Optimizing the Gains of PD controller Using Artificial Bee Colony for Controlling the Rigid Gantry Crane System

Control position and reduction of swinging of the payload of a rigid gantry crane system is a challenging work because of under-actuated system. This paper addresses challenges by proposing the artificial bee colony (ABC) algorithm to optimize the gains of the PD controller to form what the so-called the artificial bee colony (ABC)-PD controller. The effectiveness of the proposed control algorithm is tested under constant step functions and compared with Ziegler-Nichols (ZN)-PD controller. The results show that the proposed controller produces slower rise time and peak time, but faster settling time than the ZN-PD controller as well as no overshoot under the predefined trajectories.  Â

Mathematical Modeling of a Moving Planar Payload Pendulum on Flexible Portal Framework

Mathematical modeling of a moving planar payload pendulum on elastic portal framework is presented in this paper. The equations of motion of such a system are obtained by modeling the portal frame using finite element in conjunction with moving finite element method and moving planar payload pendulum by using Lagrange's equations. The generated equations indicate the presence of nonlinear coupling between dynamics of portal framework and the payload pendulum. The combinational direct numerical integration technique, namely Newmarkand fourth-order Runge-Kutta method, is then proposed to solve the coupled equations of motion. Several numerical simulations are performed and the results are verified with several benchmarks. The results indicate that the amplitude and frequency of the payload pendulum swing angle are greatly affected by flexibility of structure and the cable in term of carriage speed

Optimizing the Gains of PD Controller Using Artificial Bee Colony for Controlling the Rigid Gantry Crane System

Control position and reduction of swinging of the payload of a rigid gantry crane system is a challenging work because of under-actuated system. This paper addresses challenges by proposing the artificial bee colony (ABC) algorithm to optimize the gains of the PD controller to form what the so-called the artificial bee colony (ABC)-PD controller. The effectiveness of the proposed control algorithm is tested under constant step functions and compared with Ziegler-Nichols (ZN)-PD controller. The results show that the proposed controller produces slower rise time and peak time, but faster settling time than the ZN-PD controller as well as no overshoot under the predefined trajectories

Penerapan Kendali Cerdas Pada Sistem Tangki Air Menggunakan Logika Fuzzy

Implementasi kendali cerdas pada sistem tangki air menggunakan logic fuzzy disajikan pada makalah ini. Sistem tangki air yang merupakan sistem yang dikontrol adalah suatu model dari proses kontrol dengan sensor tunggal dan aktuator tunggal. Kendali logik Fuzzy sebagai kendali cerdas pada penelitian ini didisain dan diimplementasikan untuk membuat ketinggian air mengikuti Perubahan ketinggian air acuan secepat mungkin dan mempertahankan ketinggian air sedekat mungkin dengan ketinggian air acuan, dibawah variasi lingkungan. Proses disain dari kontrol logik fuzzy dilakukan menggunakan nilai error (e) dan beda error (de) ketinggian air diukur oleh sensor sedangkan keluaran kendali adalah input tegangan untuk mensupply motor pompa (u). Secara matematik, operasi fuzzy set dan aturan fuzzy diberlakukan pada input dan ouput ini untuk meminimalisasi harga error dan Perubahan error. Dari hasil eksperimen, kendali logik fuzzy mempunyai 7 set fuzzy untuk input error, 3 fuzzy set untuk Perubahan error dan 21 aturan fuzzy untuk aksi kendali. Eror “steady state” yang dihasilkan lebih kecil 37.5% dari pengendali konvensional PI/Proporsional dan Integral (sebagai pengendali pembanding). Untuk respon dari variasi ketinggian air, kendali logik fuzzy cukup cepat tetapi lebih lambat 55.5% dari pengendali PI.The implementation of intelligent controller on water tank system using fuzzy logic was discussed in this paper. Water tank system, which was controlled system in this research, was a model of process control with single sensor and single actuator (Single Input Single Output). Fuzzy logic controller as intelligent controller in this research were designed and implemented for making water level follow the reference water level change as fast as possible and keeping water level close to the reference water level under variation of environment. The design of fuzzy logic controller was conducted by using input value of error (e) and difference of error (de) water level were measured by sensor and the output of controller was input voltage to supply pump motor (u). Mathematically, fuzzy set operation and fuzzy rules were conducted to this input and ouput to minimize value of error and difference of error. From experiment results, fuzzy logic controller has 7 fuzzy set for error input, 3 fuzzy set for change of error and 21 fuzzy rules for control action. Steady state error was 37.5% smaller than PI/Proporsional and IntegraI controller (as reference controller). For respon of water level variation, fuzzy logic controller was fast enough, but 55.5% slower than PI controller

DYNAMICS AND CONTROL OF FLEXIBLE GANTRY CRANE SYSTEM

Gantry crane system, a non-slewing-luffing crane system is most widely used in many work places. However, the heavier lifting capacities and the greater size of gantry crane, the vibrational motion become more significant during crane operations and it must be considered. The equations of motion of the system can be obtained by modeling the crane framework using finite element in conjuction with moving finite element method and gantry crane by using Lagrange’s equations. The combinational direct integration technique, namely Newmark- and fourth-order Runge-Kutta method is proposed to solve the coupled equations of motion. Numerical simulation results show that the combination of flexibility of crane framework and hoist cable produces greater amplitudes and lower swing angles frequency compared to the gantry crane system with flexible hoist cable or crane framework only with respect to the rigid model. Furthermore, all the flexible models of gantry crane system have lower frequencies in the time histories of swing angles of payload with respect to the rigid model for all the parametric studies. The trends of maximum displacements of crane framework and hoist cable increase with the increase of payload mass and initial swing angle of payload. The increases are slightly linear for payload mass and nonlinear for initial swing angle of payload. Under the increase of structural damping, hoist cable stiffness, cross-sectional dimensions of crane framework and hoist cable length, the trends decrease for all the maximum displacements. Control simulations clearly demonstrate that Zero-Vibration-Derivative-Derivative (ZVDD), Fuzzy Logic Controller (FLC) and Proportional-Integral-Derivative (PID) controllers have rough fluctuations in controlling flexible gantry crane with respect to their performances in controlling the rigid model of gantry crane. Compared to FLC and PID, ZVDD has larger steady state error

PERFORMANCE ANALYSIS OF PSO-PD CONTROLLER IN CONTROLING THE RIGID GANTRY CRANE SYSTEM

Karya tulis ini membahas tentang algoritma particle swarm optimization (PSO) untuk mengoptimalkan penguat pengendali PD yang dinamakan pengendali PSO-PD. Efektivitas algoritma pengendali yang diusulkan diuji dengan menggunakan fungsi step dan dibandingkan dengan pengendali PD berbasis Zigler-Nichols (ZN-PD). Hasil simulasi yang didapatkan menunjukkan bahwa pengendali PSO-PD menghasilkan waktu naik dan waktu puncak yang lebih lambat dibandingkan dengan pengendali ZN-PD, tetapi memiliki waktu tunak yang lebih cepat dan nilai overshoot yang kecil di bawah trayektori yang didefinisikan.Kata kunci: Sistem gantry crane, PSO, Gain PD, Sudut ayunan AbstractThis paper presents the particle swarm optimization (PSO) algorithm to optimize the gains of the PD controller to form what so-called the particle swarm optimization (PSO-PD) controller. The effectiveness of the proposed control algorithm is tested under constant step function and compared with Ziegler-Nichols (ZN-PD) controller. Simulation results show that proposed controller has slower rise time and peak time than ZN-PD controller as well as small overshoot under the predefined trajectories

Numerical investigation of the effect of ocean depth variations on the dynamics of a ship mounted two-DoF manipulator system

The dynamics of a ship need to be considered in the development of a manipulator system that will be applied to the ocean-based operation. This paper aims to investigate the effect of ocean depth variations on the ship motion as disturbances to a ship-mounted two-DoF (Degrees of Freedom) manipulator joint torque using an inverse dynamics model. Realization is conducted by deriving the mathematical model of a two-DoF manipulator system subject to six-DoF ship motion, which is derived by using Lagrange-Euler method. It is then combined with numerical hydrodynamic simulation to obtain the ship motions under ocean depth variations, such as shallow (50 m), intermediate (750 m), and deep (3,000 m) waters. Finding results show that randomness of the ship motions appears on the manipulator joint torque. In the azimuth link, maximum joint torque is found in shallow water depth with an increment of 8.271 N.m (285.69 %) from the undisturbed manipulator. Meanwhile, the maximum joint torque of the elevation link is found in intermediate water depth with an increment of 53.321 N.m (6.63 %). However, the difference between depth variations is relatively small. This result can be used as a baseline for sizing the electrical motor and developing the robust control system for the manipulator that is mounted on the ship by considering all ocean depth conditions

Cascade Optimization of an Axial-Flow Hydraulic Turbine Type Propeller by a Genetic Algorithm

This study proposes the use of the genetic algorithm (GA) method in hydraulic turbine optimization for renewable energy applications. The algorithm is used to optimize the performance of a two-dimensional hydrofoil cascade for an axial-flow hydraulic turbine. The potential flow around the cascade is analyzed using the surface vorticity panel method, with a modified coupling coefficient to deal with the turbine cascade. Each section of the guide vane and runner blade hydrofoil cascade is optimized to satisfy the shock-free criterion, which is the fluid dynamic ideal to achieve minimum profile losses. Comparison is also made between the direct and random switching methods for the GA crossover operator. The optimization results show that the random switching method outperforms the performance of the direct switching method in terms of the resulting solutions, as well as in terms of the computational time required to reach convergence. As an alternative to experimental trials, the performance of both turbine designs are predicted and analyzed using the three-dimensional computational fluid dynamics (CFD) approach under several operating conditions. The simulation results show that the optimized design, which is obtained by applying the shock-free criterion using the GA, successfully improves the performance of the initial turbine design

SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS

This study presents the identification of slow drift motions of floating structures from model test data. To compute the slow drift motions, nonlinear and nonstationary system identification which exploits the concept of a state-space based time domain input-ouput models is proposed, comprising the time-varying nonlinear autoregressive with exogenous input (TVNARX) and Volterra models. Three steps of improvements had been made to increase the modeling capacity of input-output models. The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods

Mathematical Modeling of a Moving Planar Payload Pendulum on Flexible Portal Framework

Mathematical modeling of a moving planar payload pendulum on elastic portal framework is presented in this paper. The equations of motion of such a system are obtained by modeling the portal frame using finite element in conjunction with moving finite element method and moving planar payload pendulum by using Lagrange’s equations. The generated equations indicate the presence of nonlinear coupling between dynamics of portal framework and the payload pendulum. The combinational direct numerical integration technique, namely Newmarkand fourth-order Runge-Kutta method, is then proposed to solve the coupled equations of motion. Several numerical simulations are performed and the results are verified with several benchmarks. The results indicate that the amplitude and frequency of the payload pendulum swing angle are greatly affected by flexibility of structure and the cable in term of carriage speed.