Abstract: Heating, Ventilating and Air Conditioning (HVAC) system is a nonlinear MIMO system which is very difficult to control. This paper presents adaptive fuzzy output feedback control based on observer for nonlinear HVAC System whose state variables are not available. Fuzzy systems are employed to approximate the unknown nonlinear functions of the HVAC system and the state observer is desig...

In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking perf...

Due to the contradiction between high precision control with complexity of fuzzy controller design, an method for multi-variable fuzzy controller design is presented. A dynamic compensation model for the fuzzy controller is introduced, which simplify the analysis and design of multi-variable fuzzy controller, and improve control performance. The method is applied to high precision water tank te...

This paper investigates the application of fuzzy model and generalised predictive control strategy for the construction of a model-based predictive fuzzy controller for non-linear processes. In this method a GPC controller is used with the Takagi Sugeno Kang (TSK) piece-wise fuzzy modeling approach in an adaptive strategy. The developed method is applied to control a continuous stirred tank rea...

In this paper, an adaptive fuzzy tracking control approach is proposed for a class of single-inputsingle-output (SISO) nonlinear systems in which the unknown continuous functions may be nonlinearlyparameterized. During the controller design procedure, the fuzzy logic systems (FLS) in Mamdani type are applied to approximate the unknown continuous functions, and then, based on the minimal learnin...

The Takagi-Sugeno (T-S) fuzzy multiple-variable integral control system with fuzzy state observer is designed for the coordinated control of multi-input-multi-output (MIMO) nonlinear boilerturbine system whose operating points vary within a wide range. Linear models are first derived from the original nonlinear model on several operating points. Next the fuzzy multi-variable integral controller...

A novel indirect adaptive backstepping control approach based on type-2 fuzzy system is developed for a class of nonlinear systems. This approach adopts type-2 fuzzy system instead of type-1 fuzzy system to approximate the unknown functions. With type-reduction, the type-2 fuzzy system is replaced by the average of two type-1 fuzzy systems. Ultimately, the adaptive laws, by means of backsteppin...

In this paper, a new adaptive fuzzy reasoning method using compensatory fuzzy operators is proposed to make a fuzzy logic system more adaptive and more effective. Such a compensatory fuzzy logic system is proved to be a universal approximator. The compensatory neural fuzzy networks built by both control-oriented fuzzy neurons and decision-oriented fuzzy neurons cannot only adaptively adjust fuz...

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi Chapter . Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  Working memory studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  Adaptive system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  Fuzzy system . . . . . . . . . . . . ...

This paper addresses the problem of designing fin control for the ship roll stabilization. A novel adaptive robust fuzzy control (ARFC) algorithm is presented for ship roll nonlinear system with unstructured uncertainties. In the algorithm, the Takagi-Sugeno type fuzzy logic systems are employed to approximate uncertain functions in the systems, and a systematic procedure is developed for the s...