This paper presents a Lyapunov-based switched trajectorytrackingcontrol design for a rear-steered automated guided AGV (AGV). Given a moving reference whose position and orientation have to be tracked by the AGV, the main objective of the controller is to reduce AGV’s distance from the reference while adjusting its orientation. The distance reduction issue is important, especially in huge warehouses operating a group of AGVs, since the rate of AGV-to-reference distance reduction contributes to the possibility of AGV-to-AGV collision. A set of control algorithms is proposed to handle large AGV’s orientation. Simulations that show the performance of the proposed method is presented.
The kinematics analysis of agricultural vehicles is carried out and the kinematics model shown in Figure 3 is established in the plane coordinate system. The front wheel of the model turns and rear wheel drive. In the process of work, the steering wheel and the driving wheel adjust the angle and speed by adjusting the voltage. In the whole kinematics analysis, the agricultural vehicle is regarded as a rigid body running on horizontal plane. In order to determine the agricultural vehicle’s position and attitude in the whole trajectory, the navigation coordinate is set up. The center point of the test car’s rear axle was selected as a reference point to define the position and position information of the car. Pose information is defined as (x, y, φ). In which, x, y are the axial coordinates of the vehicle’s rear axle (m); φ is the heading angle (rad); δf is the front wheel steering angle (rad); v is the center speed of the rear axle (m/s); v f is the front axle center speed (m/s);
The current research of autonomous vehicle motion control mainly focuses on trajectorytracking and velocity track- ing. However, numerous studies deal with trajectorytracking and velocity tracking separately, and the yaw stability is seldom considered during trajectorytracking. In this research, a combination of the longitudinal–lateral control method with the yaw stability in the trajectorytracking for autonomous vehicles is studied. Based on the vehicle dynamics, considering the longitudinal and lateral motion of the vehicle, the velocity tracking and trajectorytracking problems can be attributed to the longitudinal and lateral control. A sliding mode variable structure control method is used in the longitudinal control. The total driving force is obtained from the velocity error in order to carry out velocity tracking. A linear time-varying model predictive control method is used in the lateral control to predict the required front wheel angle for trajectorytracking. Furthermore, a combined control framework is established to control the longitudinal and lateral motions and improve the reliability of the longitudinal and lateral direction control. On this basis, the driving force of a tire is allocated reasonably by using the direct yaw moment control, which ensures good yaw stability of the vehicle when tracking the trajectory. Simulation results indicate that the proposed controlstrategy is good in tracking the reference velocity and trajectory and improves the performance of the stability of the vehicle. Keywords: Autonomous vehicle, Trajectorytracking, Direct yaw moment control (DYC), Model predictive control (MPC), Longitudinal–lateral control
In present days all the human beings are well known about his own time because time is precious than gold.All the persons are use a vehicle and mobile phones for his personal use. We are going to use that personal need into to use an emergency warn messaging system. In our real time clock also used to see the exact world clock time. In this wrist watch contains flexi force sensor, MEMS Accelerometer, GPS Transceiver. Sensor to detect the pressure of the human skin.MEMS Accelerometer is used to accelerates the small mechanical movement is convert to electrical signal. Sensor is used to convert the force into a digital signal. IEEE 802.15.4 protocol is used to transmit these kind of data in wireless medium. The controller also used to monitor the process of sensor and MEMS Accelerometer. To find the location using GPS Transceiver and send a warning message using GSM Technology.
A new control law for trajectorytracking in marine vessels under uncertainties was presented. To deal with the uncertainties, a new term has been incorpo- rated into the methodology presented in Serrano et al. . This new approach allows reducing the effect of uncertainties in the tracking error. To tune the con- troller, the Monte Carlo experiment was used, and a cost function that depends on tracking errors was minimized. The proposed controllers are easy to im- plement, making them suitable for implementation in low-profile processors.
Abstract—Nonlinear dynamic model of a high-altitude unmanned airship, expressed by generalized coordinate, was built. A nonlinear compensation was introduced into the control loop to linearize and decouple the nonlinear system globally. In view of the imprecisely known inertia parameters of the airship, an adaptive law was proposed based on the feedback linearization to realize asymptotic tracking of any continuous time-varying desired trajectory from an arbitrary initial condition. The stability of the closed-loop control system was proved via the use of Lyapunov stability theory. Finally, numerical simulation results demonstrate the validity and effectiveness of the proposed adaptive control law.
This paper present an optimal Fractional Order PID (FOPID) controller based on Particle Swarm Optimization (PSO) for controlling the trajectorytracking of Wheeled Mobile Robot(WMR).The issue of trajectorytracking with given a desired reference velocity is minimized to get the distance and deviation angle equal to zero, to realize the objective of trajectorytracking a two FOPID controllers are used for velocity control and azimuth control to implement the trajectorytrackingcontrol. A path planning and path tracking methodologies are used to give different desired tracking trajectories. PSO algorithm is using to find the optimal parameters of FOPID controllers. The kinematic and dynamic models of wheeled mobile robot for desired trajectorytracking with PSO algorithm are simulated in Simulink-Matlab. Simulation results show that the optimal FOPID controllers are more effective and has better dynamic performance than the conventional methods.
Direct optimization The direct optimization ap- proaches [12, 2, 7, 4] estimate the motion parameters between two neighboring frames by minimizing a deter- ministic cost function. The direct optimization approach assumes slow motion between two frames. This kind of approach is efficient but not very robust in situations with rapid sudden motion, ambiguity, and long-time occlusion. Particle filtering Condensation  is the first particle fil- tering [6, 11] based algorithm introduced in visual tracking. Particle filtering approximates the posterior distribution us- ing a set of “weighted particles”. The particle filtering algo- rithm has advantages on handling sudden motion and short- time occlusion. However, it often difficult to handle am- biguity or long-time occlusion. Maccormick & Black pro- posed a “probabilistic exclusion principle”  to address the ambiguity problem. But their approach is limited to a special observation model for contour tracking.
It is difficult to test real autonomous vehicle under harsh conditions. Using the hardware-in-loop scaled platform to test scaled autonomous vehicle becomes an apparent alter- native. In this paper, we use the HIL platform to test the slip of scaled autonomous passing through U-turn under high-speed condition. After comparing its result with the real vehicle testing, we have proved the feasibility of using HIL scaled platform as surrogates of the real autonomous vehicle for testing automated vehicle. Note that the proposed test platform has a very high flexibility in simulating real world traffic operations, including those with purely traditional vehicles. For example, it can be used for conducting traffic capacity analysis [28–30], Long Distance Commuter lane (Qu and Wang, 2015), traffic oscillations [31, 32], traffic safety analysis [33–35], and others. At the end of this paper, we use a simple case study of high-speed U-turn to build the trackingcontrol function. A simplified vehicle dynamics model and a trajectorytracking algorithm have been considered to build the simulation test. The experiment results demonstrate the effectivity of HIL scaled platform.
The vehicletracking system is an electronic device that tracks the vehicle‟s location. Most of the tracking systems use GPS module to locate the vehicle‟s position .Many systems also combines communication components such as satellite transmitters to communicate the vehicle‟s location to a remote user . Google maps are used to view the vehicle‟s location. The design of the tracking system is divided into three parts; basic design, intermediate design and an advance Design. The basic design of the vehicletracking system consists of a GSM module, a GPS module, a MCU (ATMEL), a Relay circuit and a LCD. The user sends SMS and the system responds to the user‟s request by providing the coordinates of a location in accordance to the requirements of mobile phone users through the GPRS network. The intermediate and advance design is an improvement of the basic design. There are five features introduced in the project. SMS codes are specifically assigned to each of these features. For example, if the user sends „555‟ to the tracking system. The GSM modem will receive the SMS and transmit to the MCU unit, where the SMS code will be compared against the codes stored in the library. In this project, the code ‟555‟ is assigned to find the location of a vehicle. So, the MCU will get the location from the GPS module and reply back
Kinematics modeling is required for designing the motion and trajectory of the robot without considering the dynamics aspect such as force and friction. Kinematics modeling can be tested using simulation to avoid the complexity of the real system in testing the effectiveness of the proposed method. Simulation was conducted by Ceccarelli et al. 2008 utilizing the kinematic design for a manipulator by creating an algorithm for evaluating manipulator workspace , Lin et al. 2014 proposed an intuitive kinematic control of a robot via interface with human motion to control a robot directly teleoperated in avoiding obstacle and finishing its task , Reihara 2011 analyzed and solved the kinematics problem for an AdeptThree robot arm with the application of DH convention simulated in LabView , and Zodey et al. 2014 analyze the kinematics of a robotics gripper by simulating the capability of hand modeling, grasp definition, grasp modeling, grasp analysis and graphic to support the presentation .
a 11-dimensional state space by driver temporal command parameters. This method drastically reduces the dimension of the state space, thus improving computational e ﬃ ciency. 2.2. Driver Command and Vehicle Priors. The driver com- mands are the steering wheel angle, and the vehicle longitu- dinal acceleration, from which we deduce the vehicle speed through integration. The experiments presented below have been conducted on a mid-velocity curve. While traveling such a curve, a light vehicle driver’s command law is commonly modelled by a trapezoid, with steering wheel angle velocities lying between 1.5 and 4 degrees per second, and with absolute longitudinal accelerations lying between 1 m · s − 2 and 3 m · s − 2 . In order to take into account a
The model of a quadrotor unmanned aerial vehicle (UAV) is nonlinear and dynamically unstable. A flight controller design is proposed on the basis of Lyapunov stability theory which guarantees that all the states remain and reach on the sliding surfaces. The controlstrategy uses sliding mode with a backstepping control to perform the position and attitude trackingcontrol. This proposed controller is simple and effectively enhance the performance of quadrotor UAV. In order to demonstrate the robustness of the proposed control method, White Gaussian Noise and aerodynamic moment disturbances are taken into account. The performance of the nonlinear control method is evaluated by comparing the performance with developed linear quadratic regulator and existing backstepping control technique and proportional-integral-derivative from the literature. The comparative performance results demonstrate the superiority and effectiveness of the proposed controlstrategy for the quadrotor UAV.
The electromechanical coupling system of the electrically driven track vehicle consists of an alternating current motor and a working machine. The electromagnetic system and the mechanical system interact with each other and form a complex nonlinear system. When the electromechanical performance is not suitable, the induction motor is likely to be blocked and cannot drive the crawler device. In severe cases, it may even burn out the motor . Therefore, it is necessary to perform electromechanical coupling dynamics analysis when analysing and controlling a track vehicle. In the current research, many scholars have established kinematic and dynamic models of track vehicles and applied them to motion analysis  and . However, there are few studies combining vehicletrajectorytrackingcontrol with electromechanical coupling dynamic analysis.
Abstract To overcome the drawbacks of using a traditional proportional‐integral‐derivative (PID) control method for a robot driver system, such as requiring preliminary offline learning, big overshoot and large speed fluctuation, a new method for speed tracking of a robot driver system based on sliding mode control is proposed in this paper. Firstly, the coordinated control model of multiple manipulators for the robot driver is built, which achieved coordinated control of the throttle mechanical leg, clutch mechanical leg, brake mechanical leg and shift mechanical arm for the robot driver. On the basis of this, a speed tracking sliding mode controller for a vehicle robot driver is designed using the method of multiple sliding surfaces design, and the variable structure control laws of throttle and brake are designed respectively, which realize the speed tracking of the given driving test cycle. Experimental results demonstrate that compared with the PID control method, the proposed method can obviously reduce the overshoot of vehicle speed trackingcontrol and greatly improve the accuracy of vehicle speed tracking. The vehicle speed tracking accuracy stays within a tolerance band of ±2 km/h, which meets the requirements of
We study the trackingcontrol of a very manoeuvrable vehicle aimed at autonomous tasks. Two models are used and are shown to be flat; this property is then used to obtain open loop controls. The study is complemented by a stabilization around the desired trajectory.
In this work, robust trajectorytrackingcontrol of a quadrotor subject to external disturbances is developed using angular acceleration feedback. The hierarchical control structure is used as a control framework. Acceleration based disturbance observer integrated with PID controllers is designed for the positional dynamics of the quadrotor where linear acceleration signals provide better stiffness against the disturbance forces. For attitude control, a nested angular position, velocity and acceleration control structure is employed where PID and PI controllers are used. In order to get reliable angular position, velocity and acceleration signals, an estimation algorithm based on the cascaded structure of extended and classical Kalman filters is utilized. Furthermore, in this work, a nonlinear optimization technique is used to obtain the reference attitude angles form command signals generated from the high-level control of the hierarchical control structure. Unlike analytical method for calculating the reference attitude angles where nonsmooth and large Euler angles might be obtained, the constrained nonlinear optimization technique provides smooth and desired bounded values. Also in the analytical approach, the desired yaw angle (ψ) needs to be fixed to some value (ψ ∗ ), but in case of the proposed method, yaw angle need not be constant. The efficiency of the proposed control method is tested on a high fidelity model of the quadrotor where sensor bias and noise in measurements are also taken into account when 3-D circular helix type trajectory is considered. Results are compared with a
especially in traffic jams or long-distance driving cir- cumstances. However, the wheel slip control is the basis of active safety control systems and intelligent driver assistance systems. For instance, the anti-lock brake system (ABS) regulates the slip of each wheel at its optimum value to prevent it from locking during braking, such that the shortest stopping distance is achieved and the capability of directional stability and steer-handling is maintained . The electronic stability program (ESP) may produce additional yaw moment by commanding the target slip of one or two wheels to prevent vehicle from spinning and drifting out of lane . Finally, the adaptive cruise control system (ACC) can follow target speed or forward ve- hicle at the desired safety headway distance by com- manding the target slip of the wheels and the target torque of the power system . As a consequence, de- signing the wheel slip controller has important theo- retical and practical significance for active safety con- trol systems and intelligent driver assistance systems. In recent years, many control approaches which are robust against system uncertainty and external dis- turbance have been proposed for the wheel slip con- trol due to the modeling errors, the measurement or estimation errors, and the changing of external en- vironment conditions of the wheel dynamic system, such as sliding mode control , hybrid control  and fuzzy control , etc. Johansen et al.  established the speed-dependent nominal linearized slip model with a perturbation term as a basis for the wheel slip control, and utilized gain-scheduled LQR approach to design the gain matrices of the control- ler. Pasillas-Lépine  adopted wheel deceleration logic-based switching and wheel dynamic model to design the five-phase anti-lock brake algorithm, and proved the existence and stability of limit cycles by the Poincaré map. Hsu  proposed an intelligent exponential sliding-mode controlstrategy for ABS, and a functional recurrent fuzzy neural network uncertainty estimator was designed to reduce the chattering of the exponential sliding-mode controlstrategy by approximating and compensating the unknown nolinear term of ABS dynamics on-line. Jing et al.  presented a switched controlstrategy for the anti-lock brake system and then analyzed the stability condition of the closed-loop system by Lyapunov-based method in the Filippov frame- work. The proposed controlstrategy in [7-9, 19] may
been proposed. In , almost-global stability results are achieved by considering geometric methods and then applied to the control of a quadrotor aerial vehicle. Backstepping control design has been proposed in  in order to perform aggressive maneuvers by considering the dynamics of a small-scale helicopter. A global stabilizing controller based on synergistic Lyapunov functions has appeared in . In , , inner-outer loop control strategies have been employed to stabilize the dynamical model of a miniature helicopter. The proposed methodology takes into account for the feedback interconnection between the inner attitude and the outer position control loops. More recently, a survey describing feedback control design for under-actuated VTOL systems has appeared in .