Research on Anti-Windup Controller of Autonomous Navigation Vehicle Based on Improved Adaptive Filter

2014 ◽  
Vol 1025-1026 ◽  
pp. 1119-1124
Author(s):  
Yun Zhang ◽  
Dean Zhao ◽  
Jun Zhang ◽  
Yun Liu
Keyword(s):  
Kalman Filtering ◽  
Adaptive Filtering ◽  
Pid Control ◽  
Autonomous Navigation ◽  
Variable Structure ◽  
System Stability ◽  
Control Technique ◽  
Convergence Criterion ◽  
Control Precision ◽  
And Control

This paper presents relevant methods on navigation accuracy improvement of agricultural vehicle focusing on positioning accuracy and control precision. An adaptive kalman filtering, combination of Sage_Husa adaptive filtering and strong tracking kalman filtering based on strict convergence criterion, is adopted to improve filtering accuracy with strong ability of adaptive filtering and restraining filter divergence. A new variable-structure switching method to prevent PID controller from integrator windup can effectively solve the integral saturation phenomenon, which adopts a kind of adaptive adjustment rate to adjust the integral term of PID control algorithm. Finally, this paper puts the improved adaptive filtering and anti-windup variable-structure PID control technique into combination to effectively restrain interference and integral saturation, so as to achieve the purpose of improving system stability and control precision. The simulation and experiment results show that methods described above greatly enhance the capabilities of restraining filtering divergence and improving control precision.

PID+CMAC Neural Network Control of Micro Positioning Platform

2015 ◽  
Vol 713-715 ◽  
pp. 768-772
Author(s):  
Xiao Jing Yang ◽  
Yao Li
Keyword(s):  
Neural Network ◽  
Pid Control ◽  
Network Control ◽  
System Stability ◽  
Inverse Dynamic ◽  
Cmac Neural Network ◽  
Control Precision ◽  
Neural Network Controller ◽  
Nonlinearity Effect ◽  
And Control

Because of some intrinsic properties of the PZT actuator, such as hysteresis, creep and nonlinearity effect, it’s difficult to achieve satisfactory results and control precision for conventional PID controller. In order to improve the control precision of the PZT driven of micro positioning platform, we proposed a CMAC neural network based on PID control scheme, which has the characteristics of realizing feed-forward control and obtaining the inverse dynamic model of controlled object by the CMAC neural network controller, and realizing feedback control by conventional controller, which can ensure the system stability and suppress disturbance. Form MATLAB simulation results, it demonstrates that the CMAC+PID control algorithm can be able to improve the control precision and response time of the system, and enhance the anti-interference ability and robustness, comparing with the traditional digit PID control algorithms.

scholarly journals Autonomous navigation control based on improved adaptive filtering for agricultural robot

2020 ◽  
Vol 17 (4) ◽  
pp. 172988142092535
Author(s):  
Weikuan Jia ◽  
Yuyu Tian ◽  
Huichuan Duan ◽  
Rong Luo ◽  
Jian Lian ◽  
...  
Keyword(s):  
Adaptive Filtering ◽  
Autonomous Navigation ◽  
Dynamic Performance ◽  
Variable Structure ◽  
Convergence Criteria ◽  
Agricultural Robots ◽  
Navigation Control ◽  
Navigation Accuracy ◽  
And Control ◽  
Agricultural Robot

Under the complex agricultural operation environment, reliable navigation system is the basic guarantee to realize the agricultural robot automated operation. This study focuses on improving navigation accuracy and control accuracy and conducts related research on autonomous navigation control of agricultural robots. This article discusses the advantages of using strict convergence criteria and combining Sage–Husa adaptive filtering with strong tracking Kalman filtering and then proposes an improved adaptive Kalman filter algorithm. The new algorithm can effectively suppress the filter divergence, improve the dynamic performance of the filter, and ensure its better filtering accuracy and strong adaptive ability to improve navigation accuracy of GPS. Further variable structure switching method is used to prevent proportional integral differential (PID) controller integral saturation phenomenon, which effectively solves the controller over-saturation problem. And combining this method with an improved adaptive filtering algorithm not only can effectively inhibit control interference but also achieve the anti-saturation effect, thereby enhancing the stability and accuracy of the control system. Finally, the simulation and experiment of the new method show that the proposed method greatly improves the ability of the filter to suppress divergence and control precision.

Duffing Chaotic System Stability Control Based on Sliding Mode Control

2012 ◽  
Vol 605-607 ◽  
pp. 1639-1642
Author(s):  
Ding Ma
Keyword(s):  
Chaotic System ◽  
Control Method ◽  
Sliding Mode ◽  
Variable Structure ◽  
Stability Control ◽  
System Stability ◽  
Terminal Sliding Mode ◽  
Sliding Mode Variable Structure ◽  
The Stability ◽  
And Control

Considering the Duffing chaotic system, the problem of stability control based on the terminal sliding mode variable structure is studied. A new terminal sliding mode surface and control law are designed. On this basis, the stability of closed-loop system is analyzed. Simulation results show the effectiveness of the control method.

scholarly journals Position Tracking Control of PMSM Based on Fuzzy PID-Variable Structure Adaptive Control

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Pei Pei ◽  
Zhongcai Pei ◽  
Zhiyong Tang ◽  
Han Gu
Keyword(s):  
Adaptive Control ◽  
Pid Control ◽  
Control Method ◽  
Sliding Mode ◽  
Dynamic Performance ◽  
Variable Structure ◽  
Fuzzy Pid ◽  
Structure Control ◽  
Control Precision ◽  
Sliding Mode Variable Structure

A novel Fuzzy PID-Variable Structure Adaptive Control is proposed for position tracking of Permanent Magnet Synchronous Motor which will be used in electric extremity exoskeleton robot. This novel control method introduces sliding mode variable structure control on the basis of traditional PID control. The variable structure term is designed according to the sliding mode surface which is designed by system state equation, so it could compensate for the disturbance and uncertainty. Considering the chattering of sliding mode system, the fuzzy inference method is adopted to adjust the parameters of PID adaptively in real time online, which can attenuate chattering and improve control precision and dynamic performance of system correspondingly. In addition, compared with the traditional sliding mode control, this method takes the fuzzy PID control item to replace the equivalent control item of sliding mode variable structure control, which could avoid the control performance reduction resulted from modeling error and parameter error of system. It is proved that this algorithm can converge to the sliding surface and guarantee the stability of system by Lyapunov function. Simulation results show that Fuzzy PID-Variable Structure Adaptive Control enjoys better control precision and dynamic performance compared with traditional control method, and it improves the robustness of system significantly. Finally, the effectiveness and practicability of the algorithm are verified by the method of Rapid Control Prototyping on the semiphysical simulation test bench.

An Efficient Approach for Modeling and Control of a Quadrotor

2016 ◽  
Vol 4 (2) ◽  
pp. 1-16
Author(s):  
Ahmed S. Khusheef
Keyword(s):  
Pid Control ◽  
Control Method ◽  
Mechanical Design ◽  
Loop Control ◽  
Modeling And Control ◽  
Loop Control System ◽  
And Control ◽  
Close Loop Control ◽  
Close Loop Control System ◽  
Made In

 A quadrotor is a four-rotor aircraft capable of vertical take-off and landing, hovering, forward flight, and having great maneuverability. Its platform can be made in a small size make it convenient for indoor applications as well as for outdoor uses. In model there are four input forces that are essentially the thrust provided by each propeller attached to each motor with a fixed angle. The quadrotor is basically considered an unstable system because of the aerodynamic effects; consequently, a close-loop control system is required to achieve stability and autonomy. Such system must enable the quadrotor to reach the desired attitude as fast as possible without any steady state error. In this paper, an optimal controller is designed based on a Proportional Integral Derivative (PID) control method to obtain stability in flying the quadrotor. The dynamic model of this vehicle will be also explained by using Euler-Newton method. The mechanical design was performed along with the design of the controlling algorithm. Matlab Simulink was used to test and analyze the performance of the proposed control strategy. The experimental results on the quadrotor demonstrated the effectiveness of the methodology used.

scholarly journals Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2534
Author(s):  
Oualid Doukhi ◽  
Deok-Jin Lee
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Autonomous Navigation ◽  
Control Technique ◽  
Local Motion ◽  
Aerial Robots ◽  
Novel Approach ◽  
Outdoor Environments ◽  
Aerial Vehicle ◽  
High Level

Autonomous navigation and collision avoidance missions represent a significant challenge for robotics systems as they generally operate in dynamic environments that require a high level of autonomy and flexible decision-making capabilities. This challenge becomes more applicable in micro aerial vehicles (MAVs) due to their limited size and computational power. This paper presents a novel approach for enabling a micro aerial vehicle system equipped with a laser range finder to autonomously navigate among obstacles and achieve a user-specified goal location in a GPS-denied environment, without the need for mapping or path planning. The proposed system uses an actor–critic-based reinforcement learning technique to train the aerial robot in a Gazebo simulator to perform a point-goal navigation task by directly mapping the noisy MAV’s state and laser scan measurements to continuous motion control. The obtained policy can perform collision-free flight in the real world while being trained entirely on a 3D simulator. Intensive simulations and real-time experiments were conducted and compared with a nonlinear model predictive control technique to show the generalization capabilities to new unseen environments, and robustness against localization noise. The obtained results demonstrate our system’s effectiveness in flying safely and reaching the desired points by planning smooth forward linear velocity and heading rates.

scholarly journals COLREG-Compliant Optimal Path Planning for Real-Time Guidance and Control of Autonomous Ships

2021 ◽  
Vol 9 (4) ◽  
pp. 405
Author(s):  
Raphael Zaccone
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Optimal Path ◽  
Open Water ◽  
Optimal Path Planning ◽  
Guidance And Control ◽  
Real Time Applications ◽  
And Control

While collisions and groundings still represent the most important source of accidents involving ships, autonomous vessels are a central topic in current research. When dealing with autonomous ships, collision avoidance and compliance with COLREG regulations are major vital points. However, most state-of-the-art literature focuses on offline path optimisation while neglecting many crucial aspects of dealing with real-time applications on vessels. In the framework of the proposed motion-planning, navigation and control architecture, this paper mainly focused on optimal path planning for marine vessels in the perspective of real-time applications. An RRT*-based optimal path-planning algorithm was proposed, and collision avoidance, compliance with COLREG regulations, path feasibility and optimality were discussed in detail. The proposed approach was then implemented and integrated with a guidance and control system. Tests on a high-fidelity simulation platform were carried out to assess the potential benefits brought to autonomous navigation. The tests featured real-time simulation, restricted and open-water navigation and dynamic scenarios with both moving and fixed obstacles.

Intelligent Information of TS Fuzzy PID Control System of BLDCM

2013 ◽  
Vol 846-847 ◽  
pp. 313-316 ◽  
Author(s):  
Xiao Yun Zhang
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Pid Control ◽  
Control Method ◽  
Design Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Precision ◽  
Simulation Results ◽  
Intelligent Information

This paper presented a new method based on the Fuzzy self - adaptive PID for BLDCM. This method overcomes some defects of the traditional PID control. Such as lower control precision and worse anti - jamming performance. It dynamic model of BLDCM was built, and then design method for TS fuzzy PID model is given, At last, it compared simulation results of PID control method with TS Fuzzy PID control method. The results show that the TS Fuzzy PID control method has more excellent dynamic antistatic performances, as well as anti-jamming performance. The experiment shows that TS fuzzy PID control has the stronger adaptability robustness and transplant.

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