Nonlinear PI Research Articles

An Improved Scheme of Power Quality in Wind Generation System Using Novel Nonlinear PI Controller

This paper is based on the research of low wind speed area, which is velocity alters rapidly and the wind power concentration is lower. Not only the maximum power point tracking (MPPT) strategy for Wind Generation System would be even more demanding, but also the efficiency of converter in generator sider and gird side by voltage space vector PWM (SVPWM) in field oriented control would be even more achieving. The reaction of controller is the key of control scheme. The wind power system in low wind speed area needs more smoothing and short time oscillation. A new type of nonlinear PI controller has devoted to the enhancement of wind generation system adoption in low wind speed area. The result has presented the comparison between tradition controller and novel controller via Matlab/Simulink.

Decentralized neuro-fuzzy controllers of nonlinear quadruple tank system

This paper presented two decentralized neuro-fuzzy controllers to control the level in lower two tanks in nonlinear quadruple tank system (QTS). The controllers are designed based on adaptive neuro-fuzzy inference system technique. The relation between inputs/outputs was proved using relative gain array, and then, we can divide the quadruple tank system into two subsystems and control each of them separately. The first controller is a neuro-fuzzy inverse nonlinear (NFIN) model, which predicts the voltage required to control the level to track the referred one. So, the voltage was fed to neuro-fuzzy forward nonlinear model (NFFN) to obtain the desired level. The second is neuro-fuzzy nonlinear gain scheduling PI controller, which is designed to control the nonlinear QTS at any operating point. The results show that the NFIN controller has a more accurate tracking level and less computational time in both minimum and non-minimum phases.

New Pseudoinverse-Based Path-Planning Scheme With PID Characteristic for Redundant Robot Manipulators in the Presence of Noise

In this paper, a new path-planning scheme based on pseudoinverse-type formulation for redundant robot manipulators with the existence of noise is proposed and investigated. Such a pseudoinverse-based path-planning (PPP) scheme contains the proportional, integral, and derivative information of the desired Cartesian path (of the end-effector), and can thus be viewed as a nonlinear proportional–integral–derivative (PID) controller for redundant robot manipulators. In other words, the proposed PPP scheme has the PID characteristic in terms of the desired Cartesian path. Theoretical results are given to show that the Cartesian error synthesized by the proposed PPP scheme has the property of global and exponential convergence (that is to say, the error trajectory is asymptotically stable) and to indicate that such a scheme has the capability to suppress noise. Simulation results based on a four-link planar robot manipulator with the existence of zero, constant, and bounded time-varying noises are presented to further substantiate the efficacy and superiority of the proposed PPP scheme for the path planning of redundant robot manipulators. The physical realizability of the proposed PPP scheme is also demonstrated by applying this scheme to a practical six-link planar robot manipulator.

Hybrid Perimeter Control for Two-region Urban Cities With Different States

Macroscopic fundamental diagram (MFD) describes a unimodal, low-scatter relationship between network vehicle density and network space mean flow for homogenous network regions, and provides a possible solution to traffic signal control for urban road networks. Transfer between multiple states has been ignored in a few control methods, despite continuous advances in the areas of congestion perimeter control because different states should have different control objectives. This paper proposes a boundary hybrid control for two-region urban cities based on three network states: free flow, critical flow, and congestion flow as characterized by MFD. The hybrid perimeter control for two-region urban cities with different states can be set up according to different control objectives by analyzing the control adaptation characteristics for the single-control method of Bang-Bang, PI feedback control, and nonlinear PI control based on the MFD curve at a single-boundary entrance under different conditions. Furthermore, the confirmation of rapid reduction in the saturation, traffic distribution, and signal timing of the boundary intersection is derived. An urban center network located approximately 20 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> in Hefei is taken as an example. Comparison results show that the hybrid control performs significantly better than the single-control scheme in completing vehicle travel, decreasing travel delay, and preventing network oversaturation.

Nonlinear PI output power regulation in a light water reactor

Robust nonlinear control of the load following operation has been attempted for a nuclear facility with a pressurized water reactor. A multi-linear model of the plant has been employed to contrive an appropriate proportional-integral (PI) controller further applied to the original nonlinear system. PI parameters (kP,kI) are adopted within the largest intersecting stability regions for all local models. Plant uncertainties due to the variable model parameters are moreover characterized within a multiplicative layout and the largest bound for the local models is assigned as the overall system uncertainty. Nyquist stability criterion is accordingly investigated for the robust stability of the PI controller. The proposed strategy is finally applied in two realistic load following scenarios addressed as output trajectory tracking problems. Results confirm a successful robust control practice for the nonlinear plant with a feasible control rod drive current as the regulating input.

Probabilistic fuzzy logic controller for uncertain nonlinear systems

This paper proposes a probabilistic fuzzy proportional - integral (PFPI) controller for controlling uncertain nonlinear systems. Firstly, the probabilistic fuzzy logic system (PFLS) improves the capability of the ordinary fuzzy logic system (FLS) to overcome various uncertainties in the controlled dynamical systems by integrating the probability method into the fuzzy logic system. Moreover, the input/output relationship for the proposed PFPI controller is derived. The resulting structure is equivalent to nonlinear PI controller and the equivalent gains for the proposed PFPI controller are a nonlinear function of input variables. These gains are changed as the input variables changed. The sufficient conditions for the proposed PFPI controller, which achieve the bounded-input bounded-output (BIBO) stability are obtained based on the small gain theorem. Finally, the obtained results indicate that the PFPI controller is able to reduce the effect of the system uncertainties compared with the fuzzy PI (FPI) controller.

Nonlinear Controllers in the Regulation Problem of the Robots

The report presents the results on the application of nonlinear PI and PID regulators in the position stabilization problem of the robots. As an example the position stabilization problem of a three-wheeled mobile robot with a displaced mass center is considered.

Robust Control of Railway Traction System

Abstract In this paper, a robust control strategy of a railway traction system with induction motor is proposed. The control problem is divided into sub-loops such as, current loop, acceleration loop, speed loop and position loop. A conventional PI controller is designed for the current loop, which is a very fast loop in comparison to the other mechanical loops. A nonlinear PI controller is used to control the acceleration loop. The speed and position loops are controlled via robust PI-PD controllers. The robustness problem is considered both as disturbance rejection, which arise due to resistive forces, and as robustness against uncertainties such as, the mass of the railway vehicle and the wheel diameter. The practical applicability of the method is emphasized via verification and validation steps with realistic constraints on acceleration, jerk, torque and power on a case study. Simulation results reveal that the proposed controller structure is quite effective for a railway traction system.

Experimental Study of Nonlinear PID Controllers in an Air Levitation System

This paper presents an experimental study of different non-linear PI controllers using an academic platform based on an Air Levitation System. The comparison is based on common performance indexes, computed over the data extracted from the experiments. The results verify that, in addition to the PID controller in its classic form, several non-linear modifications can be considered to cope with different control needs, such as optimization on the number of control actions, or go beyond the restrictions that linearity impose on the performance that can be obtained by a PID controller.

Robust nonlinear adaptive mould level control for steel continuous casting

Abstract The mould level control for steel continuous casting is an open research problem. In ACINOX-Las Tunas steelwork there are occasional problems with the amplitude of mould level variations and with the stability of the control system. The control quality should be better satisfied and a robust nonlinear PI controller with guaranteed robustness designed with a new NPI-RR method is proposed. This achieves a good trade-off between robustness and disturbance attenuation and also optimizing the trade-off between disturbance attenuation and control effort. The slow disturbances, related to erosion or clogging of the stopper valve and the tundish level variations, can be compensated through an adaptive scheme with gain scheduling, fuzzy logic and online identification. The simulation scale results illustrate the effectiveness of the proposal.

Unifying adaptive control with the nonlinear PI methodology: Designs for unknown strict‐feedback nonlinear systems with nonsmooth actuator nonlinearities

SummaryIn this paper, we extend the nonlinear PI control methodology within an adaptive control framework. An adaptive nonlinear PI controller is proposed for output tracking of strict‐feedback nonlinear systems with nonsmooth actuator nonlinearities and unknown control directions. The current approach relaxes the standard assumption of known bounds for the associated system nonlinearities made in earlier nonlinear PI schemes. New theoretical boundedness results have been proved that enable the successful combination of backstepping and linear parametric approximators with the nonlinear PI approach and ensure semiglobal approximate tracking of the output to some reference trajectory. Following recent extensions of the nonlinear PI method to strict‐feedback systems, the intermediate virtual control laws are derived through suitable integral equations. Simulation results are also presented in this paper that verify our theoretical analysis.

Non-linear PI regulators in control problems for holonomic mechanical systems

ABSTRACTIn this paper we propose a solution to the regulation problem of holonomic mechanical systems without velocity measurements by constructing nonlinear PI controllers. An approach based on the Lyapunov functional method is used to analyse the stability of the closed-loop system which has the form of Volterra integro-differential equation. The paper presents the quasi-invariance principle for Volterra nonlinear integral differential equations. Furthermore, we present sufficient conditions that one can use to conclude the asymptotic stability of the closed-loop system via using a Lyapunov functional with semi-definite time derivative. The simulation results of the two-link robot manipulator demonstrate the effectiveness of the proposed PI controller.

Real-time integration of control strategies for an isolated DFIG-based WECS

This paper deals with voltage and frequency control of a stand-alone wind energy conversion system (WECS) based on a double fed induction generator (DFIG) under wind speed and load variations. In this context, two kinds of linear and nonlinear control strategies, classical PI and backstepping, have been applied to the system in real time. A series of experiments have been conducted to evaluate and to compare dynamic performances of the proposed control approaches. Experiments on a 1.5Kw doubly fed induction machine in real time are carried out using dSpace DS1104 card based on the MATLAB/Simulink environment. Experimental results show the validity of implemented controllers and demonstrate the effectiveness, the precision and the rapidity of the backstepping control strategy compared with the PI controller.

Consensus in Networks of Agents With Unknown High-Frequency Gain Signs and Switching Topology

The agreement control problem of single and double-integrator agents with unknown and nonidentical control directions is addressed in this note under switching network topology. Distributed nonlinear PI control laws are proposed which ensure asymptotic consensus among the agents based on a new boundedness lemma and a generalized version of Barbalat's lemma for uniformly piecewise right continuous functions. Theoretical results are verified by simulation studies.

Robust control of internal states in a polymer electrolyte membrane fuel cell air-feed system by considering actuator properties

Air stoichiometry, pressure, and relative humidity in the air-feed system of a vehicular polymer electrolyte membrane fuel cell (PEMFC) influence efficiency, durability and reliability. It is critical to develop robust control algorithms for these internal states to improve system performance. There is limited extant research on designing robust control algorithms that consider the three internal states as well as the constraints of real actuators, such as an air compressor, a membrane humidifier, and a back-up pressure valve (BPV). This study examines robust control strategies for the three internal states based on adaptive second order sliding mode (ASOSM) and nonlinear proportional-integral (NPI) feedback control algorithms. In the study, control targets are established based on stable properties of the PEMFC system. The study involves proposing and comparing five control strategies that are a combination of NPI and ASOSM algorithms. The following results are obtained: (1) the stable control targets for the three internal states are followed adequately by using an NPI or an ASOSM algorithm and differences only exists in dynamic processes; (2) with respect to the control of air stoichiometry, an NPI algorithm performs better than an ASOSM algorithm as chattering in air stoichiometry can be avoided and the convergence time to the target value is acceptable; (3) with respect to the control of cathodic pressure, an ASOSM algorithm performs better than an NPI algorithm as the overshoots in cathodic pressures can be effectively reduced; (4) with respect to the control of relative humidity, both NPI and ASOSM algorithms lead to a practical bang–bang strategy. The strategy that performs the best among the five strategies is selected, and the robustness of the selected strategy with respect to parameter uncertainties is verified.

Design and Implementation of a Nonlinear PI Predictive Controller for a Grid-Tied Photovoltaic Inverter

This paper presents the design, implementation, and performance testing of a nonlinear proportional-integral (PI) predictive controller for a grid-tied inverter used in photovoltaic systems. A conventional cascade structure is adopted to design the proposed controller, where the outer loop is used to regulate the dc-link voltage, and the inner loop is designed as a current controller for adjusting the active and reactive powers injected into the grid. For each loop, the controller is derived based on combining a continuous-time nonlinear model predictive control and nonlinear disturbance observer techniques. It turns out that the composite controller reduces to a nonlinear PI controller with a predictive term that plays an important role in improving tracking performance. The salient feature of the proposed approach is its ability to approximately preserve the nominal tracking performance during the startup phase. Both simulation and experimental results are provided to demonstrate the effectiveness of the proposed approach in terms of nominal performance recovery, disturbance rejection, and current control.

EKF-based self-regulation of an adaptive nonlinear PI speed controller for a DC motor

EKF-based self-regulation of an adaptive nonlinear PI speed controller for a DC motor

Design of Model Reference Adaptive control and Nonlinear PI Controller for Continuous Stirred Tank Reactor

Design of Model Reference Adaptive control and Nonlinear PI Controller for Continuous Stirred Tank Reactor

Fuzzy-PSS and fuzzy neural network non-linear PI controller-based SSSC for damping inter-area oscillations

In this paper, a new approach is recommended for damping out power system oscillations. In this approach, a new fuzzy neural proportional–integral (PI) controller (FNPIC) based static synchronous series compensator (SSSC) and a fuzzy-power system stabilizer (fuzzy-PSS) with a new structure are simultaneously employed. Adaptive learning rates based on the Lyapunov stability theory to enhance the convergence speed of the proposed controller are obtained. In the structure of fuzzy-PSS, a pattern search algorithm is used to adjust four gains. A two-area four-machine power system and a three-area, three-machine power system are employed to investigate the efficiency of the proposed method. Simulations results confirm the capabilities of proposed controller in suppressing the power system oscillations.

Robust IDA-PBC for underactuated mechanical systems subject to matched disturbances

The problem of robustification of interconnection and damping assignment passivity-based control for underactuated mechanical system vis-a-vis matched, constant, and unknown disturbances is addressed in the paper. This is achieved adding an outer-loop controller to the interconnection and damping assignment passivity-based control. Three designs are proposed, with the first one being a simple nonlinear PI, while the second and the third ones are nonlinear PIDs. While all controllers ensure stability of the desired equilibrium in spite of the presence of the disturbances, the inclusion of the derivative term allows us to inject further damping enlarging the class of systems for which asymptotic stability is ensured. Numerical simulations of the Acrobot system and experimental results on the disk-on-disk system illustrate the performance of the proposed controller. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.