Tuning Of Controller Parameters Research Articles

DDPG based LADRC trajectory tracking control for underactuated unmanned ship under environmental disturbances

Realizing trajectory tracking control of underactuated unmanned ships is critical for safe and stable navigation during offshore operations. The principal difficulties of this task lie in the coupling problem caused by the underactuated system and the uncertainty caused by the modeling error, internal parameter perturbations, and external environment. In this paper, a three-degree-of-freedom ship model is first built based on the manipulative modeling group equation. Then, a trajectory tracking line-of-sight guidance law is proposed to achieve the desired heading angle and forward speed during trajectory tracking, and the Lyapunov function is used to analyze its stability. Furthermore, the heading angle controller and forward speed controller are designed based on the linear active disturbance rejection control framework. In addition, to solve the challenging problem of controller parameter tuning and further improve the controller’s robustness, the Deep Deterministic Policy Gradient algorithm is applied to adjust the controller parameters. Finally, the effectiveness of the proposed method is verified by the simulation results of sinusoidal, circular, and square trajectories with wind and current disturbances.

Special issue on “Optimal design and operation of energy systems”

Special issue on “Optimal design and operation of energy systems”

Theoretical and experimental investigations on control parameters of piezo-based vibro-acoustic modulation health monitoring of contact acoustic nonlinearity in a sandwich beam

Contact-type defects are prevalent in composite constructions and sandwich panels due to failure mechanisms such as bolt loosening and delamination. Contact acoustic nonlinearity is a manifestation of such defects that nonlinear health monitoring systems can detect. Vibro-acoustic modulation (VAM) is a well-established technique for the early detection of nonlinear defects in structures. It employs bi-tone excitation to reveal damage-induced nonlinearity, which results in the appearance of sidebands in the response spectrum. The objective of this research is to use PZT-based excitation to monitor bolt loosening in a sandwich beam in real-time. To address the limited capacity of the PZT transducers to excite the nonlinear mechanism, a sensitivity analysis (SA) for input factors of VAM testing was conducted to improve damage detection using the results. The Morris approach is used to investigate the sensitivity of VAM damage metrics derived analytically in the frequency domain. To reduce the number of tests required for the experimental SA, the response surface methodology (RSM) is applied. The analysis of variance and Fischer's statistics are used to calculate the SA of experimental damage indices. In RSM computations, the discrete influence of excitation frequencies on the modulation sidebands is addressed. For reliable SA of experimental results, the effect of background noise is taken into account. The findings of this study may be applied to the selection of appropriate damage metrics in real-world applications of VAM health monitoring systems, as well as the effective tuning of input control parameters to maximize damage detectability.

Optimization with genetic algorithms of individual pitch control design with and without azimuth offset for wind turbines in the full load region

The reduction of fatigue loadings in wind turbines to increase their lifetime has become of special interest from a control viewpoint. Individual Pitch Control (IPC) is a well-known approach used to mainly mitigate periodic blade loads, and it is usually implemented with the assistance of the multi-blade coordinate (MBC) transformation, which transforms and decouples the measured blade load signals from a rotating frame into a non-rotating tilt-axis and yaw-axis. Nevertheless, these axes still show coupling between them in practical scenarios adversely affecting the system performance. Previous studies have demonstrated the benefits of including an extra tuning parameter in the MBC, the azimuth offset, in improving the performance achieved by the IPC. However, the tuning of this parameter and its real improvements that can be obtained compared to the IPC without this offset require more research. Here, two 1P+2P IPC, with and without additional azimuth offset, are designed and applied to the 5 MW reference turbine model developed by NREL using the FAST software as a simulation platform. The controller parameter tuning is formulated as an optimization problem that minimizes the blade fatigue load according to the Dirlik index and that is resolved through genetic algorithms. To fairly analyze the improvement entailed by the addition of the azimuth offset, both optimized IPC schemes, with and without azimuth offset, are compared qualitatively and quantitatively using a classical controller as the baseline case. From the simulation results, it can be stated that the optimal IPC scheme with azimuth offset compared with the IPC scheme without offset achieves improvements of around 11% in load reduction and pitch signal effort.

Design of Fitness Function for Intelligent Parameter Tuning of PID Controller on Belt Conveyor with PSO

Design of Fitness Function for Intelligent Parameter Tuning of PID Controller on Belt Conveyor with PSO

Adaptability analysis of linear continuous control systems with reference model

The problem of analyzing the tuning parameters of linear continuous controllers related to the class of state models is studied. To do this, algorithms for adjusting the controller are used, which are based on estimates of the plant parameters. Within the framework of this study, the adaptability property of the system is considered, and the primary goal is to determine the possibility of finding an exact solution to the problem of tuning the control loop for a given reference transient. Moreover, the study extends to a whole class of input actions, such as piecewise continuous functions of time. Based on the analysis of the convergence properties of the identification residual in a closed control system, additional simplified conditions for the adaptability of control systems using an identifier and a reference model are put forward, which supplement the already existing knowledge on this topic.

A Method for Evaluating the Impact of Controllers and Wind Turbine Generators on Low-Frequency Oscillation

Based on the celebrated Generalized Nyquist Criterion, this paper presents a new frequency-domain method to analyze the impact of governor-turbine systems (GTSs), power system stabilizers (PSSs) and wind turbine generators (WTGs) on small disturbance stability in power systems. Compared with other common analysis method, the new method can avoid the calculations of eigenvalues, eigenvectors and residues, and the impact of multiple controllers or WTGs can be obtained using simple matrix operations. In addition, the method is intuitive for users since the stability analysis results can be displayed in the complex plane directly. The new method indicates that the impact of controllers and WTGs on power system is determined by the phase of certain elements in the transfer function matrices of controllers, WTGs and synchronous grid. Based on the information provided by the afore-mentioned transfer function matrices, the parameters of controllers can be optimized properly. The proposed method has been tested using the data of a four-machine two-area system and a regional power grid in China. The results demonstrate that the effect of controllers and WTGs can be conveniently identified, and the effectiveness of parameter tuning for controllers is verified.

Modified PSO tuned two stage lead lag STATCOM control action for small signal stability enhancement of variable wind integrated power system

In this work Modified PSO (MPSO) is proposed to tune two stage lead lag control action based on STATCOM for enhancing small signal stability of an intermittent wind source penetrated power system. The Modified PSO has been compared with standard PSO and fractional PSO to tune controller parameters of STATCOM based control action. Multi machine system subjected to sudden and intermittent wind variations have been considered in this work. Subject to this wind penetration the lead lag control action with only PSO and two stage lead lag control action with fractional PSO and modified PSO has been implemented to damp the system oscillations pertaining to initial operating condition. It was found that subject to intermittent nature of wind penetration the rotor angle small signal stability is being hampered and subject to this when the modified PSO tuned two stage lead lag STATCOM control action is applied, it damps the oscillations heavily and the results have been compared with only PSO and fractional PSO control algorithms.

Generalized Homogeneous Unit Control

The methodology of the unit sliding mode control design (known since 1970s) for linear MIMO (Multiply Inputs Multiply Outputs) systems is revised based on the concept of the generalized homogeneity. The conventional restriction about a consistency of the number of control inputs with the dimension of the sliding surface is eliminated. A simple procedure for control parameters tuning is developed. The robustness of the homogeneous unit controller with respect to bounded matched perturbations is proven. The theoretical results are supported by numerical simulations.

Research on Parameter Optimization Method of Sliding Mode Controller for the Grid-Connected Composite Device Based on IMFO Algorithm.

In order to make the grid-connected composite device (GCCD) controller meet the requirements of different operating modes and complex working conditions of power grid, this paper proposes to introduce sliding mode control (SMC) into GCCD controller. Firstly, the mathematical model of MMC converter is established, and the sliding mode controller is designed based on the SMC principle. Then, aiming at the problems of complex controller structure and difficult parameter tuning in multiple modes of the GCCD, this paper proposes a controller parameter optimization method based on improved Month Flame optimization (IMFO) algorithm. This method improves the MFO algorithm by introducing good point set (GPS) initialization and Levy flight strategy, which accelerates the convergence speed of the algorithm while avoiding falling into local optimization, and realizes the optimization of converter controller parameters. Under a variety of standard test functions, the advantages of the proposed IMFO algorithm are verified by comparing it with the traditional algorithm. Finally, in order to realize the automatic tuning of control parameters, the Python-PSCAD joint simulation method is studied and implemented. Taking the comprehensive integral of time and absolute error (CITAE) index as the objective function, the parameters of the sliding mode controller are optimized. The simulation results show that the controller parameters optimized by the IMFO algorithm can make the GCCD have better dynamic performance.

Method for PID-tuning via feedback control system pole placement

Pole placement is the only PID-tuning technic that allows one to obtain a control system with desired, and, moreover, highly predictable performance and control quality. Number of controller tuning parameters is equal to number of poles closed-loop poles it can precicely place, so that PID-controller can place exactly three poles, and PI- can place only two. For this reason PI-controller is best used with first-order processes (second-order closed loop system), and PID-controller with second-orded ones (third-order closed loop system). However, many processes have higher order than two, and still are controlled with PID-controllers. To tune it using pole placement techniques, it is necessary to consider only dominant poles, which affect performance of the system to the greatest extent. First, it is necessary to study a PI-controller with a second-order process, which is the most basic case. Tuning is performed using global optimization methods to fit dominant poles of a tuned system to dominant poles of a reference system.

Robust PID optimal tuning of a Delta parallel robot based on a hybrid optimization algorithm of particle swarm optimization and differential evolution

AbstractIn this paper, we propose an approach to tune optimal parameters of a robust PID controller by means of computed torque control (CTC) strategy for trajectory tracking of a Delta parallel robot, using a hybrid optimization algorithm of Particle Swarm Optimization (PSO) and differential evolution (DE). It differs from previous works that they propose robust PID controller parameters tuning based on conventional gradient-based optimization algorithms and apply them to process control. First, we reduce the tuning problem of a robust PID controller with CTC strategy satisfying requirements including robustness and disturbance attenuation to an optimization problem with nonlinear constraints by considering the nonlinear dynamic model of a Delta parallel robot. Second, we set up the design characteristics for the trajectory tracking of a Delta parallel robot. Then, we propose a robust PID controller in a way of obtaining the global optimization solution of the nonlinear optimization problem by running a PSO-DE hybrid optimization algorithm of finding the global optimal solution by maintaining the diversity of swarm during evolution based on the evolution of cognitive experience. Simulation and experimental results demonstrate that the proposed controller outperforms previous works with respect to robust performance and active disturbance attenuation when it is applied to tracking control of a Delta parallel robot.

MSP designing with optimal fractional PI–PD controller for IPTD processes

Abstract An effective tuning methodology of modified Smith predictor (MSP) based fractional controller designing for purely integrating time delayed (IPTD) processes is reported here. IPTD processes with pole at the origin are truly difficult to control; exhibit large oscillations once get disturbed from their steady state. Proposed MSP design consists of fractional PI (proportional-integral) and fractional PD (proportional-derivative) controllers together with P (proportional) controller. Fractional controllers are competent to provide improved closed loop responses due to flexibility of additional tuning parameters. Fractional tuning parameters of PI and PD controllers are derived through optimization algorithms where integral absolute error (IAE) is considered as cost function. Efficacy of the proposed methodology is validated for IPTD processes having wide range of time delay. Stability and robustness issues are explored under process model uncertainties with small gain theorem. Performance of the proposed MSP-FO(PI–PD) controller is validated through simulation study relating five IPTD process models. Overall satisfactory closed loop responses are observed for each case during transient as well as steady state operational phases.

Extending the LQR to the design of PID type‐ii and type‐iii control loops

AbstractThis paper concerns the improvement on Proportional‐Integration‐Derivative (PID) control for standard second‐order plus time‐delay systems (SOPTD). To achieve higher tracking precision and stronger disturbance rejection, a PID type‐ii and type‐iii control‐loops design method based on the combination of the linear quadratic regulator (LQR) and dominant pole configuration technology is proposed in this paper. The PID type‐ii control loop is capable of achieving perfect tracking of step and ramp reference signals with zero steady‐state position and velocity error. The PID type‐iii control loop is capable of achieving perfect tracking of step, ramp and parabolic reference signals with zero steady‐state position, velocity and acceleration error. The effectiveness of the proposed PID type‐ii and type‐iii controller parameters tuning rules has been demonstrated via simulation of over‐damped, critical‐damped and under‐damped systems. To be specific, compared with the PID type‐i control loop, rise time, settling time and disturbance rejection property of the system have been significantly improved while realizing faster reference signal tracking. Finally, the effects of non‐dominant pole on the stability and robustness of PID type‐ii and PID type‐iii closed loop systems have also been discussed.

Verification and Validation of Model-Scale Turbine Performance and Control Strategies for the IEA Wind 15 MW Reference Wind Turbine

To enable the fast growth of the floating offshore wind industry, simulation models must be validated with experimental data. Floating wind model-scale experiments in wind–wave facilities have been performed over the last two decades with varying levels of fidelity and limitations. However, the turbine controls in these experiments have considered only limited control strategies and implementations. To allow for control co-design, this research focuses on implementing and experimentally validating more advanced turbine control actions and strategies in a wind–wave basin for a 1:70-scale model of the International Energy Agency’s wind 15 MW reference wind turbine. The control strategies analyzed include torque control, collective pitch control, and transition region control (setpoint smoothing). Our experimental and numerical results include the effects of varying rotor speeds, blade pitches, and wind environments on the turbine thrust and torque. Numerical models from three different software tools are presented and compared to the experimental results. Their ability to effectively represent the aero-dynamic response of the wind turbine to the control actions is successfully validated. Finally, turbine controller tuning parameters based on the derivatives of thrust and torque are derived to allow for improved offshore wind turbine dynamics and to validate the ability of modeling tools to model the dynamics of floating offshore wind turbines with control co-design.

IK-SPSA-Based Performance Optimization Strategy for Steam Generator Level Control System of Nuclear Power Plant

The steam generator (SG) is a critical component of the steam supply system in the nuclear power plant (NPP). Hence, it is necessary to control the SG level well to ensure the stable operation of the NPPs. However, its dynamic level response process has significant nonlinearity (such as the ‘swell and shrinks’ effect) and time-varying properties. As most of the SG level control systems (SGLCS) are constructed based on the Proportional-Integral-Derivative (PID) controllers with fixed parameters, the controller parameters should be optimized to improve the performance of the SGLCS. However, traditional parameters tuning methods are generally experience-based, cumbersome, and time-consuming, and it is difficult to obtain the optimal parameters. To address the challenge, this study adopts a knowledge-informed simultaneous perturbation stochastic approximation (IK-SPSA) based on adjacent iteration points information to improve the performance of the SGLCS. Rather than the traditional controller parameter tuning method, the IK-SPSA method optimizes the control system directly by using measurements of control performance. The method’s efficiency lies in the following aspects. Firstly, with the help of historical information during the optimization process, the IK-SPSA can dynamically sense the current status of the optimization process. Secondly, it can accomplish the iteration step size tuning adaptively according to the optimization process’s current status, reducing the optimization cost. Thirdly, it has the stochastic characteristic of simultaneous perturbation, which gives it high optimization efficiency to optimize high dimensional controller parameters. Fourthly, it incorporates an intelligent termination control mechanism to accomplish optimization progress control. This mechanism could terminate the optimization process intelligently through historical iterative process information, avoiding unnecessary iterations. The optimization method can improve the stability, safety, and economy of SGLCS. The simulation results demonstrated the effectiveness and efficiency of the method.

A Dielectric Elastomer Actuator-Driven Vibro-Impact Crawling Robot.

Over the last decade, many bio-inspired crawling robots have been proposed by adopting the principle of two-anchor crawling or anisotropic friction-based vibrational crawling. However, these robots are complicated in structure and vulnerable to contamination, which seriously limits their practical application. Therefore, a novel vibro-impact crawling robot driven by a dielectric elastomer actuator (DEA) is proposed in this paper, which attempts to address the limitations of the existing crawling robots. The novelty of the proposed vibro-impact robot lies in the elimination of anchoring mechanisms or tilted bristles in conventional crawling robots, hence reducing the complexity of manufacturing and improving adaptability. A comprehensive experimental approach was adopted to characterize the performance of the robot. First, the dynamic response of the DEA-impact constraint system was characterized in experiments. Second, the performance of the robot was extensively studied and the fundamental mechanisms of the vibro-impact crawling locomotion were analyzed. In addition, effects of several key parameters on the robot’s velocity were investigated. It is demonstrated that our robot can realize bidirectional motion (both forward and backward) by simple tuning of the key control parameters. The robot demonstrates a maximum forward velocity of 21.4 mm/s (equivalent to 0.71 body-length/s), a backward velocity of 16.9 mm/s, and a load carrying capacity of 9.5 g (equivalent to its own weight). The outcomes of this paper can offer guidelines for high-performance crawling robot designs, and have potential applications in industrial pipeline inspections, capsule endoscopes, and disaster rescues.

Sensored speed control of brushless DC motor based salp swarm algorithm

<p>This article uses one of the newest and efficient meta-heuristic optimization algorithms inspired from nature called salp swarm algorithm (SSA). It imitates the exploring and foraging behavior of salps in oceans. SSA is proposed for parameters tuning of speed controller in brushless DC (BLDC) motor to achieve the best performance. The suggested work modeling and control scheme is done using MATLAB/Simulink and coding environments. In this work, a 6-step inverter is feeding a BLDC motor with a Hall sensor effect. The proposed technique is compared with other nature-inspired techniques such as cuckoo search optimizer (CSO), honey bee optimization (HBO), and flower pollination algorithm (FPA) under the same operating conditions. This comparison aims to show the superiority features of the proposed tuning technique versus other optimization strategies. The proposed tuning technique shows superior optimization features versus other bio-inspired tuning methods that are used in this work. It improves the controller performance of BLDC motor. It refining the speed response features which results in decreasing the rising time, steady-state error, peak overshoot, and settling time.</p>

A New Robotic Knee Impedance Control Parameter Optimization Method Facilitated by Inverse Reinforcement Learning

Recent efforts in the design of intelligent controllers for configuring robotic prostheses have demonstrated new possibilities in improving mobility and restoring locomotion for individuals with lower-limb disabilities. In these efforts, personalizing the controller of the robotic device is a crucial step in order to meet individual user's needs and physical conditions. Reinforcement learning (RL) based control designs are among some of the most promising approaches to achieving real-time, optimal adaptive tuning capability. However, such designs to date rely on subjectively determining human-robot walking performance measures, commonly in a quadratic form. To further automate the RL design for robotic knee control parameter tuning and potentially improve human-robot locomotion performance, this study introduces a new bilevel optimization method to objectively specify such control design performance measures via inverse reinforcement learning (IRL), which in turn, will be used in low level (forward) RL design of the impedance control parameters. We demonstrate the effectiveness of the bilevel optimization approach with improved human-robot walking performance using systematic OpenSim simulation studies.

Instantaneous Power Control Within an Advanced Power Generation Center for More-Electric Aircraft Applications

This article presents an instantaneous power control (IPC) to regulate the power flow of a back-to-back converter (BTB converter) within an advanced power generation center (APGC) for more-electric aircraft applications. The APGC essentially is composed of two power generation channels (each channel is with a permanent magnet generator driven by two different engine shafts and an ac/dc converter) with a BTB converter connected in between. The BTB converter allows power transfer between these two channels and thus two different shafts of an aircraft engine. Control of the power transfer was achieved using the phase current synchronization (PCS) method where current flowing through the BTB converter is controlled to be in phase with that of one generator within the APGC. In this article, we propose an improved IPC technique. Compared with the previously proposed PCS method, the IPC method enables independent control of active power and reactive transferred from one channel to the other. The IPC also allows improved dynamic response in power control and elimination of tedious tuning of control parameters. The effectiveness and performance of the proposed IPC method are compared with those of the PCS method in terms of power control within the APGC in both simulation and experiments.