Table 13.Characterization of the price–demand functions of the reviewed papers. Model typeDemand functionReferences LinearD=a−bP, wherea,b>0Askarpoor and Davoudpour (2013), Bajwa et al. (2016b), Deng and Yano (2006), González-Ramírez et al. (2011), Guan and Philpott (2011), Marda...
Fig. 3. Examples of nonlinear expressions that can be evaluated with NLR methods. (A) Power curve where Y = C1XC2; (B) Fourier series where Y = C1 × cos (X + C2) + C3 × sin (2 × X + C2) + C4. A function is nonlinear if it is not possible to express it in terms of...
While traditional linear MPC controllers optimize control actions to minimize a quadratic cost function, nonlinear MPC controllers support generic custom cost functions. For example, you can specify your cost function as a combination of linear or nonlinear functions of the system states and inputs. T...
This book provides a coherent and unified treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology. R. Subsequent chapters explain the salient features of the main fitting function nls (), ...
Examples collapse all Linear Inequality Constraint Copy Code Copy Command Find the minimum value of Rosenbrock's function when there is a linear inequality constraint. Set the objective function fun to be Rosenbrock's function. Rosenbrock's function is well-known to be difficult to minimize. It ...
function. This issue worsens when considering contact, which leads to abrupt, non-smooth kinks in the stress response. Our model, inspired by generative video modelling, is particularly suited to this nonlinear setting and overcomes many of these challenges, although being, from a mechanical ...
5.Calculate the rated torque value using the following function: pmsm.T_rated = mcbPMSMRatedTorque(pmsm); 6.Create a seed structure with the file paths to read the .csv files that you created in step 2. seed.Ldfilepath = 'JMAG_Ld.csv'; ...
Various optimization methods have different requirements on the function that is being minimized. For some methods, the estimation of model parameters is performed independently of the estimation of the error model parameters. The following table summarizes the error models and any separate formulas used...
Table 7 Solution accuracy of benchmark problem via mp-NLP algorithms Full size table Table 8 Computational complexity of benchmark problem via mp-NLP algorithms Full size table Since the objective function of the benchmark problem displays a mild nonlinearity, the CS on its own is a very accura...
TABLE 2. DESCRIBING FUNCTIONS FOR COMMON NONLINEAR ELEMENTS DESCRIBING FUNCTION: N(X) = A1 + JB1 OR |N(X)| = (A12 + B12)1/2.∠N(X)=TAN−1(B1/A1) CharacteristicDescribing-Function Coefficients al=4S/πX bl=O a1 =(4S/πX)cosθ b1=0 θ=sin−1(D/X) a1 =(2kl/π)[θ...