H∞ Controller with Graphical LMI Region Profile for Gantry Crane System

This paper presents investigations into the development of H∞ controller with pole clustering based on LMI techniques to control the payload positioning of INTECO 3D crane system with very minimal swing. The linear model of INTECO 3D crane system is obtained using the system identification process. Using LMI approach, the regional pole placement known as LMI region combined with design objective in H∞ controller guarantee a fast input tracking capability, precise payload positioning and very minimal sway motion. A graphical profile of the transient response of crane system with respect to pole placement is very useful in giving more flexibility to the researcher in choosing a specific LMI region. The results of the response with the controllers are presented in time domains. The performances of control schemes are examined in terms of level of input tracking capability, sway angle reduction and time response specification. Finally, the control techniques is discussed and presented

An accurate pattern classification for empty fruit bunch based on the age profile of oil palm tree using neural network

This paper proposes an efficient method for pattern classification system of empty fruit bunch (EFB) by using a neural network technique. The main advantage of this method is the accuracy and speed of algorithm such that it can be computed rapidly with the proposed system. To test the effectiveness of the proposed method, 120 of EFB’s data with different ages and length that been obtained from Malaysian Palm Oil Board (MPOB) are use in the pattern classification process. In addition, there  are three classes of EFB in this system, which are Class 1 (less than 7 year old), Class 2 (8 to 17 year old) and Class 3 (more than 17 year old). It is envisaged that the proposed method is very useful in classifying the EFB and  90% of the sample parameters are successfully classified to its class

Simple Pole Placement Controller for Elastic Joint Manipulator

This paper presents investigations into the development of simple pole placement controller for tip angular position tracking and deflection reduction of an elastic joint manipulator system. A Quanser elastic joint manipulator is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. The pole placement controller is designed based on integral state feedback structure and the feedback gain is computed based on the desired time response specifications of tip angular position. The proposed control scheme is also compared with a hybrid Linear Quadratic Regulator (LQR) with input shaper control scheme. The performances of the control schemes are assessed in terms of tip angular tracking capability, level of deflection angle reduction and time response specifications. Finally, a comparative assessment of the control techniques is presented and discussed

A Modified Grey Wolf Optimizer For Improving Wind Plant Energy Production

The main problem of existing wind plant nowadays is that the optimum controller of single turbine degrades the total energy production of wind farm when it is located in a large wind plant. This is owing to its greedy control policy that can not cope with turbulence effect between turbines. This paper proposes a Modified Grey Wolf Optimizer (M-GWO) to improvise the controller parameter of an array of turbines such that the total energy production of wind plant is increased. The modification employed to the original GWO is in terms of the updated mechanism. This modification is expected to improve the variation of exploration and exploitation rates while avoiding the premature convergence condition. The effectiveness of the M-GWO is applied to maximize energy production of a row of ten turbines. The model of the wind plant is derived based on the real Horns Rev wind plant in Denmark. The statistical performance analysis shows that the M-GWO provides the highest total energy production as compared to the standard GWO, Particle Swarm Optimization (PSO) and Safe Experimentation Dynamics (SED) methods

A modified grey wolf optimizer for improving wind plant energy production

The main problem of existing wind plant nowadays is that the optimum controller of single turbine degrades the total energy production of wind farm when it is located in a large wind plant. This is owing to its greedy control policy that can not cope with turbulence effect between turbines. This paper proposes a Modified Grey Wolf Optimizer (M-GWO) to improvise the controller parameter of an array of turbines such that the total energy production of wind plant is increased. The modification employed to the original GWO is in terms of the updated mechanism. This modification is expected to improve the variation of exploration and exploitation rates while avoiding the premature convergence condition. The effectiveness of the M-GWO is applied to maximize energy production of a row of ten turbines. The model of the wind plant is derived based on the real Horns Rev wind plant in Denmark. The statistical performance analysis shows that the M-GWO provides the highest total energy production as compared to the standard GWO, Particle Swarm Optimization (PSO) and Safe Experimentation Dynamics (SED) methods

A modified sine cosine algorithm for improving wind plant energy production

This paper presents a Modified Sine Cosine Algorithm (M-SCA) to improve the controller parameter of an array of turbines such that the total energy production of wind plant is increased. The two modifications employed to the original SCA are in terms of the updated step size gain and the updated design variable equation. Those modifications are expected to enhance the variation of exploration and exploitation rates while avoiding the premature convergence condition. The effectiveness of the M-SCA is applied to maximize energy production of a row of ten turbines. The statistical performance analysis shows that the M-SCA provides the highest total energy production as compared to other existing methods

The Vehicle Steer by Wire Control System by Implementing PID Controller

The latest technology of vehicle steer-by-wire (VSBW) system has promised significant improvement in vehicle safety, dynamics, stability, comfort and maneuverability. Due to complete separation between steering wheel and the front wheels gives the practical problems for steering control especially on directional control and wheel synchronization of vehicle. This paper presents investigations into the development of PID control scheme for directional control and wheel synchronization of a VSBW system. Two PID controllers are used to control the steering wheel angle and front wheel angle. The PID controllers use the front wheel tracking error to generate controlled steering angle. The Ziegler Nichols method is used for tuning the PID parameters. The implementation environment is developed within Matlab/Simulink software for evaluation of performance of the control scheme. Implementation results of the response of the VSBW system with the PID controller are presented in time domains. The performances of control schemes are examined in terms of input tracking capability, wheel synchronization and time response specifications with the absence of disturbances

Single Input Fuzzy Logic Controller For Liquid Slosh Suppression

The chaotic nature of liquid slosh and the complex fluid dynamic motion in the container makes the traditional model-based control techniques complex and difficult to synthesize in practice. This paper presents investigations into the development of single input fuzzy logic controller (SIFLC) for liquid slosh control. The proposed approach, known as the SIFLC, reduces the conventional two-input FLC (CFLC) to a single input single output (SISO) controller. Two parallel SIFLC are developed for both lateral tank position and liquid slosh angle control. With the purpose to confirm the design of control scheme, a liquid slosh model is considered to represent the lateral slosh motion. The performances of the control schemes are accessed in terms of lateral tank tracking capability, level of liquid slosh reduction and time response specifications. Supremacy of the proposed approach is shown by comparing the results with hybrid model-free Fuzzy-PID controller with derivative filter (PIDF). Finally, it is seen from the simulation results that the proposed control scheme has able to reduce the liquid slosh without unambiguously model the liquid slosh behavior

A fractional order PID tuning tool for automatic voltage regulator using marine predators algorithm

The fractional-order proportional-integral-derivative (FOPID) controller stands as a widely embraced choice for the task of automatic voltage regulation (AVR) when it comes to maintaining the voltage output of synchronous generators. Nevertheless, fine-tuning the FOPID controller presents a formidable challenge, mainly because it possesses five tuning gains, in contrast to the conventional PID controller, which has three gains. Consequently, this paper introduces a novel tuning tool tailored to the AVR system by utilizing the marine predators algorithm (MPA). To gauge the effectiveness of the proposed approach, two key evaluation criteria are employed: step response analysis and trajectory tracking analysis. The results of this research reveal that the MPA-FOPID controller demonstrates exceptional performance criteria, notably enhancing the AVR transient response in comparison to other FOPID controllers optimized through recent metaheuristic algorithms

GGrey Wolf Optimizer For Identification Of Liquid Slosh Behavior Using Continuous-Time Hammerstein Model

This paper presents the identification of liquid slosh plant using the Hammerstein model based on Grey Wolf Optimizer (GWO) method. A remote car that carrying a container of liquid is considered as the liquid slosh experimental rig. In contrast to other research works, this paper consider a piece-wise affine function in the nonlinear function of the Hammerstein model, which is more generalized function. Moreover, a continuous-time transfer function is utilized in the Hammerstein model, which is more suitable to represent a real system. The GWO method is used to tune both coefficients in the nonlinear function and transfer function of the Hammerstein model such that the error between the identified output and the real experimental output is minimized. The effectiveness of the proposed framework is assessed in terms of the convergence curve response, output response, and the stability of the identified model through the bode plot and pole zero map. The results show that the GWO based method is able to produce a Hammerstein model that yields identified output response close to the real experimental slosh output