A fuzzy sliding controller for nonlinear systems

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Variable structure control with chattering elimination and guaranteed stability for a generalized T-S model

In this paper, a fuzzy based Variable Structure Control (VSC) with guaranteed stability is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. The main contribution of this work is that, firstly, new functions for chattering reduction and error convergence without sacrificing invariant properties are proposed, which is considered the main drawback of the VSC control. Secondly, the global stability of the controlled system is guaranteed.The well known weighting parameters approach, is used in this paper to optimize local and global approximation and modeling capability of T-S fuzzy model.A one link robot is chosen as a nonlinear unstable system to evaluate the robustness, effectiveness and remarkable performance of optimization approach and the high accuracy obtained in approximating nonlinear systems in comparison with the original T-S model. Simulation results indicate the potential and generality of the algorithm. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved with the proposed FLC-VSC controller. The effectiveness of the proposed controller is proven in front of disturbances and noise effects

Variable structure control with chattering reduction of a generalized T-S model

In this paper, a fuzzy logic controller (FLC) based variable structure control (VSC) is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. New functions for chattering reduction and error convergence without sacrificing invariant properties are proposed. The main feature of the proposed method is that the switching function is added as an additional fuzzy variable and will be introduced in the premise part of the fuzzy rules; together with the state variables. In this work, a tuning of the well known weighting parameters approach is proposed to optimize local and global approximation and modelling capability of the Takagi-Sugeno (T-S) fuzzy model to improve the choice of the performance index and minimize it. The main problem encountered is that the T-S identification method can not be applied when the membership functions are overlapped by pairs. This in turn restricts the application of the T-S method because this type of membership function has been widely used in control applications. The approach developed here can be considered as a generalized version of the T-S method. An inverted pendulum mounted on a cart is chosen to evaluate the robustness, effectiveness, accuracy and remarkable performance of the proposed estimation approach in comparison with the original T-S model. Simulation results indicate the potential, simplicity and generality of the estimation method and the robustness of the chattering reduction algorithm. In this paper, we prove that the proposed estimation algorithm converge the very fast, thereby making it very practical to use. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved

Adaptive Building Envelope: An Integral Approach to Indoor Environment Control in Buildings

The problem of energy consumption of buildings is complex and multidimensional, as it is a cross section of building envelope performance, indoor environmental conditions and user demands and preferences. In order to fulfil the EU goal stated in the 2020 climate and energy package and beyond, the implementation of high-performance buildings is crucial. Part of the solution is properly designed, flexible and adequately controlled building envelope that can contribute to reduced energy consumption and to increased occupancy comfort. In the presented chapter first, a structured treatment of the indoor environment formation is proposed that can be used in order to define appropriate fields of interventions when designing building automation systems. Furthermore, interaction between adaptive building envelope elements, indoor and exterior environment is discussed and elaborated. Second, the conventional and artificial intelligence control approaches used in building automation are discussed and commented, whereas advantages and disadvantages of each group are discussed. At the end, an example of building automation system designed on the principles of a holistic treatment of indoor environment in buildings is presented. The discussed system was designed at the Faculty of Civil and Geodetic Engineering using a combination of conventional and artificial intelligence control methods

Self-tuning Fuzzy Control Method Based on the Trajectory Performance of the Phase Plane

The phase plane is already an important method to design fuzzy control systems and analyze their stability. The concept of the real-time response trajectory characteristic vectors and angles between the real-time characteristic vectors on the phase plane are put forward in this paper according to the analysis of the response trajectory performance on the phase plane of a fuzzy control system. The method of rule self-tuning fuzzy control based on the response trajectory performance on phase plane is presented by analyzing the characteristics of angles between the real-time characteristic vectors. The simulation results show that the method is not only capable of increasing greatly the ability to identify and describe the plant in small error, reducing the overshoot, settle time greatly and improving the convergence speed of the fuzzy control system, but also possesses a simple arithmetic and does not require much more storage space and calculation time

Human Being Emotion in Cognitive Intelligent Robotic Control Pt I: Quantum / Soft Computing Approach

Abstract. The article consists of two parts. Part I shows the possibility of quantum / soft computing optimizers of knowledge bases (QSCOptKB™) as the toolkit of quantum deep machine learning technology implementation in the solution’s search of intelligent cognitive control tasks applied the cognitive helmet as neurointerface. In particular, case, the aim of this part is to demonstrate the possibility of classifying the mental states of a human being operator in on line with knowledge extraction from electroencephalograms based on SCOptKB™ and QCOptKB™ sophisticated toolkit. Application of soft computing technologies to identify objective indicators of the psychophysiological state of an examined person described. The role and necessity of applying intelligent information technologies development based on computational intelligence toolkits in the task of objective estimation of a general psychophysical state of a human being operator shown. Developed information technology examined with special (difficult in diagnostic practice) examples emotion state estimation of autism children (ASD) and dementia and background of the knowledge bases design for intelligent robot of service use is it. Application of cognitive intelligent control in navigation of autonomous robot for avoidance of obstacles demonstrated.