Proportional Derivative Controller Research Articles

Evaluating the Performance of Fuzzy-PID Control for Lane Recognition and Lane-Keeping in Vehicle Simulations

This study presents the use of a vision-based fuzzy-PID lane-keeping control system for the simulation of a single-track bicycle model. The lane-keeping system (LKS) processes images to identify the lateral deviation of the vehicle from the desired reference track and generates a steering control command to correct the deviation. The LKS was compared to other lane-keeping control methods, such as Ziegler–Nichols proportional derivative (PD) and model predictive control (MPC), in terms of response time and settling time. The fuzzy-PID controller had the best performance, with fewer oscillations and a faster response time compared to the other methods. The PD controller was not as robust under various conditions due to changing parameters, while the MPC was not accurate enough due to similar reasons. However, the fuzzy-PID controller showed the best performance, with a maximum lateral deviation of 2 cm, a settling time of 12 s, and Kp and Kd values of 0.01 and 0.06, respectively. Overall, this work demonstrates the potential of using fuzzy-PID control for effective lane recognition and lane-keeping in vehicles.

Otomatisasi Pengontrol Temperatur Suhu Untuk Mesin Pengering Pelet Menggunakan Kontroler Autonics TK4S Dengan Metode PID

A pellet dryer machine is a tool that makes it easy to dry pellets so it doesn't have to require sunlight to dry the pellets. Various methods have also been widely used to control the temperature on the machine. One of the obstacles experienced is controlling the temperature so that it remains stable and has a good response time. In this journal, a pellet drying machine with PID (proportional integral derivative) method will be designed to keep the temperature stable. The temperature that makes the setpoint is 100°C. In the design carried out, it is by comparing sistems that are given Proportional control, Proportional and Integral (PI) control and Proportional Derivative (PD) control. For the controller used, it is an Autonics TK4S type controller. In the control, PID tuning will be carried out which will later be carried out variations of each Kp, Ki, and Kd values.

Cascade Proportional Derivative Controller For A Flexible Link Robot Manipulator Using The Bees Algorithm

In this study, a flexible robot arm model and the design of its controller are introduced. The robot arm consists of a single flexible link. It is desired to control the circular position of the robot arm and the vibration of the tip point. Cascade proportional derivative controller was used to control the position and reduce the tip vibration. Controller gains were found using the bees algorithm. The weighted function of system responses such as settling time, maximum overshoot, steady-state error is used as a performance criterion while searching for the best parameters. In addition, controller gains were obtained with the genetic algorithm to evaluate the working performance of the bees algorithm. It has been observed that the Cascade PD controller, whose gains are optimized by the bees algorithm, successfully controls the flexible robot arm system and reduces the vibration of the tip point.

Smart agriculture: Development of a skid-steer autonomous robot with advanced model predictive controllers

The agricultural domain has been experiencing extensive automation interest over the past decade. The established process for measuring physiological and morphological traits (phenotypes) of crops is labour-intensive and error-prone. In this paper, a mobile robotic platform, namely The Autonomous Robot for Orchard Surveying (AROS), was developed to automate the process of collecting spatial and visual data autonomously. Furthermore, six different control frameworks are presented to evaluate the feasibility of using a kinematic model in agricultural environments. The kinematic model does not consider wheel slippage or any forces associated with dynamic motion. Thus, the following six controllers are evaluated: Proportional-Derivative (PD) controller, Sliding Mode Controller (SMC), Control-Lyapunov Function (CLF), Nonlinear Model Predictive Controller (NMPC), Tube-Based Nonlinear Model Predictive Controller (TBNMPC), and Model Predictive Sliding Mode Control (MPSMC). This paper provides insight into the degree of disturbance rejection that the mentioned control architectures can achieve in outdoor environments. Experimental results validate that all control architectures are capable of rejecting the present disturbances associated with unmodelled dynamics and wheel slip on soft ground conditions. Additionally, the optimal-based controllers managed to perform better than the non-optimal controllers. Performance improvements of the TBNMPC of up to 209.72% are realized when compared to non-optimal methods. Results also show that the non-optimal controllers had low performance due to the underactuated constraint present in the kinematic model.

Proportional–integral and proportional–derivative controller design based on analytically computed centroid point for controlling integrating processes

The proportional–integral and proportional–derivative controller is characterized by its capability to effectively control integrating processes compared with proportional–integral/proportional–integral–derivative controllers. Recently, several graphical methods have been proposed for tuning the PI-PD controller parameters by computing the centroid point of the stability boundary locus. However, these approaches are time-consuming because they entail plotting the stability boundary locus for finding the centroid point. Another disadvantage of those design methods is that the design procedure has to be redone as the transfer function changes. In this article, a generalized stability boundary locus is constructed in terms of the controller and assumed plant transfer function model parameters to enable the designer to avoid replotting the stability boundary locus as the process transfer function changes. More importantly, two analytical approaches, which simplify the design of the proportional–integral and proportional–derivative controller very much, are proposed to compute the centroid point of the generalized stability boundary locus. Analytical expressions for computing the performance measures of the designed closed-loop system have also been provided so that one can predict the performance of the designed closed-loop system. It has been shown by simulation examples that the analytical centroid of convex stability region method provides quicker responses with faster disturbance rejections compared to other reported design methods. Also, the simulation results have displayed that analytical weighted geometrical center gives more robust closed-loop responses in terms of gain margin, phase margins, and maximum sensitivity than analytical centroid of convex stability region. Finally, the feasibility of the proposed methods is tested using a real-time application based on an aerodynamical system. Real-time results have demonstrated that the analytical centroid of convex stability region and analytical weighted geometrical center methods give quicker responses with small overshoots compared to other reported methods.

Fractional Order Active Disturbance Rejection Control for Canned Motor Conical Active Magnetic Bearing-Supported Pumps

Active magnetic bearings (AMBs) are electromagnetic mechanism systems in which non-contact bearings support a rotating shaft using attractive forces generated by electromagnets through closed-loop control. For complete support of a five degree of freedom (DOF) rotor system, most AMB structures include two radial actuators and one for the axial direction. Conical active magnetic bearings (CAMBs) is one of the development directions of conventional magnetic bearings in which the requirement of the axial bearing can be eliminated. In this paper, we propose a structure with a CAMB integrated into a canned motor pump to eliminate the need for mechanical bearings and shaft seals. However, this system necessitates a more complicated control strategy due to a significant coupling effect between rotor motion and hydrodynamic disturbances. This paper presents a fractional order active disturbance rejection control (FOADRC) including a fractional order extend state observer (FOESO) and a proportional derivative controller (PD) to track and reject lumped disturbances actively. The proposed controller achieves better performance than the integer-type ADRC and traditional PID controller. The control performance of the proposed FOADRC is illustrated in terms of very good disturbance rejection capability that is demonstrated through MATLAB/Simulink simulation results.

Dynamic Vehicle Modelling and Controlling Techniques for Autonomous Vehicle Systems

The driving scenario of an automated vehicle is the crucial technology in the design of autonomous cars. This suggested approach aims to address the shortcomings of autonomous cars, such as their poor real- time performance and low control precision. The process for building a virtual simulation environment for autonomous vehicle testing and validation is described in this study. Model Predictive Control and Proportional Integral and Derivative Control are used in MATLAB simulation to build three car models. These are related to the 2D and 3D animation used in collision detection and visualization. The virtual engine visualization is included throughout the model. A variety of test circumstances are used to validate the simulation model, and the model’s performance is assessed in the presence of various barriers. The simulation's findings demonstrate that the autonomous vehicle has a strong potential for self-adaptation even in challenging and complex working environments. No instances of car sideslip or track departure have been noted. It is discovered that this autonomous car performs remarkably well overall when compared to other autonomous vehicles. The suggested approach is essential for enhancing autonomous vehicle driving safety, maintaining vehicle control in challenging situations, and improving the advancement of intelligent vehicle driving assistance.

Non Linear Control System for Humanoid Robot to Perform Body Language Movements.

In social robotics, especially with regard to direct interactions between robots and humans, the robotic movements of the body, arms and head must make an adequate displacement to guarantee an adequate interaction, both from a functional and social point of view. To achieve this, the use of closed-loop control techniques that consider the complex nonlinear dynamics and disturbances inherent in these systems is required. In this paper, an implementation of a nonlinear controller for the tracking of trajectories and a profile of speeds that execute the movements of the arms and head of a humanoid robot based on the mathematical model is proposed. First, the design and implementation of the arms and head are initially presented, then the mathematical model via kinematic and dynamic analysis was performed. With the above, the design of nonlinear controllers such as nonlinear proportional derivative control with gravity compensation, Backstepping control, Sliding Mode control and the application of each of them to the robotic system are presented. A comparative analysis based on a frequency analysis, the efficiency in polynomial trajectories and the implementation requirements allowed selecting the non-linear Backstepping control technique to be implemented. Then, for the implementation, a centralized control architecture is considered, which uses a central microcontroller in the external loop and an internal microcontroller (as internal loop) for each of the actuators. With the above, the selected controller was validated through experiments performed in real time on the implemented humanoid robot, demonstrating proper path tracking of established trajectories for performing body language movements.

Nonoscillation of damped linear differential equations with a proportional derivative controller and its application to Whittaker-Hill-type and Mathieu-type equations

The proportional derivative (PD) controller of a differential operator is commonly referred to as the conformable derivative. In this paper, we derive a nonoscillation theorem for damped linear differential equations with a differential operator using the conformable derivative of control theory. The proof of the nonoscillation theorem utilizes the Riccati inequality corresponding to the equation considered. The provided nonoscillation theorem gives the nonoscillatory condition for a damped Euler-type differential equation with a PD controller. Moreover, the nonoscillation of the equation with a PD controller that can generalize Whittaker-Hill-type equations is also considered in this paper. The Whittaker-Hill-type equation considered in this study also includes the Mathieu-type equation. As a subtopic of this work, we consider the nonoscillation of Mathieu-type equations with a PD controller while making full use of numerical simulations.

Sliding Mode-Based Active Disturbance Rejection Control of Assistive Exoskeleton Device for Rehabilitation of Disabled Lower Limbs.

In this study, a hybrid control strategy is proposed to improve the tracking performance of lower limb exoskeleton system dedicated for rehabilitation the motion of hip and knee limbs in disabled persons. The proposed controller together with exoskeleton device is practically instructive to make exercises for people suffering weakness in their lower limbs. The proposed controller combined both active disturbance rejection control (ADRC) with sliding mode control (SMC) to get their powerful characteristics in terms of rejection capability and robustness characteristics. The dynamic modelling of swinging lower limbs are developed and the controller has been designed accordingly. The numerical simulations have been conducted to validate the effectiveness of proposed controller. A comparison study in performance has been performed between the proposed controller and the traditional controller ADRC based on proportional-derivative controller. The simulated results showed that the proposed controller has better tracking performance than conventional version. In addition, the results showed that the sliding mode-based ADRC can considerably reduce the chattering level and better rejection capability, fast tracking behavior and less control effort.

Anti-disturbance Trajectory Tracking Control for a Quadrotor UAV with Input Constraints⋆

This paper presents the trajectory tracking control for a quadrotor unmanned aerial vehicle(UAV) with disturbances and input constraints. The UAV's system is decomposed into an outer position loop and an inner attitude loop. The position tracking control is achieved by a class of saturated proportional-derivative(PD) control laws. Assuming that the unknown disturbances mainly effect on the translational dynamics, an adaptive control term is investigated to compensate the effects of the disturbances. The position tracking control force implies a coupled-attitude system that connects the inner attitude loop with the outer position loop. An intrinsic PD control law, which is directly designed on the special orthogonal group SO(3), is proposed to track the desired attitude. In order to reduce the calculational difficulty of the attitude tracking control law, an observer-based control law is further developed while the control law and observer can be designed separately. Simulation results complete this work.

An Energy Efficient Jumping Drone - A Simple Projectile Motion Approach

Jumping robots are interesting devices that offer several advantages in terms of navigation about cluttered environments. However, they present unique challenges with respect to their design and control. In this paper, we propose a design that uses four planar thrusters/propellers on a jumping robot. Such a system provides better maneuverability due to agility provided by the propellers to guide the motion. From energy consumption perspective, we use the gravity for free fall and a spring mechanism to execute the jumping motion without loss of much energy on impact. The primary contribution of this paper is developing a novel navigation and control method for such jumping robots to go to the desired goal. In this paper, we present a projectile motion planning approach for the control of the proposed system. We propose proportional (P) and proportional-derivative (PD) controllers that compute the launch velocity required for the jumping drone after impact with the ground to follow a projectile motion in each jump to reach the goal position. The jumping drone bounces after impact with the ground, and the drone is then actuated for a certain time till it attains the required launch velocity after which it is made to move freely under the influence of gravity. Such a system shows significant reduction of energy consumption (by 81.35%) as compared to a normal drone navigating to the same goal location. Simulation results validate the effectiveness of the proposed approach.

Synergistic PID and Output Feedback Control on Matrix Lie Groups

In this paper, we develop multiple synergistic hybrid feedback control laws for mechanical systems on matrix Lie groups with left-invariant metrics. With the goal of globally asymptotically tracking a desired reference trajectory, we propose a hybrid proportional-derivative (PD) type control law and an output feedback version which only utilizes configuration measurements. Moreover, to ensure global asymptotic tracking in the presence of a constant and unknown disturbance in the system dynamics, we introduce two novel proportional-integral-derivative (PID) type control laws with slightly different properties in terms of gain selection and integral action. The theoretical developments are validated through numerical simulation of an underwater vehicle.

Construction and management of smart campus: Anti-disturbance control of flexible manipulator based on PDE modeling.

With the rapid development of smart campus, this paper studies the attitude tracking control of flexible manipulator (FM) in colleges and universities under elastic vibration and external disturbances. First, different from the traditional modeling based on ordinary differential equations (ODEs), the partial differential equations (PDEs) dynamic model of a manipulator system is established based on the Hamilton principle (HP). Second, the boundary control condition of the end system of the manipulator is introduced to adjust the vibration of the manipulator. Furthermore, a Proportional-Derivative (PD) boundary control (PDBC) strategy is proposed by the Lyapunov function to suppress the vibration of the manipulator. Finally, a numerical comparison simulation based on MATLAB/SIMULINK further verifies the robustness and anti-disturbance performance of the control method proposed in this paper.

Fault tolerance evaluation of model-free controllers with application to unmanned aerial vehicles

Although important improvements in the area of robust control of nonlinear systems have been presented in the literature, most of the developed controllers suffer from complexity and large dependency on accurate mathematical formulation of the models. Recently, model-free robust control techniques were introduced and have shown good performance when applied to multi-input–multi-output systems. The model-free approach is characterized by the nonuse of any prior knowledge about the underlying structure and/or associated parameters of the dynamical system. Therefore, the major criteria for assessing the effectiveness of these controllers are related to their ability to handle unknown inputs and disturbances, as well as achieving the desired tracking performance in presence of faults and malfunctions. This work considers the development of robust fault-tolerant controllers based on the model-free approach and their application to multirotor unmanned aerial vehicles’ (UAVs) systems. The different controllers based on intelligent proportional-derivative (iPD), intelligent backstepping (iBackstepping), and adaptive control are compared in terms of performance, ease of implementation and parameters tuning. The simulated results, tested on Matlab/Simulink on a full nonlinear model of a hexarotor UAV, validate the theoretical advantages of the adaptive approach with respect to multiple criteria such as improved tracking performance in case of existence of actuators faults when compared to the iPD and iBackstepping control methods at the cost of increased complexity.

Balancing and Tracking Control of Ballbot Mobile Robots Using a Novel Synchronization Controller Along With Online System Identification

Ballbots are omnidirectional self-balancing platforms that can be exploited in many applications to detect, track, or interact with objects or humans, such as a service robot. Ballbot will enable mobile robots to stand tall and move elegantly through busy environments. However, maintaining equilibrium through synchronization of motion between the ball and the body of a Ballbot is still an open research problem. This article presents a synchronization control (SC) design, with synchronization and coupling errors for Ballbots to stabilize the body and control ball transfer simultaneously. The proposed SC method is applied to the two 2-D planar models of a Ballbot robot. The dynamic model of the Ballbot is derived, and parameters are identified online using the intelligent particle swarm optimization method. The proposed controller is proven to guarantee asymptotic convergence to zero errors in tracking and synchronization. The stabilizing and transferring problems are investigated through several simulations and experiments by using an actual Ballbot platform. Moreover, the controller performance is compared with an augmented proportional derivative controller and a partial feedback linearization controller. The results and comparisons demonstrate a superior stabilization accuracy of the proposed SC method.

Task-Priority Operational Space Control for Vehicle-Manipulator Systems with Modelling Errors

The dynamics of underwater vehicle-manipulator systems (UVMSs) are very hard to model, which reduces the feasibility of model-based control approaches. Even so, such strategies prove useful in redundancy resolution. In this paper, higher-order sliding mode control is combined with task-priority operational space control (OSC) in order to handle and utilize the redundancy of UVMSs despite the presence of dynamic model errors. At each task level, the generalized super-twisting algorithm is implemented to reject effects caused by model errors while maintaining a continuous control signal. The general problem of OSC with uncertain models is analyzed, and some of its challenges are highlighted, including an algebraic loop. We conduct a simulation study on a highly redundant UVMS, where we compare task-level higher-order sliding mode control to proportional-derivative control. Though this paper is motivated by challenges specific to UVMSs, the results also hold for other vehicle-manipulator systems.

UAV Chasing Based on YOLOv3 and Object Tracker for Counter UAV Systems

This paper proposes a vision-based unmanned aerial vehicle (UAV) chasing system that can be embedded in a pursuer UAV (pUAV) to protect the attack from an evader UAV (eUAV). The proposed UAV chasing system consists of two parts, i.e., the UAV tracking and control signal generation parts. Combining a deep learning-based object detector, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">you only look once</i> version three (YOLOv3), and the existing object trackers, the proposed UAV tracking algorithm can improve the tracking performance of pUAV within affordable computational complexity. Then, the control signals of the pUAV are generated by utilizing the predicted bounding box area of the eUAV and the proportional-derivative control method. Following the object tracking benchmark performance criteria, various combinations of YOLOv3 and object trackers are examined and compared. From the evaluation results, the UAV tracking algorithm with the highest performance is chosen, whose average success rate and average precision rate for object tracking are 2.86% and 5.61% higher than YOLOv3, respectively. Through the field test, it is verified that the proposed UAV chasing system outperforms the YOLOv3 system in terms of bounding box misalignment (33% accuracy improvement) and computational complexity (71% reduction).

Control Improvement of Low-Cost Cast Aluminium Robotic Arm Using Arduino Based Computed Torque Control

Gravity causes non-linearity in position control of an articulated industrial robotic arm. Especially for a joint position control of a robot’s shoulder and elbow that works parallel with the gravity direction. To overcome the problem, Computed Torque Control algorithm was implemented. This algorithm linearized the feedback, so a regular linear Proportional Derivative controller can be implemented. The contribution of this research is to find an effective controller to control a heavy weight low-cost robotic arm link/body using low-cost controller such as Arduino. A Computed Torque Control was implemented to control the shoulder joint of an articulated robotic arm. This joint is the most affected joint by the gravity. It works along the vertical plane, and loaded by the rest of the arm and the robot’s load. The proposed controller was compared to a Proportional Integral Derivative (PID) Controller and a Cascade PID Controller. The experiment showed that the Computed Torque Controller can control the position of the arm properly both in the direction along or against the gravity. A linear PID controller could not bring the arm to the set point when it moves against the gravity, but it works well when the arm moves in the opposite direction. A Cascade PID controller has an overshot when the arm moves along the gravity. But it works properly when it moves up against the gravity. A Computed Torque Control works well in both directions even in the presence of gravity force because it includes the gravity on its algorithm.

Proportional Integral Resonant and Proportional Derivative Controllers Applied to Zero Sequence Harmonic Compensation in Four-Wire Microgeneration Systems

Proportional Integral Resonant and Proportional Derivative Controllers Applied to Zero Sequence Harmonic Compensation in Four-Wire Microgeneration Systems