Abstract
Hydraulic systems that damp active oscillation operate according to a certain non-linear and time-varying algorithm. It is difficult to create a controller based on its dynamic model. This chapter proposes a new operation regime of the controller based on neuron nets by combining the advantages of the adaptive, radial, and basic functions of the neuron net. Its undoubted advantages are a learning (tilting) ability in real time to process indefinite, nonlinear disturbances, and to change the value of the active force in the hydraulic leaf spring by adjusting the weight coefficients of the neuron net and/or the radial parameters of the basic function. The model is a ¼ hydraulic active sprung mass of a mobile vehicle. The modeling shows that the use of a neuron net controller makes the sprung mass much more efficient.
TopIntroduction
Most of the operating time, wheeled agricultural tractors have to work in fields with different soil backgrounds, along dirt or rough roads or even off roads (Senkevich S. et al, 2019; Senkevich S.E. et al, 2019). These conditions require sprung mass which allows supporting a regulated smooth ride and an effective protection of the operator from vibrations. The sprung mass must also keep the tires in contact with the road surface in order to support good stability and controllability of the vehicle (TC). This is especially important when a vehicle turns, brakes or accelerates (Frolov, 1995). The parts of sprung mass are usually located in the corners of the vehicle and connect the transmission and the frame with the wheels. Typically, the sprung mass includes elements of such two main types as elastic elements and dampers installed in parallel. Elastic elements smooth dynamic loads caused by moving along rough road. When the sprung mass is transmitted a dynamic disturbance from the irregularities of the roads, the elastic elements are deformed and accumulate potential energy, which is then released. When the vehicle moves forward and back, the suspension dampers dissipate the oscillation energy. Similarly, elastic elements and dampers keep controlled movement of the vehicle frame during the turns (Derbaremdiker,1985). Most of the vehicles use steel elastic elements in the sprung mass, which are divided into 3 types: coil, torsion, leaf springs. Some vehicles use pneumatic and hydro-pneumatic elastic elements. As dampers in the vehicle sprung mass hydraulic shock absorbers are basically used (Derbaremdiker, 1985; Senkevich, S.E. et al, 2020; Senkevich S. et al, 2020a; Senkevich S. et al, 2020b).
Key Terms in this Chapter
Hydroelastic Suspension: Is a type of suspension that provides control of the level of the body relative to the road through the use of hydraulic elastic elements.
Adaptive Suspension: (Another name is semi-active suspension) Is a type of active suspension in which the degree of damping of shock absorbers varies depending on the condition of the road surface, traffic parameters and driver's requests.
Neural Network: Is a mathematical model, as well as its software or hardware embodiment, built on the principle of the organization and functioning of biological neural networks.
Sprung Mass: Is called the mass of the elements that are held by the suspension of the tractor (or car) over the road.
Unsprung Mass: Is a concept applicable to ground vehicles with a suspension, which means the mass, including the mass of the wheels and other parts of the structure, separated by the suspension from the frame or body.
Nonlinear Characteristics: (Nonlinear system) Is a dynamic system in which processes are described by nonlinear differential equations. The properties and characteristics of nonlinear systems depend on their state.
Active Suspension: Is an active vehicle suspension system that controls the vertical movement of the wheels relative to the body.