Discrete-Time Sliding Mode Control with Integral Compensation of Output Error

In this paper, a simple new design method of the sliding mode control based on the integral compensation of an output error is described. The key to this method is to obtain a control with a switching function. The proposed linear control input is robust against plant parameter deviations and external disturbances. We confirmed the effectiveness of the proposed method through simulation of a second and a third order plant

Optimal Speed Control for Direct Current Motors Using Linear Quadratic Regulator

Direct Current (DC) motors have been extensively used in many industrial applications. Therefore, the control of the speed of a DC motor is an important issue and has been studied since the early decades in the last century. This paper presents a comparison of time response specification between conventional Proportional-Integral-Derivatives (PID) controller and Linear Quadratic Regulator (LQR) for a speed control of a separately excited DC motor. The goal is to determine which control strategy delivers better performance with respect to DC motor’s speed. Performance of these controllers has been verified through simulation using MATLAB/SIMULINK software package. According to the simulation results, liner quadratic regulator method gives the better performance, such as settling time, steady state error and overshoot compared to conventional PID controller. This shows the superiority of liner quadratic regulator method over conventional PID controlle

Modelling of an electro-hydraulic actutor using extended adaptive distance gap statistic approach

The existence of high degree of non-linearity in Electro-Hydraulic Actuator (EHA) system has imposed a challenging task in developing its model so that effective control algorithm can be proposed. In general, there are two modelling approaches available for EHA system, which are the dynamic equation modelling method and the system identification modelling method. Both approaches have disadvantages, where the dynamic equation modelling is hard to apply and some parameters are difficult to obtain, while the system identification method is less accurate when the system’s nature is complicated with wide variety of parameters, nonlinearity and uncertainties. This thesis presents a new modelling procedure of an EHA system by using fuzzy approach. Two sets of input variables are obtained, where the first set of variables are selected based on mathematical modelling of the EHA system. The reduction of input dimension is done by the Principal Component Analysis (PCA) method for the second set of input variables. A new gap statistic with a new within-cluster dispersion calculation is proposed by introducing an adaptive distance norm in distance calculation. The new gap statistic applies Gustafson Kessel (GK) clustering algorithm to obtain the optimal number of cluster of each input. GK clustering algorithm also provides the location and characteristic of every cluster detected. The information of input variables, number of clusters, cluster’s locations and characteristics, and fuzzy rules are used to generate initial Fuzzy Inference System (FIS) with Takagi-Sugeno type. The initial FIS is trained using Adaptive Network Fuzzy Inference System (ANFIS) hybrid training algorithm with an identification data set. The ANFIS EHA model and ANFIS PCA model obtained using proposed modelling procedure, have shown the ability to accurately estimate EHA system’s performance at 99.58% and 99.11% best fitting accuracy compared to conventional linear Autoregressive with External Input (ARX) model at 94.97%. The models validation result on different data sets also suggests high accuracy in ANFIS EHA and ANFIS PCA model compared to ARX model

An approach to design of digital sliding mode control for DC-DC converters

The primary goal of research in this Ph.D. dissertation is to investigate the possibilities of application of modern control methods in controlling the output voltage of the DC-DC converters (buck, boost) in order to ensure the system robustness to the input voltage and load variations. This dissertation deals with the analysis and application of sliding mode control algorithms in the synthesis of these converters in order to improve the properties of existing converters and to modify them, as well as to adjust and tune the digital sliding mode controls based on the input-output plant model to be applicable in these converters. The design procedure is based on the converter models given in the form of discrete transfer functions. The proposed control for converters is a combination of the digital sliding mode control and (generalized) minimum variance control techniques. The problem caused by an unstable zero of the boost converter, which prevents the direct control of the output voltage of this converter, has been overcome by introducing the generalized minimum variance control. Also, only the output voltage of converter must be measured for the realization of the proposed control, so there is no need for an additional current sensor. This dissertation includes the modification of the developed algorithms with the aim of applying them to low-cost, standard 8- bit microcontrollers. Finally, the efficiency of the proposed solutions is verified by digital simulation and a series of experiments on the laboratory developed prototypes of both converters, as well as by their comparative analysis. The satisfactory experimental results are obtained regarding the typical characteristics of the converters