Locally Optimal Takagi-Sugeno Fuzzy Controllers Amir massoud Farahmand Mohammad javad Yazdanpanah [email protected] [email protected] Department of Electrical and Computer Engineering University of Tehran Tehran, Iran Fuzzy Control Successful in many applications Ease of use Intuitive and interpretable Powerful nonlinear controller Department of Electrical and Computer Engineering University of Tehran Takagi-Sugeno Plant Model R i : IF x1 (t ) is M1i and ... and xn (t ) is M in THEN x (t) A i x(t ) Biu (t ) r x (t ) hi x(t ) Ai x(t ) Biu (t ) i 1 , hi ( x) wi ( x) r w ( x) i 1 r wk ( x) M k ( xi (t )) i 1 i i Theorem 1. The continuous uncontrolled T-S fuzzy system is globally quadratically stable if there exists a common positive definite matrix P such that AiT P PAi 0, i 1,..., r Department of Electrical and Computer Engineering University of Tehran Parallel Distributed Compensation Control rule i : IF x1 (t ) is M1i and ... and xn (t ) is M in THEN u(t) -Ki x(t) r u hi ( x) K i x(t ) i 1 r r x (t ) hi ( x) h j ( x) Ai Bi K j x(t ) i 1 j 1 G G ji h i ( x)Gii x(t ) hi ( x)h j ( x). ij x(t ) 2 i 1 i 1 j 1 r r r 2 T Stability condition: Gij Ai Bi K j Gij G ji G G ji P P ij 0, i, j 1,..., r 2 2 Department of Electrical and Computer Engineering University of Tehran Locally Optimal Design Linearization x f ( x, u ) Ai , Bi Locally optimal design x Ai x Bi u K i R 1 B T P J x(t ), u (t ) x T Qx u T Ru .dt 0 Department of Electrical and Computer Engineering University of Tehran Experiments: Problem description Nonlinear Mass-SpringDamper system Mx(t ) g x(t ), x(t ) f x(t ) x(t )u(t ) x2 x (t ) 3 2 x 0 . 01 x 0 . 1 x 1 . 4387 0 . 13 x 1 1 2 2 0 f x, u A x ux 0x0 0.01 0.3x12 1 1 x 0 u 0 f x, u B 2 u x x0 1.4387 0.13x2 x0 Department of Electrical and Computer Engineering University of Tehran Experiments: Fuzzy Settings The dynamics of the plant is approximated using Gaussian membership function ( x xc ) 2 M k ( x(t )) exp 2 2 Approximation error Department of Electrical and Computer Engineering University of Tehran Experiments: Stabilization (I) 2 0.5 5 0 4 1 -0.5 0 -1 3 -1 2 U X2 X1 -1.5 -2 -2 -2.5 1 -3 -3 -3.5 0 -4 -4 -5 -1 -4.5 0 1 2 3 4 T 5 6 7 0 1 2 3 4 5 6 0 1 7 2 3 4 5 T T Comparison of T-S controller (bold) and linear controller (dotted) with different initial conditions Both TS and linear controller are stable in this case. However, the behavior of fuzzy controller is smoother and with lower overshoot. Department of Electrical and Computer Engineering University of Tehran 6 7 Experiments: Stabilization (II) 10 2 8 0 6 -2 2 1 0 4 -4 U x2 x1 -1 -2 -3 2 -6 0 -8 -4 -5 -2 0 1 2 3 4 5 6 T 7 -10 0 1 2 3 4 5 6 7 -6 0 1 2 T The linear controller is not stable in this case, but the fuzzy controller can handle it easily. Response of T-S controller to (10 0)' Department of Electrical and Computer Engineering University of Tehran 3 4 T 5 6 7 Experiments: Performance Comparison Linear TS Q=I, R=1 5.80 5.47 Q=10I,R= 1 9.06 8.44 Q=I, R=10 5.58 5.62 ,, Department of Electrical and Computer Engineering University of Tehran Experiments: Performance Comparison Q=10I,I=1 Q=I,I=10 -4 -4 -3 -3 -3 -2 -2 -2 -1 -1 -1 0 0 1 1 1 2 2 2 3 3 3 x1 x1 Q=I,I=1 -4 0 4 4 -4 -3 -2 -1 0 x2 1 2 3 4 4 -3 -2 -1 0 x2 1 2 3 -4 -3 -2 -1 0 1 Fig. 3. Performance region comparison for different performance indices: (Q=1, R=1), (Q=10, R=1), and (Q=1, R=10), from left to right, respectively (dark region means linear one has better performance). Department of Electrical and Computer Engineering University of Tehran 2 3 4 Conclusions and Suggestions Conclusions Stable Fuzzy Controller Local Optimality How close is it to the global optimal solution?! Suggestions Comparison with other T-S controllers Modeling error and stability (polytopic systems) Considering the effect of membership functions explicitly Department of Electrical and Computer Engineering University of Tehran
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