MIMO Control Research Articles

Utilization of LabView in MIMO control for multiple tanks Level Measurement System

The modernisation of the existing device of facts acquisition machine in procedure manage is upgraded to the recent technologies for running the technique station. This paper offers the perspectives on the prevailing 3 tank structures installation is used for controlling the levels of two interacting systems. Liquid degree control has a completely big software domain in enterprise circulate over; the 3 tank system is one of the most broadly used experiments in laboratory & studies institutes. The measurement of business technique level parameter is one of the wonderful importances in manner manage. the extent of liquids may additionally have an effect on each the stress and fee of float in and out of the tank. subsequently, the excellent can be affected. automated manage applications would require control indicators for operation of actuation. stage transmitter is used to measure level of the tank. in this gadget the level in the process tank is sensed the usage of a degree transmitter and the corresponding present day output being measured and managed with the aid of the use of statistics acquisition gadget. [1],[ 3],[5]

Simplified Fractional-Order Design of A Mimo Robust Controller

Abstract This paper presents how to design as simply as possible a robust MIMO controller for a refrigeration system with a 2 inputs, 2 outputs and a nonlinear model. Even if the proposed method starts from the CRONE MIMO approach, the analysis of the linear MIMO behavior of the system model shows that its MIMO controller can be decentralized and designed in two simple steps based on the SISO CRONE methodology. Simulation results show the good control performance and robust stability for a wide set of operating points.

Enhancing performance of generalized minimum variance control via dynamic data reconciliation

The design, tuning, and implementation of controllers are crucial for the solutions to control problems. Generalized minimum variance control (GMVC) has attractive properties and it is widely used for controller performance enhancement. The measured signals of process output variables, which are used as feedback signals, are generally subject to measurement noise. However, the GMVC theory assumes the feedback signals are the process outputs, which rarely consider the unavoidable measurement noise. By additionally considering the measurement noise, the control performance of GMVC with the measurement noise is analyzed in this paper. The dynamic data reconciliation (DDR) method, which uses the information of both the process model and the measurement data to reconcile the measured signals, is introduced. It is combined with GMVC to reduce the effect of the measurement noise on the results of GMVC. The effectiveness of GMVC combined with DDR is illustrated in two case studies, where the proposed method is compared with the original GMVC and the GMVC with the conventional digital filter. The results in both SISO and MIMO control systems show that the proposed GMVC combined with DDR can reduce the effect of the measurement noise and achieve better control performance.

Quantitative-fuzzy Controller Design for Multivariable Systems with Uncertainty

This work serves as a pioneer contribution in terms of application of Quantitative Feedback Theory (QFT) methodology and fuzzy logic method to design a controller for MIMO systems. Due to the presence of uncertainty in multivariable dynamic systems, the application of robust control methods for achieving high accuracy in tracking is inevitable. On the other hand, application of QFT to MIMO uncertain systems still remains to be one of the most difficult control problems for engineers. In this paper, authors attempt to simplify the MIMO control problem by proposing a new algorithm which joins QFT and fuzzy techniques. In order to illustrate the utility of the proposed algorithm, its application on a two degree of freedom link robot manipulator is depicted. Initially, a QFT controller is designed for each link to overcome the track and disturbance rejection problems. Then, a bi-level tuned PD-fuzzy controller is employed as one strategy for curbing probable errors in the previous controller. The controller design was carried in the following stages; first, a linear PD controller independently applied to each actuator. Then, fuzzy rules were developed to design a fuzzy PD controller. Fuzzy controller normalizing parameters were regulated according to maximum PD control errors. In the second stage, named nonlinear tuning, other parameters of the fuzzy controller were tuned using genetic algorithms. Finally, nonlinear simulations of arbitrary path tracking shows that the proposed controller has a consistent tracking ability, and also it can clearly be seen that the mentioned approach is precise and very simple in comparison to other MIMO control techniques.

Model Predictive Control Of Diesel Engine Air Path With Actuator Delays

Existing results show that Model Predictive Control (MPC) can satify the desired settling time, zero steady-state error, and overshoot criteria for the MIMO control of the Diesel Engine Air Path (DEAP) system. However, the effect of actuator delay that considerably affects system performance, is not addressed sufficiently In this study, MPC of DEAP is extended with a delay term added to the actuators Exhaust Gas Recirculation valve and Variable Geometry Turbocharger valve on the plant model. A linear state-space model of the plant is obtained by using system identification techniques and the states of the identified model are extended due to delay term. It is shown that MPC performs better when the delay is taken into account in the algorithm.

A new approach to estimate the Minimum Variance Control law for Nonminimum phase Multivariable Systems

Abstract This paper introduces a new approach to calculate the minimum variance control law, which consists of a more direct and non-iterative procedure. It is based on factorization methods that preserve the directionality of nonminimum phase factors what yields a performance index closer to the actual achievable one. The proposed methodology was carried out for different case studies and compared with those obtained from a generalized interactor matrix. The results have shown the capability of the proposed methodology to yield a suitable MIMO controller performance index.

Design Methodology for Responsive and Rrobust MIMO Control of Heterogeneous Multicores

Heterogeneous multicore processors (HMPs) are commonly deployed to meet the performance and power requirements of emerging workloads. HMPs demand adaptive and coordinated resource management techniques to control such complex systems. While Multiple-Input-Multiple-Output (MIMO) control theory has been applied to adaptively coordinate resources for single-core processors, the coordinated management of HMPs poses significant additional challenges for achieving robustness and responsiveness, due to the unmanageable complexity of modeling the system dynamics. This paper presents, for the first time, a methodology to design robust MIMO controllers with rapid response and formal guarantees for coordinated management of HMPs. Our approach addresses the challenges of: (1) system decomposition and identification; (2) selection of suitable sensor and actuator granularity; and (3) appropriate system modeling to make the system identifiable as well as controllable. We demonstrate the practical applicability of our approach on an ARM big.LITTLE HMP platform running Linux, and demonstrate the efficiency and robustness of our method by designing MIMO-based resource managers.

Simplified Fractional-Order Design of a MIMO Robust Controller

This paper presents how to design as simply as possible a robust MIMO controller for a refrigeration system with a 2 inputs, 2 outputs and a nonlinear model. Even if the proposed method starts from the CRONE MIMO approach, the analysis of the linear MIMO behavior of the system model shows that its MIMO controller can be decentralized and designed in two simple steps based on the SISO CRONE methodology. Simulation results show the good control performance and robust stability for a wide set of operating points.

Design Methodology for Responsive and Robust MIMO Control of Heterogeneous Multicores

Design Methodology for Responsive and Robust MIMO Control of Heterogeneous Multicores

Design Methodology for Responsive and Robust MIMO Control of Heterogeneous Multicores

Design Methodology for Responsive and Robust MIMO Control of Heterogeneous Multicores

Benchmark for PID control of Refrigeration Systems based on Vapour Compression

The Benchmark proposed for the 3rd IFAC Conference on Advances in Proportional-Integral-Derivative Control (PID’18) held in July 2017 is described. This facilitates researchers to test their recent developments in the design of PID controllers on a challenging control problem. The paper focuses on the control of refrigeration systems: the canonical vapour-compression cycle is first described and then the MIMO control problem selected for the Benchmark PID 2018 is addressed, where the cooling power (through the outlet temperature of the evaporator secondary fluid) is intended to be controlled, as well as the degree of superheating at the evaporator outlet, using the compressor speed and the expansion valve opening as manipulated variables. The control systems described in this paper are ready to test other multivariable control strategies, despite being focused on PID regulators. Full documentation about the Benchmark was linked on the website of PID’18 and it will remain in http://www.dia.uned.es/~fmorilla/benchmarkPID2018/.

On λ-matrices and their applications in MIMO control systems design

In the present paper, we have introduced a new control design algorithms based on the theory of matrix polynomials. The first procedure is called block decoupling control which is based on the spectral factors of the denominator of the right matrix fraction description (RMFD), the advantages of this control are the non-interacted behaviour, simplicity in control design and low order controller is obtained due to the cancellation property of the proposed algorithm. The second control algorithm is the whole set of latent-structure assignment via the approaches of block root placement. Of course, the procedure has been developed even if the system is not block transformable, a process done with the aid of conversion between state space and matrix fraction description. The last method defined as a MIMO PID controller design via the placement of block roots with the help of Diophantine equation resolution, the latter systematic procedure retains both regulation and tracking objectives with small gains and minimum error.

Tuning of PID controller using optimization techniques for a MIMO process

In this paper, two processes were considered one is Quadruple tank process and the other is CSTR (Continuous Stirred Tank Reactor) process. These are majorly used in many industrial applications for various domains, especially, CSTR in chemical plants.At first mathematical model of both the process is to be done followed by linearization of the system due to MIMO process and controllers are the major part to control the whole process to our desired point as per the applications so the tuning of the controller plays a major role among the whole process. For tuning of parameters we use two optimizations techniques like Particle Swarm Optimization, Genetic Algorithm. The above techniques are majorly used in different applications to obtain which gives the best among all, we use these techniques to obtain the best tuned values among many. Finally, we will compare the performance of the each process with both the techniques.

ITER-like vertical stabilization system for the east Tokamak

A ITER-like vertical stabilization (VS) algorithm has been successfully deployed and commissioned at EAST. The proposed algorithm decouples the VS from the plasma shape control, while the algorithms previously implemented to stabilize the EAST plasma exhibit a strong coupling with plasma shape control system. As a consequence, the VS algorithms previously implemented at EAST prevent the deployment of advanced multi-input-multi-output (MIMO) plasma shape control schemes, such as the ones proposed in Albanese et al 2016 (Proc. 2016 IEEE Multi-Conf. System Control (Buenos Aires, Argentina) pp 611–6) and Kolemen et al (2015 J. Nucl. Mater. 463 1186). Indeed, such MIMO controllers rely on the decoupling with the VS system.The proposed ITER-like stabilizes the plasma column (i.e. it controls to zero the plasma vertical speed) on the fastest possible time scale, while leaves the control of the plasma vertical position to the plasma shape controller. Thanks to this frequency separation approach, the plasma shape controller can than be designed starting from the stabilized system, without explicitly taking the VS into account. In this paper we present the implementation details of the adopted solution for the EAST vertical stabilization, together with the results obtained during the 2016 experimental campaign.

Modeling and Control of Industrial ROV’s for Semi-Autonomous Subsea Maintenance Services

Remotely Operated Vechicles (ROV’s) takes a big part in the installation, maintenance and inspection of offshore subsea energy activities, such as inspections of Oil & Gas and wind energy pipelines and cables. By improving the ROV automation the operational cost can be significantly decreased as well as improving the inspection quality. This study examines an industrial ROV, where the investigations include modeling of a real industrial prototype, which is then linearized and used for Linear Quadratic Regulator (LQR) development. The results are validated both based on non-linear model simulations. Furthermore, the LQR controller is compared with the existing built-in heading and depth PID controllers, where it is shown that the LQR controller both gives an improved closed-loop transient performance and rejects noise better than the built-in controller. It is concluded that the ROV prototype has an acceptable physical design but that the automation could potentially be improved by adding a MIMO control scheme such as the proposed LQR controller.

Adaptive MIMO Controller Design for Chaos Synchronization in Coupled Josephson Junctions via Fuzzy Neural Networks

In this paper, we have discussed the synchronization between coupled Josephson Junctions which experience different chaotic oscillations. Due to potential high-frequency applications, the shunted nonlinear resistive-capacitive-inductance junction (RCLSJ) model of Josephson junction was considered in this paper. In order to obtain the synchronization, an adaptive MIMO controller is developed to drive the states of the slave chaotic junction to follow the states of the master chaotic junction. The developed controller has two parts: the fuzzy neural controller and the sliding mode controller. The fuzzy neural controller employs a fuzzy neural network to simulate the behavior of the ideal feedback linearization controller, while the sliding mode controller is used to ensure the robustness of the controlled system and reduce the undesired effects of the estimate errors. In addition, the Lyapunov candidate function is also given for further stability analysis. The numerical simulations are carried out to verify the validity of the proposed control approach. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Tensor methods for MIMO decoupling and control design using frequency response functions

Decentralized control design is commonly applied to design controllers for multi-variable control applications. The success of decentralized control design methodologies hinges on the quality of decoupling of the system. The aim of this paper is to develop a decoupling procedure that applies to multi-variable systems and only requires a frequency response function of the system. The proposed method builds on recent tensor decomposition methods. The potential of the method is shown both in a simulation and using experimental data. When applied on noisy data and on real-life systems, which are not possible to be exactly decoupled, the proposed method typically performs better compared to eigen-decomposition based method.

Autocovariance-based MPC model mismatch estimation for systems with measurable disturbances

In this paper, we propose a novel autocovariance-based plant-model mismatch estimation approach for linear MPC MIMO control loops with changing setpoints and measurable disturbances. Assuming a noise model is available and that there are of periods of operating data where the active set of the controller is fixed and the plant-model mismatch is invariant, we establish an explicit relation between the autocovariance matrices of the mean-centered process outputs and the plant-model mismatch. We then formulate the mismatch estimation problem as an optimization aimed at minimizing the difference between the theoretical autocovariance, computed from the established relation, and actual output autocovariances, calculated from the plant data. We elaborate our results for step-response models typically used in MPC, as well as for parametric (transfer function models) in both continuous time and discrete time. A simulation case study for an unconstrained MPC controller with measurable disturbances is used to illustrate the theoretical results.

On lambda-matrices and their applications in MIMO control systems design

In the present paper, we have introduced a new control design algorithms based on the theory of matrix polynomials. The first procedure is called block decoupling control which is based on the spectral factors of the denominator of the right matrix fraction description (RMFD), the advantages of this control are the non-interacted behaviour, simplicity in control design and low order controller is obtained due to the cancellation property of the proposed algorithm. The second control algorithm is the whole set of latent-structure assignment via the approaches of block root placement. Of course, the procedure has been developed even if the system is not block transformable, a process done with the aid of conversion between state space and matrix fraction description. The last method defined as a MIMO PID controller design via the placement of block roots with the help of Diophantine equation resolution, the latter systematic procedure retains both regulation and tracking objectives with small gains and minimum error.

MIMO control application for pulp and paper mill wastewater treatment by electrocoagulation

MIMO control application for pulp and paper mill wastewater treatment by electrocoagulation