Search results

The purpose of this paper is to study the parameter estimation problem of nonlinear multivariable output error moving average systems.

A partially coupled extended stochastic gradient algorithm is presented for nonlinear multivariable systems by using the decomposition technique.

The proposed algorithm can realize the coupled computation of the parameter estimates between subsystems.

This paper develops a coupled parameter estimation algorithm for nonlinear multivariable systems and directly estimates the system parameters without over-parameterization.

The paper's purpose is to initiate an effort that will result in a systematic approach for design of control systems for multivariable, nonlinear, and unstable space robots.

The design approach is based on multivariable describing function (DF) models of the space robot coupled with the use of factorization technique. The design approach is to obtain the multivariable DF models followed by application of a previously developed factorization‐based controller design formula. Finally, the design must be verified by a non‐linear simulation to make sure that approximations made during design are valid.

It is found that the DF approach may successfully be applied in order to control nonlinear, multivariable, and unstable systems such as space robots.

At present, the approach is verified to be applicable to rigid space robots.

The major outcome of this research is that complicated controllers of a class of space robots may be replaced by simpler controllers, taking into account the amplitude dependency features of the space robot; this amplitude dependency is the most important characteristic of a non‐linear system.

This is the first paper in the area of multivariable and unstable space robot controller design that is based on the application of the DF technique. In fact this is the first work in the area of general unstable non‐linear control system design that is based on a DF technique.

The purpose of this paper is to study the identification methods for multivariable nonlinear Box‐Jenkins systems with autoregressive moving average (ARMA) noises, based on the auxiliary model and the multi‐innovation identification theory.

A multi‐innovation generalized extended least squares (MI‐GELS) and a multi‐innovation generalized ex‐tended stochastic gradient (MI‐GESG) algorithms are developed for multivariable nonlinear Box‐Jenkins systems based on the auxiliary model. The basic idea is to construct an auxiliary model from the measured data and to replace the unknown terms in the information vector with their estimates (i.e. the outputs of the auxiliary model).

It is found that the proposed algorithms can give high accurate parameter estimation compared with existing stochastic gradient algorithm and recursive extended least squares algorithm.

In this paper, the AM‐MI‐GESG and AM‐MI‐GELS algorithms for MIMO Box‐Jenkins systems with nonlinear input are presented using the multi‐innovation identification theory and the proposed algorithms can improve the parameter estimation accuracy. The paper provides a simulation example.

Argues that in increasingly turbulent and complex environments, the tools of “systems thinking” may provide a valuable resource in the drive to attain integration between strategic and operational objectives. Particular examples in the domain of production control and supply‐chain management are presented as illustrations of the dynamicist’s paradigm. Hence it is suggested that familiar concepts such as JIT/Kanban and supply chains are actually special cases of generic feedback control principles, while pure MRP is a classic example of feedforward. In practice, the complexities of real world operations require combinations of these two approaches and the paper therefore assesses the implications of these theoretical concepts, for the design of practical operations systems.

The purpose of this paper is to describe the application of a systematic single‐range controller design procedure to control a cruise missile.

The controller design approach is based on one describing function model of the missile followed by linear system identification. The missile includes discontinuous nonlinear terms, and therefore, a small signal model is not obtainable by straight linearization. Once a linear approximation to the quasilinear model of the missile is obtained, a H_∞ controller is designed to achieve a robust nonlinear closed‐loop system.

It is found that performance of the closed‐loop system with the applied simple controller design approach competes with one other complicated describing function‐based controller design technique.

At present, the research is limited to design of linear H_∞ controllers.

The major outcome of this paper is the verification that the applied simple describing function‐based H_∞ controller design procedure may be used to design high‐performance controllers for cruise missiles.

This is the first paper that adopts an existing single‐range H_∞ controller design procedure to design high‐performance controllers for cruise missiles.

In this paper, the aim is to present a modeling strategy for a flexible rotor/active magnetic bearing (AMB) system with non‐collocation. Special attention is paid to the vibration reduction and the stable passage through the first critical speed.

The finite element method based on Euller‐Bernoulli beam theory is applied in the formulation of the rotor model. Since rotor/AMB systems are complex mechatronic systems, reduced order approach is used in the control system design. This study applies the modal decomposition method and the modal truncation method, thus retaining the lower order bending modes. The obtained numerical results are compared with the measured open loop frequency responses and the existing differences are compensated in order to obtain accurate numerical model.

Frequency response of the entire system model (flexible shaft, actuators, power amplifiers and sensors) with amplitudes expressed in rotor lateral displacements can be verified by the measured frequency responses. The deviations in the amplitude and phase diagrams are then successfully corrected using the appropriate model modifications.

The results of this research find direct applications in flexible rotors supported by AMBs, e.g. high speed spindles, turbo molecular pumps, flywheel energy storage systems, etc. The presented procedure can be especially valuable in the design of model based controllers.

An AMB system model is developed and presented in this paper, in conjunction with a systematic description of an efficient procedure for the elimination of the typical mismatches between the simulation and experiment. Firstly, rotor/AMB test rig is stabilized with an appropriately tuned PID controller and an open loop frequency response is obtained for such a system. This response is then compared to corresponding simulation results for which mismatches are identified and eliminated thus yielding an accurate model of the system.

The purpose of this paper is to stabilize the type-2 Takagi–Sugeno (T–S) fuzzy systems with the sufficient and guaranteed stability conditions. The given conditions efficaciously handle parameter uncertainties by the upper and lower membership functions of the type-2 fuzzy sets (FSs).

This paper reports on a relevant study of stable fuzzy controllers and type-2 T–S fuzzy systems and reported that the synthesis of controller for nonlinear systems described by the type-2 T–S fuzzy model is a key problem and it can be resolve to convex problems via linear matrix inequalities (LMIs).

The multigain fuzzy controllers are established to improve the solvability of the stability conditions, and the authors design multigain fuzzy controllers which have extensive information of upper and lower membership grades. Consequently, the authors derive the traditional stability condition in terms of LMIs. One simulation examples illustrate the effectiveness and robustness of the derived stabilization conditions.

The uncertain MIMO nonlinear system described by Type-2 Takagi-Sugeno (T-S) fuzzy model, and successively LMI approach used to determine the system stability conditions. The proposed control approach will give superior fault-tolerant control permanence under the actuator fault [partial loss of effectiveness (LOE)]. Also the controller robust against the unmeasurable process disturbances. Additionally, the statistical z-test are carried out to validate the proposed control approach against the control approach proposed by Himanshukumar and Vipul (2019a).

This paper aims to present a robust design approach to realize disturbance attenuation for a yaw – pitch gimballed system subject to actuator saturation and disturbances.

To minimize the impacts of disturbances in the presence of saturation nonlinearity and acquire desired response performance, the control approach is of double closed-loop configuration. State feedback controllers are synthesized via convex optimization and used to stabilize the inner loops; robust controllers are synthesized via mixed H _∞ optimization and used to stabilize the outer loops.

It is shown through performance simulations that the proposed control scheme is effective in terms of command following, stability and disturbance attenuation.

The presented robust control approach provides a theoretical method to facilitate designing a stable servo control loop for a yaw – pitch gimballed seeker.

This paper supplies an effective way of addressing stabilization problem induced from actuator saturation and system uncertainties.

The main purpose of this paper is to select appropriate voltage vectors in the switching techniques and, by selecting the proper voltage vectors, be able to achieve a DC link with the same outputs and a symmetric multi-level inverter.

The proposed structure, a two-stage DC–AC symmetric multi-level inverter with modified Model Predictive Control (MMPC) method, is presented for Photovoltaic (PV) applications. The voltage of DC-link capacitors of the boost converter is controlled by MMPC control method to select appropriate switching vectors for the multi-level inverter. The proposed structure is provided for single-phase power system, which increases 65 V input voltage to 220 V/50 Hz output voltage, with 400 V DC link. Simulation results of proposed structure with MMPC method are carried out by PSCAD/EMTDC software.

Based on the proposed structure and control method, total harmonic distortion (THD) reduces, which leads to lower power losses and higher circuit reliability. In addition, reducing the number of active switches in current path causes to lower voltage stress on the switches, lower PV leakage current and higher overall efficiency.

In the proposed structure, a new control method is presented that can make a symmetric five-level voltage with lower THD by selecting proper switching for PV applications.

The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources.

Taguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms.

Research indicates that integral control parameters (K_i) affect outputs substantially more than proportional control parameters (K_p). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676.

This paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve.