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Inverted Pendulum Control System - Lab Report Example

Summary
The report "Inverted Pendulum Control System" critically analyzes the comprehensive explanation of the design and set-up of controls necessary for the inverted pendulum. A theoretical overview of the control concept of an inverted pendulum and the research methodology are detailed in this report…
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Extract of sample "Inverted Pendulum Control System"

Control Systems Lab Report (Name) (University) Abstract The control and balance of an inverted pendulum is a widely used concept in numerous control systems aimed at enhancing the performance of any system. The preference of this principle is based on its ability to enable learners to employ a number of monitoring techniques that are readily available. The use of inverted pendulum enhances learning experiences due to its unsteady and non-linear properties. The results of this paper are a comprehensive explanation of the design and set-up of controls necessary for the inverted pendulum. A theoretical overview of the control concept of an inverted pendulum and the research methodology are detailed in this report, in addition to a detailed experimental data from Labview. Contents 1.0 Introduction 4 2.0 Theory 5 3.0 Construction steps 6 4.0 Results 7 5.0 Discussion 8 6.0 Conclusion 9 7.0 References 10 Control System Lab Report 1.0 Introduction The principle of inverted pendulum poses control challenges that experience every time; this is due to its properties. A number of inferences can be made from this concept; preference of this principle is based on the fact that it is non-linear and is characterized by its unsteady properties, therefore calling for balancing that requires knowledge of system controls to achieve successfully. These experimental findings were obtained from Labview, software, based on engineering controls that enable learners to visualize reality around them with much ease. This ability enhances retentions and memory creation hence effective learning (Bhattacharya, 2013). The engineering applications present various types of controls for this case. The nature of the engineering applications presents three types of controls that can be effectively applied and manipulated to enhance the effectiveness of the controls system. For instance, a combination of the three types can be made possible to enhance the performance of the system. The controls systems are commonly abbreviated as PID (Proportional Integral Differential). Therefore, a control system is based on this three types of controls- Proportional Integral Differential. To ensure the pendulum is maintained upright throughout the period of simulation, the position and motion angle of the pendulum were controlled by Proportional Integral Differential chosen for this experiment (Bhattacharya, 2013). All the factors that could affect the balance of the instrument were taken care of during the experiment to obtain reliable results out of it. The experimental data obtained was carefully and accurately computed to allow for objective analysis. This allowed for a discussion of the cause factors of the imbalance of the inverted pendulum deduced from computations. It is worth noting that the balancing of the inverted pendulum was effected by the combination of the Proportional Integral Differential control systems and the lowest settling time of the pendulum (Ding, 2013). 2.0 Theory The three Proportional Integral Differential (PID) control are necessary for keeping the pendulum stable- in an upright position- during the simulation process since the inverted pendulum always presents stability challenges as well as its non-linear characteristic. A small angle from the vertical line position is used to make the pendulum steady. The pendulum points at the centre of the track at the point of stability. The reverse is always true in the case where the pendulum is in the state of instability. This where the pendulum points away from the centre of the track. The vertical position keeps the pendulum upright hence enhancing the stability of the pendulum (Ding, 2013). Adrift in the pendulum, to the left of the centre of the path, will cause the controls to point to the right to maintain the pendulum at a steady state. As this happens, the pendulum will lean more to the right falling afterward. To catch up the cart is moved to the right with declining pendulum to make it stabilize hence preventing the declining leftwards (Nonami, 2013). Illustrated as follows; Figure 1; Inverted Pendulum 3.0 Construction steps The balancing of the inverted pendulum follows a number of steps. This steps, in most cases, consider a combination of the three controls (the PID) during the simulation process. The first step entails the opening of the Labview followed by clicking on a blank VI page. Secondly, the block section diagram was switched on hence sparking the simulation loop functional where the system was built to start the pendulum control process. The configured simulation parameters option was used to set the simulation parameters while the control system was selected by use of the simulation loop (Nonami, 2013). Thirdly, communication was established between the two-position encoding centres and the control-system by introduction of block DAC. This action done by clicking on diagram block then passing the cursor on the input section. Opening a functional unit, clicking on the express and signal manipulated and sourced in the DDT gave a normalization angle used in the process. After this, a connection was made between the input and the output from the DAC after which there was the creation of a switch block that had two extra wire divisions (Nonami, 2013). At this stage, the entire control system was created for the balancing of the inverted pendulum. In addition to this, there was a need to maintain neatness of the block diagram. To do this, a subsystem was created having more blocks. Indicators were introduced to the system to give values that were objective from the subsystem blocks (Nonami, 2013). 4.0 Results Figures were used to illustrate the resultant findings from the experiment. The illustrations contain the motions noted when codes were added to the system. Below are the diagrams of the system; Figure 2 Block Diagram Figure 3 Setup parameters 5.0 Discussion When the illustrations are carefully studied, one will find out that control parameter determines the balancing of the pendulum. The control parameters you chose will greatly affect the pendulum balancing.in the case of this experiment, the PID parameters were used to keep the inverted pendulum vertically upright. Present values in the control system were as a result of proportional controllers. Integral controllers resulted in the past values of the error while the future values of the error resulted from derivative controllers (Vilanova, & Visioli, 2012). The combination of the three control systems heavily depends on the variable from the measurement process. The errors that are resultant from the system are responded to by the combination of the controls (PID). Their errors are usually as a result of a deviation from the normal as measured based on the deviation angle. This deviation angle was controlled by controllers to keep the pendulum in a vertically straight position during the entire simulation process. The PID controls compensates the effects that are caused by external factors to the balancing of the inverted pendulum (Vilanova, & Visioli, 2012). 6.0 Conclusion Conclusively, the PID controls are effective to keep the inverted pendulum balance during the entire simulation process, that is, to keep the inverted pendulum steady throughout entire process of simulation. The properties of the inverted pendulum make suitable for enhancing learning since it is unstable and non-linear. This is achieved through its ability to visualize reality and make it available to learners indoors. A combining the three types of controls provides a better balance In the inverted pendulum since they have the ability to control external factors that may affect the balance of the inverted pendulum. 7.0 References Bhattacharya, S. (2013). Control systems engineering. Dorling Kindersley. Ding, Z. (2013). Nonlinear and adaptive control systems. London: Institute of Engineering and Technology. Nonami, K. (2013). Autonomous control systems and vehicles. Vilanova, R., & Visioli, A. (2012). PID control in the third millennium Read More
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