Hoop System Research Articles

Optimal tuning of a PID controller using a wound healing algorithm based on the clonal selection principle

Control strategies for uncertainties or nonlinear effects need to be developed for control systems. Optimization algorithms developed with the rapid development of computer technology are frequently used to improve the steady-state response with the help of the ambiguous mathematical characteristics or nonlinearity of control systems. In this study, an optimum proportional–integral–derivative (PID) controller was designed using the wound healing algorithm based on the clonal selection principle. The proposed algorithm is applied in self-tuning a PID controller in the ball and hoop system which represents a system of complex industrial processes. In order to adjust the PID parameters with the aid of the developed algorithm, an integral absolute error (IAE) has been chosen as the objective function. Thus, the system reached the optimum solution quickly and time was saved. The advantages of the proposed algorithm have been proved by comparing the obtained results with other algorithms. To succeed this, a programme was written in the MATLAB GUI environment.

Robustness Analysis of GWOPID Approach in Control of Ball Hoop System with ITAE Objective Function

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

Performance evaluation of GWO/PID approach in control of ball hoop system with different objective functions and perturbation

The present work deals with robustness and comparative analysis of grey wolf optimization (GWO)/proportional-integral-derivative (PID) approach in control of a ball and hoop (BH) system with differ...

Ball in double hoop: demonstration model for numerical optimal control

Ball and hoop system is a well-known model for the education of linear control systems. In this paper, we have a look at this system from another perspective and show that it is also suitable for demonstration of more advanced control techniques. In contrast to the standard use, we describe the dynamics of the system at full length; in addition to the mode where the ball rolls on the (outer) hoop we also consider the mode where the ball drops out of the hoop and enters a free-fall mode. Furthermore, we add another (inner) hoop in the center upon which the ball can land from the free-fall mode. This constitutes another mode of the hybrid description of the system. We present two challenging tasks for this model and show how they can be solved by trajectory generation and stabilization. We also describe how such a model can be built and experimentally verify the validity of our approach solving the proposed tasks. **All codes and drawings are available at http://github.com/aa4cc/flying-ball-in-hoop

Modelling and Control of a Robotic Hula–hoop System without Velocity Measurements

The contact kinematics of a robotic hoop and a pole system is obtained by using the Montana’s equations, considering the case of contact without slipping. The resulting kinematic model is completely nonholonomic. After some mild assumptions, a set of Pfaffian constraints is established. Then, a dynamic model of the system is developed by employing the Lagrange– d’Alembert formulation. This dynamic model, which represents an underactuated mechanical system, is later used to design a controller which does not need velocity measurements. The proposed method, and its robustness against model uncertainties, is validated through numeric simulations.

Tuning of PID Controller Using GA for Ball and Hoop System

The PID controller is one of the control strategies having simple structure was understood by plant operator, which is comparatively easy to tune. Irrespective of the attractiveness, the tuning characteristic of PID controllers is a task for engineers and scientists. Numerous procedures for tuning PID-controllers are recommended such as: Ziegler Nichols tuning method auto-tuning, artificial intelligence and optimization techniques. Evolutionary optimization techniques (EOTs) as emergent techniques, an efficient GA-based tuning approach aiming at enhancing PID control for complex processes is proposed. The test and simulation results demonstrate that the GA-based proposed scheme is capable and can be used to overcome the flaws of traditional fixed gain controller. The main role of the article is to appraise the algorithm for tuning of PID-controller gains along with minimization of cost function and argue about the capability, computational efficiency of GA to solve the problems in control systems.

Dynamic inertia weight artificial bee colony versus GA and PSO for optimal tuning of PID controller

Artificial bee colony (ABC) algorithm is one of the most recently used optimisation algorithms. ABC algorithm has been extracted from the intelligent behaviour of honeybees swarm. Artificial bee colony has limitations due to its stochastic searching characteristic and complex computation that result in slow convergence to the global optimum solution. Inertia weight-based ABC method is introduced to improve the performance of the standard ABC algorithm by controlling the effect of the initial population in the new expected solution which leads improvement in the convergence rate of ABC. This work compares the performance of inertia weight ABC algorithm with the standard ABC, PSO, and GA algorithms in tuning the proportional-integral-derivative (PID) controllers for the ball and hoop system which represents a system of complex industrial processes, known to be nonlinear and time variant. Simulation results show that inertia weight ABC algorithm is highly competitive, often outperforming PSO and GA algorithms and achieving convergence rate better than the standard ABC.

Optimal Tuning of PID Controller using Adaptive Hybrid Particle Swarm Optimization Algorithm

Particle swarm optimization (PSO) has proved its ability as an efficient search tool in many optimization problems. However, PSO is easy to be trapped into local minima due to its mechanism in information sharing. Under this circumstance, all the particles could quickly converge to a position by the attraction of the best particle; all particles could hardly be improved. To overcome premature convergence of the standard PSO algorithm, this paper presents an adaptive hybrid PSO, namely (AHPSO) by employing an adaptive mutation operator for local best particles instead of applying the mutation operator to the global best particle as has been done in previous work. The developed algorithm is a new approach which allows the swarm to be more diverse by making better exploration of the local search space instead of global search space investigated by previous researchers. The proposed algorithm holds on the properties of simple structure, fast convergence, and at the same time enhances the variety of the population, and extends the search space. It is applied to self-tuning of proportional-integral-derivative-(PID) controller in the ball and hoop system which represents a system of complex industrial processes. The results are compared with those obtained by applying standard PSO, and adaptive hybrid PSO based on global best particles. It has been shown that the developed AHPSO local best algorithm is faster in convergence and the obtained results are proved to have higher fitness than the other two algorithms.

Application of Chaotic Particle Swarm Optimization to PID Parameter Tuning in Ball and Hoop System

 Abstract—In this paper, an intelligent PID controller based on Chaotic Particle Swarm Optimization (CPSO) algorithm for Ball and Hoop system is designed. In this system, two goals are tracked; the first one implies on set-point tracking, and the second one includes both set-point tracking and disturbance rejection. The classical methods of PID tuning such as Ziegler-Nichols are based on trial and error, and generally, their responses have a high settling time and overshoot; however, the proposed CPSO-PID controller determines the parameters of PID controller automatically and intelligently by minimizing the integral absolute error (IAE). The simulation results on Ball and Hoop system show that the proposed CPSO-PID controller leads to superior performance compared to Ziegler-Nichols method in both set-point tracking and disturbance rejection in terms of rise time, settling time, maximum overshoot, and the integral of absolute error (IAE) performance criterion.

A Remote Laboratory for a Basic Course on Control Engineering

The current work presents a remote laboratory for a basic course in control engineering over which several experiments may be performed. The proposed experiments have been carefully selected in order to illustrate the maximum number of concepts learnt in the classroom over a unique plant, a Ball & Hoop system. In this work, Labview has been used to acquire and handle process data whereas OPC technology is used to connect remote servers with web-integrated front-end applications. This choice has been made on the basis that these tools do not require very advanced skills and may be a reasonable approach for a wide range of simple remote laboratories.

The ball and hoop system

A simple electromechanical device consisting of a ball rolling on the rim of a hoop is considered. Although the device is simple in construction, it turns out to be rich in dynamics, and as such of interest to control system analysts and researchers. By the same token it can be used to study the dynamics of certain liquid slosh problems.