Multi-input Multi-output Control System Research Articles

Inverse system based decoupling design and control strategy for crude oil heat exchanger networks

This work focuses on a decoupling control approach for the crude oil heat exchanger network to improve the energy efficiency and achieve continuous energy saving. The desired control variables are identified by the signed directed graph (SDG) model based on the complex network theory. Then the principal component analysis (PCA) method and the evaluation index are employed to construct the initial controller as well as the control variables pairing. The presented system is a multi-input multi-output (MIMO) control system where the coupling problems are considered, and a decoupling control strategy based on the inverse system theory of neural network is proposed. The existence of the inverse system is proved by the reversibility derivation, and the original system is decoupled into two second-order subsystems. Consequently, the proposed decoupling control system is tested on the example of heat exchanger network (HEN) belonging to Crude Distillation Unit. The fluctuating value of temperature is reduced averagely by 57.1% compared with the non-decoupling control strategy and the mean absolute percentage error is within 0.02 under different operating conditions. The results show that the proposed decoupling control method has excellent decoupling performance and can improve the control performance of the system.

Optimal Design of I-PD and PI-D Industrial Controllers Based on Artificial Intelligence Algorithm

This research aims to apply Artificial Intelligence (AI) methods, specifically Artificial Immune Systems (AIS), to design an optimal control strategy for a multivariable control plant. Two specific industrial control approaches are investigated: I-PD (Integral-Proportional Derivative) and PI-D (Proportional-Integral Derivative) control. The motivation for using these variations of PID controllers is that they are functionally implemented in modern industrial controllers, where they provide precise process control. The research results in a novel solution to the control synthesis problem for the industrial system. In particular, the research deals with the synthesis of I-P control for a two-loop system in the technological process of a distillation column. This synthesis is carried out using the AIS algorithm, which is the first application of this technique in this specific context. Methodological approaches are proposed to improve the performance of industrial multivariable control systems by effectively using optimization algorithms and establishing modified quality criteria. The numerical performance index ISE justifies the effectiveness of the AIS-based controllers in comparison with conventional PID controllers (ISE1 = 1.865, ISE2 = 1.56). The problem of synthesis of the multi-input multi-output (MIMO) control system is solved, considering the interconnections due to the decoupling procedure.

Kinematics, dynamics and control of stiffness-tunable soft robots

Modeling and control methods for stiffness-tunable soft robots (STSRs) have received less attention compared to standard soft robots. A major challenge in controlling STSRs is their infinite degrees of freedom, similar to standard soft robots. In this paper, demonstrate a novel STSR by combing a soft-rigid hybrid spine-mimicking actuator with a stiffness-tunable module. Additionally, we introduce a new kinematic and dynamic modeling methodology for the proposed STSR. Based on the STSR characteristics, we model it as a series of PRP segments, each composed of two prismatic joints(P) and one revolute joint(R). This method is simpler, more generalizable, and more computationally efficient than existing approaches. We also design a multi-input multi-output (MIMO) controller that directly adjusts the pressure of the STSR’s three pneumatic chambers to precisely control its posture. Both the novel modeling methodology and MIMO control system are implemented and validated on the proposed STSR prototype.

Design of 3×3 Multi Input Multi Output (MIMO) Decoupling on Coupled Tank System with PID Controller

Multivariable processes are the general classification for process features in the chemical industry. The variables in a single process unit interact with one another through more than one input and output. Since parameters interact with one another, changing one parameter's variable requires changing another parameter's variable as well. Further research is needed to determine how to create controllers that can handle interactions in the process. A MIMO control system is exemplified by the coupled tank system. Coupled tanks are present, and they communicate with one another by horizontal pipes. An interacting system can be represented using a coupled tank setup. Decoupling can be added to reduce the interactions that take place between variables. According to the results of the simulation, adding decoupling reduces the IAE value compared to not adding it. When the setpoint for tank level 1 (H1) was changed, the system's IAE value was 17.35 without the addition of decoupling, whereas it was 11.71 with it.

Control and Stability Analysis of Current-Controlled Grid-Connected Inverters in Asymmetrical Grids

In symmetrical grids, single-input single-output (SISO) analysis/design tools are applicable for the analysis and design of grid-tied inverter systems as their average <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">αβ</i> - or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -frame models are to a high extent decoupled (in the high-frequency range). In this way, designing the control system could be done in a straightforward manner. However, this is not the case under asymmetrical grids. In this condition, the interaction between different phases makes the average model of the grid-tied inverter a multi-input multioutput (MIMO) system, and therefore, complicated to analyze and design. To cope with this challenge, this article deals with deriving the MIMO control system considering the impact of the asymmetrical grid. Then, the MIMO system turns into two decoupled SISO systems. Thus, a simple yet accurate model is developed which intuitively demonstrates the effect of the grid asymmetry on creating coupling between current control loops. In this way, the stability analysis could be carried out irrespective of the MIMO system difficulties. The experimental results validate the accuracy of the proposed approach in asymmetrical grid conditions.

Modeling and Flight Control of Small UAV with Active Morphing Wings

In recent research works, morphing wings were studied as an interesting field for a small unmanned aerial vehicle (UAV). The previous studies either focused on selecting suitable material for the morphing wings or performing experimental tests on UAVs with morphing wings. Though, the dynamic modeling of active flexible morphing wings and their involved interactions with the aerodynamics of the UAV body are challenging subjects. Using such a model to control a small UAV to perform specific maneuvering is not investigated yet. The dynamic model of UAV with active morphing wings generates a multi-input multi-output (MIMO) system which rises the difficulty of the control system design. In this paper, the aeroelastic dynamic model of morphing wing activated by piezocomposite actuators is established using the finite element method and modal decomposition technique. Then, the dynamic model of the UAV is developed taking into consideration the coupling between the wing and piezocomposite actuators, as well as the dynamic properties of the morphing actuators with the aerodynamic wind disturbances. A model predictive control (MPC) is designed for the MIMO control system to perform specific flight maneuvering by tracking desired trajectories of UAV altitude and yaw angle. Additionally, the MPC achieves constrained behavior of pitch and roll angles to get satisfactory UAV motion. Also, the behaviors of the UAV control system using MPC are evaluated after adding Dryden wind turbulence to the UAV outputs. Finally, a UAV flight simulation is conducted which shows that the control system successfully rejects the applied disturbances and tracks the reference trajectories with acceptable behavior of pitch and roll angles.

Synthetic Lyapunov stabilization technique for designing actuation-constrained multi-input multi-output control systems

The main objective of this paper is to present a non-predictive method in the design of nonlinear multi-input multi-output (MIMO) control systems with the presence of constraints that are determinant in practical conditions, namely, the frequency bandwidth limitation of the actuation system and saturation boundaries in control commands. If these constraints are applied in the non-predictive control design problem, it is not possible to simultaneously satisfy Lyapunov stability and actuation constraints, analytically. Instead of model-predictive-based algorithms, which in most cases are computationally expensive, this paper proposes an algorithm based on synthetic Lyapunov stability. In this technique, by defining an intelligent filter applied to the system desired trajectories, defining intelligent proximity coefficients in decoupled inequalities resulting from Lyapunov stability, and determining the admissible boundaries of control commands, a space of regulatory parameters is generated. By appropriately adjusting these parameters based on statistical analysis conducted on the overall dynamics of the system, the Lyapunov stability is guaranteed, and the mentioned control constraints are not violated. In summary, the proposed control algorithm includes the formulation of discrete-time dynamics of sliding functions, the presentation of the procedure of defining and adjusting the control algorithm parameters with the proposed synthetic stability criterion, and the calculation of control inputs based on constraints imposed on the problem. Finally, the algorithm is applied to a cart moving in the X-Y plane, including two rigid cooperative arms that are carrying a load. The most important features of synthetic Lyapunov stability compared to the model predictive-based method are its small computational load and its acceptable performance in satisfying both the Lyapunov stability conditions and determinant control constraints in more realistic situations.

Optimal fractional-order PID control design for time-delayed multi-input multi-output seismic-excited structural system

The application of the fractional-order PID (FOPID) controller is recently becoming a topic of research interest for vibration control of structures. Some researchers have successfully implemented the FOPID controller in a single-input single-output (SISO) control structural system subjected to earthquake excitations. However, there is a lack of research that focuses on its application in multi-input multi-output (MIMO) control systems to implement it in seismic-excited structures. In this case, the cross-coupling of the process channels in the MIMO control structural system may result in a complex design process of controllers so that each loop is independently designed. From an operational point of view, the time delay and saturation limit of the actuators are other challenges that significantly affect the performance and robustness of the controller so that ignoring them in the design process may lead to unrealistic results. According to the challenges, the present study proposed an optimal fractional-order PID control design approach for structural control systems subjected to earthquake excitation. Gases Brownian motion optimization (GBMO) algorithm is utilized for optimal tuning of the controller parameters. Considering six real earthquakes and seven performance indices, the performance of the proposed controller, implemented on a ten-story building equipped with an active tendon system (ATS), is compared with those provided by the classical PID controller. Simulation results indicate that the proposed FOPID controller is more efficient than the PID in both terms of seismic performance and robustness against time-delay effects. The proposed FOPID controller can maintain suitable seismic performance in small time delays, while a significant performance loss is observed for the PID controller.

Managing the energy of the air conditioning systems using a modified multi-variable control technique

This research is a continuation of our previous work [19], in which, I’ve investigated many control techniques for the multi-input multi-output (MIMO) control systems for air conditioners. In the present work, I’ve suggested another control technique which exhibited better performance in the cases where permanent disturbances are present. I’ve applied the technique to a model room that simulates a computer room and is conditioned by a simple, less expensive, and energy-saver HVAC system. The two control inputs are; the opening angle of a fresh air gate and the steam flow rate from a humidifier. The two controlled outputs are the temperature and humidity. The control technique and the in-door conditions are simulated using a written program that works along with a commercial code. The sampling interval for each controlled variable is modified to allow more accuracy for measured data. When applying accidental and permanent disturbances in both controlled variables, the suggested technique exhibited accepted performance. The controlled variables that are affected with permanent disturbances achieved their set-point values after longer time intervals than those of the cases where only accidental disturbances are present. Two comparisons were made between the controlled and uncontrolled system by operating the system for a certain period, and fixing the fresh air opening at 25% and 50% of the full opening area. The consumed energy in the two cases was compared with that of the case when applying the control technique for the same period. An energy-saving of about 15.3% was recorded in the first case and about 37.6% for the second case. The present technique is a case-independent and may be applied to any MIMO control system with little modifications.

A general vibration control methodology for human‐induced vibrations

This paper proposes a general methodology for the design of vibration control of human-induced vibrations. This uses a feedback loop for the design of control parameters and accounts for the nature of human excitation and how humans feel the vibration. The methodology developed considers not only single-input single-output control systems but also multi-input multi-output control systems, especially useful to cancel vibrations coming from modes with closely spaced natural frequencies. The strategy finds simultaneously the optimal placements of a set of inertial mass dampers and the design parameters (control gain matrix for active vibration control, damping ratios and tuning frequencies of tuned mass dampers for passive vibration control). To make this strategy implementable and suitable to human-induced vibrations, elements such as input-output frequency weighting, output time weighting, band-pass filters, actuator dynamics, and nonlinearities are considered within the design. The proposed methodology is illustrated in an application example on a realistic open-layout floor by designing single-input single-output and multi-input multi-output active and passive strategies with one and two dampers. Simulation tests are carried out to evaluate the performance of the controllers in terms of their vibration reduction capacity using a performance index indicator.

The Behavior Analysis of Magnetoresistive Tunnel Junction Devices in State Space

The behavior of magnetoresistive tunnel junction (MTJ) devices in the electronic (digital) circuits is governed by several differential equations. The LLG equation determines the dynamic of the magnetic polarization vector which ultimately affects the (anti)parallel resistance of MTJs. This vector differential equation is decomposed into two scalar differential equations. In the proposed method, the differential equations are expressed in the state space and the corresponding well-developed theories are applied. In fact, the device is considered as a multi-input multi-output control system and the qualitative solutions are presented. The state diagram gives an insight into the device behavior. It can provide additional information about the device performance and can be considered as a complementary technique of other available analysis approaches. With this ability, the designer can engineer the MTJ devices for their optimum performance in the circuit. Using this theory, we also suggested a power and performance improving approach for the spin transfer torque MTJ-based logic circuits. To show the efficiencies offered by the proposed method, a STT-MRAM cell and an array are designed and it is shown that better specifications can be achieved in terms of switching time and power dissipation. The reliability issues are also investigated and we show that the proposed power/performance improvement approach can effectively consider the reliability concerns.

Robust control with compensation of adaptive model for dual-stage inertially stabilized platform

To achieve excellent tracking accuracy, a coarse-fine dual-stage control system is chosen for inertially stabilized platform. The coarse stage is a conventional inertially stabilized platform, and the fine stage is a secondary servo mechanism to control lens motion in the imaging optical path. Firstly, the dual-stage dynamics is mathematically modeled as a coupling multi-input multi-output (MIMO) control system. Then, by incorporating compensation of adaptive model to deal with parameter variations and nonlinearity, a systematic robust H∞ control scheme is designed, which can achieve good tracking performance, as well as improve system robustness against model uncertainties. Lyapunov stability analysis confirmed the stability of the overall control system. Finally, simulation and experiment results are provided to demonstrate the feasibility and effectiveness of the proposed control design method.

New Smith predictive fuzzy immune PID control algorithm for MIMO networked control systems

Aiming at the problem of network-induced delays for multi-input multi-output networked control systems (MIMO NCS), a new Smith predictive fuzzy immune PID algorithm is introduced to effectively reduce the adverse effect of network-induced delays about stability in MIMO NCS, firstly, by using the v-norm type to decouple the coupling plant. Based on the generalized plant after decoupling, the new Smith predictor is designed. Then, an modified fuzzy immune feedback control algorithm is used to tune PID controller parameters online. When there is a model mismatch or parameter perturbation, the set-point tracking performance and robustness of output response can be significantly optimized. The proposed algorithm does not contain the network delay prediction model and does not need to measure, estimate, or identify the network delay. It can be used in MIMO NCS where the network bandwidth is constrained and the network-induced delays are large. Numerical examples with Ethernet protocol are built to illustrate the correctness and effectiveness of this new algorithm.

Realization of Nonlinear Time-Delay Input–Output Equations

In this letter the problem of transforming a nonlinear multi-input multi-output time-delay control system, described by a set of higher order functional differential equations relating system inputs and outputs, into a set of first order functional differential equations, is studied. The globally linearized system equations are described in terms of polynomials in a delay operator and derivative operator. The Euclidean left division of polynomials is used to compute the basis of a certain free submodule of differential 1-forms. The integrability of the submodule is proved to be necessary and sufficient for the solvability of the problem.

Extended State Observer-Based Sliding Mode Control for Multi-input Multi-output System with Multiple Disturbances

This paper proposes a generalized design procedure for the extended state observer-based sliding mode control for multi-input multi-output linear systems with multiple disturbances (matched and/or mismatched) using an extended state observer. First, the system is transferred to a regular form to decouple the states having matched and mismatched uncertainties; then, a novel sliding surface is designed based on the state and disturbance estimation obtained through extended state observer (ESO). The proposed generalized ESO-based sliding mode controller (SMC) is designed to counteract the effect of matched and/or mismatched disturbances which are bounded, while the classical SMC fails to provide the desired performance in the presence of mismatched disturbance. This paper develops a simple method for the design of sliding surface coefficients and the selection of switching gain. The proposed control strategy is validated through numerical simulations, and the comparison with ESO-based state feedback control shows a reduced-order closed-loop dynamics and better transient performance.

Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules.

High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial–temporal complexity. This paper presents a multi-input multi-output (MIMO) self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional–integral–derivative (PID) neural network (FCPIDNN) and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

An Immune System-Inspired Reconfigurable Controller

Based on the biological immune mechanism, a design approach for the immune reconfigurable controller (IRC) is proposed. Using four units to imitate the immune system’s surveillance process, response process, memory mechanism, and self-learning process, respectively, the IRC is capable of actuator fault detection and fault-tolerant control for multi-input multioutput systems. Meanwhile, in order to further improve the control performance, an online optimization process with the multiobjective clonal selection algorithm is designed. To verify its effectiveness, the IRC is applied to the coagulation bath of polyacrylonitrile carbon fiber production line. Comparison experiments with conventional PID and reconfigurable model-based predictive controller control schemes are conducted. The simulation results demonstrate that the IRC can rapidly eliminate the fluctuation due to the actuator fault and guarantees the stability of the coagulation bath. In addition, the IRC has the ability of quick response to the same failure as well as unknown faults.

Development of a fractional order based MIMO controller for high dynamic engine testbeds

Testbed are used to tune and assess automotive engines. As more High Dynamic (HD) scenarios need to be simulated, the testbeds require Multi Input Multi Output (MIMO) and robust control systems. A cooperation involving a major testbed manufacturer and two university laboratories was therefore set up. This paper presents the Control-System Design (CSD) methodology developed from system identification to the design and assessment of the MIMO robust controller for a HD testbed coupled with a spark-ignition engine. It is specially highlighted how the entire process has been automated and simplified and how the fractional order based MIMO CRONE CSD has been parameterized to obtain the best performance. Experimental results show that the proposed fractional order based MIMO control system is able to improve robustness and decoupling.

Method of “transition into space of derivatives”: 40 years of evolution

In 1975, the “method of transition into space of derivatives” was proposed. It is an efficiently verifiable frequency criterion for the existence of a nontrivial periodic solution in multidimensional models of automatic control systems with one differentiable nonlinear term. The method used the classical torus principle and refrained from any constructions in the phase space of the system under study. Moreover, the method allowed researchers to broaden the class of systems to which it could be applied. In this work, we give a survey of the results presenting generalization and expansion of the method. We also show the connection between the method of transition into space of derivatives, the well-known generalized Poincare–Bendixson principle proposed by R. A. Smith, and the results of contemporary authors who are active in the theory of oscillations in multidimensional systems. In the recent years, the author obtained frequency criteria for the existence of orbitally stable cycles in multiinput multioutput (MIMO) control systems and methods for the construction of multidimensional systems having a unique equilibrium and an arbitrarily prescribed number of orbitally stable cycles, which are described in the paper. The extension of the generalized Poincare–Bendixson principle to multidimensional systems with angular coordinate is presented. We show the application of described methods of investigation of oscillation processes in multidimensional dynamical systems to solving S. Smale’s problem in the chemical kinetics theory of biological cells and also to finding hidden attractors of the generalized Chua system and the minimal global attractor of a system with a polynomial nonlinear term. The publication is illustrated by numerous examples.

Laguerre-based modelling and predictive control of multi-input multi-output systems applied to a communicating two-tank system (CTTS)

In this paper, a novel method is constructed for model predictive control (MPC) of multi-input multi-output (MIMO) systems. The latter are represented by a discrete-time MIMO ARX model expansion on Laguerre orthonormal bases. The resulting model, entitled the MIMO ARX-Laguerre model, provides a recursive representation with parameter number reduction. This reduction is strongly linked to the choice of Laguerre poles, and therefore we propose a new algorithm to optimize the Laguerre poles of the resulting model. The recursive formulation of the MIMO ARX-Laguerre model is used to obtain the MPC strategy. An [Formula: see text]-norm finite moving horizon cost function is used to obtain a control law which is implemented as a quadratic programming (QP) problem. The effectiveness of the proposed controller that takes into account physical constraints is illustrated by a numerical simulation example and by a practical validation on an experimental communicating two-tank system (CTTS).