Currently, many research studies reveal that for state regulator problems, the higher the degree of controllability is, the better the control effect likely is. Note that for the output regulator problems, the control performance is often evaluated by outputs. This article hence generalizes the concept and applications of degree of controllability to the case of output regulator. To this end, a kind of degree of output controllability is presented. Furthermore, simulations on wind turbines and the inverted pendulum system demonstrate that better control effect may be achieved by increasing the degree of output controllability measure. These results imply that similar to the case of degree of controllability for state regulation control, the degree of output controllability measure is likely a feasible candidate index for the design and optimization of the structural parameters of controlled plants in the case of output regulation control.
ArbelA (1981) Controllability measures and actuator placement in oscillatory systems. International Journal of Control33(3): 565–574.
2.
BlackwoodM (2016) Maximum efficiency of a wind turbine. Undergraduate Journal of Mathematical Modeling: One + Two6(2): 1–10. Article 2
3.
EdenJTanYLauD, et al. (2016) On the positive output controllability of linear time invariant systems. Automatica71: 202–209.
4.
FarzadASKarolosMGDanielV (2012) Wind turbine integrated structural and LPV control design for improved closed-loop performance. International Journal of Control85: 1178–1196.
5.
EisingR (1984) The distance between a system and the set of uncontrollable. Lecture Notes in Control and Information Sciences58: 303–314.
6.
FreckerMI (2003) Recent advances in optimization of smart structures and actuators. Journal of Intelligent Material Systems and Structures14(4): 207–216.
7.
HabibiHRahimi NohoojiHHowardI (2017a) Optimum efficiency control of a wind turbine with unknown desired trajectory and actuator faults. Journal of Renewable & Sustainable Energy9(6): 063305.
8.
HabibiHNohoojiHRHowardI (2017b) A neuro-adaptive maximum power tracking control of variable speed wind turbines with actuator faults. In: Australian and New Zealand control conference, Australia, 17 December, 2017, Institute of Electrical and Electronics Engineers (IEEE).
9.
HabibiHHowardISimaniS (2019) Reliability improvement of wind turbine power generation using model-based fault detection and fault tolerant control: a review. Renewable Energy135: 877–896.
10.
HeC (1997) On the distance to uncontrollability and the distance to instability and their relation to some condition numbers in control. Numerische Mathematik76(4): 463–477.
11.
HuangL (2003) Fundamental theory on Stability and Robustness. Beijing, China: Science Press, pp. 142–227.
12.
KalmanREHoYCNarendraKS (1962) Controllability of linear dynamical systems. Contributions to Differential Equations1: 189-213.
13.
KangOParkYParkYS, et al. (2009) New measure representing degree of controllability for disturbance rejection. Journal of Guidance, Control, and Dynamics32: 189–213.
14.
LeeHParkY (2016) Degree of controllability for linear unstable systems. Journal of Vibration and Control22: 1928–1934.
15.
KubruslyCSMalebrancheH (1985) Sensors and controllers location in distributed systems-A survey. Automatica21(2): 117–128.
16.
LongmanRWAlfriendKT (1981) Actuator placement from degree of controllability criteria for regular slewing of flexible spacecraft. Acta Astronautica8: 703–718.
17.
MalcolmDJHansenAC (2002) WindPACT turbine rotor design study. Golden, CO: National Renewable Energy Laboratory.
18.
MarcVDWDe JagerB (2001) A review of methods for input/output selection. Automatica37(4): 487–510.
19.
MullerPCWeberHI (1972) Analysis and optimization of certain qualities of controllability and observability for linear dynamical system. Automatica8: 237–246.
20.
PaigeC (1981) Properties of numerical algorithms related to computing controllability. IEEE Transactions on Automatic Control26: 130–138.
21.
RohHParkY (1997) Actuator and exciter placement for flexible structures. AIAA Journal of Guidance20: 850–856.
22.
VaidyaURajaramRDasguptaS (2012) Actuator and sensor placement in linear advection PDE with building system application. Journal of Mathematical Analysis and Applications394: 213–224.
23.
ViswanathanCNLongmanRWLikinsPW (1984) A degree of controllability definition: fundamental concepts and application to modal systems. AIAA Journal of Guidance20: 850–856.
24.
XiaYPYinMHYangZQ, et al. (2014) Investigation on the degree of controllability of wind turbines for the maximum power point tracking. Control Conference 33rd Chinese: 2336–2341.
25.
XiaYYinMCaiC, et al. (2018a) A new measure of the degree of controllability for linear system with external disturbance and its application to wind turbines. Journal of Vibration and Control24: 739–759.
26.
XiaYYinMZouY (2018b) Implications of the degree of controllability of controlled plants in the sense of LQR optimal control. International Journal of Systems Science49(2): 358–370.
27.
YaakoubiAEAttariKAsselmanA, et al. (2019) Novel power capture optimization based sensorless maximum power point tracking strategy and internal model controller for wind turbines systems driven SCIG. Frontiers in energy13(4): 742–756.
28.
YinMLiWChungCY, et al. (2017) Optimal torque control based on effective tracking range for maximum power point tracking of wind turbines under varying wind conditions. Iet Renewable Power Generation11(4): 501–510.
29.
ZhangXLongLLvY, et al. (2018) Control and simulation of fractional order inverted pendulum systems. In: Chinese control and decision conference, shenyang, 9 June, 2018, pp 6736–6741. IEEE Xplore Data Base.
