARMEN. CARMEN's methodology for modeling control knowledge (MMCK) uses problem-solving entities (i.e., tasks, meta-knowledge sources (MKSs), basic-knowledge sources (BKSs) and engines) to integrate different kinds of knowledge and reasoning. These entities reflect the ways experts organize their problem-solving activities. Explanations about control strategies can be clearly given according to the roles these entities play in problem solving. >","PeriodicalId":79994,"journal":{"name":"IEEE transactions on systems, man, and cybernetics","volume":"1 1","pages":"1483-1490"},"PeriodicalIF":0.0,"publicationDate":"1995-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83068991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fuzzy typographical analysis for character preclassification","authors":"Shy-Shyan Chen, F. Shih, P. Ng","doi":"10.1109/21.464440","DOIUrl":"https://doi.org/10.1109/21.464440","url":null,"abstract":"This paper presents a fuzzy-logic approach for analyzing typographical structures of textual blocks in order to be used for character preclassification. An efficient baseline detection method embedded with tolerance analysis is developed for locating precisely the baseline. Fuzzy logic is taken into account when the decision ambiguity of typographical categorization is occurred. The constraints on the fuzzy membership functions are formulated. Their boundary conditions are considered to preserve the continuity. An improved character recognition rate can be achieved by means of the typographical categorization. >","PeriodicalId":79994,"journal":{"name":"IEEE transactions on systems, man, and cybernetics","volume":"6 1","pages":"1408-1413"},"PeriodicalIF":0.0,"publicationDate":"1995-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76449472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Stability, capacity, and statistical dynamics of second-order bidirectional associative memory","authors":"A. Leung, L. Chan, E. Lai","doi":"10.1109/21.464439","DOIUrl":"https://doi.org/10.1109/21.464439","url":null,"abstract":"The stability, capacity and statistical dynamics of second-order bidirectional associative memory (BAM) are presented here. We first use an example to illustrate that the state of second-order BAR I may converge to limited cycles. When error in the retrieved pairs is not allowed, a lower bound of memory capacity is derived. That is O(min(n/sup 2//(log n),p/sup 2//(log p))) where n and p are the dimensions of the library pairs. Since the state of second-order BAM may converge to limited cycles, the conventional method cannot be used to estimate its memory capacity when small errors in the retrieval pairs are allowed. Hence, the statistical dynamics of second-order BAM is introduced: starting with an initial state close to the library pairs, how the confidence interval of the number of errors changes during recalling. From the dynamics, the attraction basin, memory capacity, and final error in the retrieval pairs can be estimated. Also, some numerical results are given. Finally, an extension of the results to higher-order BAM is discussed. >","PeriodicalId":79994,"journal":{"name":"IEEE transactions on systems, man, and cybernetics","volume":"33 1","pages":"1414-1424"},"PeriodicalIF":0.0,"publicationDate":"1995-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88026199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}