Measurements, Models, Systems and Design

531 s.

Discrete-time sliding mode control of high precision linear drive using frictional model

The paper deals with high precision motion control of linear drive system. The accuracy and behavior of the linear drive system are highly affected by the non-linear frictional component compromising of stiction, viscous and stribeck effect present in the system especially in the vicinity of zero velocity. In order to achieve the high accuracy and motion it is mandatory to drive our system with low velocity resulting in many non linear phenomena like tracking error, limit cycles and undesired stick-slip motion etc. This paper discuss the design and implementation of discrete time sliding mode control along with the implementation of dynamic frictional model in order to estimate and compensate the disturbance arising due to frictional component. Experimental results are presented to illustrate the effectiveness and achievable control performance of the proposed scheme

Design and Implementation of Internal Model Based Controllers for DC/ AC Power Converters

The aim of this thesis is to design and implement an advanced control system for a working three-phase DC to AC power converter. Compared to' the traditional PI controller used widely in industry, the new voltage controller can track the reference voltage with improved accuracy and efficiency in the presence of different kind of local loads, and also works well in the single phase voltage control. This voltage controller is combined with a power controller to yield a complete controller. An important aspect of this work is the hardware implementation of the whole system. Main parts ofthis thesis are: ???????? 1. Review ofH-infinity and repetitive control techniques and their applications in power converters. 2. Design of a new voltage controller to eliminate the DC component in the output voltages, and taking into account the practical issues such as the processing delay due to the digital signal processor (DSP) implementation. 3. Modelling and simulation of the converter system incorporating different control techniques and with different kinds of loads. 4. Hardware implementation and the two-processor controller. The parallel communication between the DSPs. 5. The main problems encountered in???????????????????? hardware implementation and programming. The software used to initialize DSPs, implement the discretetime voltage controller and other functions such ~ generations of space vector pulse width modulation (SVPWM) signals, circuit protections, analog to digital (AD) cOl)versions, data transmission, etc. 6. Experimental results the under circumstances of no load connected to the converter, pure three-phase resistive loads, three-phase unbalanced resistive' loads and the series resistor-inductor loads. /Imperial Users onl

A new approach for designing self-organizing systems and application to adaptive control

There is tremendous interest in the design of intelligent machines capable of autonomous learning and skillful performance under complex environments. A major task in designing such systems is to make the system plastic and adaptive when presented with new and useful information and stable in response to irrelevant events. A great body of knowledge, based on neuro-physiological concepts, has evolved as a possible solution to this problem. Adaptive resonance theory (ART) is a classical example under this category. The system dynamics of an ART network is described by a set of differential equations with nonlinear functions. An approach for designing self-organizing networks characterized by nonlinear differential equations is proposed

Comparative performance of intelligent algorithms for system identification and control

This paper presents an investigation into the comparative performance of intelligent system identification and control algorithms within the framework of an active vibration control (AVC) system. Evolutionary Genetic algorithms (GAs) and Adaptive Neuro-Fuzzy Inference system (ANFIS) algorithms are used to develop mechanisms of an AVC system, where the controller is designed based on optimal vibration suppression using the plant model. A simulation platform of a flexible beam system in transverse vibration using finite difference (FD) method is considered to demonstrate the capabilities of the AVC system using GAs and ANFIS. MATLAB GA tool box for GAs and Fuzzy Logic tool box for ANFIS function are used to design the AVC system. The system is men implemented, tested and its performance assessed for GAs and ANFIS based algorithms. Finally, a comparative performance of the algorithms in implementing system identification and corresponding AVC system using GAs and ANFIS is presented and discussed through a set of experiments

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

This study aims to develop an expert system implementation of P controller and fuzzy logic controller to address issues related to improper control input estimation, which can arise from incorrect gain values or unsuitable rule-based designs. The research focuses on improving the control input adaptation by using an expert system to resolve the adjustment issues of the P controller and fuzzy logic controller. The methodology involves designing an expert system that captures error signals within the system and adjusts the gain to enhance the control input estimation from the main controller. In this study, the P controller and fuzzy logic controller were regulated, and the system was tested using step input signals with small values and larger than the saturation limit defined in the design. The PID controller used CHR tuning to least overshoot, determining the system's gain. The tests were conducted using different step input values and saturation limits, providing a comprehensive analysis of the controller's performance. The results demonstrated that the adaptive fuzzy logic controller performed well in terms of %OS and settling time values in system control, followed by the fuzzy logic controller, adaptive P controller, and P controller. The adaptive P controller showed similar control capabilities during input saturation, as long as it did not exceed 100% of the designed rule base. The study emphasizes the importance of incorporating expert systems into control input estimation in the main controller to enhance the system efficiency compared to the original system, and further improvements can be achieved if the main processing system already possesses adequate control ability. This research contributes to the development of more intelligent control systems by integrating expert systems with P controllers and fuzzy logic controllers, addressing the limitations of traditional control systems and improving their overall performance

Design of cross-coupled CMAC for contour-following – a reinforcement-based ILC approach

One of the most popular applications of a bi-axial motion stage is precision motion control. The reduction of tracking error and contour error is one of the most coveted goals in precision motion control systems. The accuracy of a motion control system is often affected by external disturbances. In addition, system non-linearity such as friction also represents a major hurdle to motion precision. In order to deal with the aforementioned problem, this paper proposes a fuzzy logic-based Reinforcement Iterative Learning Control (RILC) and a Cross-Coupled Cerebellar Model Articulation Controller (CCCMAC). In particular, the proposed fuzzy logicbased RILC and a LuGre friction model-based compensation approach are exploited to improve motion accuracy. The fuzzy logic-based RILC aims at reducing tracking error and compensating for external disturbance, while the LuGre friction model is responsible for friction compensation. In addition, the CCCMAC consisting of a cerebellar model articulation controller and a cross-coupled controller aims at reducing contour error and dealing with the problem of dynamics mismatch between different axes. Performance comparisons between the proposed fuzzy logic-based Reinforcement Iterative Learning Cross-Coupled Cerebellar Model Articulation Controller (RIL–CCCMAC) and several existing control schemes are conducted on a bi-axial motion stage. Experimental results verify the effectiveness of the proposed RIL–CCCMAC

Dual Design PID Controller for Robotic Manipulator Application

This research introduces a dual design proportional–integral–derivative (PID) controller architecture process that aims to improve system performance by reducing overshoot and conserving electrical energy. The dual design PID controller uses real-time error and one-time step delay to adjust the confidence weights of the controller, leading to improved performance in reducing overshoot and saving electrical energy. To evaluate the effectiveness of the dual design PID controller, experiments were conducted to compare it with the PID controller using least overshoot tuning by Chien–Hrones–Reswick (CHR)  technique. The results showed that the dual design PID controller was more effective at reducing overshoot and saving electrical energy. A case study was also conducted as part of this research, and it demonstrated that the system performed better when using the dual design PID controller. Overshoot and electrical energy consumption are common issues in systems that can impact performance, and the dual design PID controller architecture process provides a solution to these issues by reducing overshoot and saving electrical energy. The dual design PID controller offers a new technique for addressing these issues and improving system performance. In summary, this research presents a new technique for addressing overshoot and electrical energy consumption in systems through the use of a dual design PID controller. The dual design PID controller architecture process was found to be an effective solution for reducing overshoot and saving electrical energy in systems, as demonstrated by the experiments and case study conducted as part of this research. The dual design PID controller presents a promising solution for improving system performance by addressing the issues of overshoot and electrical energy consumption