Classical PI Controller Research Articles

A Five-Level H-Bridge STATCOM for an Off-Grid PV Solar Farm under Two Controllers PI and PIλ-MPC Hybrid

Investigations were presented in order to eliminate the reactive power on microgrid loads fed by an off-grid and mid-power photovoltaic solar energy system (PVSES) with a static synchronous compensator (STATCOM) device. The electric network is specifically characterized by P-Q loads, ambient temperature, and widely variable solar radiation levels. Two main innovations are developed. Firstly, the STATCOM apparatus is a 5-level H-bridge inverter with capacitances as load and must totally compensates the reactive power in the network load. Secondly, this compensation is controlled by a set of fractional PI (PIλ) and model predictive control (MPC) hybrid. The efficiencies of these controllers were compared with classical PI controllers. Large simulations, without and with reactive power compensation, in steady and transient states, are carried out to underline the merits of the presented works, by performing in the MATLAB-Simulink environment.

An Integrated Biomimetic Control Strategy with Multi-agent Optimization for Nonlinear Chemical Processes

In this paper, a framework is proposed for integrating a Biologically-Inspired Optimal Control Strategy (BIO-CS) with Multi-Agent Optimization (MAO) algorithms for process systems engineering applications. In this framework, the BIO-CS employs gradient-based optimal control solvers in an intelligent manner to simultaneously control multiple outputs of the process at their desired setpoints. Also, the MAO uses the capabilities of nonlinear heuristic-based optimization techniques such as Efficient Ant Colony Optimization (EACO), Efficient Genetic Algorithm (EGA) and Efficient Simulated Annealing (ESA) by sharing process information to obtain as an upper layer optimal operating setpoints for the controller that satisfy the overall process objective. The resulting approach is a unique combination of control and optimization methods that provide optimal solutions for dynamic systems. The applicability of the proposed framework is demonstrated using a nonlinear, multivariable fermentation process. In particular, a multivariable control structure associated with the first-principles-based model derived from mass and energy balances of the fermentation process is addressed. The performance of the proposed approach for each step is compared to Sequential Quadratic Programming (SQP) and a classical Proportional-Integral (PI) controller in terms of optimization and control, respectively. The proposed approach improves the overall performance of the process in terms of cumulative production rate by approximately 10-15%, resulting in economic benefits. The obtained results illustrate the capabilities of this novel integrated framework to achieve desired nonlinear system performance considering scenarios associated with setpoint tracking and plant-model mismatch.

Direct Torque Control with Adaptive PI Speed Controller based on Neural Network for PMSM Drives

This paper presents an adaptive speed controller based on artificial intelligent technique to improvethe performance of classical Direct Torque Control (DTC) for Permanent Magnet Synchronous Motor (PMSM) drives. The proposed method applies back propagation (BP) based neural network (NN) to tune the parameters of classical proportional-integral (PI) speed controller. Comparisons between conventional PI speed controller and proposed method are carried out by Simulation.Simulation results demonstrate that conventional DTC system based on the proposed NN speed controller can achieve higher performance with fast speed response, small overshoot and robustness.

A comparative analysis of DFPI correctors and different techniques to regulate a shunt active power filter

Power quality is a subject of intense study over recent years, given that it affects the economic impact and costs of utilities, supply and manufacturing. Modern powered electronic equipment is usually nonlinear in nature and causes propagation of harmonic current. This disruptive current can be countered by various solutions, but active power filtering is the most captivating solution. In this paper, a Shunt Active Power Filter (SAPF) system is considered with a new corrector design for both the DC and AC sides. The new design is based on an association between double fuzzy logic and single PI correctors resulting in two 'DFPI' correctors devoted to regulating the DC voltage and the AC current of the SAPF. The DFPI corrector is more advantageous than the classic PI or fuzzy controllers implemented alone for regulation purposes of the SAPF control variables (DC voltage and the AC current). This is demonstrated, in this paper, through the addressed theoretical analysis of the proposed DFPI corrector and the studies shown in the simulation section comparing the proposed DFPI, single fuzzy, double fuzzy and PI controllers. Performances in terms of the filtering quality of the AC feeder side and the SAPF DC-bus voltage regulation quality (THDis%/THDVs%) are noted. The obtained numerical results prove the effectiveness of the DFPI corrector which also described a faster response time, a reduced overshoot and a lessened static error.

A comparative analysis of DFPI correctors and different techniques to regulate a shunt active power filter

Power quality is a subject of intense study over recent years, given that it affects the economic impact and costs of utilities, supply and manufacturing. Modern powered electronic equipment is usually nonlinear in nature and causes propagation of harmonic current. This disruptive current can be countered by various solutions, but active power filtering is the most captivating solution. In this paper, a Shunt Active Power Filter (SAPF) system is considered with a new corrector design for both the DC and AC sides. The new design is based on an association between double fuzzy logic and single PI correctors resulting in two 'DFPI' correctors devoted to regulating the DC voltage and the AC current of the SAPF. The DFPI corrector is more advantageous than the classic PI or fuzzy controllers implemented alone for regulation purposes of the SAPF control variables (DC voltage and the AC current). This is demonstrated, in this paper, through the addressed theoretical analysis of the proposed DFPI corrector and the studies shown in the simulation section comparing the proposed DFPI, single fuzzy, double fuzzy and PI controllers. Performances in terms of the filtering quality of the AC feeder side and the SAPF DC-bus voltage regulation quality (THDis%/THDVs%) are noted. The obtained numerical results prove the effectiveness of the DFPI corrector which also described a faster response time, a reduced overshoot and a lessened static error.

Lyapunov Function Analysis for System with Stochastic Nonsmooth PI Controller

This paper deals with non-smooth feedback stabilisation in presence of stochastic unbounded(normally distributed) noise. The integral term of classical proportional-integral controller is replaced by a discontinuous integrator. The overall control effort is still continuous. The behaviour of the proposed scheme under stochastic perturbations is presented. We have given a sound and non-trivial Lyapunov analysis of the closed loop system controlled by the proposed controller on stochastic dynamics.

Hybrid Energy Storage System Microgrids Integration for Power Quality Improvement Using Four-Leg Three-Level NPC Inverter and Second-Order Sliding Mode Control

Rising demand for distributed generation based on renewable energy sources (RES) has led to several issues in the operation of utility grids. The microgrid is a promising solution to solve these problems. A dedicated energy storage system could contribute to a better integration of RES into the microgrid by smoothing the renewable resource's intermittency, improving the quality of the injected power and enabling additional services like voltage and frequency regulation. However, due to energy/power technological limitations, it is often necessary to use hybrid energy storage systems (HESS). In this paper, a second-order sliding mode controller is proposed for the power flow control of a HESS, using a four-leg three-level neutral-point-clamped (4-Leg 3L-NPC) inverter as the only interface between the RES/HESS and the microgrid. A 3-D space vector modulation and a sequence-decomposition-based ac-side control allow the inverter to work in unbalanced load conditions while maintaining a balanced ac voltage at the point of common coupling. DC current harmonics caused by unbalanced load and the NPC floating middle point voltage, together with the power division limits, are carefully addressed in this paper. The effectiveness of the proposed technique for the HESS power flow control is compared to a classical PI control scheme and is proven through simulations and experimentally using a 4-Leg 3L-NPC prototype on a test bench.

Simple Observer-Based Feedback Strategy for Controlling Fed-Batch Hybridoma Cultures

Cultures of hybridoma cells in bioreactors are commonly used to produce monoclonal antibodies. As an alternative to nonlinear model predictive control, which has recently been applied successfully to optimize the process productivity, a simpler control approach is developed in the present study. This strategy is based on a classical PI controller and software sensors for the reaction rates, which exploit the particular structure of the dynamic model. The dynamic behavior of the process can indeed be subdivided into four operating zones, depending on the overflow metabolism of the hybridoma cells. In addition, robustness towards model uncertainties and measurement noise is investigated.

Model‐free control of a seeded batch crystallizer

AbstractAs the use of a batch crystallization process in several industrial applications is extensive, finding an effective control strategy is important to improve the product quality, which is typically characterized by a unimodal and narrow crystal size distribution (CSD) with a large mean crystal size. To achieve this requirement, an accurate mathematical model is needed to predict the process comportment and to design an efficient and robust controller. However, due to the highly nonlinear comportment, the difficulties of characterizing several phenomenological effects, the kinetic parameters, uncertainty, and the unknown disturbances, the used model may not describe the real process behaviour, resulting in a poor control strategy. In this work, a model‐free control and its corresponding intelligent PI (iPI), the recently introduced approach, has been proposed to ensure that the desired unimodal CSD with a desired mean size could be reached facing these problems with an easy control structure, choosing the seeded batch crystallizer of adipic acid as a case study. The proposed iPI is compared with the classic PI controller. The simulation results demonstrate the effectiveness and disturbance rejection capability of the iPI controller against the classic PI.

Lyapunov‐based high‐performance controller for modular resonant DC/DC converters for medium‐voltage DC grids

This study presents a high-performance controller based on the Lyapunov stability criterion that enhances the dynamic performance and disturbance rejection capability of resonant DC/DC converters when compared with classical PI control. The series–parallel resonant converter (SPRC) is used as the candidate converter to which this controller design is applied but the design can be generalised to other types of resonant DC/DC converters. By using a multiple module approach, low-power modules of this resonant converter are stacked to enable operation at medium-voltage DC (MVDC). The proposed controller design is applied to modular structure of the SPRC to verify its high-performance output in conjunction with active sharing control loops that ensure uniform current/voltage distribution across the multiple interconnected modules. Detailed controller design, closed-loop stability criteria, robustness and parameter sensitivity are investigated and controller performance is compared and verified against the classical PI control in simulation and low-scaled experimental prototype. Operations in single-module and two-module input-series output-parallel modes are both studied. The study affirms the selection of the modular DC/DC converter architecture and its associated proposed controls for high-performance MVDC applications.

A New Hybrid UPFC Controller for Power Flow Control and Voltage Regulation Based on RBF Neurosliding Mode Technique

This paper presents a new technique to design a Unified Power Flow Controller (UPFC) for power flow control and DC voltage regulation of an electric power transmission system which is based on a hybrid technique which combines a Radial Basis Function (RBF) neural network (online training) with the sliding mode technique to take advantage of their common features. The proposed controller does not need the knowledge of the perturbation bounds nor the full state of the nonlinear system. Hence, it is robust and produces an optimal response in the presence of system parameter uncertainty and disturbances. The performance of the proposed controller is evaluated through numerical simulations on a Kundur power system and compared with a classical PI controller. Simulation results confirm the effectiveness, robustness, and superiority of the proposed controller.

Closed-Loop Vagus Nerve Stimulation Based on State Transition Models.

Vagus nerve stimulation (VNS)is a potential therapeutic approach in a number of clinical applications. Although VNS is commonly delivered in an open-loop approach, it is now recognized that closed-loop stimulation may be necessary to optimize the therapy. In this paper, we propose an original generic closed-loop control system that can be readily integrated into an implantable device and allows for the adaptive modulation of multiple VNS parameters. The proposed control method consists of a state transition model (STM), in which each state represents a set of VNS parameters, and a state transition algorithm that optimally selects the best STM state, minimizing the error between an observed physiological variable and a given target value. The proposed method has been integrated into a real-time adaptive VNS prototype system and has been applied here to the regulation of the instantaneous heart rate, working synchronously with cardiac cycles. A quantitative performance evaluation is performed on seven sheep by computing classical control performance indicators. A comparison with a proportional-integral (PI)controller is also performed. The STM controller presents a median mean square error, overshoot, and settling time, respectively, equal to 622.21 ms , 72.8%, and 7.5 beats. The proposed control method yields satisfactory accuracy and time response, while presenting a number of benefits over classical PI controllers. It represents a feasible approach for multiparametric VNS control on implantable devices. Closed-loop multiparametric stimulation may improve response and minimize side effects on current pathologies treated by VNS.

Implementation and comparative study of control strategies for an isolated DFIG based WECS

Nowadays, a global interest for renewable energy sources has been growing intensely. In particular, a wind energy has become the most popular. In case of autonomous systems, wind energy conversion system (WECS) based on a double fed induction generator (DFIG) is widely used. In this paper, in order to control the stand-alone system outputs under wind speed and load variations, three kinds of nonlinear control strategies have been proposed, applied and compared, such as: Classical PI controller, Back-Stepping and Sliding Mode controllers. A series of experiments have been conducted to evaluate and to compare the developed controllers’ dynamic performances under load demand and speed variations. The design and the implementation of different control strategies to a 1.5kW doubly fed induction machine is carried out using a dSpace DS1104 card based on MATLAB/Simulink environment. Experimental results are presented to show the validity of the implemented controllers and demonstrate the effectiveness of each controller compared with others.

Development of Sliding Mode Controller for a Modified Boost Ćuk Converter Configuration

This paper introduces a sliding mode control (SMC)-based equivalent control method to a novel high output gain Ćuk converter. An additional inductor and capacitor improves the efficiency and output gain of the classical Ćuk converter. Classical proportional integral (PI) controllers are widely used in direct current to direct current (DC-DC) converters. However, it is a very challenging task to design a single PI controller operating in different loads and disturbances. An SMC-based equivalent control method which achieves a robust operation in a wide operation range is also proposed. Switching frequency is kept constant in appropriate intervals at different loading and disturbance conditions by implementing a dynamic hysteresis control method. Numerical simulations conducted in MATLAB/Simulink confirm the accuracy of analysis of high output gain modified Ćuk converter. In addition, the proposed equivalent control method is validated in different perturbations to demonstrate robust operation in wide operation range.

DDC Control Techniques for Three-Phase BLDC Motor Position Control

In this article, a novel hybrid control scheme is proposed for controlling the position of a three-phase brushless direct current (BLDC) motor. The hybrid controller consists of discrete time sliding mode control (SMC) with model free adaptive control (MFAC) to make a new data-driven control (DDC) strategy that is able to reduce the simulation time and complexity of a nonlinear system. The proposed hybrid algorithm is also suitable for controlling the speed variations of a BLDC motor, and is also applicable for the real time simulation of platforms such as a gimbal platform. The DDC method does not require any system model because it depends on data collected by the system about its Inputs/Outputs (IOS). However, the model-based control (MBC) method is difficult to apply from a practical point of view and is time-consuming because we need to linearize the system model. The above proposed method is verified by multiple simulations using MATLAB Simulink. It shows that the proposed controller has better performance, more precise tracking, and greater robustness compared with the classical proportional integral derivative (PID) controller, MFAC, and model free learning adaptive control (MFLAC).

A Real-Time SOSM Super-Twisting Technique for a Compound DC Motor Velocity Controller

In this paper, a real-time robust closed-loop control scheme for controlling the velocity of a Direct Current (DC) motor in a compound connection is proposed. This scheme is based on the state-feedback linearization technique combined with a second-order sliding mode algorithm, named super-twisting, for stabilizing the system and achieving control goals. The control law is designed to track a periodic square reference signal, being one of the most severe tests applied to closed-loop systems. The DC motor drives a squirrel-cage induction generator which represents the load; this generator must work above the synchronous velocity to deliver the generated power towards the grid. A classical proportional-integral (PI) controller is designed for comparison purposes of the time-domain responses with the proposed second-order sliding mode (SOSM) super-twisting controller. This robust controller uses only a velocity sensor, as is the case of the PI controller, as the time derivative of the velocity tracking variable is estimated via a robust differentiator. Therefore, the measurements of field current and stator current, the signal from a load torque observer, and machine parameters are not necessary for the controller design. The validation and robustness test of the proposed controller is carried out experimentally in a laboratory, where the closed-loop system is subject to an external disturbance and a time-varying tracking signal. This test is performed in real time using a workbench consisting of a DC motor—Alternating Current (AC) generator group, a DC/AC electronic drive, and a dSPACE 1103 controller board.

Nonlinear Controllers Based on Exact Feedback Linearization for Series-Compensated DFIG-Based Wind Parks to Mitigate Sub-Synchronous Control Interaction

The increasing penetration of wind power in the grid has driven the integration of wind farms with power systems that are series-compensated to enhance power transfer capability and dynamic stability. This may lead to sub-synchronous control interaction (SSCI) problems in series-compensated doubly-fed induction generator (DFIG)-based wind farms. To mitigate SSCI, nonlinear controllers based on exact feedback linearization (EFL) are proposed in this paper. Before deriving the control laws, the exact feedback linearizability of the studied system is scrutinized. Frequency scanning analysis is employed to test the designed EFL controllers. Moreover, the performance of the EFL controllers is compared to that of classical proportional-integral (PI) controllers. A series-compensated 100 MW DFIG-based wind park is utilized to assess the performance of the designed controllers through the alleviation of sub-synchronous resonance. Analyses of the studied system reveal that the resistance is negative under sub-synchronous frequency conditions, whereas the reactance becomes negative at approximately 44 Hz. The designed EFL controllers effectively alleviate SSCI and result in positive reactance and resistance values within the whole sub-synchronous frequency range. The results from the frequency scanning method are also validated through the time domain simulation and the eigenvalue analysis.

Firefly Optimization Algorithm for the Reactive Power Control of an Isolated Wind-Diesel System

This paper investigates the application of firefly optimization algorithm to design an optimal control for voltage stability of a stand-alone hybrid renewable generation unit based on reactive power control. The studied renewable generation unit mainly consists of a permanent magnet induction generator driven by wind turbine and a synchronous generator driven by diesel engine. A STATCOM is used to stabilize the terminal load bus voltage via compensating of reactive power. The main control objective aims to stabilize the terminal load voltage against any disturbances in load reactive power and/or input wind power by adjusting the total system reactive power. This is accomplished by controlling STATCOM phase angle and hence to control the load bus voltage and also by controlling the excitation voltage of the synchronous generator. The proposed renewable energy power system based on the proposed optimal controller has been tested through step change in input wind power and load reactive power. The system performance based on the proposed control is compared with model predictive control, a robust H∞ control, and a classical PI control.

Intelligent tuning of vibration mitigation process for single link manipulator using fuzzy logic

In this work, active vibration mitigation for smart single link manipulator is presented. Two piezoelectric transducers were utilized to act asactuator and sensor respectively. Classical Proportional (P) controller was tested numerically and experimentally. The comparison between measured results showed good agreement. The proposed work includes the introducing of fuzzy logic for tuning controller's gain within finite element method. Classical Proportional-Integral (PI), Fuzzy-P and Fuzzy-PI controllers were totally integrated as a series of [IF-Then] states and solved numerically by using Finite Element (FE) solver (ANSYS). Proposed method will pave the way on solving the tuning process totally within single FE solver with high efficiency. Proposed method satisfied mitigation in the overall free response with about 52% and 74% of the manipulator settling time when Fuzzy-P and Fuzzy-PI controllers were activated respectively. This contribution can be utilized for many other applications related to fuzzy topics.

Study on the control of variable resistance for isokinetic muscle training system.

Isokinetic muscle strength training is presently the most advanced method of muscle strength training. However, the existing control schemes of the training equipment are usually limited to the structure of the brake. In order to solve this problem, this paper presents a solution to an isokinetic system based on the force control of a DC servomotor. A new fuzzy impedance nonlinear controller is designed by analyzing the relevant requirements of isokinetic motion. A series of force tracking comparison experiments between a fuzzy PI controller and a classical PI controller are studied. In addition, some strength training experiments employing different driving forces and target speeds are also conducted. The results demonstrate the effectiveness of this fuzzy impedance force tracking control strategy. Using the aforementioned methods, a comprehensive motion algorithm was designed.