Classical Proportional Integral Derivative Controller Research Articles

Control of Position, Velocity and Acceleration of Actuators Using Optimal State Estimation

Abstract In order to improve performance of closed loop control and achieve highly accurate reference trajectory tracking, motion controllers have to utilize the advanced control and system state estimation algorithms. Classical PID (Proportional-Integral-Derivative) controller includes calculation of derivation of a process value in order to achieve system desired performance of a system. This paper presents Kalman filter as an optimal estimation algorithm on the model of a hydraulic actuator which is equally applicable to any other application that involves calculating derivations of noisy measurements. Alternative form of Kalman filter, suitable for implementation on a PLC (Programmable Logic Controller) or any other embedded system is also presented.

Optimized Proportional-Integral-Derivative Controller for Upper Limb Rehabilitation Robot

This paper proposes a nature inspired, meta-heuristic optimization technique to tune a proportional-integral-derivative (PID) controller for a robotic arm exoskeleton RAX-1. The RAX-1 is a two-degrees-of-freedom (2-DOFs) upper limb rehabilitation robotic system comprising two joints to facilitate shoulder joint movements. The conventional tuning of PID controllers using Ziegler-Nichols produces large overshoots which is not desirable for rehabilitation applications. To address this issue, nature inspired algorithms have recently been proposed to improve the performance of PID controllers. In this study, a 2-DOF PID control system is optimized offline using particle swarm optimization (PSO) and artificial bee colony (ABC). To validate the effectiveness of the proposed ABC-PID method, several simulations were carried out comparing the ABC-PID controller with the PSO-PID and a classical PID controller tuned using the Zeigler-Nichols method. Various investigations, such as determining system performance with respect to maximum overshoot, rise and settling time and using maximum sensitivity function under disturbance, were carried out. The results of the investigations show that the ABC-PID is more robust and outperforms other tuning techniques, and demonstrate the effective response of the proposed technique for a robotic manipulator. Furthermore, the ABC-PID controller is implemented on the hardware setup of RAX-1 and the response during exercise showed minute overshoot with lower rise and settling times compared to PSO and Zeigler-Nichols-based controllers.

Design and development of a Stewart platform assisted and navigated transsphenoidal surgery

In this study, technical details of a Stewart platform (SP) based robotic system as an endoscope positioner and holder for endoscopic transsphenoidal surgery are presented. Inverse and forward kinematics, full dynamics, and the Jacobian matrix of the robotic system are derived and simulated in MATLAB/Simulink. The required control structure for the trajectory and position control of the SP is developed and verified by several experiments. The robotic system can be navigated using a six degrees of freedom (DOF) joystick and a haptic device with force feedback. Position and trajectory control of the SP in the joint space is achieved using a new model-free intelligent PI (iPI) controller and it is compared with the classical PID (proportional-integral-derivative) controller. Trajectory tracking experimental results showed that the tracking performance of iPI is better than that of PID and the total RMSE of the trajectory tracking is decreased by 17.64% using the iPI controller. The validity of the robotic system is proven in the endoscopic transsphenoidal surgery performed on a realistic head model in the laboratory and on a cadaver in the Institute of Forensic Medicine. The key feature of the system developed here is to operate the endoscope via the joystick or haptic device with force feedback under iPI control. Usage of this system helps surgeons in long, fatiguing, and complex operations. This system can generate new possibilities for transsphenoidal surgery such as fully automated robotic surgery systems.

A proportional–integral-based robust state-feedback control method for linear parameter-varying systems and its application to aircraft

The integration of advanced linear parameter-varying and classical proportional–integral–derivative control methods has attracted great attention in control of nonlinear dynamic systems. However, linear parameter-varying proportional–integral–derivative control synthesis is a nonconvex bilinear matrix inequality problem. Although the synthesis conditions can be convexified in the case of proportional–integral control, a strong constraint on the structure of matrix variables usually leads to infeasible solutions. In this paper, a linear parameter-varying proportional–integral control design method is proposed to remove that constraint. The approach is based on the assumption of state-feedback proportional–integral control to guarantee the linear matrix inequality variables to be full matrices instead of block diagonal matrices, and extended linear matrix inequalities are proposed to synthesize the controller. This increases the likelihood of finding feasible linear matrix inequality solutions and reduces the conservatism. The proposed method is applied to control longitudinal and lateral dynamics of an F-16 aircraft and promising simulation results are obtained.

Real-Time Implementation of Continuous Model Based Sliding Mode Control Technique for Trajectory Tracking Control of Mobile Robot

In this study, real-time trajectory tracking control of an autonomous mobile robot, actuated by two DC motors, has been designed, analyzed and studied. Two different control approaches such as model based sliding mode (SMC) and the classical proportional–integral–derivative (PID) control are employed to increase the tracking performance of the mobile robot. A model based SMC technique has been presented in order to consider the complete dynamic model of the robot and in order to increase trajectory tracking performance of the system. The experimental outcomes strongly verified that the proposed controller gives a quite well trajectory tracking response and smaller magnitude overshot compared with the classical PID controller.

Data-Driven PID Controller and Its Application to Pulp Neutralization Process

The pulp neutralization process is a complex industrial process with strong nonlinearity and time-varying dynamics. In general, this kind of process is hardly controlled by using traditional control techniques such as the proportional-integral-derivative (PID) controller. To resolve this problem, a novel PID control scheme is proposed by integrating a data-driven compensation of unmodeled dynamics and a multistep ahead of optimal control strategy. Essential difference from the classical PID controller lies in the use of unmodeled dynamics, the measured data from the pulp neutralization process is used directly for building the nonlinear PID controller, which plays an important role in control system design. Based on multistep ahead prediction optimal control theory, the controller parameters can be obtained through optimizing a cost function. Some theoretical results on the stability and convergence of the closed-loop system are established. To demonstrate the effectiveness of the proposed control techniques, a simulation model and a cobalt nickel hydroxide pulp neutralization process are employed. Simulations were carried out using data extracted from an actual pulp neutralization process, followed by some industrial experiments. Results from both simulations and experiments indicate that our proposed controller can effectively control the pH value of the pulp neutralization process with promising control performance.

Equivalent input disturbance‐based robust LFC strategy for power system with wind farms

Due to the intermittent power generation, wind farms integrated into the grid may cause a problem of large frequency fluctuation, when the capacity of load frequency control (LFC) is not enough to compensate the unbalance between the generation and the load demand. In this study, a new robust LFC strategy against load disturbance and wind power fluctuation is proposed to improve the disturbance-resistant performance of the power system with wind farms. First, a simplified model of the power system with wind farms is established without considering the accurate model information. Then, a control scheme based on the compensation of equivalent input disturbance (EID) is introduced, and a method of EID estimation is presented. The robust LFC design addresses various disturbances and internal/external uncertainties of power systems. Finally, to evaluate the effectiveness of the proposed method, two case studies are carried out and the performance comparisons with the classical proportional–integral–derivative control scheme are used to confirm the proposed method.

Note: Wide-operating-range control for thermoelectric coolers.

A new algorithm for controlling the temperature of a thermoelectric cooler is proposed. Unlike a classic proportional-integral-derivative (PID) control, which computes the bias voltage from the temperature error, the proposed algorithm exploits the linear relation that exists between the cold side's temperature and the amount of heat that is removed per unit time. Since this control is based on an existing linear relation, it is insensitive to changes in the operating point that are instead crucial in classic PID control of a non-linear system.

Real‐time hybrid control of electrohydraulic active suspension

SummaryElectrohydraulic actuators are an attractive choice for active suspension, because these systems provide a high power‐to‐weight ratio. However, their dynamics are highly nonlinear. In addition, the use of one simple controller for both position and force is complicated, because there is a compromise between them in the case of active suspension. Most existing controllers do not efficiently fulfill the requirements, because only one state variable is considered.In this paper, we address these problems by developing a new hybrid controller for both position and force and implementing it in a real‐time test bench. Our goal is to control the vertical position of the passenger seat while tracking the force transmitted to passengers and keeping it within tolerable and comfortable limits. Therefore, the proposed controller is a combination of two controllers. Its flexible structure redirects the control signal to control the proper controlled state variable. The real‐time results of the newly designed hybrid controller are compared with those obtained using a classical proportional integral derivative controller, because this is the most widely used controller in the industry. As expected, the proposed controller demonstrates better performance in real‐time operation. Copyright © 2017 John Wiley & Sons, Ltd.

A hybrid LQR-PID control design for seismic control of buildings equipped with ATMD

This paper presents an efficient hybrid control approach through combining the idea of proportional-integral-derivative (PID) controller and linear quadratic regulator (LQR) control algorithm. The proposed LQR-PID controller, while having the advantage of the classical PID controller, is easy to implement in seismic-excited structures. Using an optimization procedure based on a cuckoo search (CS) algorithm, the LQR-PID controller is designed for a seismic- excited structure equipped with an active tuned mass damper (ATMD). Considering four earthquakes, the performance of the proposed LQR-PID controller is evaluated. Then, the results are compared with those given by a LQR controller. The simulation results indicate that the LQR-PID performs better than the LQR controller in reduction of seismic responses of the structure in the terms of displacement and acceleration of stories of the structure.

PID controller design for second order nonlinear uncertain systems

Although the classical PID (proportional-integral-derivative) controller is most widely and successfully used in engineering systems which are typically nonlinear with various uncertainties, almost all the existing investigations on PID controller focus on linear systems. The aim of this paper is to present a theory on PID controller for nonlinear uncertain systems, by giving a simple and analytic design method for the PID parameters together with a mathematic proof for the global stability and asymptotic regulation of the closed-loop control systems. To be specific, we will construct a 3-dimensional manifold within which the three PID parameters can be chosen arbitrarily to globally stabilize a wide class of second order nonlinear uncertain dynamical systems, as long as some knowledge on the upper bound of the derivatives of the nonlinear uncertain function is available. We will also try to make the feedback gains as small as possible by investigating the necessity of the manifold from which the PID parameters are chosen, and to establish some necessary and sufficient conditions for global stabilization of several special classes of nonlinear uncertain systems.

Comparison Analysis of Model Predictive Controller with Classical PID Controller For pH Control Process

pH control plays a important role in any chemical plant and process industries. For the past four decades the classical PID controller has been occupied by the industries. Due to the faster computing technology in the industry demands a tighter advanced control strategy. To fulfill the needs and requirements Model Predictive Control (MPC) is the best among all the advanced control algorithms available in the present scenario. The study and analysis has been done for First Order plus Delay Time (FOPDT) model controlled by Proportional Integral Derivative (PID) and MPC using the Matlab software. This paper explores the capability of the MPC strategy, analyze and compare the control effects with conventional control strategy in pH control. A comparison results between the PID and MPC is plotted using the software. The results clearly show that MPC provide better performance than the classical controller.

Real-time trajectory tracking of an unmanned aerial vehicle using a self-tuning fuzzy proportional integral derivative controller

In the present study, a desired reference trajectory was autonomously tracked by means of a quadrotor unmanned aerial vehicle with a self-tuning fuzzy proportional integral derivative controller. A proportional integral derivative controller and a fuzzy system tuning gains from proportional integral derivative controller are applied to stabilize the quadrotor, to control the attitude and to track the trajectory. Inputs of fuzzy logical controller consist of the speed required for the distance between the current position of unmanned aerial vehicle and the defined reference point and differences between orientation angles and variance in differences. Outputs of fuzzy logical controller consist of the proportional integral derivative coefficients which produce pitch, roll, yaw and height values. The fuzzy proportional integral derivative control algorithm is real-time applied to the quadrotor in MATLAB/Simulink environment. Based on data from experimental studies, although both classical proportional integral derivative controller and self-tuning fuzzy proportional integral derivative controller have accomplished to track a defined trajectory with the aircraft, the self-tuning fuzzy proportional integral derivative controller has been able to control with less errors than the classical proportional integral derivative controller.

A Combined Control Strategy for Fixed-Wing Unmanned Aerial Vehicles

This study proposes a combined proportional–integral–derivative (PID) flight control strategy within a fixed-wing unmanned aerial vehicle (UAV). This type of UAV has high speed and high maneuverability. Considering relatively simple implementation, low computational effort, and intuitive operation, the classic PID controller is still popular but imperfect because of several well-known reasons. A number of practical and improved PID control methods, such as integral separation, anti-windup, and gearshift integral, are always used separately in many control fields. In this study, the combined PID flight control strategy is designed and applied to promote the classic PID control performance, along with the aforementioned methods, to fixed-wing UAV. The proposed approach adopts different controls depending on the deviation outputs and UAV physical limitations. The design flowchart and flight control loop are also presented. The combined PID flight control strategy can achieve a smaller overshoot and a shorter settling time than the conventional PID control. Comparable typical flight parameter tracking results (i.e., pitch, roll, altitude, and path angle) from principle simulation, hardware-in-the-loop simulation, and real flight experiment validate the efficacy and practicability of the combined PID flight control strategy.

Processing control of the forging integration based on force compliance

The method of force compliance was proposed during process of the manipulator cooperating with the movement of the forging press, which could avoid the destructive effect generated by the deformation resistance of the workpiece for the key parts. Taking the 20T forging manipulator as the target, the inverse kinematics model and the dynamic model of the major-motion mechanism were established. Through taking the pressure as the controlled variable, the dynamic model of the hydraulic lifting system was built. Based on the buffering principle, the mathematics model of the horizontal buffering system was deduced. Taking the deformation model of workpiece as the input, the variations of the displacements and forces for hydraulic cylinders were obtained by the simulation. Finally, the effectiveness of active pressure compliance method of the lifting control system using the classical proportional–integral–derivative control strategy and that of the passive compliance method for the buffering system were verified.

Building energy consumption flatness-based control using algebraic on-line estimation

A new model-based on-line control of building energy consumption with no drawbacks related to the thermal model or the unplanned changes (occupation, exterior temperature, …) is presented in this paper. The main theoretical tools of this method are the flatness-based control and the recent new setting of numerical differentiation for fast and on-line parameter estimation. Indeed the estimation techniques form an added value in terms of the reliability of the thermal model. Furthermore, the main advantage of using the differential flatness control scheme is that the system behavior can be described by the trajectory of a so-called flat output and a number of its successive time derivatives. This leads to a simple design of the control strategy without the integration of any differential equations. Numerical simulations as well as comparative studies with a classical PID (proportional-integral-derivative) controller are provided to demonstrate the relevance of the proposed approach.

Fractional Control of a Humanoid Robot Reduced Model with Model Disturbances

ABSTRACTThere is an open discussion between those who defend mass-distributed models for humanoid robots and those in favor of simple concentrated models. Even though each of them has its advantages and disadvantages, little research has been conducted analyzing the control performance due to the mismatch between the model and the real robot, and how the simplifications affect the controller’s output. In this article we address this problem by combining a reduced model of the humanoid robot, which has an easier mathematical formulation and implementation, with a fractional order controller, which is robust to changes in the model parameters. This controller is a generalization of the well-known proportional–integral–derivative (PID) structure obtained from the application of Fractional Calculus for control, as will be discussed in this article. This control strategy guarantees the robustness of the system, minimizing the effects from the assumption that the robot has a simple mass distribution. The humanoid robot is modeled and identified as a triple inverted pendulum and, using a gain scheduling strategy, the performances of a classical PID controller and a fractional order PID controller are compared, tuning the controller parameters with a genetic algorithm.

Design of a Fuzzy Logic Based Controller for Fluid Level Application

In industrial process control, fluid level control is one of the most basic aspects. Many control methods such as on-off, linear and PID (Proportional Integral Derivative) were developed time by time and used for precise controlling of fluid level. Due to flaws of PID controller in non-linear type processes such as inertial lag, time delay and time varying etc., there is a need of alternative design methodology that can be applied in both linear and non-linear systems and it can be execute with fuzzy concept. By using fuzzy logic, designer can realize lower development cost, superior feature and better end product. In this paper, level of fluid in tank is control by using fuzzy logic concept. For this purpose, a simulation system of fuzzy logic controller for fluid level control is designed using simulation packages of MATLAB software such as Fuzzy Logic Toolbox and Simulink. The designed fuzzy logic controller first takes information about inflow and outflow of fluid in tank than maintain the level of fluid in tank by controlling its output valve. In this paper, a controller is designed on five rules using two-input and one-output parameters. At the end, simulation results of fuzzy logic based controller are compared with classical PID controller and it shows that fuzzy logic controller has better stability, fast response and small overshoot.

Dynamic Hybrid Control of a Hexapod Walking Robot: Experimental Verification

In this paper, a walking robot that consists of its body and six legs is considered for trajectory control. The leg mechanism is a 1-UP&2-UPS (U-universal joint, P-prismatic joint, and S-spherical joint) parallel mechanism with the arm-leg conversion function. Due to the nonlinearity and uncertainties of the robot, it is difficult to obtain its exact dynamic model, therefore this paper utilizes the decentralized control strategy to design a dynamic hybrid controller, in which the outer loop is an impedance controller, the middle and inner loops are designed by using the sliding-mode control and the nonlinear proportional-integral-derivative (PID) control, respectively. The inverse kinematics of one leg is derived for mathematic model, based on which three control methods including the classical PID control, position-velocity loops cascade control, and dynamic hybrid control are examined. Contrast tracking experiments were performed with one robotic leg. The experimental results are shown to identify their differences and prove the effectiveness and applicability of the proposed dynamic hybrid control.

Iterative algorithm and curve fitting technique for tuning with time delay system PID controller

In this paper, hybrid technique proposed for tuning Time Delays System with proportional-integral-derivative (PID) controller. So, the performance and the robustness for a class of Time Delay System are improved. The proposed hybrid technique is the combination of the iterative algorithm and curve fitting technique. The proposed iterative algorithm is improved, performance of the feedback tuning iterative technique; so the computational complexity of the iterative algorithm reduced. By using the iterative technique, the best polynomial coefficients of curve fitting technique is determined. Using the curve fitting technique, the Time Delay System is tuned and the stability parameters of the system is maintained. The curve fitting technique is one of the non linear programming techniques which can be constructed that approximately fits the data from the extract data. The proposed hybrid technique is implemented in MATLAB working platform and the tuning performance is evaluated. Then, the system performance of the proposed hybrid technique is compared with classical PID controller, Ziegler-Nichols tuning method.