Fuzzy control of parabolic antenna with friction compensation

In this paper a fuzzy logic controller was developed for a parabolic dish antenna system. Friction is one of the disturbances associated such systems and was represented with dead zone in the Simulink block. The effect of the disturbance due to the friction was investigated by simulation using Simulink/MATLAB 2012a software. The results obtained from the system with the fuzzy logic controller were compared with the ones obtained with equivalent proportional derivative controller and it showed that with the fuzzy logic controller the system had better performance and also demonstrates its ability to reduce the effect of friction in parabolic antenna dish systems and most likely other nonlinearities in such systems

Fuzzy control of parabolic antenna with backlash compensation

A fuzzy logic based controller (FLC) was proposed for position control of a parabolic dish antenna system with the major aim of eradicating the effect backlash disturbance which may be present in the system. The disturbance is nonlinear and is capable of generating steady state positional errors. Simulation results obtained using SIMULINK/MATLAB 2012a were compared with those obtained when the controller was proportional-derivative controller (PDC). The fuzzy controller portrays that it has the capability of reducing the noise due to backlash and possibly others more than the proportional-derivative controller

Design of QFT-based self-tuning deadbeat controller

This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. Nevertheless, usually there are large peaks in the deadbeat response.By integrating QFT specifications into deadbeat algorithm, the large peaks could be tolerated. On the other hand, emerging QFT with adaptive element will produce a robust controller with wider coverage of uncertainty. By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called self tuning QFT-based deadbeat controller could be achieved. The output response that is fast, robust and adaptive is expected. Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. Grain drying process is very complex with highly nonlinear behaviour, long delay, affected by environmental changes and affected by disturbances. Performance comparisons have been performed between the proposed self-tuning QFT-based deadbeat, standard QFT and standard dead-beat controllers. The efficiency of the self-tuning QFT based dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant

Improvement of data refresh rate for dual serial port to universal serial bus acquisition system

Before the Universal Serial Bus (USB) Technologies has become popular, there are a lot of software and hardware computer peripheral development based on traditional external interface like General Purpose Interface Bus (GPIB- IEEE488), parallel port, serial port and PS/2. Developing these custom software and hardware computer peripheral is less difficult as compared to peripheral that is designed based on USB. The main reason for the difficulty is that the USB is designed to be user friendly but not developer friendly. For that reason, many developers will maintain using the traditional port when designing their custom application. To support traditional interface on newer PC with only USB port, there are devices in the market to convert the old external port to USB. One of the converters is the USB to dual serial converter. In the market, there are products which are readily available. However, it lacks of certain capability such as the ability to access serial port simultaneously which reduce the data refresh rate. The main purpose of this paper is to discuss technique in designing a USB to serial converter with capability of connecting two serial devices which is accessible simultaneously to improve the data refresh rate

Application of optimized higher order sliding mode control on MEMS optical switch

MEMS optical switches are used in optical networks in order to provide the desired bandwidth. This paper presents the results of an optimised Higher Order Sliding Mode (HOSM) position controller design. The algorithm requires time derivatives of the sliding variable. A Robust Exact Differentiator is used to estimate time derivatives of the sliding variable. A novel application of Particle Swarm Optimization (PSO) is introduced for optimal tuning of the HOSM controller. Robustness of the controller is investigated and the performance is compared with that obtained by a First Order Sliding Mode (FOSM) controller

Stability study of model predictive control in presence of undesirable factors.

In this study, the stability behavior of Generalized Predictive Controllers (GPC) as one of model predictive control algorithm is studied and effects of noise, error in delay estimation, input disturbances, unstable system and non-minimum phase system is analyzed. The results showed that GP-controller can be achieved stability and resist against wrong parameterization. This stability studies is completed by means of a numerical example. The results show that the GP algorithm can guarantee the stability of this system

Design of combined robust controller for a pneumatic servo actuator system with uncertainty

In this paper the position control design of a pneumatic servo actuator system using a combined H-inf /QFT technique is presented. First, an H-inf controller is designed to assure robust stability for the system. Particle swarm optimization (PSO) algorithm is used to tune the weighting functions. This method is used to find the optimal values of weighting functions parameters that lead to obtain an optimal H-inf-controller by minimizing the infinity norm of the transfer function of the nominal closed loop system. The quantitative feedback theory (QFT) is used to enhance the closed loop system performance. A multiplicative unstructured model extracted from the parametric uncertainty is used for control design. Finally, the simulation results are presented and compared with previous work

Analytical formulation of the integral square error for linear stable feedback control system

The paper aims to introduce a method for the analytical formulation of the integral square error (ISE). In this manner, the aim of the research is to create a parametric solution of the ISE for linear continuous feedback control systems while the closed-loop system is stable and the difference between reference and output, or error, is strictly proper. The potential advantage of this technique is that it allows the finding of an analytical solution for the ISE criterion and hence it is well adopted when a parametric solution of the ISE for optimal control problems is needed. This method is also superior to the numerical methods, because it returns the exact solution of the ISE. Comparisons with a powerful numerical method are given to validate the proposed method

A genetically trained simplified ANFIS controller to control nonlinear MIMO systems

This paper presents a simplified ANFIS (Adaptive Neuro-Fuzzy Inference System) structure acting as a PID-like feedback controller to control nonlinear multi-input multi-output (MIMO) systems. Only few rules have been utilized in the rule base of this controller to provide the control actions, instead of the full combination of all possible rules. As a result, the proposed controller has several advantages over the conventional ANFIS structure particularly the reduction in execution time without sacrificing the controller performance, and hence, it is more suitable for real time control. In addition, the real-coded genetic algorithm (GA) has been utilized to train this MIMO ANFIS controller, instead of the hybrid learning methods that are widely used in the literature. Consequently, the necessity for the teaching signal required by other techniques has been eliminated. Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. To demonstrate the accuracy and the generalization ability of the proposed controller, two nonlinear MIMO systems have been selected to be controlled by this controller. In addition, this controller robustness to output disturbances has been also evaluated and the results clearly showed the remarkable performance of this MIMO controller