This paper presents a many-objective optimal (MOO) control design of an adaptive and robust sliding mode control (SMC). A second-order system is used as an example to demonstrate the design method. The robustness of the closed-loop system in terms of stability and disturbance rejection are explicitly considered in the optimal design, in addition to the typical time-domain performance specifications such as the rise time, tracking error, and control effort. The genetic algorithm is used to solve for the many-objective optimization problem (MOOP). The optimal solutions known as the Pareto set and the corresponding objective functions known as the Pareto front are presented. To assist the decision-maker to choose from the solution set, we present a post-processing algorithm that operates on the Pareto front. Numerical simulations show that the proposed many-objective optimal control design and the post-processing algorithm are promising.
Many-Objective Optimal Design of Sliding Mode Controls
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received March 9, 2016; final manuscript received August 2, 2016; published online September 26, 2016. Assoc. Editor: Hashem Ashrafiuon.
- Views Icon Views
- Share Icon Share
- Cite Icon Cite
- Search Site
Sardahi, Y., and Sun, J. (September 26, 2016). "Many-Objective Optimal Design of Sliding Mode Controls." ASME. J. Dyn. Sys., Meas., Control. January 2017; 139(1): 014501. https://doi.org/10.1115/1.4034421
Download citation file:
- Ris (Zotero)
- Reference Manager