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Volume 146
Issue 2
IEE Proceedings - Control Theory and Applications
Volume 146, Issue 2, March 1999
Volumes & issues:
Volume 146, Issue 2
March 1999
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- Author(s): S. Askarpour and T.J. Owens
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 113 –118
- DOI: 10.1049/ip-cta:19990522
- Type: Article
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p.
113
–118
(6)
Parametric and subspace approaches to eigenstructure assignment are integrated to provide a simple algorithm for eigenstructure assignment by state feedback. The algorithm provides naturally for the case of common open- and closed-loop right characteristic vectors. The integrated approach enables the eigenstructure assignable with multiple eigenvalues to be readily identified. - Author(s): L.S. Shieh ; W. Wang ; Jason S.H. Tsai
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 119 –130
- DOI: 10.1049/ip-cta:19990082
- Type: Article
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p.
119
–130
(12)
The paper presents a time-domain design methodology for optimal digital design of multivariable sampled-data parametric uncertain systems using genetic algorithms (GAs). A continuous-time parametric uncertain plant, cascaded with an analogue parametric uncertain prefilter is formulated by means of multiple linear cascaded continuous-time nominal models, generated from the perturbed system and prefilter parameters via the GAs. For each linear cascaded analogue nominal model, an optimal analogue controller with regional eigenvalue placement is designed. Then, a new digital redesign method, taking into account the closed-loop intersample behaviour, is developed to convert the optimal analogue controller into a PAM or PWM digital controller for digital control of the continuous-time plant cascaded with a digitised prefilter. The global optimisation searching technique provided in GAs is employed to determine the digital interval plant, prefilter and controller from the obtained respective multiple linear digital models for finding the ranges of their respective implementation errors. As a result, the obtained digital models and controller perfected by the design engineer can be practically implemented. Also, the searching technique is utilised to redetermine the practically implementable optimal PAM or PWM digital controller cascaded with a digital prefilter for optimal digital control of the multivariable sampled-data parametric uncertain system. - Author(s): M.S. Mahmoud ; M. Zribi ; Y.C. Soh
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 131 –136
- DOI: 10.1049/ip-cta:19990519
- Type: Article
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p.
131
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(6)
The exponential stabilisation problem of a class of dynamical systems with time delay and mismatched uncertainties is considered. The structure of the uncertainties is affinely bounded. The time delay factor could be variable or of constant value. In the case when the time delay is variable, it is established that state-feedback controllers can be constructed to render the closed-loop system exponentially asymptotically stable. Several published results are then derived as special cases. The important case of constant delay is further examined using one-term and two-term state-feedback controllers. A simulation example of a water-quality model is given to illustrate the effectiveness of the proposed control schemes. - Author(s): A. Leva and A.M. Colombo
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 137 –146
- DOI: 10.1049/ip-cta:19990521
- Type: Article
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p.
137
–146
(10)
The aim of the paper is to address the problem of optimising the set-point weights of an ISA-PID controller automatically. First, the importance of the problem and its consequences on industrial applications are described. Then a framework for studying the effects of set-point weighting in ISA-PID controllers is introduced. Finally, a method and the corresponding procedure for tuning the weights are developed. Simulation examples showing the effectiveness of the proposed approach are also presented. - Author(s): Y.-C. Chang and C.-H. Lee
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 147 –156
- DOI: 10.1049/ip-cta:19990517
- Type: Article
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p.
147
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(10)
A dynamic feedback control design is proposed to treat the trajectory tracking control for constrained robots actuated by brushed DC motors. Only measurements of both angular motor position and motor armature current are required to construct the hybrid position/force control law. It is shown that for any preassigned attraction region all the variables of the closed-loop system are bounded and different robustness performance is achieved with respect to different uncertain signals. The attraction region can not only be arbitrarily enlarged but also explicitly constructed. Moreover, the proposed control algorithm can be employed directly to treat the tracking control of electrically driven unconstrained robots, and, consequently, both simple linear time-varying as well as linear time-invariant controllers are constructed. Finally, simulation examples are given to demonstrate the effectiveness of our proposed control algorithms. - Author(s): W.-S. Lin and C.-H. Tsai
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 157 –164
- DOI: 10.1049/ip-cta:19990515
- Type: Article
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p.
157
–164
(8)
A neurofuzzy logic controller with a compensating neural network and a fine-tuning mechanism in the consequent membership functions is proposed to design the model-following control of MIMO nonlinear systems. The control strategy is developed to facilitate interconnection compensation among subsystems by the compensating neural network and to realise feedback linearisation by online function approximation. By tailoring the fine-tuning mechanism to overcome the equivalent uncertainty appearing within subsystems or as a result of plant uncertainty, function approximation error, external disturbances, or measurement noise, the system is robust to some extent. The overall neurofuzzy control system is proved to be uniform ultimate bounded by using Lyapunov stability theory. Simulation results of a two-link manipulator demonstrate the effectiveness and robustness of the proposed controller. - Author(s): W.G. Seo ; J.S. LEE ; B. H. PARK
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 165 –170
- DOI: 10.1049/ip-cta:19990520
- Type: Article
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p.
165
–170
(6)
A controller is presented which guarantees system stability by using a feedback controller coupled with an intelligent compensator, and achieves precise tracking by using a set of iterative learning rules. In the feedback plus intelligent controller unit, the feedback control part stabilises the overall closed-loop system and keeps its error bounded, and the intelligent compensator estimates and compensates for the nonlinear part of the system, thereby keeping the feedback gains reasonably low in the feedback controller. In the iterative learning controller, a simple learning control rule is used to achieve precise tracking of the reference signal and a parameter learning rule is used to update the parameters of the intelligent compensator, thereby identifying the uncertain nonlinearity as closely as possible. - Author(s): D.Q. Zhang and S.K. Panda
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 171 –177
- DOI: 10.1049/ip-cta:19990518
- Type: Article
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p.
171
–177
(7)
A new chatter-free and fast-response sliding-mode controller with a smooth control law (SMCS) is proposed. Unlike the conventional sliding-mode controller (SMC) or sliding-mode controller with boundary layer (SMCB), which obey the variable-structure control principle by adopting a switching control term, the proposed SMCS uses a continuously varying term instead which takes the distance of the system state from the sliding surface into account. As a result, chatter is eliminated, and the control performance is improved in contrast to the popularly used SMCB in terms of system response, robustness, adaptability and maximum steady-state error. Both theoretical analysis and simulation studies have been carried out to verify the superiority of SMCS over SMCB. A step-by-step systematic design procedure for SMCS is presented and applied to speed control of a PMSM drive system. - Author(s): J. E. Normey-Rico and E. F. Camacho
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 179 –185
- DOI: 10.1049/ip-cta:19990081
- Type: Article
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p.
179
–185
(7)
The paper describes how to increase the robustness of the Smith predictor-based generalised predictive controller while maintaining a nominal performance. The design of filters to improve robustness has several advantages: it is much simpler than the normal procedure used in generalised predictive controllers; it allows for better robustness indices than the optimal predictor–based GPC with the same order of filter; and it maintains the same reference to output nominal performance for every choice of filter. To illustrate the properties of the filtered Smith predictor–based generalised predictive controller some examples, taken from recent papers, are presented. - Author(s): H. Melkote and F. Khorrami
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 186 –196
- DOI: 10.1049/ip-cta:19990085
- Type: Article
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p.
186
–196
(11)
Robust adaptive nonlinear control of permanent magnet stepper motors is considered in this paper. The control design methodology is based on our earlier work. A controller is designed for a detailed model of the motor that accounts for the cogging torque and nonsinusoidal flux distribution in the air gap and is robust to parametric and dynamic uncertainties in the entire electromechanical system and achieves reduced torque ripple. The uncertainties are shown to be bounded by polynomials in the states. An adaptive torque profile is designed for the motor that possesses desirable robustness properties. Thereafter, a sinusoidal commutation scheme is utilised to formulate desired phase currents that would generate the desired torque. Voltage level control inputs are designed using backstepping and the robust control design methodology to track the desired currents. The overall stability of the system is shown using Lyapunov techniques. The tracking errors are shown to be globally uniformly bounded. Simulation results are provided to illustrate the efficacy of the advocated approach. - Author(s): J.-S. Ju and M.H. Perng
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 197 –203
- DOI: 10.1049/ip-cta:19990086
- Type: Article
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p.
197
–203
(7)
The performance of a multivariable control system is limited by intrinsic properties (such as right-half-plane poles/zeros and condition number) of the plant, hence a required performance of a control system is achievable only when the plant is properly designed to fit the need of a control engineer. Such a plant is sometimes referred to as an `(input–output) controllable plant', and is referred to as a control-configured-plant (CCP) in this paper. However, due to the lack of a systematic approach, existing CCPs (such as the T2-CCV and the AO-IAF `Mohawk' airplanes) are highly ill-conditioned with lightly damped RHP poles/zeros. As a result, it is extremely difficult to achieve a good control performance with such plants. Motivated by these facts, this paper presents a general approach to the design/redesign of a multivariable CCP, which attempts at a plant S(A, B, C) which satisfies constraints on its pole/zero locations and conditioning numbers of G(s)=C(sI−A)−1B in a frequency range, while the H2 norm of G(s) is maximised. An illustrative example is given to show that a CCP resulting from the present approach can achieve a much better control performance than an `ordinary' multivariable plant. - Author(s): M.G.M. Madden and P.J. Nolan
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 204 –212
- DOI: 10.1049/ip-cta:19990088
- Type: Article
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p.
204
–212
(9)
The paper presentsDE /IFT , a new fault diagnosis engine which is based on the authors'IFT algorithm for induction of fault trees. It learns from an examples database comprising sensor recordings, all of which have been classified as corresponding to either the normal behaviour of the system or to one or more fault states. The fault trees generated byIFT are translated into functions in the C programming language. The disgnosis engine links these into a shell program to yield a software system for monitoring and fault diagnosis which has a fast reaction time and is capable of dealing with complicated fault situations. The use ofDE /IFT is demonstrated by diagnosing incipient faults in a simulated pneumatic servo-controlled robot arm, where the sensor recordings it uses are transient responses of the servo system to an input test signal. A variety of different situations are considered, including singly occurring faults and multiple simultaneous faults, developing steadily over time or occurring intermittently. - Author(s): C.F. Chen and C.-H. Hsiao
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 213 –219
- DOI: 10.1049/ip-cta:19990516
- Type: Article
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p.
213
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(7)
An examination is given to compare the fast capabilities of operational matrices of integration formed by various orthogonal functions. It is found that the Haar wavelet operational matrix is the fastest. Based on the newly established matrix, a simple and complete procedure for optimising a dynamic system is formulated. Different constraints and various conditions of the time-invariant system optimisation problems are considered and solved with the new wavelet approach. - Author(s): Z. Ding
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 220 –226
- DOI: 10.1049/ip-cta:19995014
- Type: Article
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p.
220
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(7)
The paper addresses the output tracking of a class of uncertain nonlinear output feedback systems affected by disturbances that are known to be bounded but are otherwise unknown. The system uncertainty is parametrised by a parameter vector of which a normed upper bound is known. An adaptive controller is designed to guarantee arbitrary disturbance attenuation on the output tracking error for smooth reference signals under the minimum phase assumption. The paper represents an extension of disturbance decoupling results to uncertain systems as well as an extension of adaptive control results to the disturbance decoupling problem. - Author(s): R. Ghosh ; S. Sen ; K.B. Datta
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 227 –233
- DOI: 10.1049/ip-cta:19990166
- Type: Article
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p.
227
–233
(7)
The problem of evaluating the stability bounds of discrete-time singularly perturbed systems is considered. A direct method using critical stability criteria has been developed to obtain the exact upper bound ε0 of the singular perturbation parameter ε for which the overall system will remain stable ∀ε∈[0, ε0). The concept of the block bialternate product is utilised to substantially reduce the order of the matrices to be dealt with. It appears that the proposed method is more efficient than that suggested by Li and Li (1992), which makes use of the generalised Nyquist plot. It also completely removes the computational complexity associated with the quadratic dependence on the system matrix A(ε) as encountered by Tesi and Vicino (1990). - Author(s): X. Hong ; C.J. Harris ; P.A. Wilson
- Source: IEE Proceedings - Control Theory and Applications, Volume 146, Issue 2, p. 234 –240
- DOI: 10.1049/ip-cta:19990121
- Type: Article
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p.
234
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(7)
A new state estimator algorithm is based on a neurofuzzy network and the Kalman filter algorithm. The major contribution of the paper is recognition of a bias problem in the parameter estimation of the state-space model and the introduction of a simple, effective prefiltering method to achieve unbiased parameter estimates in the state-space model, which will then be applied for state estimation using the Kalman filtering algorithm. Fundamental to this method is a simple prefiltering procedure using a nonlinear principal component analysis method based on the neurofuzzy basis set. This prefiltering can be performed without prior system structure knowledge. Numerical examples demonstrate the effectiveness of the new approach.
Integrated approach to eigenstructure assignment by state feedback
Optimal digital design of hybrid uncertain systems using genetic algorithms
Exponential stabilisation of state-delay systems
Method for optimising set-point weights in ISA-PID autotuners
Robust tracking control for constrained robots actuated by DC motors without velocity measurements
Neurofuzzy-model-following control of MIMO nonlinear systems
Intelligent learning control for a class of nonlinear dynamic systems
Chattering-free and fast-response sliding mode controller
Robustness effects of a prefilter in Smith predictor–based generalised predictive controller
Robust nonlinear control and torque ripple reduction for permanent magnet stepper motors
General approach to control-configured-plant (CCP) design/redesign
Monitoring and diagnosis of multiple incipient faults using fault tree induction
Wavelet approach to optimising dynamic systems
Almost disturbance decoupling of uncertain nonlinear output feedback systems
Method for evaluating stability bounds for discrete-time singularly perturbed systems
Neurofuzzy state identification using prefiltering
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