Mahmud Iwan Solihin

Fuzzy-tuned PID Anti-swing Control of Automatic Gantry Crane

Anti-swing control is a well-known term in gantry crane control. It is designed to move the payload of gantry crane as fast as possible while the payload swing angle should be kept as small as possible at the final position. A number of studies have proposed anti-swing control using the well-known proportional, integral, derivative (PID) control method. However, PID controllers cannot always effectively control systems with changing parameters. Some studies have also proposed intelligent-based control including fuzzy control. However, the designers often have to face the problem of tuning many parameters during the design to obtain optimum performance. Thus, a lot of effort has to be taken in the design stage. In this paper Fuzzy-tuned PID controller design for anti-swing gantry crane control is presented. The objective is to design a practical anti-swing control which is simple in the design and also robust. The proposed Fuzzy-tuned PID utilizes fuzzy system as PID gain tuners to achieve robust performance to parameters’ variations in the gantry crane. A complex dynamic analysis of the system is not needed. PID controller is firstly optimized in MATLAB using a rough model dynamic of the system which is identified by conducting a simple open-loop experiment. Then, the PID gains are used to guide the range of the fuzzy outputs of the Fuzzy-tuned PID controllers. The experimental results show that the proposed anti-swing controller has satisfactory performance. In addition, the proposed method is straightforward in the design.

Optimal PID controller tuning of automatic gantry crane using PSO algorithm

In this paper, a novel method for tuning PID controller of automatic gantry crane control using particle swarm optimization (PSO) is proposed. PSO is one of the most recent optimization techniques based on evolutionary algorithm. PSO is also known as computationally efficient method. This work presents in detail how to apply PSO method in finding the optimal PID gains of gantry crane system in the fashion of min-max optimization. The simulation results show that with proper tuning a satisfactory PID control performance can be achieved to drive nonlinear plant. The controller is able to effectively move the trolley of the crane in short time while canceling the swing angle of the payload hanging on the trolley at the end position. The robustness of the controller is also tested.

Objective function selection of GA-based PID control optimization for automatic gantry crane

Gantry cranes are widely used in various applications to transfer a payload from one position to desired position. Gantry crane system is an underactuated system where the number of inputs is less than the number of outputs. When the input signal is given to the actuator, the trolley starts to accelerate whilst causing a swing of payload hanging on a flexible cable. Many researchers have proposed anti-swing controls of gantry crane using PID+PD structure where PID controller is used for trolley positioning control and PD controller is used to dampen the swing oscillation. This is because of the simplicity of PID control structure. Some have combined intelligent methods such as fuzzy and neural networks to improve the performance of the proposed PID control structure. This paper discusses GA-based PID+PD controller tuning for automatic gantry crane system. The discussion is emphasized on the selection of the objective function since the objective function is the key to use the GA (genetic algorithm). The optimized PID gains would be mainly due to the appropriate objective/fitness function. The simulation results show that a good anti-swing control performance can be obtained from the proposed objective function.

Self-erecting inverted pendulum employing PSO for stabilizing and tracking controller

The main objective of this paper is to design a state feedback controller for stabilizing and tracking control of self-erecting inverted pendulum employing intelligent method using particle swarm optimization (PSO). This is motivated by the fact that one has to face trial and error approach in conventional feedback control design by pole placement method or linear quadratic regulator (LQR) method via Riccati equation. The simulation results show the effectiveness of the proposed method. The proposed state feedback controller works jointly with swing-up controller in the self-erecting inverted pendulum system.

Comparison of LQR and PSO-based state feedback controller for tracking control of a flexible link manipulator

In this paper, the state feedback control design problem for tracking control of a flexible link manipulator is considered. The calculation of state feedback control gains is conventionally handled by pole placement method or LQR method via Riccati equation. Unfortunately, they still possess trial and error approach of choosing some parameters. Particularly, choosing elements of Q and R matrices in the state feedback control using LQR method has to be done by trial. Therefore, an intelligent method to resolve this problem is proposed by adopting PSO algorithm. The experimental work is carried out to evaluate the effectiveness of the proposed method.

Fuzzy-tuned PID control design for automatic gantry crane

This paper discusses fuzzy-tuned PID controller design for anti-swing gantry crane control. The objective is employing simple structure of PID control by utilizing fuzzy system as gain tuners to improve its robustness to cope with parameters variations in the crane system. The proposed fuzzy-tuned PID system has simple structure. Instead of fixed PID gains, the gains are determined by means of a fuzzy inference system. Weighting factors are also added to fuzzy output. The simulation result shows that the proposed Fuzzy-tuned PID controllers has similar performance with PID controllers with advantage of robustness to parameters variations for anti-swing gantry crane control.

Sensorless anti-swing control of automatic gantry crane using Dynamic Recurrent Neural Network-based soft sensor

Sensor is an indispensable component in feedback control. In anti-swing feedback control of automatic gantry crane system, sensors are normally employed to detect trolley position and payload swing angle. However, sensing the payload motion of a real gantry crane, in particular, is troublesome and often costly since there is hoisting mechanism on parallel flexible cable. Therefore, sensorless anti-swing control method for automatic gantry crane system is proposed in this study. The anti-swing control is performed in feedback control scheme without using real swing angle sensor. Instead, soft sensor approach is used to substitute the real swing angle sensor. The soft sensor is designed based on Dynamic Recurrent Neural Network (DRNN) as a state estimator. Thus, a DRNN is trained using input-output data to estimate payload swing angle from trolley acceleration and input voltage of trolley actuator. An experimental study using lab-scale automatic gantry crane is carried out to evaluate the effectiveness of the proposed sensorless anti-swing control. The results show that the proposed sensorless method is effective for payload swing suppression since similar performance to the sensor-based feedback anti-swing control is obtained.

Robust PID anti-swing control of automatic gantry crane based on Kharitonov's stability

PID (proportional+integral+derivative) control is known as simple and easy-to-implement controller. However, the robustness performance is often not satisfactory when dealing with parameter variations of the plant. In addition, its design procedure is not straightforward for the system which is non-SISO (Singe Input Single Output) system like a gantry crane. In this paper, a stable robust PID controller for anti-swing control of automatic gantry crane is proposed. The proposed method employs Genetic Algorithm (GA) in min-max optimization to find the stable robust PID. In the optimization, the robustness of the controller is tested using Kharitonovs polynomials robust stability criterion to deal with parametric uncertainty appears in gantry crane model. For practicality, the model is identified by conducting simple open-loop experiment in the beginning. The experimental results show that a satisfactory robust PID control performance can be achieved. The controller is able to effectively move the trolley of the crane in short time while canceling the swing of the payload for different conditions of payload mass and cable length variations.

Development of Soft Sensor for Sensorless Automatic Gantry Crane Using RBF Neural Networks

To attain a good control performance of automatic gantry crane system, sensors are indispensable instrument for feedback signals. However, sensing the payload motion of a real gantry crane, particularly swing motion, is not easy and sometimes costly. Therefore, a sensorless automatic gantry crane system is developed and proposed in this paper. A soft sensor based on artificial neural network is introduced to eliminate the real sensor. Instead, a sensor measuring armature current of DC motor driving the cart is used to provide dynamic information for the soft sensor. A simulation study using dynamic model of lab-scale automatic gantry crane is carried out to evaluate the effectiveness of the proposed soft sensor. The results show that the soft sensor can estimate effectively the unmeasured state. Moreover, the proposed method has robustness to deal with parameter variations

Robust controller design for uncertain parametric systems using modern optimization approach

This paper presents a robust feedback controller design for parametric uncertainty systems via constrained optimization. The proposed controller design employs modern optimization tools (Particle Swarm Optimization and Differential Evolution) in a single objective constrained optimization. The objective of the optimization is to search for a set of robust controller gains such that the stability radius of the closed-loop system is maximized. The constraint of the optimization is a closed-loop poles region which is directly related to the desired time-domain control performance. The proposed controller design is applied to control of pendulum-like systems (gantry crane, flexible joint and inverted pendulum). The results show the robust performance of the designed controller.