AN OPTIMAL REAL-TIME TRAJECTORY TRACKING CONTROL DESIGN FOR PENDUBOT VIA TAKAGI-SUGENO FUZZY MODEL

2005 ◽  
Vol 29 (2) ◽  
pp. 247-265
Author(s):  
Zhen Cai ◽  
Chun-Yi Su
Keyword(s):  
Real Time ◽  
Trajectory Tracking ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Trajectory Tracking Control ◽  
Linear Regulator ◽  
Control Scheme ◽  
The Stability ◽  
Takagi Sugeno ◽  
Underactuated Robot

In this paper, an optimal fuzzy control scheme is presented to achieve trajectory tracking for the Pendubot, an underactuated robot by combining linear optimal control theory and linear regulator theory with the Takagi-Sugeno fuzzy methodology. The stability of the entire closed-loop fuzzy system is analyzed by the designed optimal fuzzy controller. The real-time application of the proposed algorithm on the Pendubot is also addressed.

scholarly journals Actuator Saturated Fuzzy Controller Design for Interval Type-2 Takagi-Sugeno Fuzzy Models with Multiplicative Noises

Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 823
Author(s):  
Wen-Jer Chang ◽  
Yu-Wei Lin ◽  
Yann-Horng Lin ◽  
Chin-Lin Pen ◽  
Ming-Hsuan Tsai
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Actuator Saturation ◽  
Design Method ◽  
Fuzzy Model ◽  
The Stability ◽  
Interval Type ◽  
Takagi Sugeno

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.

scholarly journals Q-learning trajectory planning based on Takagi–Sugeno fuzzy parallel distributed compensation structure of humanoid manipulator

2019 ◽  
Vol 16 (1) ◽  
pp. 172988141983020 ◽  
Author(s):  
Shuhuan Wen ◽  
Xueheng Hu ◽  
Xiaohan Lv ◽  
Zongtao Wang ◽  
Yong Peng
Keyword(s):  
Reinforcement Learning ◽  
Trajectory Planning ◽  
Trajectory Tracking ◽  
Fuzzy Controller ◽  
Learning Algorithm ◽  
Fuzzy Model ◽  
Large Error ◽  
Learning Trajectory ◽  
Tracking Accuracy ◽  
Takagi Sugeno

NAO is the first robot created by SoftBank Robotics. Famous around the world, NAO is a tremendous programming tool and he has especially become a standard in education and research. Aiming at the large error and poor stability of the humanoid robot NAO manipulator during trajectory tracking, a novel framework based on fuzzy controller reinforcement learning trajectory planning strategy is proposed. Firstly, the Takagi–Sugeno fuzzy model based on the dynamic equation of the NAO right arm is established. Secondly, the design and the gain solution of the state feedback controller based on the parallel feedback compensation strategy are studied. Finally, the ideal trajectory of the motion is planned by reinforcement learning algorithm so that the end of the manipulator can track the desired trajectory and realize the valid obstacle avoidance. Simulation and experiment shows that the end of the manipulator based on this scheme has good controllability and stability and can meet the accuracy requirements of trajectory tracking accuracy, which verifies the effectiveness of the proposed framework.

scholarly journals Design and Implementation of Integral Backstepping Sliding Mode Control for Quadrotor Trajectory Tracking

Processes ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1951
Author(s):  
Shun-Hung Tsai ◽  
Yi-Ping Chang ◽  
Hung-Yi Lin ◽  
Luh-Maan Chang
Keyword(s):  
Trajectory Tracking ◽  
Sliding Mode ◽  
Unmanned Aircraft ◽  
Trajectory Tracking Control ◽  
Attitude Tracking ◽  
Control Scheme ◽  
Tracking Controller ◽  
Backstepping Sliding Mode Control ◽  
Trajectory Tracking Controller ◽  
The Stability

A robust trajectory tracking control scheme for quadrotor unmanned aircraft vehicles under uncertainties is proposed herein. A tracking controller combined with the sliding mode and integral backstepping is performed for position and attitude tracking. The stability of the trajectory tracking controller of the quadrotor is investigated via Lyapunov stability analysis. By incorporating force and torque disturbances into numerical simulations, the results demonstrate the effectiveness of the proposed quadrotor trajectory controller. Finally, the experiments validate the feasibility of the proposed controller.

scholarly journals Improved T-S Fuzzy Control for Uncertain Time-Delay Coronary Artery System

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Zhenyu Zhu ◽  
Zhanshan Zhao ◽  
Haoliang Cui ◽  
Fengdong Shi
Keyword(s):  
Coronary Artery ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Practical Significance ◽  
Linear Matrix ◽  
System State ◽  
Fuzzy Models ◽  
The Stability ◽  
Uncertain Time ◽  
Takagi Sugeno

This paper is based on the Takagi-Sugeno (T-S) fuzzy models to construct a coronary artery system (CAS) T-S fuzzy controller and considers the uncertainties of system state parameters in CAS. We propose the fuzzy model of CAS with uncertainties. By using T-S fuzzy model of CAS and the use of parallel distributed compensation (PDC) concept, the same fuzzy set is assigned to T-S fuzzy controller. Based on this, a PDC controller whose fuzzy rules correspond to the fuzzy model is designed. By constructing a suitable Lyapunov-Krasovskii function (LKF), the stability conditions of the linear matrix inequality (LMI) are exported. Simulation results show that the method proposed in this paper is correct and effective and has certain practical significance.

A Novel Trajectory Tracking Control Method for a Nonholonomic Mobile Robot with System Uncertainties and Disturbances

2013 ◽  
Vol 823 ◽  
pp. 193-198
Author(s):  
Run Zhou Zhao ◽  
Xi Zheng Zhang ◽  
Cai Hong Shi ◽  
Wei Chen
Keyword(s):  
Trajectory Tracking ◽  
Control Method ◽  
Hybrid Control ◽  
Kinematic Model ◽  
Network Dynamic ◽  
Trajectory Tracking Control ◽  
Dynamic Controller ◽  
Control Scheme ◽  
System Uncertainties ◽  
The Stability

This paper focuses on the trajectory tracking problem of mobile robots with system uncertainties and disturbances. With the integration of a kinematic controller and a dynamic controller, a hybrid control method is presented. Firstly, an adaptive kinematic controller is proposed through the kinematic model and backstepping method. Secondly, a neural network dynamic controller is proposed, with the consideration of system uncertainties and disturbances. The stability of the proposed control scheme is verified via the Lyapunov method and Barbalat lemma. Finally, results of circular trajectory simulation have illustrated the effectiveness of the present control scheme.

scholarly journals Robust trajectory tracking control for unmanned surface vessels under motion constraints and environmental disturbances

2021 ◽  
pp. 147509022110396
Author(s):  
Ruo Zhang ◽  
Yuanchang Liu ◽  
Enrico Anderlini
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Autonomous Navigation ◽  
Lyapunov Theory ◽  
Trajectory Tracking Control ◽  
Environmental Disturbances ◽  
Motion Constraints ◽  
Surface Vessels ◽  
Control Scheme ◽  
The Stability

To achieve a fully autonomous navigation for unmanned surface vessels (USVs), a robust control capability is essential. The control of USVs in complex maritime environments is rather challenging as numerous system uncertainties and environmental influences affect the control performance. This paper therefore investigates the trajectory tracking control problem for USVs with motion constraints and environmental disturbances. Two different controllers are proposed to achieve the task. The first approach is mainly based on the backstepping technique augmented by a virtual system to compensate for the disturbance and an auxiliary system to bound the input in the saturation limit. The second control scheme is mainly based on the normalisation technique, with which the bound of the input can be limited in the constraints by tuning the control parameters. The stability of the two control schemes is demonstrated by the Lyapunov theory. Finally, simulations are conducted to verify the effectiveness of the proposed controllers. The introduced solutions enable USVs to follow complex trajectories in an adverse environment with varying ocean currents.

scholarly journals Robust Takagi-Sugeno Fuzzy Dynamic Regulator for Trajectory Tracking of a Pendulum-Cart System

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Miguel A. Llama ◽  
Wilfredo De La Torre ◽  
Francisco Jurado ◽  
Ramon Garcia-Hernandez
Keyword(s):  
Trajectory Tracking ◽  
Fuzzy Controller ◽  
Reference Signal ◽  
Fuzzy Model ◽  
Viscous Friction ◽  
Upright Position ◽  
Linear Matrix ◽  
Fuzzy Controllers ◽  
Fuzzy Partition ◽  
Takagi Sugeno

Starting from a nonlinear model for a pendulum-cart system, on which viscous friction is considered, a Takagi-Sugeno (T-S) fuzzy augmented model (TSFAM) as well as a TSFAM with uncertainty (TSFAMwU) is proposed. Since the design of a T-S fuzzy controller is based on the T-S fuzzy model of the nonlinear system, then, to address the trajectory tracking problem of the pendulum-cart system, three T-S fuzzy controllers are proposed via parallel distributed compensation: (1) a T-S fuzzy servo controller (TSFSC) designed from the TSFAM; (2) a robust TSFSC (RTSFSC) designed from the TSFAMwU; and (3) a robust T-S fuzzy dynamic regulator (RTSFDR) designed from the RTSFSC with the addition of a T-S fuzzy observer, which estimates cart and pendulum velocities. Both TSFAM and TSFAMwU are comprised of two fuzzy rules and designed via local approximation in fuzzy partition spaces technique. Feedback gains for the three fuzzy controllers are obtained via linear matrix inequalities approach. A swing-up controller is developed to swing the pendulum up from its pendant position to its upright position. Real-time experiments validate the effectiveness of the proposed schemes, keeping the pendulum in its upright position while the cart follows a reference signal, standing out the RTSFDR.

scholarly journals Observer-Based Fuzzy Control for Memristive Circuit Systems

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Qian Ye ◽  
Xuyang Lou
Keyword(s):  
Fuzzy Control ◽  
Chaotic System ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Chaotic Circuit ◽  
Control Scheme ◽  
Simulation Results ◽  
Memristive Circuit ◽  
Takagi Sugeno

This paper proposes an observer-based fuzzy control scheme for a class of memristive chaotic circuit systems. First, the Takagi-Sugeno fuzzy model is adopted to reconstruct the nonlinear chaotic circuit system. Next, based on the proposed fuzzy model, an observer-based fuzzy controller is developed to estimate the states and stabilize the origin. Third, the results are extended to explore the L∞-gain observer-based fuzzy control for the chaotic system with disturbances. Finally, simulation results are also addressed to show the effectiveness of the proposed control scheme.

scholarly journals Design of an Unmatching Observer-Based Controller for Discrete-Time Fuzzy Systems with Time Delay

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zejian Zhang ◽  
Dawei Wang
Keyword(s):  
Time Delay ◽  
Discrete Time ◽  
Fuzzy Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Fuzzy Model ◽  
Membership Functions ◽  
Design Flexibility ◽  
Control Scheme ◽  
The Stability

The problem of an unmatching observer-based controller design for discrete-time fuzzy systems with time delay is investigated, in which the fuzzy controller shares different membership functions from the fuzzy model. The objective is to design a state observer and unmatching fuzzy controller such that the discrete closed-loop system with time delay is asymptotically stable. A sufficient condition that contains the information of the membership functions of fuzzy model and fuzzy controller for the stabilization via an unmatching observer-based output feedback is presented. The proposed control scheme is well capable of enhancing the design flexibility, and the stability condition is less conservative. Three numerical examples are given to illustrate the effectiveness and advantages of the proposed method.

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