Nonlinear Internal Model Control Research Articles

INVERSE NEURO-FUZZY MODEL BASED CONTROLLER DESIGN FOR A PH NEUTRALIZATION PROCESS

Since pH neutralization processes have extremely nonlinear characteristics, controlling it might be difficult. Therefore, a special controller design is needed to handle the high nonlinearities of the process. In this study, an inverse neuro-fuzzy model-based controller (NFMBC) design is presented for control of a pH neutralization process (NP). Input-output (IO) data set of the process is collected by applying a proper excitation signal. Then, forward and inverse neuro-fuzzy models of the process are constructed by using this data set after a training process. In terms of design simplicity, a two-input-one-output model structure is chosen for both neuro-fuzzy models. These forward and inverse neuro-fuzzy models are used in a nonlinear internal model control (NIMC) structure in order to provide robustness against disturbances and model mismatches. To examine the proposed controller's performance, simulation studies are carried out under setpoint variation and disturbance conditions. Additionally, the performance of the inverse NFMBC is compared to that of a fuzzy proportional integral derivative (FPID) controller with a 7x7 rule base. The results demonstrate that the designed controller provides more effective control performance for setpoint variations and also exhibits higher robustness against disturbances in the acid flow rate than the FPID controller.

Tuning Parameter-free Model Predictive Control with Nonlinear Internal Model Control Structure for Vehicle Lateral Control

Tuning Parameter-free Model Predictive Control with Nonlinear Internal Model Control Structure for Vehicle Lateral Control

Non-linear forced vibration control for a vertical wing-plate with sustainable perturbation by using internal model control mechanism

This article studies the non-linear vibration control problem for a vertical wing-plate with sustainable perturbation by using piezoelectric actuator. For the vertical wing-plate system with hysteresis non-linearity, the operator-based robust right coprime factorisation approach is considered to ensure the stability of the non-linear system. After, for compensating the sustainable perturbation and hysteresis non-linearity to improve the non-linear vibration control performance, the non-linear internal model control scheme that includes the designed internal closed-loop model and the compensator is considered. Finally, simulation and experimental examples are given to show the effectiveness of the proposed control system.

Nonlinear Internal Model Control of Wind Farm Power Optimization under Wake Effect

This paper is dealing with the efficiency of wind power under the wake effect. In our previous work, the efficiency is shown to be first depending on the wind turbine's applied control strategy, besides the influence of the environment topology. It is also widely demonstrated that the wind turbine performance decreases under sudden wind profile variations. Therefore, the first main control objective was to perform an optimal wind power capture, particularly below-rated wind speed, while avoiding substantial loads on the drive train shafts. Herein, the focus is on the wake effect in wind farms. Indeed, a wind farm is often subject to wake effect in addition to wind disturbance, in consequence, the wind turbines may fail in respecting the optimal power production as expected. The second main objective is then to maximize the power extraction under the wake effect. So, as an extension of our previous work, this present one aims to apply nonlinear internal model control to each turbine within a small wind farm and to point out that, it is indeed essential to consider the wake phenomenon to determine the real performance of a wind farm power production. Validation results using a wind farm simulator are provided to illustrate the theoretical developments applied on a single turbine in comparison with our previous work performed without wake effect, as well as using a small windfarm comprising 5 machines.

Robust output regulation for unknown nonlinear strict‐feedback systems with input delay

AbstractThis article investigates the robust output regulation problem for unknown nonlinear strict‐feedback systems with input delay. Nonlinear fuzzy internal model and adaptive fuzzy backstepping control are integrated to obtain a feedforward‐feedback composite controller. As a distinctive feature, Pade approximation technique is introduced to deal with the input delay of nonlinear output regulation problem for the first time. The process of control strategy can be divided into two steps. In the first step, a novel nonlinear fuzzy internal model is designed to get the feedforward compensator. In the second step, an adaptive fuzzy backstepping control scheme is proposed to get the feedback controller, which can guarantee semiglobally uniformly ultimately bounded of the closed‐loop system. Simulation results of an interconnected power system show the validity of the theoretical results.

Design of Nonlinear Internal Model Controller using Local Linear Models, and its Application

In chemical plants and other process industries, desired conditions are achieved by adjusting controllers. However, it is difficult to obtain the desired control response because most of the controllers use fixed Proportional-Integral-Differential (PID) control. On the other hand, the internal model control method, in which the control target is described by a detailed mathematical expression, has been proposed. The internal model control is simple to control system structure and is characterized by high robust stability against uncertainties of the control target. However, there are few examples of applying internal model control to nonlinear systems. In this paper, we propose a new method for designing an internal model control system that constructs multiple local linear models for a nonlinear system and adjusts the system parameters corresponding to the models. The effectiveness of the proposed method is verified through experiments.

A novel adaptive generic model control strategy for internal thermally coupled air separation columns with multivariable recursive estimation

A gasification process is key in clean electricity production and decarbonization in an integrated gasification combined cycle (IGCC) plant. The quality of the gasification process depends on the stability of the product-concentration streamed from the internal thermally coupled air separation column (ITCASC) unit. There is a need for a stable product-concentration supply to sustain clean electricity production. A proportional-integral-derivative control (PID) control and a nonlinear internal model control (NIMC) scheme are first explored to control the IGCC-ITCASC. Moreover, a robust generic model control (RGMC) is employed to deal with the IGCC-ITCASC inherent nonlinearity and strong interaction that make it very difficult to control. To obtain a satisfactory control performance, an adaptive generic model control (AGMC) with a multivariable recursive estimation is developed. The compared control systems show that AGMC can better handle both the system nonlinearity and strong interaction while improving the control performance.

Global robust output regulation of a class of MIMO nonlinear systems by nonlinear internal model control

AbstractRecently, the global robust output regulation problem for a class of uncertain multi‐input multi‐output (MIMO) nonlinear systems which may not have well‐defined relative degree and are subject to a nonlinear exosystem has been studied based on a constructive nonlinear internal model. However, the proposed nonlinear internal model‐based control law is applicable to the case where the exogenous signals are reference input and/or measurable disturbance rather than unmeasurable disturbance. For this reason, this paper further studies the same control problem based on a general nonlinear internal model independent of the exogenous signal. It is shown that this control problem can be converted into a global robust stabilization problem of a more complicated MIMO nonlinear system with various uncertainties and well solved by a recursive state feedback controller design. Thus our approach applies to a broader class of output regulation problem of MIMO nonlinear systems.

Nonlinear Internal Model Controller based on Local Linear Models, and its Application

Nonlinear Internal Model Controller based on Local Linear Models, and its Application

Path Following Control of Quadrotor UAV With Continuous Fractional-Order Super Twisting Sliding Mode

Quadrotors are highly maneuverable drones, which are susceptible to the parameter uncertainties such as the mass, drag coefficients, and moment of inertia. Whose nonlinearities, aerodynamic disturbances, and higher coupling between the rotational and the translational dynamics stand for a problem that demands a robust controller. In the present paper, a fractional order (FO) improved super twisting proportional-integral-derivative sliding-mode control (STPIDSMC) is proposed for the quadrotor system. To improve the speed tracking performance, a FOPIDSM surface is designed. Moreover, the proposed FO control approach ensures fast convergence, high precision, good robustness against stochastic perturbations and uncertainties. Finally, the performance of the FOSTPIDSMC is investigated under different scenarios. The simulation results clearly show the high control performance, efficiency and high disturbance rejection capacity of the controller strategy proposed in this work in comparison with the nonlinear internal model control (NLIMC) and FO backstepping sliding mode control (FOBSMC) strategies.

Robust Trajectory Tracking in a Reactive Batch Distillation Process using Multirate Nonlinear Internal Model Control

Operating a reactive batch distillation (RBD) process in an optimal manner is of paramount importance for improving product quality and profitability in the face of changing market conditions. However, implementation of an open loop optimal control policy may lead to significant reduction in yield and amount of desired product produced when unmeasured disturbances occur during operation. In this work, an observer error feedback-based multirate nonlinear internal model control (NIMC) scheme is developed for optimal trajectory tracking in the face of unmeasured disturbances. In particular, mismatch in the initial conditions and process parameter variations that can occur during RBD operation are considered. To reduce the time required for online computations, a recently proposed reduced order RBD model [Reddy et al. Compt. Chem. Eng., 2017, 106, 40−56] is used for the controller synthesis. Because the thermodynamic model associated with the RBD process has discontinuities, a multirate version of unscented Kalman filter (UKF) has been developed on the basis of the reduced order model for solving the state estimation problem associated with the proposed NIMC formulation. The efficacy of the proposed approach has been demonstrated by simulating an optimal trajectory tracking problem in the RBD process involving production of butyl acetate. The proposed multirate NIMC formulation is found to be computationally efficient and work reasonably well when tested on the RBD process for solving the set point tracking problem in the presence of unmeasured disturbances. In particular, it is advantageous to operate the RBD process using the proposed UKF-NIMC scheme when the system is subjected to unmeasured disturbances.

Recursive orthogonal least squares based adaptive control of a polymerisation reactor

ABSTRACTA Nonlinear Internal Model Control (NIMC) scheme, based on a recursively updated Radial Basis Function Network (RBFN), is applied to control the nonlinear Polymerisation process. Recursive Orthogonal Least Squares (ROLS) algorithm recursively updates the weighting matrix of RBFN in real time, such that modelling errors are minimised. In addition to the ROLS based adaptive IMC, a non-adaptive IMC, based on the fixed Orthogonal Least Squares (OLS) algorithm and a normal PID controller are also applied to control the polymerisation process. The simulated results show the effectiveness of the ROLS based controller in terms of response time to step changes and disturbance rejection capabilities over the classical PID controller and the fixed OLS based IMC. Also, the proposed algorithm fits well in the IMC framework.

Speed Tracking Control of Permanent Magnet Synchronous Motor by a Novel Two-step Internal Model Control Approach

The control problem of permanent magnet (PM) synchronous motor has attracted extensive attentions in both control society and industrial applications. Much recently, a local speed tracking and nonlinear disturbance rejection problem of PM synchronous motor was investigated by nonlinear internal model design. In this paper, we propose a novel two-step controller design strategy to achieve speed tracking and nonlinear disturbance rejection of PM synchronous motor with wide speed range, which combines the advantages of classical double-loop control and nonlinear internal model control. It is worth mentioning that the proposed two-step controller design strategy can not only guarantee exact speed tracking with wide speed range, but also reject small nonlinear external disturbances in the load torque, generated by a so-called nonlinear exosystem. Simulation results demonstrate the effectiveness of our design.

An adaptive nonlinear internal-model control for the speed control of homopolar salient-pole BLDC motor

ABSTRACTIn this paper, a novel speed control method for Homopolar Brushless DC (HBLDC) motor based on the adaptive nonlinear internal-model control (ANIMC) is presented. Rotor position information is obtained online by the Hall–Effect sensors placed on the motor’s shaft, and is used to calculate the accurate model and accurate inverse model of the HBLDC motor. The online inverse model of the motor is used in the controller structure. To suppress the reference error, the negative feedback of difference between the motor speed and its model output is applied in the proposed controller. An appropriate signal is the output of the controller, which drives the power switches to converge the motor speed to the constant desired speed. Simulations and experiments are carried out on a three-phase HBLDC motor. The proposed drive system operates well in the speed response and has good robustness with respect to the disturbances. To validate the theoretical analysis, several experimental results are discussed in this paper.

Nonlinear internal model control applied to VTOL multi-rotors UAV

This paper describes a novel Nonlinear Internal Model Control (NLIMC) approach. We show that if we change, in a new manner, the control based on flatness property in order to get a closed loop structure, we can raise the performance and the robustness level with regards to structured or unstructured disturbances. The control performance is evaluated through a Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicle (UAV) where numerical simulations are performed demonstrating the effectiveness of this novel controller form. The obtained results are confirmed by series of experimental tests showing also the robustness level of this technique in presence of wind.

Comparative Results on 3D Navigation of Quadrotor using two Nonlinear Model based Controllers

Recently the quadrotors are being increasingly employed in both military and civilian areas where a broad range of nonlinear flight control techniques are successfully implemented. With this advancement, it has become necessary to investigate the efficiency of these flight controllers by studying theirs features and compare their performance. In this paper, the control of Unmanned Aerial Vehicle (UAV) quadrotor, using two different approaches, is presented. The first controller is Nonlinear PID (NLPID) whilst the second one is Nonlinear Internal Model Control (NLIMC) that are used for the stabilization as well as for the 3D trajectory tracking. The numerical simulations have shown satisfactory results using nominal system model or disturbed model for both of them. The obtained results are analyzed with respect to several criteria for the sake of comparison.

Modelling and control of nonlinear resonating processes: part II—model based control using orthogonal basis function based Wiener models

This paper is an extension of the work presented by Reddy and Saha (Int J Dyn Control 2016) i.e. Part I of this series of papers. Reddy and Saha (2016) developed Wiener type nonlinear models using orthogonal basis filters which were proved to be ideal candidates for modeling nonlinear resonating systems such as continuous stirred tank reactor(s). Those nonlinear models have further been employed in the present work for developing nonlinear model based control strategies and their closed-loop control performance have been evaluated through simulation case studies involving same continuous stirred tank reactor(s). Two types of model based control strategies are adopted viz. nonlinear model predictive control and nonlinear internal model control. In case of nonlinear internal model controller, the problem of model inversion has been addressed, first of its kind in approach, through tactful modification of Wiener model coupled with optimization technique. Deletion of positive zeros from orthogonal basis filters while modifying Wiener model is the uniqueness of this paper and it ensures stability of the controller.

Hierarchical Autopilot Design based on Immersion & Invariance and Nonlinear Internal Model Tracking Controllers for Autonomous system

In this paper, a novel control design is developed for the Octo-rotor using combined controllers based on Immersion and Invariance (I&I) approach for translational trajectory tracking and Nonlinear Internal Model Control (NLIMC) for attitude one. Numerical simulations are performed showing the effectiveness of the proposed control technique in particular under applied disturbances.

An inverse controller design method for interval type-2 fuzzy models

Recently, it has been demonstrated that interval type-2 (IT2) fuzzy sets and systems are powerful tools in representing and controlling nonlinear systems. Thus, an inverse IT2 fuzzy model (FM) based controller might be an efficient way to control nonlinear processes. In this context, IT2-FM inversion methods have been proposed and successfully implemented in control system design. In this study, an analytical methodology has been developed to form the exact inverse of a certain class of IT2-FM. The proposed inversion methodology consists of two main steps, decomposing the IT2-FM into submodels and then finding the inverse of each possible activated interval type-2 fuzzy submodel. In order to form the inverse IT2-FM controller, the analytical formulation of the interval type-2 fuzzy submodel output is tried to be reached for an inverse solution since the IT2-FM output cannot be presented in a closed form due to the Karnik---Mendel type reduction method. Thus, to form the exact inverse type-2 fuzzy model, an iterative algorithm based on an analytical methodology is proposed to overcome this problem. The proposed inverse controller is embedded into a nonlinear internal model control scheme to provide an effective closed loop control performance in the presence of modelling mismatches and disturbances. Comparative simulation studies have been given where the beneficial sides of the proposed inverse controller are shown clearly in comparison to its type-1 and conventional counterpart.

Nonlinear internal model controller design for wastegate control of a turbocharged gasoline engine

Internal Model Control (IMC) has a great appeal for automotive powertrain control in reducing the control design and calibration effort. Motivated by its success in several automotive applications, this work investigates the design of nonlinear IMC for wastegate control of a turbocharged gasoline engine. The IMC design for linear time-invariant (LTI) systems is extended to nonlinear systems. To leverage the available tools for LTI IMC design, the quasi-linear parameter-varying (quasi-LPV) models are explored. IMC design through transfer function inverse of the quasi-LPV model is ruled out due to parameter variability. A new approach for nonlinear inversion, referred to as the structured quasi-LPV model inverse, is developed and validated. A fourth-order nonlinear model which sufficiently describes the dynamic behavior of the turbocharged engine is used as the design model in the IMC structure. The controller based on structured quasi-LPV model inverse is designed to achieve boost-pressure tracking. Finally, simulations on a validated high-fidelity model are carried out to show the feasibility of the proposed IMC. Its closed-loop performances are compared with a well-tuned PI controller with extensive feedforward and anti-windup built in. Robustness of the nonlinear IMC design is analyzed using simulations.