1,042 research outputs found
Design of PID Controllers Satisfying Gain Margin and Sensitivity Constraints on a Set of Plants
This paper presents a method for the design of PID-type controllers, including those augmented by a filter on the D element, satisfying a required gain margin and an upper bound on the (complementary) sensitivity for a finite set of plants. Important properties of the method are: (i) it can be applied to plants of any order including non-minimum phase plants, plants with delay, plants characterized by quasi-polynomials, unstable plants and plants described by measured data, (ii) the sensors associated with the PI terms and the D term can be different (i.e., they can have different transfer function models), (iii) the algorithm relies on explicit equations that can be solved efficiently, (iv) the algorithm can be used in near real-time to determine a controller for on-line modification of a plant accounting for its uncertainty and closed-loop specifications, (v) a single plot can be generated that graphically highlights tradeoffs among the gain margin, (complementary) sensitivity bound, low-frequency sensitivity and high-frequency sensor noise amplification, and (vi) the optimal controller for a practical definition of optimality can readily be identified
Robust PI Controller Design Satisfying Sensitivity and Uncertainty Specifications
This paper presents a control design method for determining proportional-integral-type controllers satisfying specifications on gain margin, phase margin, and an upper bound on the (complementary) sensitivity for a finite set of plants. The approach can be applied to plants that are stable or unstable, plants given by a model or measured data, and plants of any order, including plants with delays. The algorithm is efficient and fast, and as such can be used in near real-time to determine controller parameters (for online modification of the plant model including its uncertainty and/or the specifications). The method gives an optimal controller for a practical definition of optimality. Furthermore, it enables the graphical portrayal of design tradeoffs in a single plot, highlighting the effects of the gain margin, complementary sensitivity bound, low frequency sensitivity and high frequency sensor noise amplification
Robust PI Controller Design Satisfying Gain and Phase Margin Constraints
This paper presents a control design algorithm for determining PI-type controllers satisfying specifications on gain margin, phase margin, and an upper bound on the (complementary) sensitivity for a finite set of plants. Important properties of the algorithm are: (i) it can be applied to plants of any order including plants with delay, unstable plants, and plants given by measured data, (ii) it is efficient and fast, and as such can be used in near real-time to determine controller parameters (for on-line modification of the plant model including its uncertainty and/or the specifications), (iii) it can be used to identify the optimal controller for a practical definition of optimality, and (iv) it enables graphical portrayal of design tradeoffs in a single plot (highlighting tradeoffs among the gain margin, complementary sensitivity bound, low frequency sensitivity and high frequency sensor noise amplification)
Optimal Design of Low Order Controllers Satisfying Sensitivity and Robustness Constraint
The set of all stabilizing controllers of a given low order structure that guarantee specifications on the gain margin, phase margin and a bound on the sensitivity corresponds to a region in n-dimensional space defined by the coefficients of the controllers. For several practical criteria defined in the paper it is shown that the optimal controller lies on the surface of that region. Moreover, it is shown how to reduce that region to avoid actuator saturation during operation
On the Selection of Tuning Methodology of FOPID Controllers for the Control of Higher Order Processes
In this paper, a comparative study is done on the time and frequency domain
tuning strategies for fractional order (FO) PID controllers to handle higher
order processes. A new fractional order template for reduced parameter modeling
of stable minimum/non-minimum phase higher order processes is introduced and
its advantage in frequency domain tuning of FOPID controllers is also
presented. The time domain optimal tuning of FOPID controllers have also been
carried out to handle these higher order processes by performing optimization
with various integral performance indices. The paper highlights on the
practical control system implementation issues like flexibility of online
autotuning, reduced control signal and actuator size, capability of measurement
noise filtration, load disturbance suppression, robustness against parameter
uncertainties etc. in light of the above tuning methodologies.Comment: 27 pages, 10 figure
A Data-driven Approach to Robust Control of Multivariable Systems by Convex Optimization
The frequency-domain data of a multivariable system in different operating
points is used to design a robust controller with respect to the measurement
noise and multimodel uncertainty. The controller is fully parametrized in terms
of matrix polynomial functions and can be formulated as a centralized,
decentralized or distributed controller. All standard performance
specifications like , and loop shaping are considered in a
unified framework for continuous- and discrete-time systems. The control
problem is formulated as a convex-concave optimization problem and then
convexified by linearization of the concave part around an initial controller.
The performance criterion converges monotonically to a local optimal solution
in an iterative algorithm. The effectiveness of the method is compared with
fixed-structure controllers using non-smooth optimization and with full-order
optimal controllers via simulation examples. Finally, the experimental data of
a gyroscope is used to design a data-driven controller that is successfully
applied on the real system
PI controller tuning for load disturbance rejection using constrained optimization
© 2016, Springer-Verlag Berlin Heidelberg. In this paper, a simple and effective PI controller tuning method is presented. To take both performance requirements and robustness issues into consideration, the design technique is based on optimization of load disturbance rejection with a constraint either on the gain margin or phase margin. In addition, a simplified form of the resulting tuning formulae is obtained for first order plus dead time models. To demonstrate the ability of the proposed tuning technique in dealing with a wide range of plants, simulation results for several examples, including integrating, non-minimum phase and long dead time models, are provided
Automating control system design via a multiobjective evolutionary algorithm
This chapter presents a performance-prioritized computer aided control system design (CACSD) methodology using a multi-objective evolutionary algorithm. The evolutionary CACSD approach unifies different control laws in both the time and frequency domains based upon performance satisfactions, without the need of aggregating different design criteria into a compromise function. It is shown that control engineers' expertise as well as settings on goal or priority for different preference on each performance requirement can be easily included and modified on-line according to the evolving trade-offs, which makes the controller design interactive, transparent and simple for real-time implementation. Advantages of the evolutionary CACSD methodology are illustrated upon a non-minimal phase plant control system, which offer a set of low-order Pareto optimal controllers satisfying all the conflicting performance requirements in the face of system constraints
Design of a Fractional Order Phase Shaper for Iso-damped Control of a PHWR under Step-back Condition
Phase shaping using fractional order (FO) phase shapers has been proposed by
many contemporary researchers as a means of producing systems with iso-damped
closed loop response due to a stepped variation in input. Such systems, with
the closed loop damping remaining invariant to gain changes can be used to
produce dead-beat step response with only rise time varying with gain. This
technique is used to achieve an active step-back in a Pressurized Heavy Water
Reactor (PHWR) where it is desired to change the reactor power to a
pre-determined value within a short interval keeping the power undershoot as
low as possible. This paper puts forward an approach as an alternative for the
present day practice of a passive step-back mechanism where the control rods
are allowed to drop during a step-back action by gravity, with release of
electromagnetic clutches. The reactor under a step-back condition is identified
as a system using practical test data and a suitable Proportional plus Integral
plus Derivative (PID) controller is designed for it. Then the combined plant is
augmented with a phase shaper to achieve a dead-beat response in terms of power
drop. The fact that the identified static gain of the system depends on the
initial power level at which a step-back is initiated, makes this application
particularly suited for using a FO phase shaper. In this paper, a model of a
nuclear reactor is developed for a control rod drop scenario involving rapid
power reduction in a 500MWe Canadian Deuterium Uranium (CANDU) reactor using
AutoRegressive Exogenous (ARX) algorithm. The system identification and reduced
order modeling are developed from practical test data. For closed loop active
control of the identified reactor model, the fractional order phase shaper
along with a PID controller is shown to perform better than the present Reactor
Regulating System (RRS) due to its iso-damped nature.Comment: 11 pages, 10figure
Disturbance Observer-based Robust Control and Its Applications: 35th Anniversary Overview
Disturbance Observer has been one of the most widely used robust control
tools since it was proposed in 1983. This paper introduces the origins of
Disturbance Observer and presents a survey of the major results on Disturbance
Observer-based robust control in the last thirty-five years. Furthermore, it
explains the analysis and synthesis techniques of Disturbance Observer-based
robust control for linear and nonlinear systems by using a unified framework.
In the last section, this paper presents concluding remarks on Disturbance
Observer-based robust control and its engineering applications.Comment: 12 pages, 4 figure
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