Polynomial fuzzy controller design with disturbance observer using the SOS-based approach

2015 ◽  
Vol 10 (4) ◽  
pp. 458-464 ◽  
Author(s):  
Hugang Han ◽  
Yuta Higaki
2012 ◽  
Vol 433-440 ◽  
pp. 7407-7412
Author(s):  
Chun Fang Liu ◽  
Yin Long Xing ◽  
Tong Wang

For gantry CNC Machining Center Gantry suspension system, adopting a method of fuzzy synchronization controller and disturbance observer combined control strategy. The disturbance observer Robust feedback controller design compensate the disturbance caused by cutting the time, un-modeled dynamics, system parameter changes, ensure the robustness of a single suspension system. In order to further suppress the gantry beams carrying knife leaning, on the double suspension synchronization system uses fuzzy synchronization control strategy, the two systems through the design of the regulating role of fuzzy controller, and further to overcome suspension height deviation of the double suspension systems, to achieve synchronized suspension purposes. Simulation results show that the proposed control scheme in ensuring the system to achieve stability synchronization suspension, but also has strong robustness, dynamic process synchronization error is small, allowing to meet high accuracy requirements of the controlled objects.


Author(s):  
X. Wu ◽  
Y. Yang

This paper presents a new design of omnidirectional automatic guided vehicle based on a hub motor, and proposes a joint controller for path tracking. The proposed controller includes two parts: a fuzzy controller and a multi-step predictive optimal controller. Firstly, based on various steering conditions, the kinematics model of the whole vehicle and the pose (position, angle) model in the global coordinate system are introduced. Secondly, based on the modeling, the joint controller is designed. Lateral deviation and course deviation are used as the input variables of the control system, and the threshold value is switched according to the value of the input variable to realise the correction of the large range of posture deviation. Finally, the joint controller is implemented by using the industrial PC and the self-developed control system based on the Freescale minimum system. Path tracking experiments were made under the straight and circular paths to test the ability of the joint controller for reducing the pose deviation. The experimental results show that the designed guided vehicle has excellent ability to path tracking, which meets the design goals.


2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Wenru Fan ◽  
Bailing Tian

A multivariable super-twisting sliding mode controller and disturbance observer with gain adaptation, chattering reduction, and finite time convergence are proposed for a generic hypersonic vehicle where the boundary of aerodynamic uncertainties exists but is unknown. Firstly, an input-output linearization model is constructed for the purpose of controller design. Then, the sliding manifold is designed based on the homogeneity theory. Furthermore, an integrated adaptive multivariable super-twisting sliding mode controller and disturbance observer are designed in order to achieve the tracking for step changes in velocity and altitude. Finally, some simulation results are provided to verify the effectiveness of the proposed method.


Author(s):  
Behzad Samani ◽  
Amir H. Shamekhi

In this paper, an adaptive cruise control system with a hierarchical control structure is designed. The upper-level controller is a model predictive controller (MPC) that by minimizing an objective function in the presence of the constraints, calculates the desired acceleration as control input and sends it to the lower-level controller. So the lower-level controller, which is a fuzzy controller, determines the amount of throttle valve opening or brake pressure to get the car to this desired acceleration. The model predictive controller performs optimization at each control step to minimize the objective function and achieve the reference values. Usually, the objective function has predetermined and constant weights to meet objectives such as maintain the driver’s desired speed and increase safety and in some cases increase comfort and reduce fuel consumption. In this paper, it is suggested that instead of using constant weights in the objective function, these weights should be determined by a fuzzy controller, depending on the different conditions in which the car is placed. The simulation results show that the variability of the weights of the objective function achieves control objectives much better than the optimization of the objective function with constant weights.


Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 823
Author(s):  
Wen-Jer Chang ◽  
Yu-Wei Lin ◽  
Yann-Horng Lin ◽  
Chin-Lin Pen ◽  
Ming-Hsuan Tsai

In many practical systems, stochastic behaviors usually occur and need to be considered in the controller design. To ensure the system performance under the effect of stochastic behaviors, the controller may become bigger even beyond the capacity of practical applications. Therefore, the actuator saturation problem also must be considered in the controller design. The type-2 Takagi-Sugeno (T-S) fuzzy model can describe the parameter uncertainties more completely than the type-1 T-S fuzzy model for a class of nonlinear systems. A fuzzy controller design method is proposed in this paper based on the Interval Type-2 (IT2) T-S fuzzy model for stochastic nonlinear systems subject to actuator saturation. The stability analysis and some corresponding sufficient conditions for the IT2 T-S fuzzy model are developed using Lyapunov theory. Via transferring the stability and control problem into Linear Matrix Inequality (LMI) problem, the proposed fuzzy control problem can be solved by the convex optimization algorithm. Finally, a nonlinear ship steering system is considered in the simulations to verify the feasibility and efficiency of the proposed fuzzy controller design method.


2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Wen-Jer Chang ◽  
Bo-Jyun Huang ◽  
Po-Hsun Chen

For nonlinear discrete-time stochastic systems, a fuzzy controller design methodology is developed in this paper subject to state variance constraint and passivity constraint. According to fuzzy model based control technique, the nonlinear discrete-time stochastic systems considered in this paper are represented by the discrete-time Takagi-Sugeno fuzzy models with multiplicative noise. Employing Lyapunov stability theory, upper bound covariance control theory, and passivity theory, some sufficient conditions are derived to find parallel distributed compensation based fuzzy controllers. In order to solve these sufficient conditions, an iterative linear matrix inequality algorithm is applied based on the linear matrix inequality technique. Finally, the fuzzy stabilization problem for nonlinear discrete ship steering stochastic systems is investigated in the numerical example to illustrate the feasibility and validity of proposed fuzzy controller design method.


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