324 research outputs found

    Autodrive Land Vehicle Control by Using PID

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    In towards industry 4.0, the autodrive vehicle is needed to give people relaxed driving. There are many research in autodrive vehicle such as waymo-the Google driving car project and Tesla Self Driving Autopilot. In This paper is presented about Autodrive Land Vehicle (ALV) control by using PID. The autodrive Land vehicle can drive autonomously by using GPS Information such as Latitude and longitude to navigate in an area. The vehicle is controled to follow the given waypoint that set by operator on ground control station. PID control is used to control steering of the vehicle\u27s front wheel and to control the heading of the vehicle. From the Implementation result, it is obtained that the vehicle could track the given waypoint with small error

    Autodrive Land Vehicle Control by Using PID

    Get PDF
    In towards industry 4.0, the autodrive vehicle is needed to give people relaxed driving. There are many research in autodrive vehicle such as waymo-the Google driving car project and Tesla Self Driving Autopilot. In This paper is presented about Autodrive Land Vehicle (ALV) control by using PID. The autodrive Land vehicle can drive autonomously by using GPS Information such as Latitude and longitude to navigate in an area. The vehicle is controled to follow the given waypoint that set by operator on ground control station. PID control is used to control steering of the vehicle’s front wheel and to control the heading of the vehicle. From the Implementation result, it is obtained that the vehicle could track the given waypoint with small error

    Structure-specified H∞ loop shaping control for balancing of bicycle robots: A particle swarm optimization approach

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    In this paper, the particle swarm optimization (PSO) algorithm was used to design the structure-specified H∞ loop shaping controllers for balancing of bicycle robots. The structure-specified H∞ loop shaping controller design normally leads to a complex optimization problem. PSO is an efficient meta-heuristic search which is used to solve multi-objectives and non-convex optimizations. A model-based systematic procedure for designing the particle swarm optimization-based structure-specified H∞ loop shaping controllers was proposed in this research. The structure of the obtained controllers are therefore simpler. The simulation and experimental results showed that the robustness and efficiency of the proposed controllers was gained when compared with the proportional plus derivative (PD) as well as conventional H∞ loop shaping controller. The simulation results also showed a better efficiency of the developed control algorithm compared to the Genetic Algorithm based one

    On Radar Deception, As Motivation For Control Of Constrained Systems

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    This thesis studies the control algorithms used by a team of ECAVs (Electronic Combat Air Vehicle) to deceive a network of radars to detect a phantom track. Each ECAV has the electronic capability of intercepting the radar waves, and introducing an appropriate time delay before transmitting it back, and deceiving the radar into seeing a spurious target beyond its actual position. On the other hand, to avoid the errors and increase the reliability, have a complete coverage in various atmosphere conditions, and confronting the effort of the belligerent intruders to delude the sentinel and enter the area usually a network of radars are deployed to guard the region. However, a team of cooperating ECAVs could exploit this arrangement and plans their trajectories in a way all the radars in the network vouch for seeing a single and coherent spurious track of a phantom. Since each station in the network confirms the other, the phantom track is considered valid. This problem serves as a motivating example in trajectory planning for the multi-agent system in highly constrained operation conditions. The given control command to each agent should be a viable one in the agent limited capabilities, and also drives it in a cumulative action to keep the formation. In this thesis, three different approaches to devise a trajectory for each agent is studied, and the difficulties for deploying each one are addressed. In the first one, a command center has all information about the state of the agents, and in every step decides about the control each agent should apply. This method is very effective and robust, but needs a reliable communication. In the second method, each agent decides on its own control, and the members of the group just communicate and agree on the range of control they like to apply on the phantom. Although in this method much less data needs to communicate between the agents, it is very sensitive to the disturbances and miscalculations, and could be easily fell apart or come to a state with no feasible solution to continue. In the third method a differential geometric approach to the problem is studied. This method has a very strong backbone, and minimizes the communication needed to a binary one. However, less data provided to the agents about the system, more sensitive and infirm the system is when it faced with imperfectionalities. In this thesis, an object oriented program is developed in the Matlab software area to simulate all these three control strategies in a scalable fashion. Object oriented programming is a naturally suitable method to simulate a multi-agent system. It gives the flexibility to make the code more iv close to a real scenario with defining each agent as a separated and independent identity. The main objective is to understand the nature of the constrained dynamic problems, and examine various solutions in different situations. Using the flexibility of this code, we could simulate several scenarios, and incorporate various conditions on the system. Also, we could have a close look at each agent to observe its behavior in these situations. In this way we will gain a good insight of the system which could be used in designing of the agents for specific missions

    Design and Development of a Self-Balancing Bicycle Using Control Moment Gyro

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    Master'sMASTER OF ENGINEERIN

    Control of motorcycle steering instabilities

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    Experimental design and analysis of a gyroelastic beam

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    Division of Higher Technical Education of MexicoPublished versio
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