The design and real time implementation of an integrated fuzzy logic controller (IFLC) for a multiple-inputmultiple-output (MIMO) system is presented. The design of IFLC for an uncoupled MIMO system has been discusse...
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The design and real time implementation of an integrated fuzzy logic controller (IFLC) for a multiple-inputmultiple-output (MIMO) system is presented. The design of IFLC for an uncoupled MIMO system has been discussed. This study develops a combination of fuzzy and PID controllers (PIDC) to improve the control performance of a two-input-two-output (TITO: angular position, and rotational speed) system. These parameters play a vital role in radar-tracking system for military applications. To verify the applicability of proposed controller, two-motor unit plant along with indigenously designed multi-channel analog interface board of 16-bit precision is used. The proposed MIMO control system is interfaced to a PC through its parallel port. The performance of the system is studied by subjecting it to various standard test signals. The IFLC performs better than the other two controllers in tracking the input command for linear as well as nonlinear inputs such as step, square, triangular, and sine waves is observed.
Twin-rotor multi-input multi-output system (TRMS) is a popular experimental setup utilized mostly for development and evaluation of aerovehicle control algorithms. Motivated by its popularity, construction steps of a ...
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Twin-rotor multi-input multi-output system (TRMS) is a popular experimental setup utilized mostly for development and evaluation of aerovehicle control algorithms. Motivated by its popularity, construction steps of a TRMS setup in an academic setting are presented in this paper. Specifically, design of mechanical and electronic hardware components and development of related computer software are described in detail. Preliminary experiment results are also presented to demonstrate the performance of the system. (c) 2015 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:578-586, 2015;View this article online at;DOI
Model Predictive Control (MPC) is a well-established control strategy for the optimal control of constrained multivariable systems. Twin Rotor multi-input multi-output system (TRMS) is a nonlinear system with signific...
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Model Predictive Control (MPC) is a well-established control strategy for the optimal control of constrained multivariable systems. Twin Rotor multi-input multi-output system (TRMS) is a nonlinear system with significant cross-coupling between the horizontal and vertical axes presenting formidable challenges in modelling and control design. There are instances when a theoretical design may pose problems when it comes to practical implementation, particularly when the design is for nonlinear systems. In this context, this paper presents a practically implementable MPC design for TRMS which has been implemented successfully on a laboratory TRMS test-rig. The presented design is more suited for TRMS because it can handle the control constraints associated with the system through the optimization algorithm underlying the MPC scheme. From the view point of the system, all the control objectives are addressed, viz., stabilizing the system in a coupled condition and making its beam to track a specified reference trajectory or reach desired positions in 2DOF (two degrees of freedom) without violating the control input constraints. The design also incorporates the disturbance rejection requirement. Both simulation and experimental results are presented to show that the results from practical implementation are in accordance with the simulated results.
This paper proposes a generalized design procedure for the extended state observer-based sliding mode control for multi-inputmulti-output linear systems with multiple disturbances (matched and/or mismatched) using an...
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This paper proposes a generalized design procedure for the extended state observer-based sliding mode control for multi-inputmulti-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.
作者：
Liu, QimingTong, NichenHan, XuHebei Univ Technol
Sch Mech Engn State Key Lab Reliabil & Intelligence Elect Equip Tianjin 300401 Peoples R China Hunan Univ
Coll Mech & Vehicle Engn State Key Lab Adv Design & Mfg Vehicle Body Changsha 410082 Peoples R China
Commonly, variance-based global sensitivity analysis methods are popular and applicable to quantify the impact of a set of input variables on output response. However, for many engineering practical problems, the outp...
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Commonly, variance-based global sensitivity analysis methods are popular and applicable to quantify the impact of a set of input variables on output response. However, for many engineering practical problems, the output response is not single but multiple, which makes some traditional sensitivity analysis methods difficult or unsuitable. Therefore, a novel global sensitivity analysis method is presented to evaluate the importance of multi-input variables to multi-output responses. First, assume that a multi-input multi-output system (MIMOS) includes n variables and m responses. A set of summatory functions G(x) and H(x) are constructed by the addition and subtraction of any two response functions. Naturally, each response function is represented using a set of summatory function. Subsequently, the summatory functions G(x) and H(x) are further decomposed based on the high dimensional model representation (HDMR), respectively. Due to the orthogonality of all the decomposed function sub-terms, the variance and covariance of each response function can be represented using the partial variances of all the decomposed function sub-terms on the corresponding summatory functions, respectively. The total fluctuation of MIMOS is calculated by the sum of the variances and covariances on all the response functions. Further, the fluctuation is represented as the sum of the total partial variances for all the s-order function sub-terms, and the total partial variance is the sum of n partial variances for the corresponding s-order function sub-terms. Then, the function sensitivity index (FSI) FSIs for s-order function sub-terms is defined by the ratio of the total partial variance and total fluctuation, which includes first-order, second-order, and high-order FSI. The variable sensitivity index VSIi of variable xi is calculated by the sum of all the FSIs including the contribution of variable xi. Finally, numerical example and engineering application are employed to demonstrate the
Approximate dynamic programming is a useful tool in solving multi-stage decision optimal control problems. In this work, we first promote the action-dependent heuristic dynamic programming method to multi-inputmulti-...
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Approximate dynamic programming is a useful tool in solving multi-stage decision optimal control problems. In this work, we first promote the action-dependent heuristic dynamic programming method to multi-inputmulti-output control system by extending its action network to multi-output form. The detailed derivation is also given. We then apply this method to the fluctuation control of a spark engine idle speed. An engine idling model is set up to verify the control effect of this method. Results here show that this method requires several iterations to suppress unbalanced combustion by manipulating spark ignition timing. This method provides an alternative for a simpler multi-inputmulti-output approximate dynamic programming scheme. Moreover, it has a faster iteration convergence effect. The derivation of this method also has a rigorous mathematical basis. Although illustrated for engines, this control system framework should also be applicable to general multi-inputmulti-output nonlinear system. Copyright (C) 2011 John Wiley & Sons, Ltd.
Designing a controller to serve a process like a multi-inputmulti-output (MIMO) system is complicated due to unknown parameters, unmodeled nonlinearities, and unknown multiple-input couplings. Several controllers, su...
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Designing a controller to serve a process like a multi-inputmulti-output (MIMO) system is complicated due to unknown parameters, unmodeled nonlinearities, and unknown multiple-input couplings. Several controllers, such as the proportional-integral-derivative (PID) controller, have been introduced for the MIMO system to enhance its dynamic response due to their simplicity in design. This study aims to improve and develop the PID controller to be simpler and more intelligent. This paper proposes the design and verification of three controllers based on the multi-degree of freedom (MDOF) concept: the simplified optimum intelligent PID (SOI-PID) controller, the simplified universal intelligent PID (SUI-PID) controller, and the MDOF fuzzy logic controller (MDOF-FLC) for a MIMO system. A comparison study with different algorithms like the fuzzy logic controller (FLC) and the two degree of freedom (DOF)-PID controller was implemented to test and evaluate the proposed controllers under two MIMO systems: a proposed simple MIMO system and the four DOF robot arm manipulator. Simulation and experimental results show that the proposed SOI-PID and SUI-PID controllers respond faster with a better response than the MDOF-FLC, FLC, and two DOF-PID controller. The proposed controllers convert the PID controller into an intelligent controller via a simple design compared with intelligent algorithms.
This paper deals with the problem of secure data transmission based on multi-inputmulti-output delayed chaotic systems. A new multi-input secure data transmission scheme is proposed. Moreover, in order to increase ag...
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This paper deals with the problem of secure data transmission based on multi-inputmulti-output delayed chaotic systems. A new multi-input secure data transmission scheme is proposed. Moreover, in order to increase again the robustness of secure data transmission, delays are introduced as a second firewall against known plain-text attack. With this method, the parameters used as secret keys of the system are not identifiable and, as a result, the proposed scheme is robust to known plain-text attacks.
As operational scenarios become more complex and task demands intensify, the requirements for the intelligence and automation of manipulators in industry are increasing. This work investigates the challenge of posture...
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As operational scenarios become more complex and task demands intensify, the requirements for the intelligence and automation of manipulators in industry are increasing. This work investigates the challenge of posture tracking control for hydraulic flexible manipulators by proposing a discrete-time integral terminal sliding mode predictive control (DITSMPC) method. First, the proposed method develops a second-order dynamic model of the manipulator using the Lagrangian dynamic strategy. Second, a discrete-time sliding mode control (SMC) law based on an adaptive switching term is designed to achieve high-precision tracking control of the system. Finally, to weaken the influence of SMC buffeting on the manipulator system, the predictive time domain function is integrated into the proposed SMC law, and the delay estimation of the unknown term in the manipulator system is carried out. The DITSMPC scheme is derived and its convergence is proven. Simulation experiments comparing the DITSMPC scheme with the classical discrete-time SMC method demonstrate that the proposed scheme results in smooth torque changes in each joint of the manipulator, with the integral of torque variations being 5.22x103. The trajectory tracking errors for each joint remain within +/- 0.0025 rad, all of which are smaller than those of the classical scheme.
Increasing performance requirements in high-precision mechatronic systems lead to a situation where both multivariable and sampled-data implementation aspects need to be addressed. The aim of this paper is to develop ...
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Increasing performance requirements in high-precision mechatronic systems lead to a situation where both multivariable and sampled-data implementation aspects need to be addressed. The aim of this paper is to develop a design framework fora multi-inputmulti-output feedforward controller to improve continuous- time tracking performance through learning. The sampled-data feedforward controller is designed with physically interpretable tuning parameters using a multirate zero-order-hold differentiator. The developed approach enables interaction compensation for multi-input multi-output systems and the feedforward controller parameters are updated through learning. The performance improvement is experimentally validated in a multi-inputmulti-output motion system compared to the conventional feedforward controllers.
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