Finite register length issue in the digital implementation of discret PID algorithms
Automatica (Journal of IFAC)
Optimum realizations of sampled-data controllers for FWL sensitivity minimization
Automatica (Journal of IFAC)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Parametrizations in Control, Estimation, and Filtering Problems: Accuracy Aspects
Parametrizations in Control, Estimation, and Filtering Problems: Accuracy Aspects
Randomized algorithms for quadratic stability of quantized sampled-data systems
Automatica (Journal of IFAC)
Hybrid feedback stabilization of systems with quantized signals
Automatica (Journal of IFAC)
Computational error effects in a direct digital control system
Automatica (Journal of IFAC)
| Hi-index | 22.14 |
Based on a polynomial operator approach, a new sparse controller structure is derived, which is actually an improved version of the recently proposed structure [Li, G. (2004). A polynomial-operator-based DFIIt structure for IIR filters. IEEE Transactions on Circuits and Systems II, 51, 147-151]. The performance of the proposed structure is analyzed by deriving the corresponding expression of roundoff noise gain and the problem of finding optimized sparse structures is solved efficiently with a genetic algorithm (GA). A numerical example is given, which shows that the newly developed structure can achieve much better performance than some well-known structures and particularly outperforms the traditional optimal fully parametrized realization greatly in terms of reducing roundoff noise and implementation complexity.