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In this paper, a new stabilizing receding horizon control (RHC) scheme is proposed for linear continuous time-invariant systems with input and state constraints. The control scheme is based on the minimization of the finite horizon cost with a finite terminal weighting matrix subject to constraints. A new algorithm is suggested to implement the RHC scheme for a constrained receding horizon guidance law (CRHG). The proposed CRHG, which does not use information on the time-to-go, is obtained by using linear matrix inequality (LMI) optimization. Through simulation examples, the performance of the proposed CRHG is illustrated.

A novel nonlinear adaptive technique has been proposed for control of a pH neutralization process. For this, a standard nonlinear dynamic pH neutralization model was parametrized assuming that some key parameters of the buffer and feed streams, which sensitively affect the titration curve, are unknown. On this model, an indirect adaptive backstepping controller is designed by combining a backstepping controller and the recursive prediction error method for real-time parameter and state estimation. Through simulation studies, it has been shown that the estimated parameters and state variables are in good agreement with the actual values and that the proposed adaptive controller has excellent tracking and regulation performance.

In this note, new matrix inequality conditions on the terminal weighting matrices are proposed for linear continuous time-varying systems. Under these conditions, nonincreasing and nondecreasing monotonicities of the saddle point value of a dynamic game are shown to be guaranteed. It is proved that the proposed terminal inequality conditions ensure the closed-loop stability of the receding horizon H/sub /spl infin// control (RHHC). The stabilizing RHHC guarantees the H/sub /spl infin// norm bound of the closed-loop system. The proposed terminal inequality conditions for the monotonicity of the saddle point value and the closed-loop stability include most well-known existing terminal conditions as special cases. The results for time-invariant systems are obtained correspondingly from those in the time-varying case.

Using the recursive equation error method (REEM), the compositions of ternary flash drum have been estimated from the temperature of the drum and the product flow rates. If the equilibrium relationship is accurately known, the composition of the multicomponent system can be inferred quite reasonably. Compared with the standard recursive prediction error method (RPEM), REEM provides comparable estimation while the calculation is much simple and fast.

Two adaptive nonlinear control schemes are presented for an induction motor: tuning function and modular design approaches. The objective here is to control the speed and flux in an independent manner despite rotor resistance uncertainty. In most existing adaptive schemes with this objective, load torque is regarded as a constant but unknown parameter to be estimated rather than a disturbance. On the other hand, this paper uses an integrator to deal with the low-frequency load torque instead of trying to estimate it. Simulations show that the proposed adaptive schemes lead to uniform closed-loop performance despite the uncertainty of the rotor resistance.

Receding-horizon predictive control offers a practical approach to complex control problems where robustness and adaptability are required. Important theoretical developments have been reported, leading to many algorithms and acronyms. This paper seeks to provide an encompassing treatment of a broad range of predictive schemes. Some new results on stability are also obtained.

This paper considers the robust implementation of a class of predictive control methods represented by GPC. Such controllers are in two-degrees-of-freedom form where there are dynamics in both the forward and the feedback paths. The ‘tuning knobs’ of predictive controllers determine the characteristic polynomial PC , and for a given PC the observer or prefiltering polynomial T in the feedback path determines the robustness of the closed loop. Previous intuitive guidelines on the selection of T are shown to be limited in their effectiveness. For an open-loop stable plant, a simple criterion is provided which allows the feedback dynamics to be specified so as to enhance robustness. The T polynomial is then chosen to satisfy this criterion. In addition, robust design through T is related to an H∞ -optimal control scheme using the so-called Q-parametrization. Despite its simplicity, the new proposed approach to the design of T is seen to result in robustness comparable with that obtained from the H∞ method.

In this paper, research on the comparison of the fault characteristics of the direct current (DC) distribution system and the alternating current (AC) distribution system has been conducted. Since the DC distribution system is a promising topology to be used in future smart distribution systems having high efficiency and reliability, it is expected that there would be an increase in the installation of DC distribution systems in houses and buildings. For the analysis, DC and AC networks to be analyzed are implemented using PSCAD/EMTDC. Simulation results show that the DC distribution system has several benefits compared to the regular AC distribution system such as improved voltage drop and power quality characteristics at the customer-end during a disturbance. This is because the DC/DC converters of DC distribution system can mitigate voltage fluctuations caused by disturbance and increase power quality.

Exponential weighting of future tracking errors and control increments is employed for receding-horizon predictive control and seen to improve the dynamic behaviour of the closed-loop system. A sufficient condition for the asymptotic stability of generalized predictive control (GPC) with these weightings is derived. The condition can be easily satisfied whereas the corresponding condition for GPC with constant weighting is highly restrictive. In the case of constrained receding-horizon predictive control (CRHPC), a prescribed degree of stability is obtained just as with infinite-horizon optimal control using the same type of weighting. This makes it possible to use a simplified CRHPC law with no weighting on the tracking error but which guarantees convergence to the set-point faster than a bounding exponential

In this paper, we introduce a novel pilot structure for OFDM/OQAM system which has high spectral efficiency by isotropic orthogonal transform algorithm (IOTA) function. In contrast with classical OFDM/QAM transmission scheme, the OFDM/OQAM-IOTA system requires a specific pilot structure for channel estimation because side-lobe components of the IOTA function cause an intrinsic interference. In case of conventional pilot structure, successive signal cancellation and null insertion schemes are considered for minimizing the channel estimation error. These schemes, however, reduce overall data transmission rate, especially for frequent pilot transmission, and it results in decreased throughput. For improving the data rate, we propose an additional data transmission scheme based on signal cancellation and an efficient 2-dimensional pilot block. Analysis and simulation results verify that the proposed pilot structure exhibit not only higher data rate but also more reliable channel estimation performance than the conventional pilot structure.

A novel model reference adaptive control (MRAC) scheme for electrical servo drives is proposed, in which the control input is synthesized without any parameter identification mechanism and a PI controller is inserted ahead of the plant to reduce the steady state chattering. The proposed scheme is shown to be asymptotically stable in case that load torque disturbance sati sfies a certain condition. An application to a permanent magnet synchronous motor drive shows that the output error between the plant and the reference model tends to zero and the chattering is greatly reduced.

Udgivelsesdato: November-december This paper presents a new method to improve the sensorless performance of matrix converter drives using a parameter estimation scheme. To improve low-speed sensorless performance, the nonlinearities of a matrix converter drive such as commutation delays, turn-on and turn-off times of switching devices, and ON-state switching device voltage drop is modeled using p-q-r transformation and compensated using a reference current control scheme. To eliminate the input current distortion due to the input voltage unbalance, a simple method using p-q-r transformation is also presented. The proposed compensation method is applied for high performance induction motor drives using a 3-kW matrix converter system without a speed sensor. Experimental results are shown to illustrate the feasibility of the proposed strategy.

This paper presents an adaptive output feedback MPC for an uncertain input-constrained neutrally stable linear plant using control-relevant switching. By employing an input-to-state stabilizing MPC as the multi-controller, switching adaptive output feedback MPC is proposed for the system. Unlike the previous results which consider nominal stability and use the state feedback, our scheme uses the output feedback and can deal with modelling uncertainties. The proposed scheme guarantees global stability and uses finite horizon MPC. Simulation results are given to show the effectiveness of the scheme.

MPC (model predictive control) is representative of control methods which are able to handle physical constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global asymptotic stability can be obtained. A globally stabilizing finite-horizon MPC has lately been suggested for the neutrally stable systems using a nonquadratic terminal cost which consists of cubic as well as quadratic functions of the state. In this paper, an input-to-state-stabilizing MPC is proposed for the discrete-time input-constrained neutrally stable system using a non-quadratic terminal cost which is similar to that used in the global stabilizing MPC, provided that the external disturbance is sufficiently small. The proposed MPC algorithm is also coded using an SQP (Sequential Quadratic Programming) algorithm, and simulation results are given to show the effectiveness of the method.

It is well known that exponentially unstable linear systems can not be globally stabilized in the presence of input constraints. In the case where the linear system is neutrally stable, one can achieve global asymptotic stability using a particular Control Lyapunov Function (CLF)-based controller. Using this particular CLF as terminal cost in a receding horizon scheme, we obtain a receding horizon controller which globally stabilizes such systems. Contrary to previous results, the horizon length is fixed, and can be chosen arbitrarily. The resulting controller also outperforms the CLF controller, since it provides a lower cost as measured by a quadratic performance index.

The authors present a systematic study of an induction motor drive system employing a load commutated current source inverter (LCCSI). The steady-state characteristics of a LCCSI-fed induction motor are shown to be the intermediate characteristics between the voltage source inverter (VSI) and the auto sequentially commutated current source inverter (ASCI). The dynamic characteristics of the LCCSI-fed induction motor are investigated using a linearised model. A study through the pole/zero locations of the linearized system shows that a V/Hz ratio control loop plays an essential role in the stabilization of the system. >

This paper presents an indirect adaptive nonlinear control scheme for a power system, the dynamics of which are uncertain due to faults on the transmission lines. The method proposed combines an input-output feedback linearizing controller with an adaptation algorithm which estimates uncertain parameters in the presence of a fault. Simulations show that the power angle stabilization as well as voltage regulation is achieved in a satisfactory manner despite the nonlinearity and uncertainty of the power system.

An adaptive output feedback nonlinear control scheme is presented for a pH process, which is difficult to control due to the nonlinearities and uncertainties. A nonlinear controller is designed using a backstepping technique to handle the pH process with an input constraint. The backstepping-based controller is combined with state and parameter estimators to deal with unmeasurable state variables and unknown parameters, thereby resulting in an adaptive output feedback nonlinear controller. The input constraint mentioned above is considered in the controller and estimator designs. The stability properties of the proposed scheme are given, and simulation results show that uniform closed-loop performance is obtained despite the nonlinearity, the uncertainties of the parameters, and the unavailability of the state variables.

In this paper, new matrix inequality conditions on the terminal weighting matrices are proposed for linear continuous time-varying systems. Under these conditions, non-increasing and non-decreasing monotonicities of the saddle point value of a dynamic game are shown to be guaranteed. It is proved that the proposed terminal inequality conditions ensure the closed-loop stability of the receding horizon H/sub /spl infin// control (RHHC). The stabilizing RHHC guarantees an H/sub /spl infin// norm bound of the close-loop system. The proposed terminal inequality conditions for the monotonicity of the saddle point value and the closed-loop stability include most well-known existing terminal conditions as special cases. The results for time-invariant systems are obtained correspondingly from those in the time-varying case.

This Note presents a nonlinear device model for organic light emitting diodes (OLEDs), which can describe dynamic and static characteristics of OLEDs consistently. The parameters of the proposed model are estimated by using a particle swarm optimization algorithm. Some of the resulting parameters relate with physical characteristics of OLEDs. With only one set of experiments leading to a time response of an OLED device, this nonlinear model, together with all the parameters, is obtained, which can be a big advantage for the fast quality control of the OLEDs.

A multivariable control law based on the constrained receding-horizon predictive control (CRHPC) of Clarke and Scattolini (1991) is presented. Conditions that guarantee nominal stability and solvability are established. It is shown through a simulated example that this algorithm can stabilise systems that present difficulties to the well-known multivariable generalised predictive control (GPC).

The collocation method has been applied to derive a new SPICE (Simulation Program with Integrated Circuit Emphasis)-compatible non-quasi-static MOS (metal-oxide-semiconductor) transient model. Contrasting to the conventional approximation methods, the collocation method is simple for the model derivation and efficient in optimizing the variables of the continuity equation. The derived model is fully physics-based in that all the transient currents are directly expressed by only physically meaningful, optimized quantities. The model adequately predicts transient currents in the bias region such as the weak inversion region where conventional models show numerical difficulties.

An improved recursive estimation algorithm is presented for robust adaptive control. The estimator has the tightest dead zone which ensures ‘convergence of the estimates whilst maintaining maximum alertness’.

Reheating furnaces in iron and steel industry are main facilities of hot charge rolling processes. The main objective of such a reheating furnace is to control billet temperature uniformly, thereby resulting in successful rolling process performance and high productivity. In this paper, a dynamic model of the reheating furnace is derived using material and energy balances. A multivariable controller design procedure is then presented on the basis of a system identification technique and a predictive control algorithm. Simulations show the effectiveness of the proposed scheme.

We derive a mathematical model of a single-stand cold rolling mill and design control systems to improve the thickness precision while maintaining prescribed tension for the strip. On the basis of a linearized model of the rolling mill system, we propose a thickness controller using an internal model control (IMC) structure which effectively rejects periodic disturbances. We also discuss how the so-called BISRA AGC method can be combined with the proposed thickness controller in the presence of modeling error. It is illustrated by simulations that the proposed thickness controller yields better performance than existing methods when a periodic thickness disturbance exists, and that it is robust to the uncertainty of the mill modulus.