Input-output Linearization Control Research Articles

Comparison and implementation of different control strategies for improving production of rHSA using Pichia pastoris

Recombinant protein production by various host organisms is strictly regulated, which is determined mainly by host cell genetics and maintenance of process variables within desirable limits in a reactor. Since the process dynamics typically exhibit nonlinear interactions amongst the critical process variables, the commonly employed controllers are suboptimal for control of most bioprocesses. In this article, we present the implementation of an augmented controller for improving the production of recombinant human serum albumin (rHSA) using Pichia pastoris. The augmented controller consists of a decoupled adaptive control (DAC) and a decoupled input-output linearizing control (DIOLC) in a combined architecture that permits simultaneous control of substrate concentration and dissolved oxygen concentration, sampled at different rates during fed-batch fermentation. The performance of DAC-DIOLC controller was compared to the performance of DAC and DIOLC implemented individually on the process. Our results show that the augmented controller better regulates the substrate and dissolved oxygen (DO), along the desired control trajectory compared to the individual DAC and DIOLC controllers. The performance of the augmented DAC-DIOLC controller showed deviations of only 0.021 g/L from substrate set point compared to 0.09 g/L in PID and 0.031 g/L in DIOLC, and a 1.12% deviation from DO set point compared to 11.86% in PID and 2.58% in DAC. Overall, stricter control achieved using the augmented controller resulted in a 1.5 fold increase in rHSA production.

Adaptive Type-2 Fuzzy Logic Control Applied to the Inverted Pendulum on a Cart Problem

This paper introduces the design of an adaptive interval type-2 fuzzy logic controller and its implementation on a pendulum-cart system. It includes the theoretical foundations of: type-2 fuzzy logic system, input-output linearization control, fuzzy systems for functions approximation and adaptive systems. Type-2 fuzzy controllers provide an approach for using wide variety of opinions in control design. The above allows minimizing the effect of uncertainties in the rule base of fuzzy logic systems. These types of controllers provide greater flexibility in the application of human knowledge during the design of control systems in contrast to traditional controllers employing type-1 fuzzy logic. We propose to compare an adaptive interval type-2 fuzzy logic controller with its corresponding adaptive type-1 fuzzy logic controller. These controllers are tested in real-time on an inverted pendulum on a cart experimental prototype under the presence of parametric uncertainties in the mass of the pendulum. Five performance indexes are computed to compare both controllers, showing that type-2 fuzzy systems can help to improve the response of type-1 fuzzy systems. Copyright © 2018 Praise Worthy Prize - All rights reserved.

High Gain Observer for Sensorless Input-Output Linearizing Control for Induction Motor with Broken Rotor Bar Fault

High Gain Observer for Sensorless Input-Output Linearizing Control for Induction Motor with Broken Rotor Bar Fault

Active Disturbance Rejection Control of Linear Induction Motor

This paper proposes the theoretical framework and the experimental application of the active disturbance rejection control to linear induction motors. Such a nonlinear control (ADRC) technique can be viewed as a particular kind of input-output linearization control, where the nonlinear transformation of the state is not computed by means of the model, but it is estimated online. Such an approach permits to cope with unmodelling dynamics, as well as uncertainty in the knowledge of the model parameters and exogenous disturbances. The effectiveness of the proposed ADRC control law has been verified both by numerical simulations and experimentally on a suitably developed test setup. Moreover, the results have been compared with those achievable with the model-based feedback linearization control.

Adaptive approximate input–output linearizing control with applications to ball and beam mechanism

This paper presents the design and implementation of adaptive control with approximate input–output linearization for underactuated open-loop unstable non-linear mechanical systems. Control of a ball and beam (BB) mechanism is selected as a benchmark problem for testing the designed control. The method of input–output linearization is reviewed and an adaptive input–output linearizing control design procedure is given. An approximate BB model is developed using Euler–Lagrange equations, and input–output linearization-based adaptive tracking control is designed for the system. The model is parameterized with respect to ball mass for adaptive tracking, and the proposed control structure is tested via computer simulations and experiments. The results present the tracking performance of designed control for various ball masses, and reveal the proposed method’s capability to cover ball mass variations over non-adaptive control. The proposed control exhibits improved error performance in the presence of parametric variations in the plant. Results of the BB control case reveal successful control of underactuated non-linear mechanisms when a system parameter is unknown or time varying.

Enhanced-Performance Control of an Electromagnetic Solenoid System Using a Digital Controller

Solenoids can be used as linear or incremental motion actuators, most often by coupling the solenoid armature to a linear spring. In this configuration, its limited open-loop stable range (less than one-third of the full range) affects performance and limits applications. The input–output linearization control method is an effective technique to extend the stable range. But in practice, however, the time-delay effect from both measurement and actuation can make the system less damped and therefore more sensitive to disturbances. This effect was analyzed and a digital proportional and integrator controller plus extended state observer (ESO) is proposed to enhance the performance of the electromagnetic actuator. Simulation and experimental tests show that this combined proportional and integral and ESO technique can extend the stable range of motion to 77.6% of full stroke with less sensitivity to external disturbances.

Input–Output Linearization-Based Controller Design for Stand-Alone Solid Oxide Fuel Cell Power Plant

Application of input–output linearization control for improving the dynamic response of a stand-alone solid oxide fuel cell (SOFC) system is presented in this work. The proposed controllers are incorporated in the study system to eliminate the sluggishness in the hydrogen and oxygen partial pressure responses due to variations in the SOFC reference current. Temperature dynamics of SOFC is taken into consideration to replicate the impact of temperature variation on the system dynamics. Eigenvalue study of the linearized zero dynamics is conducted to determine the stability of the unobservable part of the system, and the remaining dynamics is considered for designing the input–output linearization-based controllers. Pole placement technique is adopted to obtain the controller gains which give the desired dynamic response. The performance of the proposed technique is compared with that of the optimized proportional–integral (PI) controller. The proposed controller efficiency is also tested under varying operating conditions and measurement noise. Simulation results show the efficacy and supremacy of the proposed method in improving the dynamic response of the study system.

Implementation of sensorless IPMSM drive using the stator current space vector orientation reference frame

Purpose In this paper an adaptive nonlinear control scheme has been proposed for direct torque and flux control of interior permanent magnet synchronous motor (IPMSM) without using mechanical sensor. Design/methodology/approach In this control method the stator resistance is online estimated by adaptive input-output state feedback linearization (AIOFL) controller. Based on proposed control scheme, the strategies of the maximum torque per ampere (MTPA) and maximum power factor (MPF) have been tested using a so-called stator flux search method. Findings The motor equations are transferred from the stationary reference frame to the (SX-SY) two-axis frame of the current by the stator current angle. In this frame, the Y component of the motor current is set to zero and the implementation of the nonlinear controller is independent of the two-axis inductances, the rotor magnetic flux, and position. Practical implications The effectiveness and capability of the proposed control method has been verified by simulation and experimental results. The proposed control scheme can be used for the sensorless control of IPMSM drive in industrial applications such as electric vehicle, traction system, and air conditioner. Originality/value The proposed controller is developed in a special axis (X-Y) rotating reference frame with the X-axis in coincide with the machine current space vector so that there is no need to use and know the machine inductances and rotor position.

Trajectory Tracking Control for a Differential Drive Wheeled Mobile Robot Considering the Dynamics Related to the Actuators and Power Stage

In this work a three-level controller that carries out the trajectory tracking task for a differential drive wheeled mobile robot (WMR) is presented. Such a controller considers, for the first time in literature, the dynamics associated with the three subsystems that compose a WMR, i.e., mechanical structure, actuators, and power stage. The high level corresponds to an input-output linearization control for the mechanical structure; the medium level is based on two sensorless controls designed via differential flatness for the actuators; and the low level is related to two cascade controls based on sliding modes and PI control for the power stage. The performance and robustness of the controller is verified and shown via realistic simulations when parametric uncertainties associated with the subsystems that compose the WMR are considered.

Two adaptive control strategies for trajectory tracking of the inertia wheel pendulum: neural networks vis à vis model regressor

AbstractThe problem addressed in this paper is to achieve robust motion control of the inertia wheel pendulum (IWP). Specifically, trajectory tracking control of the pendulum of the IWP under the assumption of uncertain model is discussed. Two new robust algorithms are introduced whose design departs from a model-based input-output linearization controller. Then, the control problem is firstly solved by means of an adaptive neural network-based controller and secondly by an adaptive regressor-based controller. For both controllers, rigorous analysis of the respective closed-loop system is given, where Barbalat’s lemma is used to conclude asymptotic convergence of the pendulum tracking error. In addition, the wheel velocity and adaptive extension signals are shown to be bounded. An extensive real-time experimental study validates the introduced theory, where the performance of a classical linear PID controller and the two new adaptive schemes are compared.

Upper Limb Electrical Stimulation Using Input-Output Linearization and Iterative Learning Control

A control scheme is developed for multijoint upper limb reference tracking using functional electrical stimulation (FES). In accordance with the needs of stroke rehabilitation, FES is applied to a reduced set of muscles in the arm and shoulder, with support against gravity provided by a passive exoskeletal mechanism. The approach fuses input–output linearization with iterative learning control, one of the few techniques to have been applied in clinical treatment trials with patients. This powerful hybrid control structure hence extends performance and scope of clinically proven technology for widespread application in rehabilitation robotic and FES domains. In addition to simplifying tracking and convergence properties of the stimulated joints, the framework enables conditions for the stability of unstimulated joints to be derived for the first time. Experimental results confirm tracking performance of the stimulated joints, together with unstimulated joint stability.

A Unified Approach to Input-output Linearization and Concurrent Control of Underactuated Open-chain Multi-body Systems with Holonomic and Nonholonomic Constraints

This paper presents a unified geometric framework to input-output linearization of open-chain multi-body systems with symmetry in their reduced phase space. This leads us to an output tracking controller for a class of underactuated open-chain multi-body systems with holonomic and nonholonomic constraints. We consider the systems with multi-degree-of-freedom joints and possibly with non-zero constant total momentum (in the holonomic case). The examples of these systems are free-base space manipulators and mobile manipulators. We first formalize the control problem, and rigorously state an output tracking problem for such systems. Then, we introduce a geometrical definition of the end-effector pose and velocity error. The main contribution of this paper is reported in Section 5, where we solve for the input-output linearization of the highly nonlinear problem of coupled manipulator and base dynamics subject to holonomic and nonholonomic constraints. This enables us to design a coordinate-independent controller, similar to a proportional-derivative with feed-forward, for concurrently controlling a free-base, multi-body system. Finally, by defining a Lyapunov function, we prove in Theorem 3 that the closed-loop system is exponentially stable. A detailed case study concludes this paper.

Feedback Linearization Control of the Inertia Wheel Pendulum

Abstract In this paper, two feedback linearizing control laws for the stabilization of the Inertia Wheel Pendulum are derived: a full-state linearizing controller, generalizing the existing results in literature, with friction ignored in the description and an inputoutput linearizing control law, based on a physically motivated definition of the system output. Experiments are carried out on a laboratory test bed with significant friction in order to test and verify the suggested performance and the results are presented and discussed. The main point to be made as a consequence of the experimental evaluation is the fact that actually the asymptotic stabilization was not achieved, but rather a limit cycling behavior was observed for the full-state linearizing controller. The input-output linearizing controller was able to drive the pendulum to the origin, with the wheel speed settling at a finite value

Sensorless Exact Input-Output Linearization Control of the Induction Machine, Based on Parallel Stator Resistance and Speed MRAS Observer, with a Flux Sliding Mode Observer

Abstract: This paper presents an exact input-output linearization control scheme for rotor speed and rotor flux control of induction motor drive. In this scheme the motor model, is described in the fixed stator frame, and it is linearized, using exact inputoutput linearization technique, allowing a decoupled control of rotor flux and torque. To avoid the use of mechanical sensor, the rotor speed estimation is made by an observer using a specific MRAS (Model reference adaptive system) technique; this observer is designed to perform simultaneous estimation of stator resistance and rotor speed. In order to estimate rotor flux, a sliding mode observer is proposed in this paper. Simulation results are realized and presented to validate and to prove the effectiveness of the proposed Sensorless control.

Discrete-time modeling and input-output linearization of current-fed induction motors for torque and stator flux decoupled control

Abstract In this paper an exact discrete-time model of the induction motor in a current-fed mode, including stator flux components is derived and validated. The equations of the motor are written in a frame aligned with the rotor electrical position, which results in a linear, time-invariant system. Based on the derived exact discrete-time representation of the motor dynamics, an input-output linearizing control law is designed for decoupled torque and stator flux control. The applied design technique led to a non-trivial, still useful, definition of the electromagnetic output of the motor. Simulation results are presented showing that the aimed performance is obtained, that is, no coupling exists between the outputs, and the initial design problem of controlling a nonlinear interacting TITO system is reduced to a problem of controlling two linear and decoupled SISO systems with simple dynamics.

Voltage-Oriented Input-Output Linearization Controller as Maximum Power Point Tracking Technique for Photovoltaic Systems

This paper presents a robust input-output linearization controller as maximum power point tracking (MPPT) technique in a photovoltaic (PV) buck dc-dc converter with applications to dc microgrids, solar vehicles, or stand-alone systems. Due to the control structure proposed in this paper, the MPPT control system is able to track very fast irradiance changes. Meanwhile, the internal stability of the overall closed-loop system is guaranteed for different load scenarios. A sector condition is only required for the load current, which is satisfied for most of the current PV applications. In turn, this condition implies the robustness against oscillations in the dc bus voltage. Finally, the MPPT control system is validated through experimental results, where the closed-loop performance is evaluated under abrupt irradiance and set-point changes, parametric uncertainty, and dc bus load variations.

Mathematical Modeling and Analysis of Different Vector Controlled CSI Fed 3-Phase Induction Motor Drive

The main objective of this paper is to build a simple mathematical competent model that describes the circuits and interconnections of a 3-phase squirrel cage induction motor used for industrial applications. This paper presents the detailed analysis of theoretical concepts used in mathematical modeling, simulation’ and hardware implementation. The objective of this work is to compare the dynamic performances of the vector control methods for CSI fed IM drives. Based on the results, dynamic performances of the proposed drives are individually analysed using the sensitivity tests. The tests that are chosen for the comparison are step changes in the reference speed and torque of the motor drive. Here the IM is mathematically modeled in different reference frames for input output linearization (IOL) control, field oriented control (FOC), and direct torque control method (DTC) which are designed using hardware equivalent mathematical equations. The most important contributions in this paper are mathematical simulation structure of IM model in rotor flux frame using current and speed that were developed and implemented in MATLAB-Simulink. The operation and performance of the different vector control methods are verified by simulation using MATLAB/SIMULINK and experimental results.

Input-output linearizing control of a thermal cracking furnace described by a coupled PDE-ODE system

This research presents a control scheme for a gas-fired ethylene dichloride (EDC) cracking furnace to handle a cracked gas temperature at the coil outlet. Input-output (I/O) linearizing control scheme is applied to the furnace model of which interaction between a lumped temperature of gas-fire radiating wall and spatially distributed dynamics of cracking coil is considered. In the proposed method, the feedback I/O linearizing controller for coupled PDE-ODE system is applied to force the cracked gas temperature to follow a desired trajectory by manipulation of a fuel gas flow rate. Simulation results showed that the proposed controller successfully forced the controlled output to a desired setpoint without off-set.

On-line implementation of decoupled input-output linearizing controller in Baker's yeast fermentation

Baker's yeast fermentation is influenced by the relative concentration of glucose and dissolved oxygen (DO) in the reactor. The process is sensitive to the oxidative capacity of the cells and exhibits a range of metabolic regimes depending on available glucose and oxygen. The time profiles of cell mass, glucose, ethanol and DO concentrations possess strong nonlinear characteristics. A decoupled input-output linearizing controller (DIOLC), which exhibited satisfactory performance in simulation experiments, was implemented online for validation. Our results showed that the DIOLC was capable of negating the interaction between glucose and dissolved oxygen, and executed satisfactory control action in experiments carried out in a 5 liter bioreactor. The performance of DIOLC was better compared to that of a PID controller implemented under identical test conditions.

Disturbance-Observer-Based Position Tracking Controller in the Presence of Biased Sinusoidal Disturbance for Electrohydraulic Actuators

A nonlinear position tracking controller with a disturbance observer (DOB) is proposed to track the desired position in the presence of the disturbance for electrohydraulic actuators (EHAs). The DOB is designed in the form of a second-order high-pass filter in order to estimate the disturbance. The nonlinear controller is designed for position tracking as a near input-output linearizing inner-loop load pressure controller and a backstepping outer-loop position controller. Variable structure control is implemented in order to compensate for the error in disturbance estimation. The desired load pressure is designed to generate the pressure using the differential flatness property of the EHA's mechanical subsystem. The disturbance within the bandwidth of the DOB can be cancelled by the proposed method. The performance of the proposed method is validated via simulations and experiments.