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In this paper, on the basis of sliding mode control theory, a new integral tangent adaptive fuzzy sliding mode control for aircraft engine was proposed. Based on the uncertainty model of aircraft engine, a hyperbolic tangent integral sliding surface was constructed at first, and it effectively overcome the problem of integral saturation effect which was often occur in the traditional integral sliding...
With the continuous development of the national economy and science and technology, the scope of the application of images is constantly expanding. The image has many uncertainties, and the improvement of this feature is often blurred and can not be accurately calibrated, which results in complex and diverse processing techniques. Image smoothing and edge detection are very important feature technologies...
This paper develops two robust adaptive controllers for UAVs. The first controller is the robust adaptive PID based on fuzzy logic. The other is the intelligent flight controller based on ANFIS. The simulation results exhibit the robustness of the developed controllers. Likewise, the results present that the intelligent flight controller based on ANFIS produces better robustness performance than robust...
An interval type-2 fuzzy neural network(IT2FNN) control method is presented for H-type gantry stage driven by dual linear motors. The synchronous motion of the dual linear motors is the main factor affecting the accuracy and robustness of the servo system. Thus, the proposed method sets the position error of the both side motors as input, the powerful self-learning ability of neural network is used...
Navigation of mobile robots in dynamic and unknown environments is usually cluttered with noise and errors. In the literature, several solutions have been proposed. Recently, type-2 fuzzy logic have showed having the ability to handle uncertainties, imprecise and incomplete data. Since, it has been constituted a new hopeful and promising technique for further improve control of mobile robots in real...
In this study, a novel fractional fuzzy proportional-integral proportional-derivative (PI-PD) based modified Smith predictor (SP) is presented for controlling of an industrial air heating system with time delay. The performance of the proposed controller is validated with real-time experimental applications. Furthermore, a performance comparison is demonstrated via results of real-time applications...
In this paper, we propose a direct adaptive iterative learning control for a class of nonaffine nonlinear discrete-time systems with unknown control direction. The fuzzy neural network is firstly used as approximator to compensate for the unknown certainty equivalent controller. Then, in order to solve the uncertainties from approximation errors and random input disturbances, a dead zone like auxiliary...
This paper first presents a simplified single wheel model for underground mining electric vehicles with bounds of system uncertainties. Then, a fuzzy parameter tuning (FPT) technique is used to adjust the parameters in the sliding mode control (SMC) to improve system stability and robustness at an unexpected external disturbances and unbound system uncertainties. The comparison of the simulation results...
This study proposes a new sliding mode control strategy based on a fuzzy reaching law to enhance the yaw angle control of a Tail-sitter UAV. First of all, the simplified yaw angle dynamic model is analyzed, then the fuzzy reaching law is designed considering both the chattering reduction and position tracking; finally, the sliding mode control law is designed for the Tail-sitter UAV's yaw angle system...
The paper describes the control method of the production facilities (baking chamber) under uncertainty. Due to the impossibility to find the adequate analytical model for this object, to control this type of the object under uncertainty the Mamdani fuzzy model is applied. A distinctive feature of this paper is connected with following: the parameters of the fuzzy model can be determined inaccuracy...
The aim of this paper is to present experimental validation results to show the design simplicity of single input interval type-2 (IT2) fuzzy PID (FPID) controllers by evaluating their performance on a real-time 3 DOF helicopter testbed. In this study, we briefly show that the presented analytical design approach gives the opportunity to construct the IT2 fuzzy mappings by tuning a single parameter...
Generalised Modus Ponens (GMP) allows to perform logical inference in the case where an observation partially matches the premise of an implication, enriching the rule exploitation as compared to binary classical logic. This paper proposes to further enhance the rule exploitation, integrating additional constraints to guide the inference, both to reduce uncertainty in case of partial match and to...
This study deals with the identification of the behavior of an individual in a group of marching locusts, as observed under laboratory conditions. In particular, the study focuses on the intermittent motion (walking initiation and pausing) of the locusts using Adaptive Neuro-Fuzzy Inference System (ANFIS). Several possible fuzzy rules were examined in a trial-and-error approach, before establishing...
This paper presents the control of an Unmanned Underwater Vehicle(UUV) with five degrees of freedom by using an adaptive neuro-fuzzy controller combined with a sliding-mode control (SMC)-theory-based learning algorithm. The proposed control structure is composed of an adaptive fuzzy neural network(AFNN) and a conventional PD controller which is used to guarantee the asymptotic stability of the system...
This paper has proposed maximum power point tracking (MPPT) control for stand-alone solar power generation systems via the type-2 Takagi-Sugeno (T-S) fuzzy-model-based approach. In order to deal with the uncertainties in the modeling procedure, the type-2 T-S fuzzy technology is employed. To handle reducing the conservatism of LMI-based stability conditions for type-2 T-S fuzzy systems, stability...
This work deals with problem of fuzzy control stabilization for wind turbine generator with parameter uncertainties. Using Linear Matrix inequality (LMI) combined with a judicious of the famous Young relation, a new methodology of stability is proposed, which can be solved by using LMI optimization techniques. Hence the control scheme is based on a PDC structure, a fuzzy observer and a H∞ standard...
Function approximation accuracy and computational cost are two major issues in approximation-based adaptive fuzzy control. In this paper, a model reference composite learning fuzzy control (MRCLFC) strategy is proposed for a class of affine nonlinear systems with functional uncertainties. In the MRCLFC, a modified modelling error that utilizes data recorded online is defined as the prediction error,...
In this paper, the real time tracking performance of the fuzzy PID controller has been evaluated on nonlinear 3-DOF helicopter system. Quanser 3-DOF helicopter system has been utilized as experimental setup. Three separate fuzzy PID controller have been employed so as to control three state of the system. The dynamics of the system has been altered via counterweight in order to examine the performances...
Many uncertain nonlinear systems can be modeled by the linear-in-parameter model, and the parameters are uncertain in the sense of fuzzy numbers. Dual fuzzy equations are alternative models for these nonlinear systems identification, while the solutions of the fuzzy equations are the controllers. In this paper, we propose a novel fuzzy controller via dual fuzzy equations. Two types of neural networks...
The design of interval Type-2 Takagi-Sugeno fuzzy control systems (IT2 T-S FCSs) holding model uncertainty has been demonstrated. An IT2 T-S fuzzy model holding model uncertainty and IT2 fuzzy controllers constructed the closed-loop fuzzy control systems. The linear matrix inequality based (LMIbased) stability conditions for the IT2 T-S FCS holding model uncertainty have been derived. The main contribution...
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