In this paper, a cart-type inverted pendulum is controlled using combining of two methods of approximate feedback linearization and sliding mode control. Both position of the cart and angular posit...

Pareto optimum control of a 2-DOF inverted pendulum using approximate feedback linearization and sliding mode control

An interval type-2 fuzzy logic controller using the switching type-1 fuzzy Takagi-Sugeno model is presented for the position control of wheeled mobile robot. The control gains for the switched regions are determined using linear quadratic regulator approach. The blending of the local controllers based on the interval type-2 design scheme yields the final motion commands for the wheeled mobile robot. MATLAB simulations have proved the effectiveness of the proposed controller.

An interval type-2 fuzzy LQR positioning controller for wheeled mobile robot

The problems of robust stability,robust stabilization and robust H_∞ control for T-S fuzzy descriptor system with uncertain parameters are studied.For all admissible uncertainties,the state feedback controllers are designed.The sufficient conditions,which maintain the stability of the closed-loop system and satisfy the H_∞-performance by means of the controller,are derived.They are expressed via LMI.These expressions bypass the shortcoming of the LMI toolbox,so the asymptotic stability is realized just once and the desired performance index is satisfied for the system.The simpleness and effectiveness are showed by an example.

Robust H_∞ control for fuzzy descriptor systems with uncertain parameters

In this paper, two different PID control methods are described to control of Maglev Guiding System for Linear Elevator. The linear elevator driven by permanent magnet linear synchronous motor (PMLSM) use the method to adopt the magnetic guidance system to control the PMLSM gap which changes frequently and can impact the vertical thrust and control the level vibration and noise in the process of start, operation, and stop to make passenger feel comfortable. The first PID control method is based on feedback linearization. In this method, single Maglev guiding systems are controlled to maintain the air gap of linear motor in the reference value independently. To achieve a more practical control method and better operation of maglev guiding system, this method is corrected and a simultaneous control method of two counterpart Maglev systems is proposed. MATLAB modeling of these systems are used in this paper. Simulation results show that the second method has a better performance.

PID control of Maglev Guiding System for Linear Elevator

This paper presents an adaptive fuzzy controller for Nonlinear in Parameters (NLP) chaotic systems with parametric uncertainties In the proposed controller, the unknown parameters are estimated by the novel Improved Speed Gradient (ISG) method, which is a modification of Speed Gradient (SG) algorithm ISG employs the Lagrangian of two suitable objective functionals for on-line estimation of system parameters The most significant advantage of ISG is that it is applicable to NLP systems and it results in a faster rate of convergence for the estimated parameters than the SG method Estimated parameters are used to design the fuzzy controller and to calculate the Lyapunov exponents of the chaotic system adaptively Furthermore, established on the well-known Takagi–Sugeno (T-S) fuzzy model, a LMI (Linear Matrix Inequality)-based fuzzy controller is designed and is tuned using estimated parameters and Lyapunov exponents Throughout the controller design procedure, several important issues in fuzzy control theory including relaxed stability analysis, control input performance specifications, and optimality are taken into account Combination of ISG parameter estimation method and T-S-based fuzzy controller yields an adaptive fuzzy controller capable to suppress uncertainties in parameters and initial states of NLP chaotic systems Finally, simulation results are provided to show the effectiveness of the ISG and adaptive fuzzy controller on chaotic Lorenz system and Duffing oscillator

Adaptive Fuzzy Control of Nonlinear in Parameters Uncertain Chaotic Systems Using Improved Speed Gradient Method

The magnetic levitation device which has non-contact characteristics, is used to replace the traditional guiding equipment, it would be applied in linear elevator to maintain a constant air gap of linear motor, and to eliminate mechanical vibration. In order to solve nonlinear problems of maglev device, feedback linearization control and fuzzy sliding mode control method is adopted to control the air gap of magnetic levitation device. Simulation results show that the control strategy has strong robustness.

Fuzzy sliding mode control of maglev guiding system based on feedback linearization

The vertical motion of roped elevator was described. The robust control problem of high rise elevator system based on Takagi-Sugeno (T-S) fuzzy model was studied. T-S fuzzy model was used to solve multi objective control and nonlinear control problems in elevator motion control system. First, the generalized model of system was built, and then system global state controller was designed by parallel-distributed compensation (PDC) method. Second, state feedback robust controller was gained based on linear matrix inequality (LMI) method. The simpleness and effectiveness of the controller were showed by the simulation, and the robustness was satisfied for the system. Multiobjective control and nonlinear control problems have been solved effectively.

Robust T-S Model Fuzzy Control of High-rise Roped Elevator System Based on LMIs

H infinitf Robust Fuzzy Control of Ultra-High Rise / High Speed Elevators with Uncertainty.

A LMIs (linear matrix inequalities) based H∞ robust fuzzy control approach to an ultra-high rise/high speed elevator in the presence of uncertainties is presented in this paper. The uncertain nonlinear systems are represented using Takage-Sugeno (T-S) fuzzy models. The proposed controllers, which are in the form of the so-called parallel distributed compensation (PDC), stabilize nonlinear systems and guarantee an induced L2 norm bound constraint on disturbance attenuation for all admissible uncertainties. Finally, simulation results show the realization of the H∞robust fuzzy control.

H ∞ robust fuzzy control of ultra-high rise/high speed elevators with uncertainty

In this paper a strategy of grading fuzzy sliding mode control (FSMC) applied in the AC servo system is presented It combines the fuzzy logic and the method of sliding mode control, which can reduce the chattering without decreasing the system robustness At the same time, the exponent approaching control is added by grading The control strategy makes the response of the system quick and no overshoot It is simulated to demonstrate the feasible of the proposed method by MATLAB65 and the good control effect is received

Dongmei Yu

Papers

Fuzzy sliding mode control of maglev guiding system based on feedback linearization

Robust T-S Model Fuzzy Control of High-rise Roped Elevator System Based on LMIs

H infinitf Robust Fuzzy Control of Ultra-High Rise / High Speed Elevators with Uncertainty.

H ∞ robust fuzzy control of ultra-high rise/high speed elevators with uncertainty

Grading fuzzy sliding mode control in AC servo system