Laser-range-finder localization based fuzzy control for mobile robots

2017 ◽  
Vol 34 (7) ◽  
pp. 2409-2421 ◽  
Author(s):  
Chung-Hsun Sun ◽  
Sheng-Kai Huang ◽  
Hsuan Chen ◽  
Cheng-Wei Ye ◽  
Yin-Tien Wang ◽  
...  

Purpose Based on laser-range-finder (LRF) sensing, the control design of location and orientation stabilization for the mobile robot is investigated. However, the practical limitation of the LRF sensing is usually ignored in the control design, which leads to incorrect localization and unexpected control results. The purpose of this study is to design the fuzzy controller subject to the practical limitation on the LRF-based localization for a differentially driven wheeled mobile robot. Design/methodology/approach First, the Takagi–Sugeno (T-S) fuzzy model is derived from the polar kinematic model of a differentially driven mobile robot. Then, the fuzzy controller is designed to the derived T-S fuzzy kinematic model in accordance with the Lyapunov stabilization theorem. The derived Lyapunov stabilization conditions for the fuzzy control design are expressed as the linear matrix inequality (LMI) form and effectively solved by LMI tools. The practical limitation on the LRF-based localization is also expressed as the LMI form and simultaneously solved with the control design. Finding The location and posture stabilization experiments are carried out on a mobile robot with LRF-based localization to prove the effectiveness of the proposed T-S fuzzy model-based control design. Furthermore, the ground truth experiment evaluates the accuracy of LRF-based localization. Originality/value The contribution of this study is to develop the fuzzy control law for a differentially driven wheeled mobile robot under the practical limitation on LRF-based localization. The proposed control design can be applied to other robots with practical limitations on the sensors.

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141775415 ◽  
Author(s):  
Xiaomeng Yin ◽  
Xinming Li ◽  
Lei Liu ◽  
Yongji Wang ◽  
Xing Wei

Achieving balance between robustness and performance is always a challenge in the hypersonic vehicle flight control design. In this research, we focus on dealing with uncertainties of the fuzzy control system from the viewpoint of reliability. A probabilistic robust mixed H2/ H∞ fuzzy control method for hypersonic vehicles is presented by describing the uncertain parameters as random variables. First, a Takagi–Sugeno fuzzy model is employed for the hypersonic vehicle nonlinear dynamics characteristics. Next, a robust fuzzy controller is developed by solving a reliability-based multi-objective linear matrix inequality optimization problem, in which the H2/ H∞ performance is optimized under the condition that the system is robustly reliable to uncertainties. By this method, the system performance and reliability can be taken into account simultaneously, which reduces the conservatism in the robust fuzzy control design. Finally, simulation results of a hypersonic vehicle demonstrate the feasibility and effectiveness of the presented method.


Author(s):  
Wei Jiang ◽  
An Zhang ◽  
Gongping Wu ◽  
Lianqing Yu ◽  
Hong Jun Li ◽  
...  

Purpose To improve the operational efficiency and intelligence of live operation robots in dynamic-unstructured operation environments, this paper aims to propose a fuzzy logic-based method for the autonomous search and visual localization control of a manipulator end effector applied to a drainage plate bolt on a high-voltage transmission line. The proposed approach is based on a four-way video image information output from a dual-operation manipulator. Design/methodology/approach First, based on the structural characteristics of the drainage line, an autonomous search method for the drainage plate bolt and a mapping relationship between the autonomous search control parameters and the relative posture of the operation manipulator-drainage line are proposed. The posture control parameters of the dual manipulators can then be obtained, and a two-dimensional fuzzy controller is designed with the posture offset distance and the posture offset angle as its input signals. This enables the localization control of the bolt and nut alignment to be realized through a visual process. Findings The proposed fuzzy control algorithm is used for bolt location control, and its performance is compared with that of the conventional approach. The simulation results indicate that the fuzzy control algorithm greatly improves the localization accuracy and operational efficiency of live operation robots. Originality/value Field operation experiments on actual transmission lines verify that the fuzzy control-based visual localization control of the robot manipulator has great engineering practicality. Therefore, the proposed method further improves operational intelligence compared with conventional algorithms.


2006 ◽  
Vol 129 (3) ◽  
pp. 252-261 ◽  
Author(s):  
Huai-Ning Wu

This paper is concerned with the design of reliable robust H∞ fuzzy control for uncertain nonlinear continuous-time systems with Markovian jumping actuator faults. The Takagi and Sugeno fuzzy model is employed to represent an uncertain nonlinear system with Markovian jumping actuator faults. First, based on the parallel distributed compensation (PDC) scheme, a sufficient condition such that the closed-loop fuzzy system is robustly stochastically stable and satisfies a prescribed level of H∞-disturbance attenuation is derived. In the derivation process, a stochastic Lyapunov function is used to test the stability and H∞ performance of the system. Then, a new improved linear matrix inequality (LMI) formulation is applied to this condition to alleviate the interrelation between the stochastic Lyapunov matrix and system matrices containing controller variables, which results in a tractable LMI-based condition for the existence of reliable and robust H∞ fuzzy controllers. A suboptimal fuzzy controller is proposed to minimize the level of disturbance attenuation subject to the LMI constraints. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.


Author(s):  
Mark D. Johnson ◽  
Mohammad A. Ayoubi

We propose a shared fuzzy controller for position and attitude control of multiple quadrotor unmanned aerial vehicles (UAVs). Using the nonlinear governing equations of motion and kinematics of a quadrotor, we develop a Takagi-Sugeno (T-S) fuzzy model for a quadrotor. Then, we consider time-varying delays due to wireless connectioninto the T-S fuzzy model. We use the sufficient stability condition based on the Lyapunov-Krasovskii stability theorem and the parallel distributed compensation (PDC) technique to determine the fuzzy control law. For practical purposes, we include actuator amplitude constraint into the design process. The problem of designing a shared fuzzy controller is cast in the form of linear matrix inequalities (LMIs). A feasible solution region is found in terms of maximum magnitude and rate of time-varying delay. In the end, the stability, performance, and robustness of the proposed shared fuzzy controller are examined via numerical simulation.


2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Huiying Sun ◽  
Long Yan

The paper mainly investigates theH∞fuzzy control problem for a class of nonlinear discrete-time stochastic systems with Markovian jump and parametric uncertainties. The class of systems is modeled by a state space Takagi-Sugeno (T-S) fuzzy model that has linear nominal parts and norm-bounded parameter uncertainties in the state and output equations. AnH∞control design method is developed by using the Lyapunov function. The decoupling technique makes the Lyapunov matrices and the system matrices separated, which makes the control design feasible. Then, some strict linear matrix inequalities are derived on robustH∞norm conditions in which both robust stability andH∞performance are required to be achieved. Finally, a computer-simulated truck-trailer example is given to verify the feasibility and effectiveness of the proposed design method.


2017 ◽  
Vol 2 (4) ◽  
pp. 228-239
Author(s):  
Sami ALLOU ◽  
Youcef ZENNIR

The paper present our control approach based in fuzzy controller for platooning vehicles. this approach based to control lateral and longitudinal movement of vehicles in different navigation trajectory. kinematic model of vehicles are described follows by describe of controller design. The communication is provided between vehicles with exchange information, speed and orientation angle with a fixed safety distance between vehicles. 3D simulation developed with matlab, Simulink and v-rep software were carried . Different reference trajectory are used to compared and approve our approach. The simulation results illustrate the efficiency of our control design and open the perspectives for future work.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hongxing Wang ◽  
LianZheng Ge ◽  
Ruifeng Li ◽  
Yunfeng Gao ◽  
Chuqing Cao

Purpose An optimal solution method based on 2-norm is proposed in this study to solve the inverse kinematics multiple-solution problem caused by a high redundancy. The current research also presents a motion optimization based on the 2-Norm of high-redundant mobile humanoid robots, in which a kinematic model is designed through the entire modeling. Design/methodology/approach The current study designs a highly redundant humanoid mobile robot with a differential mobile platform. The high-redundancy mobile humanoid robot consists of three modular parts (differential driving platform with two degrees of freedom (DOF), namely, left and right arms with seven DOF, respectively) and has total of 14 DOFs. Given the high redundancy of humanoid mobile robot, a kinematic model is designed through the entire modeling and an optimal solution extraction method based on 2-norm is proposed to solve the inverse kinematics multiple solutions problem. That is, the 2-norm of the angle difference before and after rotation is used as the shortest stroke index to select the optimal solution. The optimal solution of the inverse kinematics equation in the step is obtained by solving the minimum value of the objective function of a step. Through the step-by-step cycle in the entire tracking process, the kinematic optimization of the highly redundant humanoid robot in the entire tracking process is realized. Findings Compared with the before and after motion optimizations based on the 2-norm algorithm of the robot, its motion after optimization shows minimal fluctuation, improved smoothness, limited energy consumption and short path during the entire mobile tracking and operating process. Research limitations/implications In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot. Practical implications In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot. Social implications In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot. Originality/value Motion optimization based on the 2-norm of a highly redundant humanoid mobile robot with the entire modeling is performed on the basis of the entire modeling. This motion optimization can make the highly redundant humanoid mobile robot’s motion path considerably short, minimize energy loss and shorten time. These researches provide a theoretical basis for the follow-up research of the service robot, including tracking and operating target, etc. Finally, the motion optimization algorithm is verified by the tracking and operating behaviors of the robot and an example.


1997 ◽  
Vol 9 (2) ◽  
pp. 160-167
Author(s):  
Jun Tang ◽  
◽  
Keigo Watanabe ◽  
Akira Nomiyama ◽  
◽  
...  

This paper presents a new design for a fuzzy controller, called ""stochastic fuzzy control."" It describes the application controlling a mobile robot driven by two independent wheels. Using this scheme, the fuzzy control system provides an optimal stochastic control strategy that ensures the stability of the control system. Two design methods are considered: one assumes that the control object is completely known, and the other assumes that the control object includes unknown parameters. We design the straight line and circular path reference trajectories in accordance with the practical applications for the mobile robot, in which three patterns of speed are adopted. The effectiveness of the proposed method is demonstrated by a series of practical tests using our experimental mobile robot.


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