Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals.
Cerebellar model articulation controller neural networks is one of the computational intelligence tools that can be applied for modeling, classification, and control. Proportional velocity controller is a servo-type controller, which is commonly applied to motion control systems. This paper presents a novel combination of cerebellar model articulation controller neural networks and optimal proportional velocity controller. A simple mathematical model for applying and studying cerebellar model articulation controller is introduced, and a study of its parameters is presented individually. The effect of parameters variation on cerebellar model articulation controller performance is identified. Learning algorithms highly affect the cerebellar model articulation controller behavior even when the parameters are optimized, and proper selection of the learning scheme must be taken under consideration. Three different learning algorithms are studied for evaluating transient and steady-state cerebellar model articulation controller responses. The results showed that the change of cerebellar model articulation controller generalization size and scale of the control signal has a marked effect on the performance of cerebellar model articulation controller. Furthermore, the constant learning rate algorithm gives the best overall performance.
Computer numerical control (CNC) involves machines controlled by electronic systems designed to accept numerical data and other instructions, usually in a coded form. CNC machines are more productive than conventional equipment and consequently produce parts at less cost and higher accuracy even when the higher investment is considered. This article proposes an educational scheme for designing a CNC machine for drilling printed circuit boards (PCB) holes with small diameters. The machine consists of three-independently move-fully controlled tables. Output pulses from the personal computer (PC) parallel port are used to control the machine after processing by an interface card. A flexible, responsive and real-time visual C # program is developed to control the motion of the stepper motors. The educational scheme proposed in this article can provide engineers and students in academic institutions with a simple foundation to efficiently build a CNC machine based on the available resources.
Computer Numerical Control (CNC) is a technology that converts coded instructions and numerical data into sequential actions that describe the motion of machine axes or the behavior of an end effector. Nowadays, CNC technology has been introduced to different stages of production, such as rapid prototyping, machining and finishing processes, testing, packaging, and warehousing. The main objective of this chapter is to introduce a methodology for design and implementation of a simple and low-cost educational CNC prototype. The machine consists of three independent axes driven by stepper motors through an open-loop control system. Output pulses from the parallel port of Personal Computer (PC) are used to drive the stepper motors after processing by an interface card. A flexible, responsive, and real-time Visual C# program is developed to control the motion of the machine axes. The integrated design proposed in this chapter can provide engineers and students in academic institutions with a simple foundation to efficiently build a CNC machine based on the available resources. Moreover, the proposed prototype can be used for educational purposes, demonstrations, and future research.
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