Robust controller synthesis with consideration of performance criteria

This paper presents interactive controller synthesis methods based on an inward approach and offers some advantages over the traditional loop gain shaping methods. The indirect use of weighting functions for the robustness controller tuning is introduced. Besides that, the method allows transparent closed‐loop pole placement to achieve desirable transient performance. The obtained controllers are of lower order for comparable performance than those synthesized with rmH₂, H_∞ or µ‐synthesis. The method is particularly well suited for robust control problems where frequency domain constraints emerge from the analyses of non‐parametric uncertainties and also for control problems where the frequency domain loop shaping is used to achieve time domain performance specifications. Copyright © 2010 John Wiley & Sons, Ltd.     

A new decentralized robust controller design for multi-area load–frequency control via incomplete state feedback

This paper deals with load–frequency control of a multi-area power installation. The robust control theory is utilized to decouple the areas for a decentralized robust load–frequency controller. The proposed controller ensures that the overall multi-area power system is asymptotically stable. A new technique is included to exclude feedback from any immeasurable state. The product comprises a set of local load–frequency controllers, one for each area. The design and operation of each local controller requires solely the corresponding area's parameters and state measurements. Measurements of the immeasurable states are unnecessary. System parameter uncertainties and generation rate constraints are included in the simulation study of a three-area power system. Good results are reported. Copyright © 1998 John Wiley & Sons, Ltd.     

Robust reliability method and reliability‐based performance optimization for non‐fragile robust control design of dynamic system with bounded parametric uncertainties

An efficient robust reliability method for non‐fragile robust control design of dynamic system with bounded parametric uncertainties is presented systematically, in which the uncertainties existing in the controlled plant and controller realization are taken into account simultaneously in an integrated framework. Reliability‐based design optimization of non‐fragile robust control for parametric uncertain systems is carried out by optimizing the H₂ and H_∞ performances of the closed‐loop system, with the constraints on robust reliabilities. The non‐fragile robust controller obtained by the presented method may possess a coordinated optimum performance satisfying the precondition that the system is robustly reliable with respect to the uncertainties existing in controlled plant and controller. Moreover, the robustness bounds of uncertain parameters can be provided. The presented formulations are within the framework of linear matrix inequality and thus can be carried out conveniently. It is demonstrated by a numerical example that the presented method is effective and feasible. Copyright © 2016 John Wiley & Sons, Ltd.     

Optimal decentralized control of a wind turbine and diesel generator system

This article presents a decentralized optimal controller design technique for the frequency and power control of a coupled wind turbine and diesel generator. The decentralized controller consists of two proportional-integral (PI)-lead controllers which are designed and optimized simultaneously using a quasi-Newton based optimization technique, namely, Davidon–Fletcher–Powell algorithm. The optimal PI-lead controllers are designed in such a way that there are no communication links between them. Simulation results show the superior performance of the proposed controller with a lower order structure compared to the benchmark decentralized linear-quadratic Gaussian integral controllers of orders 4 and 11. It is also shown that the proposed controller demonstrates an effective performance in damping the disturbances from load and wind power, as well as a robust performance against the parameter changes of the power system.     

Robust disturbance attenuation for discrete‐time active fault tolerant control systems with uncertainties

The problems of stochastic stability and stochastic disturbance attenuation for a class of linear discrete‐time systems are considered in this paper. The system under study is a state space model possessing two Markovian jump parameters: one is failure process and another is failure detection and isolation scheme. A controller is designed to guarantee the stochastic stability and a disturbance attenuation level. Robustness problems for the above system with norm‐bounded parameter uncertainties are also investigated. It is shown that the uncertain system can be robustly stochastically stabilized and have a robust disturbance attenuation level for all admissible perturbations if a set of coupled Riccati inequalities has solutions. A numerical example is given to show the potential of the proposed technique. Copyright © 2003 John Wiley & Sons, Ltd.     

A decentralized receding horizon optimal approach to formation control of networked mobile robots

This paper presents a receding horizon optimal controller with guaranteed stability for multirobot formation, taking into account collision and obstacle avoidance. The proposed scheme is based on synchronous decentralized strategy wherein all the vehicles that are connected via a packed‐delaying network solve a finite horizon–constrained optimal control problem to obtain their own control action at each sampling instant. First, each robot is modeled by a single integrator dynamics; then, by defining a control law for each robot and considering the effect of communication delay, the closed‐loop dynamics is described as a delay differential equation with tunable parameters. Afterwards, a novel finite‐horizon optimal control setup is established to obtain these adjustable gains such that a desirable formation is achieved. The efficiency and applicability of the suggested scheme are demonstrated by simulation results.     

An improved neuro-adaptive-optimal control for oscillation damping in wind-integrated power systems

This article proposes an improved neuro-adaptive-optimal control scheme, based on online system identification and simultaneous control, to replace power system stabilizer in the renewable-energy-penetrated power systems. A simple, linear neural identifier, with a few adjustable connection weights is used, which ensures minimal computational burden, reduced development time, and makes the controller practically realizable. An adaptive learning rate, derived using Lyapunov stability theorems, guarantees stability of convergence of the learning algorithm as well as an optimal speed of convergence. It is demonstrated that a simple linear neural identifier, which approximates a local linear model of a system, by adjustment of its parameters online, is faithfully able to track the varying dynamics of the system. Improved oscillation-damping performance over a wide range of operating conditions and disturbances, in comparison with a well-established IEEE-PSS1A and fuzzy-logic-control-based PSS, was validated through simulation studies on a single-machine infinite-bus power system and a wind-integrated two-area power system. The computational superiority of the proposed scheme in comparison to complex and non-linear neural networks and fuzzy-logic-based control was also established. The novelty of the controller lies in its structure which, in-spite of being purely linear, performs robustly for highly complex and non-linear power system models.     

A hybrid modified grey wolf optimization-sine cosine algorithm-based power system stabilizer parameter tuning in a multimachine power system

Damping of low-frequency oscillations due to the unpredictable perturbations of a power network has always been a challenging task. In an interconnected power network, power system stabilizers (PSSs) are in practice to damp out these low-frequency oscillations by providing a necessary control signal to the automatic voltage regulator unit based on the deviation in generator speed/power output. This article proposes a novel approach of hybrid modified grey wolf optimization-sine cosine algorithm for tuning the parameters of PSS of an interconnected multimachine power system. The optimal parameter tuning of PSS with the proposed algorithm is achieved by considering a multiobjective function comprises of improving the damping and eigenvalue characteristics of the consolidated multimachine system. A benchmark model of two area four machine system is adopted to investigate the performance achieved with the proposed algorithm in the simultaneous damping of the local and interarea mode of oscillations in a multimachine power system. The system study has been carried out under a self-clearing fault condition, and the detailed analysis is presented by analyzing the eigenvalues, and their corresponding natural frequencies, damping ratios. The damping nature achieved for the system states under system uncertainties with the proposed algorithm is also presented. The performance obtained from the proposed hybrid algorithm has been compared with the standalone and state-of-the-art optimization methods.     

Robust continuous‐time controller design via structural Youla–Kučera parameterization with application to predictive control

This paper addresses the continuous‐time control of uncertain linear SISO plants and its nominal and robust stability and nominal and robust performance objectives. A specific application of the Youla–Ku?era (Q) parameterization concept leads to a new development of observer‐like controller structures. This method is combined with a nominal design of continuous‐time generalized predictive control suitable for both minimum‐phase and non‐minimum‐phase plants. The subsequent design procedure consists of two steps. Firstly, the nominal stability and nominal performance of the control system are established by using an analytical design methodology, based on a collection of closed‐loop prototype characteristics with definite time‐domain specifications. And secondly, a generic structure of the controller is enhanced by suitable Q‐parameters guaranteeing that the control system has the required robustness properties. The proposed structural (reduced‐order) Q‐parameterization relies on an observer structure of controllers, which can be easily enhanced with certain filters necessary for control robustification. To reduce the complexity of the resulting robust controllers, we suggest using a structural factorization, which allows for simple forms of robustifying (phase‐lag) correctors of low order, easy for implementation, and convenient for optimization and tuning. Two numerical examples are given to illustrate the composed technique and its practical consequences. Copyright © 2004 John Wiley & Sons, Ltd.     

Optimal hybrid control of interarea oscillation in power system using energy storage systems

Unmanaged renewables integration into the power system will raise the possibility of small-signal instability due to higher load deviations in the transmission lines. In power grids with a higher penetration level of the renewables, the load deviation can cause interarea oscillation in the grid. Meanwhile, large-scale battery energy storage systems are promising solutions to enhance power system stability by smoothening the load profile and their fast response. To damp the interarea oscillations without compromising the voltage stability, we need to consider the battery's dynamic model in axis. The battery's dynamic model in axis allows us to integrate the battery into the power system and simulate both the battery's active and reactive power injection/absorption. In this paper, we model the battery energy storage on axis. Then, the battery model is augmented into the two-area four-machine power system. An optimum hybrid controller using linear quadratic regulator techniques is designed to damp generators' frequency deviations. The results show that the interarea oscillations are damped without losing the voltage stability of the system.     

Design of robust quadratic‐optimal controllers for uncertain singular systems using orthogonal function approach and genetic algorithm

This paper discusses the robust‐optimal state feedback controller design problems of linear singular systems under the structured (elemental) parameter uncertainties by using the orthogonal function approach (OFA) and the hybrid Taguchi genetic algorithm (HTGA). A sufficient condition is proposed to ensure that the linear singular systems with the structured parameter uncertainties are regular, impulse free, and asymptotically stable. Based on the OFA, an algorithm only involving algebraic computation is derived in this paper and then is integrated with the HTGA to design the robust‐optimal state feedback controller of linear uncertain singular systems subject to robust stability constraint and the minimization of a quadratic performance index. A design example of a two degree of freedom mass–spring–damper system is given to demonstrate the applicability of the proposed approach. Copyright © 2008 John Wiley & Sons, Ltd.     

Robust feedback design for combined therapy of cancer

In this paper, a mathematical model for the scheduling of angiogenic inhibitors with a killing agent is used to derive a robust state feedback control for the combined therapy of cancer. Robustness is considered against parameter uncertainties through the solution of the associated Hamilton–Jacobi–Isaacs (HJI) partial differential equation. Unlike open‐loop optimal control paradigm, solving the HJI equation provides a guaranteed‐cost feedback control and a whole visibility of the achievable performance for any possible initial state within the region of interest and for any predefined level of parameter uncertainties. Numerical investigation is proposed using an existing model that has been partially validated using human data. Copyright © 2012 John Wiley & Sons, Ltd.     

A strategy for power system stabilization by control-effort and response-time minimization

A method is described for deriving a quasi-optimal feedback control scheme for stabilizing power systems. This is achieved by minimizing a functional which is a linear combination of response time and control effort. The transient repsonse of a power system obtained using this control strategy is found to be superior to that achieved with a controller based on a linear regulator approach. This scheme, in a slightly modified form, is easily implemented in practice. The modification does not affect the effectiveness of the scheme to control transients. Simulation results are included.     

AGC of a two‐area multi‐source power system interconnected via AC/DC parallel links under restructured power environment

In this paper, automatic generation control (AGC) of a two‐area multi‐source power system interconnected via alternating current/direct current (AC/DC) parallel links under restructured power environment is proposed. Each area is equipped with multipower generating sources such as thermal and hydro/gas. To execute the different market contracts in restructured power system, the optimal regulators are designed and implemented using optimal control theory. It is observed that the system dynamic results effectively satisfy the AGC requirements in restructured power system, as well as the system dynamic performance is improved by using AC/DC parallel links in comparison with that obtained with AC link as an area interconnection between the control areas. Furthermore, the eigenvalue study is performed to examine the system stability with and without AC/DC parallel links. Finally, the effectiveness of the optimal regulators is checked for the system under study with physical constraints like time delay, boiler dynamics, generation rate constraints, and governor dead band nonlinearity and variations in system parameters from the nominal values. It is shown that the optimal regulators optimized for linear system are robust enough and work well in the proposed realistic AGC system incorporating physical constraints and wide variations in parameters. Copyright © 2015 John Wiley & Sons, Ltd.     

Experimental results of a control time delay system using optimal control

The optimal control for a temperature system with time delay is considered. Experimental results of the control system are presented in this contribution. The integral term in the controller is approximated by a quadrature method. Experimental results obtained demonstrate the effectiveness of the approximation method. By a simple analysis in time domain, we demonstrate the robustness of the optimal controller. We compare the optimal control's performance with an industrial PID controller. This controller was robustly tuned. The experiments indicate the correct optimization of the plant when the optimal control was employed, despite limitations in the sensor, actuators, non‐modeled dynamics, and uncertain parameters of the process. Copyright © 2011 John Wiley & Sons, Ltd.     

Optimal control of electrical vehicle incorporated hybrid power system with second order fractional-active disturbance rejection controller

This article proposes a novel control methodology employing a fractional-active-disturbance-rejection-controller for the combined operation of load frequency control and automatic voltage regulator of a hybrid power system. A two area hybrid power system with diverse energy sources like solar-thermal, conventional-thermal and wind sources equipped with appropriate system nonlinearities is investigated. In order to ascertain the role of modern-day electric-vehicle (EV), the hybrid power system is incorporated with EVs in both the areas. To establish an effective frequency, voltage and tie line power control of the hybrid power system, a second order fractional-active-disturbance-rejection-controller with fractional-extended state observer is modeled as secondary controller. Magnetotactic-bacteria-optimization (MBO) technique is applied to obtain optimal values of the controller gains and the hybrid system parameters. The robustness of the controller gains is tested under different system parameter changes from their nominal values. In addition, the effect of incorporating a power system stabilizer on the hybrid power system is evaluated. Further, the impact of integrating renewable sources and EVs in the hybrid power system is explored. Moreover, the stability of the hybrid power system is monitored with the inclusion of FACTS device. The developed controller operates encouragingly with reference to system stability, rapidity and accuracy in comparison to testified control strategies available in the literature. The robustness test under load-perturbation, solar-insolation, wind input variations also proves the efficiency of MBO optimized second order fractional-active-disturbance-rejection-controller gains.     

Control‐relevant parameter estimation application to a model‐based PHEV power management system

Explicit model predictive control approach is a promising approach to fulfill automotive real‐time controls requirements. A key factor in the performance and real‐time capabilities of a predictive model‐based controller is the accuracy of the control‐oriented model. The control‐oriented model should capture the essential dynamics of the real plant and be adequately simple to make the controller implementable on a commercial hardware with limited memory and computational capabilities. In this study, control‐relevant parameter estimation is used to find a control‐oriented model for a real‐time predictive power management system for a plug‐in hybrid powertrain. Simulations, which are conducted using an equation‐based model of the powertrain, demonstrate a significant improvement of the power management system performance by improving the control‐oriented model with no effect on real‐time capabilities of the controller.     

Stabilizing a multimachine system via non-linear voltage controller with the use of a local control strategy

A new local control strategy with non-linear optimal controllers for a multimachine system is presented. Non-linear Field Voltage Controllers (NFVC) are designed with the use of the feedback linearization approach to adjust generator state variables to external reference signals resulting from optimal power flow calculation [P_i, Q_i, V_ti] in the stabilized power system. A non-linear control law has been derived for the three-dimensional [δ, ω, E′_q] one-axis model of a generator. The local control strategy has been verified for the New England 39 bus system. An extensive simulation study shows robustness of the non-linear controllers and better performance than PSS-based classical controllers. © 1997 John Wiley & Sons, Ltd.