Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB’s Toolbox

Table 2

The objective functions and their associated design variables for the optimum points of Figure 2.

Optimum design point	A	B	C
Normalized summation of angles errors	1.22×10^−2	4.14×10^−1	8.23×10^−1
Normalized summation of control efforts	9.67×10^−1	5.27×10^−1	1.09×10^−1
Design variable 𝐾1	−1.80×10^2	−8.33×10^1	−8.44×10^1
Design variable 𝐾2	−9.49×10^3	−8.23×10^3	−6.64×10^3
Design variable 𝐾3	−1.90×10^2	−1.11×10^2	−1.09×10^2
Design variable 𝐾^′1	−9.39×10^3	−5.00×10^3	−4.89×10^3
Design variable 𝐾^′2	−1.80×10^2	−3.91×10^−1	−2.55×10^−2
Design variable 𝐾^′3	−9.00×10^2	−6.49×10^−2	−1.03×10^1