One of the lowest level control tasks, especially in robotics and other manufacturing industries, upon which other high-level controls are dependent, is the speed control of a dc motor.Usually, tuning the parameters of the proportional integral derivative (PID) controller for this task employs established conventional methods that expose the knowledge of nominal process model parameters to the control algorithm.These methods have found widespread use.Notwithstanding, a promising line of inquiry is: to search alternate possibilities of a PID being designed to automatically achieve comparable good control performance without using a formal mathematical process model approximation of the actual physical system, such as dc motor plant, in the frequency or time domain.In this paper, we propose an intelligent PID design method, "optimal closed PID-loop model predictive control", that answers this question using the characteristic settling-time (including delay-time) property of dynamic processes.The performance of this proposed method is benchmarked with popular process-model based methods.Simulation results illustrate the promise and effectiveness of the proposed tuning method, in ensuring good closed-loop performance quality for the dc motor, without using formal process models.
In power system, frequency is one of the main factor which affects the A.C. system. In order to maintain the performance of the system, frequency need to be controlled on the generation part as well as load side. In this paper, fractional order PID (FOPID) controller is designed for the three-area load frequency control (LFC) in an interrelated power system (PS) in MATLAB simulation. The LFC of generating units have used in frequency control of the dissolute response in the power system. FOPID controller parameters are intended using the Flower Pollination Algorithm (FPA) for the minimize error. The prototype of generating units with FOPID controller is simulated in MATLAB/SIMULINK platform. In this study, simulation researches on a three-area LFC with different generating units are considered. The objective function is the minimization of the Integral Squared Error (ISE) for the optimum strategy of FOPID parameters. These results presented that the FOPID controller was vital to the parameter variations in the considered system. The simulation results specialized much better performance of FOPID controller for LFC in comparison with other FOPID controllers available in the literature. FPA-FOPID Controller in the system as compared to the existing ICA-FOPID and GA-FOPID controller in literature. The result shows that the FPA result outperforms as compared with other results.
The agriculture sector occupies more than 25% of the total gross domestic products in Palestine.This provides jobs for more than 15.2% of the population in West Bank and Gaza Strip.The cultivated land is over 1.854 million dunum.However, people still using traditional ways of planting which would consume time and effort.Agriculture faces huge costs and transplant losses during planting.In this study, an automated planting machine has been introduced.This machine is a hand to the agriculture sector in Palestine.It is proposed to increase the speed and precision of planting.It is designed to do the basic cultivation steps by transmitting the transplant gently to the land.The study focused on the plants used in Palestine considering their dimensions and the distance between each two neighbor seedlings.The simulation and experimental results for the prototype showed an accurate functioning of the controlled system.Besides a precise and a smooth processing during planting, the basic planting steps were done in a satisfied way from plowing passing through planting to cover it with soil.By designing this machine, main concerns could be achieved as human needs, cost, and time saving.
In this article, we are exploring and implementing the new model order reduction (MOR) method for Large-Scale Linear Dynamic System (LSLDS) to achieve reduced order.These technologies are designed to better understand and explain LSLDS based on the Modified Balanced Truncation Method (BTM).This refers to continuous/discrete LTI structures that are minimal / non-minimum.This reduced method allows MOR to preserve complete parameters with reasonable accuracy.The approach is based on the maintenance of dominant system modes and a relatively small state truncation.As the reduced-order model (ROM) is derived from the retention of dominant modes, the reduction remains stable.The main demerit of the balanced truncation method is that the ROM, stable states, does not match the original structures.By modified BTM to narrow the deviations in the ROM transfer function matrix, a gain factor is added to adjust the steady-state values of the reduction system without altering the dynamic behaviour of the system.The proposed method has been successfully applied to a real-time single area power system with ease of extension to a discrete-time case and the results obtained show the efficacy of the method.Application model and the results obtained indicate the effectiveness of the methodology.The time response of the system has been demonstrated by the proposed method, which proves to be excellent match, effectiveness and superiority compared to the response of other approaches in the literature review of the original system.
This paper suggests an IoT device utilization for skid suppression for work vehicles in the framework of Hybrid Twin and the performances of IoT utilization are experimentally evaluated. In the autonomous driving of work vehicles, stuck state or lock state should be avoided because it is very difficult to escape from these states autonomously. First of all, a state transition diagram consisting of grip, skid, stuck and lock states is configured and a skid ratio is newly defined to measure the degree of skid. Then, a three-stage skid suppression method is suggested based on skid ratio and a controlling system is implemented by using MATLAB/Simulink. Using an actual snow blower, an IoT device with some filtering processes is incorporated and the three-stage skid suppression method is applied. The experimental results show that the suggested approach is feasible but not a three-stage but a two-stage skid suppression method is likely to be efficient because of insufficient noise reduction. As future work, the noise reduction should be improved and the skid suppression method should be implemented in a Hybrid Twin approach.
This paper considers the parameter identification problem of block-oriented Hammerstein nonlinear systems with time-delay.Firstly, we adopt the data filtering technique to transform the identification model so that all the parameters will be separated in the resulting identification model which has no redundant parameters.Secondly, a multi-innovation stochastic gradient algorithm is used to estimate the system parameters.The proposed method has high computational efficiency and good accuracy.Simulation results are presented to demonstrate the effectiveness of the proposed algorithm.
Control system is a collection of elements and operations that works together to accomplish a unique task, which are measurement, control, and actuating.A good performance of this system is based on a good signal transmitting between their components.One of these main signals is called "control signal", which actuate the actuator to perform the control task.Due to some limitation of the actuator; the problem attended with the control action is how to keep it within the actuator limits to avoid the nonlinearity saturation phenomena.Therefore to achieve the high performance of the system, the control signal (control action) should be regulated instantaneously with the process output (stability of the system) in control system design.This paper presents simulating two cases of study, which are temperature and level control processes.These processes are controlled by a parallel PID controller and applying some modification techniques that are used to enhance the control signal which is essentially to fortify the actuator from the saturation phenomena.The modification techniques are based on repositioning the controller terms of the conventional parallel PID structure without any change in the tuned controller parameters.The outcome of the paper will help interested researchers in the control engineering area to select a suitable PID structure to design a perfect control system.
Corporation robots basically consist of two robots that collaborate together to perform shared goals. Single robot is not suitable to handle heavy load and cannot handle long size load. Therefore, the corporation robots system is introduced to overcome with these limitations. This paper is mainly concerned on the design and construction of the corporation robots that can follow line and carry load. The PIC16F877A is used as microcontroller brain, while the circuit will be built and connected to IR sensors and motors. The corporation robots follow the line and work together as leader and slave to carry load from one point to another point. The experimental results achieved good performance for the robots movement regarding accurate line following and smooth handling the load.
This paper presents the use of ARDUINO board to control an autonomous mobile robot (AMR) for navigation purpose.The wheeled robot is capable to perform two tasks.The first task is to move autonomously to the north direction.And the second task is to avoid collision with unexpected static and moveable obstacles.The robot uses two sensors to navigate and avoid the obstacle, a digital compass HMC5883L uses to detect the north direction and update the situation of the robot during its movement.And the ultrasonic sensor uses to avoid nearest obstacles on the robot way.C language used to program the system to do its mission and installed to the ARDUINO board.The results obtained show that the robot was able to navigate and move to the north and avoid obstacles in the outdoor environment.
The paper deals with the solution of the optimal reallocation of control resources in the metasystem of stochastic controllers, as that can be read in conjunction functioning technology of manufacturing products within the range of the enterprise. In this theoretical solution to this problem is possible only for Markov processes with a normal distribution of output indices regulators values (for example, the volume of production, the quality of manufactured products). It is proved that the variances between the controlled variables in the metasystem, and virtual work needed to support them, there is a hyperbolic dependence. Connecting a finite state machine that distributes control resources proposed in the algorithm removes the restriction of Markov processes. Perhaps finding the minimum total variance even multiplies regulators.
The advancing integration of ADAS (Advanced Driver Assistance Systems) and the increasingly complex E/E architecture across all vehicle classes require a reliable and safe method for the assessment, evaluation and validation of said systems.At the Institute of Automotive Engineering (IAE), a test tool that functions as a full-size vehicle replacement has been developed allowing the full scope of tests to be performed while minimizing the risk to the test personal and vehicles involved.The test tool consists of three separate modules: a driving module, a soft crash target carrier and the soft crash target itself.The soft crash target carrier holding the soft crash target is connected to the driving module via detachable links.Considering a collision scenario as use case, the driving module separates from the soft crash target carrier just moments before a collision is imminent, performs evasive manoeuvres and thus leaves the possibly harmful collision area.The soft crash target is quickly exchanged according to the use case under consideration and is visible to common sensor technologies (radar, lidar, camera etc.).The developed test tool can furthermore be used for controllability studies according to ISO 26262 in cases where a second vehicle or collision partner is necessary.
This paper will propose the state feedback control based networked control system (NCS) design with the differential evolution algorithm. For designing a networked control system, one has to overcome the problems about the random latency and the data packet dropouts. Here, we will apply the state feedback control theory to design a controller to overcome the random latency and the data packet dropouts of NCS and guarantee the stability of the overall system. To improve the control performance, the differential evolution algorithm (DE) is applied to search the optimal control parameters. In this way, one can design NCS more effectively and without need to solve a complex Lyapunov-Krasovskii stability criterion. Finally, computer simulations are given to demonstrate the proposed control strategy and to illustrate its effectiveness.
This paper considers the identification of nonlinear systems with color noise, and introduces a new time-varying forgetting factor based stochastic gradient (TVFF-SG) algorithm to estimate the system param-eters.The basic idea of the time-varying forgetting factor is that when the algorithm starts, we give the forgetting factor a relative smaller value, which will speed up the convergence.In addition, the forgetting factor will increase slowly as time goes on so that the convergence procedure of the model will be more stable.Simulation results are presented to demonstrate the effectiveness of the proposed algorithm.
Ball and beam system is found in most laboratories of control systems engineering due to its simplicity and easiness in construction and control theoretically. The system consists of a motor attached with a beam at the center and a ball, which is placed on the top of beam. The problem with this system, is in the time of an electrical control signal is applied to the motor, the beam can be tilted about its horizontal axis and the ball will roll on the top of the beam. Therefore, if the system cannot be controlled properly, the ball may fall down from the beam. In this paper, PID controller Algorithm based on Arduino microcontroller which depends on the feedback signal is used to control the ball position using linear potentiometer position sensor. MATLAB software program has been used to plot the system response by observing the ball position for a predefined amount of time. The controller parameters have been tuned using trial and error method, tested for different set point tracking and for disturbance rejection in order to obtain a good system characteristic.
In road construction, in particular on a bustling highway, an operator is needed to alert the drivers to decelerate the speeding vehicles. In doing so, an operator is asked to stand at a safe place, some distance from the construction site and to wave a small flag. Although the flag is light, prolonged waving flag cause tiredness to the operator. If the operator stops shaking, the safety of his co-workers is at risk. It is a straightforward thinking that replacing a human operator with a robot operator is a good choice while keeping the human-like figure. The presence of a human figure effectively alerts the drivers as compared to object signs or signal lights. This paper presents a robotic, human-like figure that performs a simple one axis controlled flag waving task. It comes with a monocular vision that video streams the oncoming vehicles. A program is written in Python language with SimpleCV module that processes the video data. A signal is sent to the controller upon detecting the approaching vehicles. As a result, the robot operator would move its arm, thus waving a flag as a warning signal. A pneumatically powered actuator drives the arm. The robot operator was tested in a controlled environment where the results showed that it has a potential for field implementation.
Power Plant Heat exchanger is widely used in chemical and petroleum plants because it can sustain wide range of temperature and pressure.Heat exchanger is a high nonlinearity and poor dynamics plant; therefore it is complex to model and difficult to control its dynamics.In this paper two types of heat exchanger model and controller are applied for selecting suitable model and controller.First model is called (Physical model) and derived using real parameter of heat exchanger plant.Second, a Second Order Plus Dead Time (SOPDT model) that is derived from the response of heat exchanger.While the controllers are consisted of fuzzy proportional derivative (FPD) controller and proportional integral derivative (PID) controller and applied to the model and their responses are compared with the existing PID controller.The PID controller response based on Physical model gives similar response of existing PID controller based real heat exchanger plant in comparison with SOPDT model.That means the Physical model is able to represent the heat exchanger plant dynamics more accurately than SOPDT model.For the controller, the FPD control gives a slight enhancement based on SOPDT model.Therefore, FPD controller is more suitable than PID controller.
This paper focuses on resolving the trajectory tracking problem of two wheeled mobile robot.We begin by presenting the kinematic model of the robot which is the base of the control law then we present a PI controller and a model predictive controller to solve the problem of trajectory tracking.We performed a comparison between the performances of the classical PI controller and the predictive controller which is an interesting approach that considers an explicit performance criterion and minimizes it during the computation of the control law.Simulation results are provided in order to show the effectiveness of model predictive control in the resolution of trajectory tracking problem.
In the process industry many of the control applications deal with liquid level, flow, temperature and pressure processes.This paper presents the approach of modeling and controller design of liquid level control system for a nonlinear Coupled-Tank System.First of all, the mathematical equations for the nonlinear system are explored.And then, proportional plus integral (PI) controller is designed to control the level of the second tank for the nonlinear model, through variable manipulation of water pump in the first tank.The simulation study is done using MATLAB and the performance analysis in time domain of the controller is identified.In addition, ITAE criterion is used to evaluate the controller performance.Finally, the simulation results indicate that the controller work very well and the proposed controller has the ability to reject the effect of the disturbance.
In this paper, the generalized synchronization and the inverse generalized synchronization of different dimensional spatial chaotic dynamical systems are studied. The generalized synchronization results have been derived using active control method and Lyapunov stability theory. Numerical simulations are performed to verify the effectiveness of the proposed schemes.
This paper uses the general framework of dynamic feedback linearization for stabilization of mobile robots. Instead of using unicycle model for control design, this paper uses a comprehensive model which is based on the physics of differential drive robots. The model used in the paper describes nonholonomic underactuated behavior of robot in terms of the physical dimensions and velocities of the wheels. Next, the proposed control is applied to this model and it is theoretically proven that dynamic feedback linearization can successfully solve the stabilization problem. To evaluate the performance of proposed control, another controller is designed based on the Lyapunov's method. The performance of the two controllers and the complexity of control gain tuning process are compared. Next, the robustness of the proposed control against uncertainties is studied. The results of analysis and simulations show that the proposed control has very good performance against parametric uncertainties.
